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Sample records for functional gene microarray

  1. Integrated analysis of microarray data and gene function information.

    PubMed

    Cui, Yan; Zhou, Mi; Wong, Wing Hung

    2004-01-01

    Microarray data should be interpreted in the context of existing biological knowledge. Here we present integrated analysis of microarray data and gene function classification data using homogeneity analysis. Homogeneity analysis is a graphical multivariate statistical method for analyzing categorical data. It converts categorical data into graphical display. By simultaneously quantifying the microarray-derived gene groups and gene function categories, it captures the complex relations between biological information derived from microarray data and the existing knowledge about the gene function. Thus, homogeneity analysis provides a mathematical framework for integrating the analysis of microarray data and the existing biological knowledge.

  2. Oligonucleotide Microarray for the Study of Functional Gene Diversity in the Nitrogen Cycle in the Environment

    PubMed Central

    Taroncher-Oldenburg, Gaspar; Griner, Erin M.; Francis, Chris A.; Ward, Bess B.

    2003-01-01

    The analysis of functional diversity and its dynamics in the environment is essential for understanding the microbial ecology and biogeochemistry of aquatic systems. Here we describe the development and optimization of a DNA microarray method for the detection and quantification of functional genes in the environment and report on their preliminary application to the study of the denitrification gene nirS in the Choptank River-Chesapeake Bay system. Intergenic and intragenic resolution constraints were determined by an oligonucleotide (70-mer) microarray approach. Complete signal separation was achieved when comparing unrelated genes within the nitrogen cycle (amoA, nifH, nirK, and nirS) and detecting different variants of the same gene, nirK, corresponding to organisms with two different physiological modes, ammonia oxidizers and denitrifying halobenzoate degraders. The limits of intragenic resolution were investigated with a microarray containing 64 nirS sequences comprising 14 cultured organisms and 50 clones obtained from the Choptank River in Maryland. The nirS oligonucleotides covered a range of sequence identities from approximately 40 to 100%. The threshold values for specificity were determined to be 87% sequence identity and a target-to-probe perfect match-to-mismatch binding free-energy ratio of 0.56. The lower detection limit was 10 pg of DNA (equivalent to approximately 107 copies) per target per microarray. Hybridization patterns on the microarray differed between sediment samples from two stations in the Choptank River, implying important differences in the composition of the denitirifer community along an environmental gradient of salinity, inorganic nitrogen, and dissolved organic carbon. This work establishes a useful set of design constraints (independent of the target gene) for the implementation of functional gene microarrays for environmental applications. PMID:12571043

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

    PubMed

    Yergeau, Etienne; Kang, Sanghoon; He, Zhili; Zhou, Jizhong; Kowalchuk, George A

    2007-06-01

    Soil-borne microbial communities were examined via a functional gene microarray approach across a southern polar latitudinal gradient to gain insight into the environmental factors steering soil N- and C-cycling in terrestrial Antarctic ecosystems. The abundance and diversity of functional gene families were studied for soil-borne microbial communities inhabiting a range of environments from 51 degrees S (cool temperate-Falkland Islands) to 72 degrees S (cold rock desert-Coal Nunatak). The recently designed functional gene array used contains 24,243 oligonucleotide probes and covers >10,000 genes in >150 functional groups involved in nitrogen, carbon, sulfur and phosphorus cycling, metal reduction and resistance and organic contaminant degradation (He et al. 2007). The detected N- and C-cycle genes were significantly different across different sampling locations and vegetation types. A number of significant trends were observed regarding the distribution of key gene families across the environments examined. For example, the relative detection of cellulose degradation genes was correlated with temperature, and microbial C-fixation genes were more present in plots principally lacking vegetation. With respect to the N-cycle, denitrification genes were linked to higher soil temperatures, and N2-fixation genes were linked to plots mainly vegetated by lichens. These microarray-based results were confirmed for a number of gene families using specific real-time PCR, enzymatic assays and process rate measurements. The results presented demonstrate the utility of an integrated functional gene microarray approach in detecting shifts in functional community properties in environmental samples and provide insight into the forces driving important processes of terrestrial Antarctic nutrient cycling.

  4. A 3800 gene microarray for cattle functional genomics: comparison of gene expression in spleen, placenta, and brain.

    PubMed

    Band, Mark R; Olmstead, Colleen; Everts, Robin E; Liu, Zonglin L; Lewin, Harris A

    2002-05-01

    A cDNA microarray representing approximately 3800 cattle genes was created for functional genomic studies. The array elements were selected from > 7000 cDNA clones identified in a large-scale expressed sequence tag (EST) project that utilized spleen and normalized and subtracted placenta cDNA libraries. Sequence similarity searches of the 3820 ESTs represented on the array using BLASTN identified 3290 (86.1%) as putative human orthologs, with the remainder consisting of "novel" genes or highly divergent orthologs. Experiments were conducted with a prototype 768 gene microarray created from spleen cDNAs and with the 3800 gene array that included genes from spleen and placenta. The 768 gene array was used to profile RNA transcripts expressed by adult and fetal spleen. The 3800 gene array was used to profile transcripts expressed by adult brain and placenta. Microarray analysis of RNA extracted from fetal and adult spleen identified 29 genes that were differentially expressed two-fold or more. Transcriptional differences of two of these genes, IGJ and CTSS, were confirmed using TaqMan technology. The comparison of brain and placenta revealed 400 genes expressed at higher levels in brain and 72 genes expressed at higher levels in placenta. These results demonstrate the potential power of microarrays for understanding the molecular mechanisms of cattle development, disease resistance, nutrition, fertility and production traits.

  5. Classification and Clustering on Microarray Data for Gene Functional Prediction Using R.

    PubMed

    López-Kleine, Liliana; Kleine, Liliana López; Montaño, Rosa; Torres-Avilés, Francisco

    2016-01-01

    Gene expression data (microarrays and RNA-sequencing data) as well as other kinds of genomic data can be extracted from publicly available genomic data. Here, we explain how to apply multivariate cluster and classification methods on gene expression data. These methods have become very popular and are implemented in freely available software in order to predict the participation of gene products in a specific functional category of interest. Taking into account the availability of data and of these methods, every biological study should apply them in order to obtain knowledge on the organism studied and functional category of interest. A special emphasis is made on the nonlinear kernel classification methods.

  6. Microarray and functional analysis of growth phase-dependent gene regulation in Bordetella bronchiseptica.

    PubMed

    Nicholson, Tracy L; Buboltz, Anne M; Harvill, Eric T; Brockmeier, Susan L

    2009-10-01

    Growth phase-dependent gene regulation has recently been demonstrated to occur in Bordetella pertussis, with many transcripts, including known virulence factors, significantly decreasing during the transition from logarithmic to stationary-phase growth. Given that B. pertussis is thought to have derived from a Bordetella bronchiseptica-like ancestor, we hypothesized that growth phase-dependent gene regulation would also occur in B. bronchiseptica. Microarray analysis revealed and quantitative real-time PCR (qRT-PCR) confirmed that growth phase-dependent gene regulation occurs in B. bronchiseptica, resulting in prominent temporal shifts in global gene expression. Two virulence phenotypes associated with these gene expression changes were tested. We found that growth-dependent increases in expression of some type III secretion system (TTSS) genes led to a growth phase-dependent increase in a TTSS-dependent function, cytotoxicity. Although the transcription of genes encoding adhesins previously shown to mediate adherence was decreased in late-log and stationary phases, we found that the adherence of B. bronchiseptica did not decrease in these later phases of growth. Microarray analysis revealed and qRT-PCR confirmed that growth phase-dependent gene regulation occurred in both Bvg(+) and Bvg(-) phase-locked mutants, indicating that growth phase-dependent gene regulation in B. bronchiseptica can function independently from the BvgAS regulatory system.

  7. Functional analysis of differentially expressed genes associated with glaucoma from DNA microarray data.

    PubMed

    Wu, Y; Zang, W D; Jiang, W

    2014-11-11

    Microarray data of astrocytes extracted from the optic nerves of donors with and without glaucoma were analyzed to screen for differentially expressed genes (DEGs). Functional exploration with bioinformatic tools was then used to understand the roles of the identified DEGs in glaucoma. Microarray data were downloaded from the Gene Expression Omnibus (GEO) database, which contains 13 astrocyte samples, 6 from healthy subjects and 7 from patients suffering from glaucoma. Data were pre-processed, and DEGs were screened out using R software packages. Interactions between DEGs were identified, and networks were built using Search Tool for the Retrieval of Interacting Genes/Proteins (STRING). GENECODIS was utilized for the functional analysis of the DEGs, and GOTM was used for module division, for which functional annotation was conducted with the Database for Annotation, Visualization, and Integrated Discovery (DAVID). A total of 371 DEGs were identified between glaucoma-associated samples and normal samples. Three modules included in the PPID database were generated with 11, 12, and 2 significant functional annotations, including immune system processes, inflammatory responses, and synaptic vesicle endocytosis, respectively. We found that the most significantly enriched functions for each module were associated with immune function. Several genes that play interesting roles in the development of glaucoma are described; these genes may be potential biomarkers for glaucoma diagnosis or treatment.

  8. Microarray Technology Reveals Potentially Novel Genes and Pathways Involved in Non-Functioning Pituitary Adenomas

    PubMed Central

    Qiao, X; Wang, H; Wang, X; Zhao, B; Liu, J

    2016-01-01

    Abstract Microarray data of non-functioning pituitary adenomas (NFPAs) were analyzed to disclose novel genes and pathways involved in NFPA tumorigenesis. Raw microarray data were downloaded from Gene Expression Omnibus. Data pre-treatment and differential analysis were conducted using packages in R. Functional and pathway enrichment analyses were performed using package GOs-tats. A protein-protein interaction (PPI) network was constructed using server STRING and Cytoscape. Known genes involved in pituitary adenomas (PAs), were obtained from the Comparative Toxicogenomics Database. A total of 604 differentially expressed genes (DEGs) were identifed between NFPAs and controls, including 177 up- and 427 down-regulated genes. Jak-STAT and p53 signaling pathways were significantly enriched by DEGs. The PPI network of DEGs was constructed, containing 99 up- and 288 down-regulated known disease genes (e.g. EGFR and ESR1) as well as 16 up- and 17 down-regulated potential novel NFPAs-related genes (e.g. COL4A5, LHX3, MSN, and GHSR). Genes like COL4A5, LHX3, MSN, and GHSR and pathways such as p53 signaling and Jak-STAT signaling, might participate in NFPA development. Although further validations are required, these findings might provide guidance for future basic and therapy researches. PMID:28289583

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

    PubMed

    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.

  10. Functional GPCR microarrays.

    PubMed

    Hong, Yulong; Webb, Brian L; Su, Hui; Mozdy, Eric J; Fang, Ye; Wu, Qi; Liu, Li; Beck, Jonathan; Ferrie, Ann M; Raghavan, Srikanth; Mauro, John; Carre, Alain; Müeller, Dirk; Lai, Fang; Rasnow, Brian; Johnson, Michael; Min, Hosung; Salon, John; Lahiri, Joydeep

    2005-11-09

    This paper describes G-protein-coupled receptor (GPCR) microarrays on porous glass substrates and functional assays based on the binding of a europium-labeled GTP analogue. The porous glass slides were made by casting a glass frit on impermeable glass slides and then coating with gamma-aminopropyl silane (GAPS). The emitted fluorescence was captured on an imager with a time-gated intensified CCD detector. Microarrays of the neurotensin receptor 1, the cholinergic receptor muscarinic 2, the opioid receptor mu, and the cannabinoid receptor 1 were fabricated by pin printing. The selective agonism of each of the receptors was observed. The screening of potential antagonists was demonstrated using a cocktail of agonists. The amount of activation observed was sufficient to permit determinations of EC50 and IC50. Such microarrays could potentially streamline drug discovery by helping integrate primary screening with selectivity and safety screening without compromising the essential functional information obtainable from cellular assays.

  11. Application of random matrix theory to microarray data for discovering functional gene modules.

    PubMed

    Luo, Feng; Zhong, Jianxin; Yang, Yunfeng; Zhou, Jizhong

    2006-03-01

    We show that spectral fluctuation of coexpression correlation matrices of yeast gene microarray profiles follows the description of the Gaussian orthogonal ensemble (GOE) of the random matrix theory (RMT) and removal of small values of the correlation coefficients results in a transition from the GOE statistics to the Poisson statistics of the RMT. This transition is directly related to the structural change of the gene expression network from a global network to a network of isolated modules.

  12. Application of random matrix theory to microarray data for discovering functional gene modules

    SciTech Connect

    Luo, F.; Zhong, Jianxin; Yang, Y. F.; Zhou, Jizhong

    2006-03-01

    We show that spectral fluctuation of coexpression correlation matrices of yeast gene microarray profiles follows the description of the Gaussian orthogonal ensemble (GOE) of the random matrix theory (RMT) and removal of small values of the correlation coefficients results in a transition from the GOE statistics to the Poisson statistics of the RMT. This transition is directly related to the structural change of the gene expression network from a global network to a network of isolated modules.

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

    PubMed

    Short, Michael D; Abell, Guy C J; Bodrossy, Levente; van den Akker, Ben

    2013-01-01

    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.

  14. Application of a Novel Functional Gene Microarray to Probe the Functional Ecology of Ammonia Oxidation in Nitrifying Activated Sludge

    PubMed Central

    Short, Michael D.; Abell, Guy C. J.; Bodrossy, Levente; van den Akker, Ben

    2013-01-01

    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. PMID:24155925

  15. Prediction of optimal gene functions for osteosarcoma using network-based- guilt by association method based on gene oncology and microarray profile.

    PubMed

    Chen, Xinrang

    2017-06-01

    In the current study, we planned to predict the optimal gene functions for osteosarcoma (OS) by integrating network-based method with guilt by association (GBA) principle (called as network-based gene function inference approach) based on gene oncology (GO) data and gene expression profile. To begin with, differentially expressed genes (DEGs) were extracted using linear models for microarray data (LIMMA) package. Then, construction of differential co-expression network (DCN) relying on DEGs was implemented, and sub-DCN was identified using Spearman correlation coefficient (SCC). Subsequently, GO annotations for OS were collected according to known confirmed database and DEGs. Ultimately, gene functions were predicted by means of GBA principle based on the area under the curve (AUC) for GO terms, and we determined GO terms with AUC >0.7 as the optimal gene functions for OS. Totally, 123 DEGs and 137 GO terms were obtained for further analysis. A DCN was constructed, which included 123 DEGs and 7503 interactions. A total of 105 GO terms were identified when the threshold was set as AUC >0.5, which had a good classification performance. Among these 105 GO terms, 2 functions had the AUC >0.7 and were determined as the optimal gene functions including angiogenesis (AUC =0.767) and regulation of immune system process (AUC =0.710). These gene functions appear to have potential for early detection and clinical treatment of OS in the future.

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

    PubMed

    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.

  17. Microarray and functional analysis of growth-phase dependent gene regulation in Bordetella bronchiseptica

    USDA-ARS?s Scientific Manuscript database

    Growth-phase dependent gene regulation has recently been demonstrated to occur in B. pertussis, with many transcripts, including known virulence factors, significantly decreasing during the transition from logarithmic to stationary-phase growth. Given that B. pertussis is thought to have derived fro...

  18. Functional assessment of time course microarray data

    PubMed Central

    Nueda, María José; Sebastián, Patricia; Tarazona, Sonia; García-García, Francisco; Dopazo, Joaquín; Ferrer, Alberto; Conesa, Ana

    2009-01-01

    Motivation Time-course microarray experiments study the progress of gene expression along time across one or several experimental conditions. Most developed analysis methods focus on the clustering or the differential expression analysis of genes and do not integrate functional information. The assessment of the functional aspects of time-course transcriptomics data requires the use of approaches that exploit the activation dynamics of the functional categories to where genes are annotated. Methods We present three novel methodologies for the functional assessment of time-course microarray data. i) maSigFun derives from the maSigPro method, a regression-based strategy to model time-dependent expression patterns and identify genes with differences across series. maSigFun fits a regression model for groups of genes labeled by a functional class and selects those categories which have a significant model. ii) PCA-maSigFun fits a PCA model of each functional class-defined expression matrix to extract orthogonal patterns of expression change, which are then assessed for their fit to a time-dependent regression model. iii) ASCA-functional uses the ASCA model to rank genes according to their correlation to principal time expression patterns and assess functional enrichment on a GSA fashion. We used simulated and experimental datasets to study these novel approaches. Results were compared to alternative methodologies. Results Synthetic and experimental data showed that the different methods are able to capture different aspects of the relationship between genes, functions and co-expression that are biologically meaningful. The methods should not be considered as competitive but they provide different insights into the molecular and functional dynamic events taking place within the biological system under study. PMID:19534758

  19. Functional assessment of time course microarray data.

    PubMed

    Nueda, María José; Sebastián, Patricia; Tarazona, Sonia; García-García, Francisco; Dopazo, Joaquín; Ferrer, Alberto; Conesa, Ana

    2009-06-16

    Time-course microarray experiments study the progress of gene expression along time across one or several experimental conditions. Most developed analysis methods focus on the clustering or the differential expression analysis of genes and do not integrate functional information. The assessment of the functional aspects of time-course transcriptomics data requires the use of approaches that exploit the activation dynamics of the functional categories to where genes are annotated. We present three novel methodologies for the functional assessment of time-course microarray data. i) maSigFun derives from the maSigPro method, a regression-based strategy to model time-dependent expression patterns and identify genes with differences across series. maSigFun fits a regression model for groups of genes labeled by a functional class and selects those categories which have a significant model. ii) PCA-maSigFun fits a PCA model of each functional class-defined expression matrix to extract orthogonal patterns of expression change, which are then assessed for their fit to a time-dependent regression model. iii) ASCA-functional uses the ASCA model to rank genes according to their correlation to principal time expression patterns and assess functional enrichment on a GSA fashion. We used simulated and experimental datasets to study these novel approaches. Results were compared to alternative methodologies. Synthetic and experimental data showed that the different methods are able to capture different aspects of the relationship between genes, functions and co-expression that are biologically meaningful. The methods should not be considered as competitive but they provide different insights into the molecular and functional dynamic events taking place within the biological system under study.

  20. Microarray-based gene expression profiling reveals genes and pathways involved in the oncogenic function of REG3A on pancreatic cancer cells.

    PubMed

    Xu, Qianqian; Fu, Rong; Yin, Guoxiao; Liu, Xiulan; Liu, Yang; Xiang, Ming

    2016-03-10

    We previously reported that regenerating islet-derived protein 3 alpha (REG3A) exacerbates pancreatic malignancies. The mechanism of this effect has not been clearly elucidated. Here we first identified key differentially expressed genes (DEGs) and signal pathways in the pancreatic cancer cell line SW1990, compared to two control cell lines, by microarray analysis. We then identified key genes and pathways regulated by REG3A or the cytokine IL6 in SW1990 cells. Afterwards, these DEGs induced by REG3A or IL6 were subjected to KEGG pathway enrichment analysis and GO function analysis by the DAVID online tool. Ultimately, we constructed protein-protein interaction networks among the DEGs by Cytoscape. Among the three pancreatic cell lines, SW1990 exhibited highly deterioration with the activation of genes and pathways related to proliferation, survival, angiogenesis, and invasion. As a result, 50 DEGs enriched in 11 pathways were identified in REG3A-treated SW1990 cells, and 28 DEGs enriched in 9 pathways were detected in IL6-treated cells. Overall, results of microarray analysis followed by qRT-PCR and Western blotting suggest that REG3A regulates pancreatic cell growth by increasing the expression of at least 8 genes: JAK1, STAT3, IL10, FOXM1, KRAS, MYC, CyclinD1, and c-fos; and activation of at least 4 signal pathways: TGFβ, PDGF, angiogenesis and RAS. Similar results were obtained with IL6 treatment. Regulation network analysis confirmed the cell growth related DEGs, and further uncovered three transcription factor families with immune functions regulated by REG3A.

  1. Ammonia-oxidizing bacterial community composition in estuarine and oceanic environments assessed using a functional gene microarray

    USGS Publications Warehouse

    Ward, B.B.; Eveillard, D.; Kirshtein, J.D.; Nelson, J.D.; Voytek, M.A.; Jackson, G.A.

    2007-01-01

    The relationship between environmental factors and functional gene diversity of ammonia-oxidizing bacteria (AOB) was investigated across a transect from the freshwater portions of the Chesapeake Bay and Choptank River out into the Sargasso Sea. Oligonucleotide probes (70-bp) designed to represent the diversity of ammonia monooxygenase (amoA) genes from Chesapeake Bay clone libraries and cultivated AOB were used to construct a glass slide microarray. Hybridization patterns among the probes in 14 samples along the transect showed clear variations in amoA community composition. Probes representing uncultivated members of the Nitrosospira-like AOB dominated the probe signal, especially in the more marine samples. Of the cultivated species, only Nitrosospira briensis was detected at appreciable levels. Discrimination analysis of hybridization signals detected two guilds. Guild 1 was dominated by the marine Nitrosospira-like probe signal, and Guild 2???s largest contribution was from upper bay (freshwater) sediment probes. Principal components analysis showed that Guild 1 was positively correlated with salinity, temperature and chlorophyll a concentration, while Guild 2 was positively correlated with concentrations of oxygen, dissolved organic carbon, and particulate nitrogen and carbon, suggesting that different amoA sequences represent organisms that occupy different ecological niches within the estuarine/marine environment. The trend from most diversity of AOB in the upper estuary towards dominance of a single type in the polyhaline region of the Bay is consistent with the declining importance of AOB with increasing salinity, and with the idea that AO-Archaea are the more important ammonia oxidizers in the ocean. ?? 2007 The Authors.

  2. Expression Atlas update—a database of gene and transcript expression from microarray- and sequencing-based functional genomics experiments

    PubMed Central

    Petryszak, Robert; Burdett, Tony; Fiorelli, Benedetto; Fonseca, Nuno A.; Gonzalez-Porta, Mar; Hastings, Emma; Huber, Wolfgang; Jupp, Simon; Keays, Maria; Kryvych, Nataliya; McMurry, Julie; Marioni, John C.; Malone, James; Megy, Karine; Rustici, Gabriella; Tang, Amy Y.; Taubert, Jan; Williams, Eleanor; Mannion, Oliver; Parkinson, Helen E.; Brazma, Alvis

    2014-01-01

    Expression Atlas (http://www.ebi.ac.uk/gxa) is a value-added database providing information about gene, protein and splice variant expression in different cell types, organism parts, developmental stages, diseases and other biological and experimental conditions. The database consists of selected high-quality microarray and RNA-sequencing experiments from ArrayExpress that have been manually curated, annotated with Experimental Factor Ontology terms and processed using standardized microarray and RNA-sequencing analysis methods. The new version of Expression Atlas introduces the concept of ‘baseline’ expression, i.e. gene and splice variant abundance levels in healthy or untreated conditions, such as tissues or cell types. Differential gene expression data benefit from an in-depth curation of experimental intent, resulting in biologically meaningful ‘contrasts’, i.e. instances of differential pairwise comparisons between two sets of biological replicates. Other novel aspects of Expression Atlas are its strict quality control of raw experimental data, up-to-date RNA-sequencing analysis methods, expression data at the level of gene sets, as well as genes and a more powerful search interface designed to maximize the biological value provided to the user. PMID:24304889

  3. Combining qPCR and functional gene microarrays to directly link changes in the expression of the nirS gene to denitrification rates in aquatic sediment mesocosms

    NASA Astrophysics Data System (ADS)

    Bowen, J. L.; Babbin, A. R.; Ward, B. B.

    2010-12-01

    Molecular methods for the investigation of biogeochemical processes, including denitrification, are being developed at an astonishing rate, but it remains difficult to use the molecular information to understand the regulation and variation in biogeochemical transformation rates. By combining information on gene abundance and expression for nirS, a key gene in denitrification, with quantitative modeling of nitrogen fluxes, we can begin to understand the scales on which genetic signals vary in space and time, and how they relate to biogeochemical function. We used quantitative PCR, a functional gene microarray, and biogeochemical modeling to assess how denitrifier community composition (evaluated by DNA and cDNA of the nirS gene) changed over time in estuarine sediment mesocosms. Sediments and water were collected from coastal Massachusetts and maintained in replicated 20 L mesocosm experiments for 45 days. Sediments were collected for microbial analysis at weekly intervals throughout the experiment. Concentrations of all major nitrogen species were measured daily and used to derive rates of nitrification and denitrification from a Monte Carlo-based nonnegative least-squares analysis of finite difference equations. Denitrification rates peaked between day 18 and day 22, slightly after the peaks in nitrite concentration that were generated from oxidization of remineralized ammonium. In most mesocosms the peak in denitrification rates coincided with the peak in nirS gene abundance (DNA). Peaks in the expression of the nirS gene (cDNA), however, did not always correlate with peaks in the denitrification rates. The nirS microarray contained 39 archetype probes, three of which accounted for more than 60% of the DNA hybridization signal. Two of these clades also dominated the hybridization signal in cDNA, indicating that those organisms that are actively expressing nirS are not always the dominant members of the community. Fifteen of the 39 probes accounted for less than

  4. Microarrays

    ERIC Educational Resources Information Center

    Plomin, Robert; Schalkwyk, Leonard C.

    2007-01-01

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

  5. Microarrays

    ERIC Educational Resources Information Center

    Plomin, Robert; Schalkwyk, Leonard C.

    2007-01-01

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

  6. Microarray studies of psychostimulant-induced changes in gene expression.

    PubMed

    Yuferov, Vadim; Nielsen, David; Butelman, Eduardo; Kreek, Mary Jeanne

    2005-03-01

    Alterations in the expression of multiple genes in many brain regions are likely to contribute to psychostimulant-induced behaviours. Microarray technology provides a powerful tool for the simultaneous interrogation of gene expression levels of a large number of genes. Several recent experimental studies, reviewed here, demonstrate the power, limitations and progress of microarray technology in the field of psychostimulant addiction. These studies vary in the paradigms of cocaine or amphetamine administration, drug doses, route and also mode of administration, duration of treatment, animal species, brain regions studied and time of tissue collection after final drug administration. The studies also utilize different microarray platforms and statistical techniques for analysis of differentially expressed genes. These variables influence substantially the results of these studies. It is clear that current microarray techniques cannot detect small changes reliably in gene expression of genes with low expression levels, including functionally significant changes in components of major neurotransmission systems such as glutamate, dopamine, opioid and GABA receptors, especially those that may occur after chronic drug administration or drug withdrawal. However, the microarray studies reviewed here showed cocaine- or amphetamine-induced alterations in the expression of numerous genes involved in the modulation of neuronal growth, cytoskeletal structures, synaptogenesis, signal transduction, apoptosis and cell metabolism. Application of laser capture microdissection and single-cell cDNA amplification may greatly enhance microarray studies of gene expression profiling. The combination of rapidly evolving microarray technology with established methods of neuroscience, molecular biology and genetics, as well as appropriate behavioural models of drug reinforcement, may provide a productive approach for delineating the neurobiological underpinnings of drug responses that lead to

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

    PubMed

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

    2016-12-01

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

  8. An insight into the key genes and biological functions associated with insulin resistance in adipose tissue with microarray technology.

    PubMed

    Zhang, Li; Cui, Ying; Fu, Fangming; Li, Zhenzuo; Pan, Xiaoxia; Li, Hongzhuan; Li, Lin

    2015-03-01

    In the present study, the key genes and biological functions associated with insulin resistance were investigated by comparing the gene expression profiles of adipose tissue obtained from insulin‑sensitive and insulin‑resistant patients. The gene expression data set GSE20950 was downloaded from the Gene Expression Omnibus, including 39 adipose tissue samples obtained from insulin‑sensitive and insulin‑resistant patients undergoing gastric bypass surgery. Adipose samples were divided into two groups (the insulin‑sensitive and insulin‑resistant groups) and the differentially expressed genes (DEGs) were screened out with packages of R. The interactions among DEGs were retrieved with Osprey and functional enrichment analysis was performed with the WebGestalt system. Information regarding the interaction network and enriched biological functions was combined to construct a functional interaction network. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis was then conducted using the Database for Annotation, Visualization and Integrated Discovery. A total of 170 DEGs were detected in the insulin‑sensitive group, 8 downregulated and 162 upregulated. Response to glucose stimulus was the most significantly over‑represented functional term. The focal adhesion pathway was identified to be significant in the genes of the functional interaction network. The present study revealed key biological functions and DEGs in adipose tissues associated with insulin resistance, which may facilitate the development of novel therapies for insulin resistance and diabetes.

  9. 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

    PubMed Central

    2012-01-01

    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, respectively, after

  10. Microarray Analysis of Pneumococcal Gene Expression during Invasive Disease

    PubMed Central

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

    2004-01-01

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

  11. Abnormal expression of the genes involved in cytokine networks and mitochondrial function in systemic juvenile idiopathic arthritis identified by DNA microarray analysis.

    PubMed

    Ishikawa, S; Mima, T; Aoki, C; Yoshio-Hoshino, N; Adachi, Y; Imagawa, T; Mori, M; Tomiita, M; Iwata, N; Murata, T; Miyoshi, M; Takei, S; Aihara, Y; Yokota, S; Matsubara, K; Nishimoto, N

    2009-02-01

    Systemic juvenile idiopathic arthritis (sJIA) is a rheumatic disease in childhood characterised by systemic symptoms and a relatively poor prognosis. Peripheral leukocytes are thought to play a pathological role in sJIA although the exact cause of the disease is still obscure. In this study, we aimed to clarify cellular functional abnormalities in sJIA. We analysed the gene expression profile in peripheral leukocytes from 51 patients with sJIA, 6 patients with polyarticular type JIA (polyJIA) and 8 healthy children utilising DNA microarrays. Gene ontology analysis and network analysis were performed on the genes differentially expressed in sJIA to clarify the cellular functional abnormalities. A total of 3491 genes were differentially expressed in patients with sJIA compared to healthy individuals. They were functionally categorised mainly into a defence response group and a metabolism group according to gene ontology, suggesting the possible abnormalities in these functions. In the defence response group, molecules predominantly constituting interferon (IFN)gamma and tumour necrosis factor (TNF) network cascades were upregulated. In the metabolism group, oxidative phosphorylation-related genes were downregulated, suggesting a mitochondrial disorder. Expression of mitochondrial DNA-encoded genes including cytochrome c oxidase subunit 1(MT-CO1) and MT-CO2 were suppressed in patients with sJIA but not in patients with polyJIA or healthy children. However, nuclear DNA-encoded cytochrome c oxidases were intact. Our findings suggest that sJIA is not only an immunological disease but also a metabolic disease involving mitochondria disorder.

  12. Whole-genome microarray analysis and functional characterization reveal distinct gene expression profiles and patterns in two mouse models of ileal inflammation.

    PubMed

    Avula, Leela Rani; Knapen, Dries; Buckinx, Roeland; Vergauwen, Lucia; Adriaensen, Dirk; Van Nassauw, Luc; Timmermans, Jean-Pierre

    2012-08-06

    Although a number of intestinal inflammatory conditions pertain to the ileum, whole-genome gene expression analyses in animal models of ileal inflammation are lacking to date. Therefore, we aimed to identify and characterize alterations in gene expression in the acutely inflamed ileum of two murine models of intestinal inflammation, namely intestinal schistosomiasis and TNBS-induced ileitis, compared to healthy controls. To this end, we used whole-genome microarrays, followed by bioinformatics analyses to detect over-represented Kyoto Encyclopedia of Genes and Genomes pathways and Gene Ontology categories. Following screening of almost all known mouse genes and transcripts represented on the array, intestinal schistosomiasis and TNBS-induced ileitis yielded 207 and 1417 differentially expressed genes, respectively, with only 30 overlapping concordantly changed genes. Functional category groups consisting of complement and coagulation cascades, extracellular matrix (ECM)-receptor interaction, Fc epsilon receptor I signaling pathways and protein activation cascade, cell adhesion categories were over-represented in the differential gene list of intestinal schistosomiasis. Antigen processing and presentation, cell adhesion molecules, ABC transporters, Toll-like receptor signaling pathways and response to chemical stimulus categories were over-represented in the differential gene list of TNBS-induced ileitis. Although cytokine-cytokine receptor interaction, intestinal immune network for IgA production, focal adhesion pathways and immune, inflammatory and defense response categories were over-represented in the differential gene lists of both inflammation models, the vast majority of the associated genes and changes were unique to each model. This study characterized two models of ileal inflammation at a whole-genome level and outlined distinct gene expression profiles and patterns in the two models. The results indicate that intestinal schistosomiasis involves Th2

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

    PubMed

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

    2012-12-18

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

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

    PubMed Central

    2012-01-01

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

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

    PubMed Central

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

    2016-01-01

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

  16. Posttranslational Modification Assays on Functional Protein Microarrays.

    PubMed

    Neiswinger, Johnathan; Uzoma, Ijeoma; Cox, Eric; Rho, HeeSool; Jeong, Jun Seop; Zhu, Heng

    2016-10-03

    Protein microarray technology provides a straightforward yet powerful strategy for identifying substrates of posttranslational modifications (PTMs) and studying the specificity of the enzymes that catalyze these reactions. Protein microarray assays can be designed for individual enzymes or a mixture to establish connections between enzymes and substrates. Assays for four well-known PTMs-phosphorylation, acetylation, ubiquitylation, and SUMOylation-have been developed and are described here for use on functional protein microarrays. Phosphorylation and acetylation require a single enzyme and are easily adapted for use on an array. The ubiquitylation and SUMOylation cascades are very similar, and the combination of the E1, E2, and E3 enzymes plus ubiquitin or SUMO protein and ATP is sufficient for in vitro modification of many substrates.

  17. Assessment of gene set analysis methods based on microarray data.

    PubMed

    Alavi-Majd, Hamid; Khodakarim, Soheila; Zayeri, Farid; Rezaei-Tavirani, Mostafa; Tabatabaei, Seyyed Mohammad; Heydarpour-Meymeh, Maryam

    2014-01-25

    Gene set analysis (GSA) incorporates biological information into statistical knowledge to identify gene sets differently expressed between two or more phenotypes. It allows us to gain an insight into the functional working mechanism of cells beyond the detection of differently expressed gene sets. In order to evaluate the competence of GSA approaches, three self-contained GSA approaches with different statistical methods were chosen; Category, Globaltest and Hotelling's T(2) together with their assayed power to identify the differences expressed via simulation and real microarray data. The Category does not take care of the correlation structure, while the other two deal with correlations. In order to perform these methods, R and Bioconductor were used. Furthermore, venous thromboembolism and acute lymphoblastic leukemia microarray data were applied. The results of three GSAs showed that the competence of these methods depends on the distribution of gene expression in a dataset. It is very important to assay the distribution of gene expression data before choosing the GSA method to identify gene sets differently expressed between phenotypes. On the other hand, assessment of common genes among significant gene sets indicated that there was a significant agreement between the result of GSA and the findings of biologists. © 2013 Elsevier B.V. All rights reserved.

  18. Washing scaling of GeneChip microarray expression

    PubMed Central

    2010-01-01

    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 'washing data set' which might

  19. Gene expression profiling in peanut using high density oligonucleotide microarrays

    PubMed Central

    Payton, Paxton; Kottapalli, Kameswara Rao; Rowland, Diane; Faircloth, Wilson; Guo, Baozhu; Burow, Mark; Puppala, Naveen; Gallo, Maria

    2009-01-01

    Background Transcriptome expression analysis in peanut to date has been limited to a relatively small set of genes and only recently has a significant number of ESTs been released into the public domain. Utilization of these ESTs for oligonucleotide microarrays provides a means to investigate large-scale transcript responses to a variety of developmental and environmental signals, ultimately improving our understanding of plant biology. Results We have developed a high-density oligonucleotide microarray for peanut using 49,205 publicly available ESTs and tested the utility of this array for expression profiling in a variety of peanut tissues. To identify putatively tissue-specific genes and demonstrate the utility of this array for expression profiling in a variety of peanut tissues, we compared transcript levels in pod, peg, leaf, stem, and root tissues. Results from this experiment showed 108 putatively pod-specific/abundant genes, as well as transcripts whose expression was low or undetected in pod compared to peg, leaf, stem, or root. The transcripts significantly over-represented in pod include genes responsible for seed storage proteins and desiccation (e.g., late-embryogenesis abundant proteins, aquaporins, legumin B), oil production, and cellular defense. Additionally, almost half of the pod-abundant genes represent unknown genes allowing for the possibility of associating putative function to these previously uncharacterized genes. Conclusion The peanut oligonucleotide array represents the majority of publicly available peanut ESTs and can be used as a tool for expression profiling studies in diverse tissues. PMID:19523230

  20. Gene Expression Atlas update—a value-added database of microarray and sequencing-based functional genomics experiments

    PubMed Central

    Kapushesky, Misha; Adamusiak, Tomasz; Burdett, Tony; Culhane, Aedin; Farne, Anna; Filippov, Alexey; Holloway, Ele; Klebanov, Andrey; Kryvych, Nataliya; Kurbatova, Natalja; Kurnosov, Pavel; Malone, James; Melnichuk, Olga; Petryszak, Robert; Pultsin, Nikolay; Rustici, Gabriella; Tikhonov, Andrew; Travillian, Ravensara S.; Williams, Eleanor; Zorin, Andrey; Parkinson, Helen; Brazma, Alvis

    2012-01-01

    Gene Expression Atlas (http://www.ebi.ac.uk/gxa) is an added-value database providing information about gene expression in different cell types, organism parts, developmental stages, disease states, sample treatments and other biological/experimental conditions. The content of this database derives from curation, re-annotation and statistical analysis of selected data from the ArrayExpress Archive and the European Nucleotide Archive. A simple interface allows the user to query for differential gene expression either by gene names or attributes or by biological conditions, e.g. diseases, organism parts or cell types. Since our previous report we made 20 monthly releases and, as of Release 11.08 (August 2011), the database supports 19 species, which contains expression data measured for 19 014 biological conditions in 136 551 assays from 5598 independent studies. PMID:22064864

  1. MGDB: crossing the marker genes of a user microarray with a database of public-microarrays marker genes.

    PubMed

    Huerta, Mario; Munyi, Marc; Expósito, David; Querol, Enric; Cedano, Juan

    2014-06-15

    The microarrays performed by scientific teams grow exponentially. These microarray data could be useful for researchers around the world, but unfortunately they are underused. To fully exploit these data, it is necessary (i) to extract these data from a repository of the high-throughput gene expression data like Gene Expression Omnibus (GEO) and (ii) to make the data from different microarrays comparable with tools easy to use for scientists. We have developed these two solutions in our server, implementing a database of microarray marker genes (Marker Genes Data Base). This database contains the marker genes of all GEO microarray datasets and it is updated monthly with the new microarrays from GEO. Thus, researchers can see whether the marker genes of their microarray are marker genes in other microarrays in the database, expanding the analysis of their microarray to the rest of the public microarrays. This solution helps not only to corroborate the conclusions regarding a researcher's microarray but also to identify the phenotype of different subsets of individuals under investigation, to frame the results with microarray experiments from other species, pathologies or tissues, to search for drugs that promote the transition between the studied phenotypes, to detect undesirable side effects of the treatment applied, etc. Thus, the researcher can quickly add relevant information to his/her studies from all of the previous analyses performed in other studies as long as they have been deposited in public repositories. Marker-gene database tool: http://ibb.uab.es/mgdb © The Author 2014. Published by Oxford University Press.

  2. Analysis of Mycobacterium leprae gene expression using DNA microarray.

    PubMed

    Akama, Takeshi; Tanigawa, Kazunari; Kawashima, Akira; Wu, Huhehasi; Ishii, Norihisa; Suzuki, Koichi

    2010-10-01

    Mycobacterium leprae, the causative agent of leprosy, does not grow under in vitro condition, making molecular analysis of this bacterium difficult. For this reason, bacteriological information regarding M. leprae gene function is limited compared with other mycobacterium species. In this study, we performed DNA microarray analysis to clarify the RNA expression profile of the Thai53 strain of M. leprae grown in footpads of hypertensive nude rats (SHR/NCrj-rnu). Of 1605 M. leprae genes, 315 showed signal intensity twofold higher than the median. These genes include Acyl-CoA metabolic enzymes and drug metabolic enzymes, which might be related to the virulence of M. leprae. In addition, consecutive RNA expression profile and in silico analyses enabled identification of possible operons within the M. leprae genome. The present results will shed light on M. leprae gene function and further our understanding of the pathogenesis of leprosy.

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

    PubMed Central

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

    2008-01-01

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

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

    PubMed

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

    2008-07-03

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

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

    PubMed

    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.

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

    PubMed

    Kim, Hi Chul; Kim, Gi-Hwan; Cho, Ssang-Goo; Lee, Eun Ju; Kwon, Yong-Jun

    2016-03-01

    Small interfering RNA (siRNA) screening approaches have provided useful tools for the validation of genetic functions; however, image-based siRNA screening using multiwell plates requires large numbers of cells and time, which could be the barrier in application for gene mechanisms study using human adult cells. Therefore, we developed the advanced method with the cell-defined siRNA microarray (CDSM), for functional analysis of genes in small scale within slide glass using human bone marrow stromal cells (hBMSCs). We designed cell spot system with biomaterials (sucrose, gelatin, poly-L-lysine and matrigel) to control the attachment of hBMSCs inside spot area on three-dimensional (3D) hydrogel-coated slides. The p65 expression was used as a validation standard which described our previous report. For the optimization of siRNA mixture, first, we detected five kinds of commercialized reagent (Lipofectamine 2000, RNAi-Max, Metafectine, Metafectine Pro, TurboFectin 8.0) via validation. Then, according to quantification of p65 expression, we selected 2 μl of RNAi-Max as the most effective reagent condition on our system. Using same validation standard, we optimized sucrose and gelatin concentration (80 mM and 0.13%), respectively. Next, we performed titration of siRNA quantity (2.66-5.55 μM) by reverse transfection time (24 h, 48 h, 72 h) and confirmed 3.75 μM siRNA concentration and 48 h as the best condition. To sum up the process for optimized CDSM, 3 μl of 20 μM siRNA (3.75 μM) was transferred to the 384-well V-bottom plate containing 2 μl of dH2O and 2 μl of 0.6M sucrose (80 mM). Then, 2 μl of RNAi-Max was added and incubated for 20 min at room temperature after mixing gently and centrifugation shortly. Five microliters of gelatin (0.26%) and 2 μl of growth factor reduced phenol red-free matrigel (12.5%) were added and mixed by pipetting gently. Finally, optimized siRNA mixture was printed on 3D hydrogel-coated slides and cell-defined attachment and si

  7. Construction of citrus gene coexpression networks from microarray data using random matrix theory.

    PubMed

    Du, Dongliang; Rawat, Nidhi; Deng, Zhanao; Gmitter, Fred G

    2015-01-01

    After the sequencing of citrus genomes, gene function annotation is becoming a new challenge. Gene coexpression analysis can be employed for function annotation using publicly available microarray data sets. In this study, 230 sweet orange (Citrus sinensis) microarrays were used to construct seven coexpression networks, including one condition-independent and six condition-dependent (Citrus canker, Huanglongbing, leaves, flavedo, albedo, and flesh) networks. In total, these networks contain 37 633 edges among 6256 nodes (genes), which accounts for 52.11% measurable genes of the citrus microarray. Then, these networks were partitioned into functional modules using the Markov Cluster Algorithm. Significantly enriched Gene Ontology biological process terms and KEGG pathway terms were detected for 343 and 60 modules, respectively. Finally, independent verification of these networks was performed using another expression data of 371 genes. This study provides new targets for further functional analyses in citrus.

  8. Construction of citrus gene coexpression networks from microarray data using random matrix theory

    PubMed Central

    Du, Dongliang; Rawat, Nidhi; Deng, Zhanao; Gmitter, Fred G.

    2015-01-01

    After the sequencing of citrus genomes, gene function annotation is becoming a new challenge. Gene coexpression analysis can be employed for function annotation using publicly available microarray data sets. In this study, 230 sweet orange (Citrus sinensis) microarrays were used to construct seven coexpression networks, including one condition-independent and six condition-dependent (Citrus canker, Huanglongbing, leaves, flavedo, albedo, and flesh) networks. In total, these networks contain 37 633 edges among 6256 nodes (genes), which accounts for 52.11% measurable genes of the citrus microarray. Then, these networks were partitioned into functional modules using the Markov Cluster Algorithm. Significantly enriched Gene Ontology biological process terms and KEGG pathway terms were detected for 343 and 60 modules, respectively. Finally, independent verification of these networks was performed using another expression data of 371 genes. This study provides new targets for further functional analyses in citrus. PMID:26504573

  9. Microarray analysis reveals differential gene expression in hybrid sunflower species

    PubMed Central

    LAI, ZHAO; GROSS, BRIANA L.; YIZOU; ANDREWS, JUSTEN; RIESEBERG, LOREN H.

    2008-01-01

    This paper describes the creation of a cDNA microarray for annual sunflowers and its use to elucidate patterns of gene expression in Helianthus annuus, Helianthus petiolaris, and the homoploid hybrid species Helianthus deserticola. The array comprises 3743 ESTs (expressed sequence tags) representing approximately 2897 unique genes. It has an average clone/EST identity rate of 91%, is applicable across species boundaries within the annual sunflowers, and shows patterns of gene expression that are highly reproducible according to real-time RT–PCR (reverse transcription–polymerase chain reaction) results. Overall, 12.8% of genes on the array showed statistically significant differential expression across the three species. Helianthus deserticola displayed transgressive, or extreme, expression for 58 genes, with roughly equal numbers exhibiting up- or down-regulation relative to both parental species. Transport-related proteins were strongly over-represented among the transgressively expressed genes, which makes functional sense given the extreme desert floor habitat of H. deserticola. The potential adaptive value of differential gene expression was evaluated for five genes in two populations of early generation (BC2) hybrids between the parental species grown in the H. deserticola habitat. One gene (a G protein-coupled receptor) had a significant association with fitness and maps close to a QTL controlling traits that may be adaptive in the desert habitat. PMID:16626449

  10. Emerging Use of Gene Expression Microarrays in Plant Physiology

    DOE PAGES

    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 weremore » 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.« less

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

    PubMed

    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.

  12. Microarray-Based Detection and Typing of the Rhizobium Nodulation Gene nodC: Potential of DNA Arrays To Diagnose Biological Functions of Interest†

    PubMed Central

    Bontemps, Cyril; Golfier, Geoffroy; Gris-Liebe, Carine; Carrere, Sébastien; Talini, Luc; Boivin-Masson, Catherine

    2005-01-01

    Environmental screening of bacteria for the presence of genes of interest is a challenging problem, due to the high variability of the nucleotide sequence of a given gene between species. Here, we tackle this general issue using a particularly well-suited model system that consists of the nodulation gene nodC, which is shared by phylogenetically distant rhizobia. 41mer and 50mer oligonucleotides featuring the nucleotide diversity of two highly conserved regions of the NodC protein were spotted on glass slides and cross hybridized with the radioactive-labeled target genomic DNA under low-stringency conditions. Statistical analysis of the hybridization patterns allowed the detection of known, as well as new, nodC sequences and classified the rhizobial strains accordingly. The microarray was successfully used to type the nodC gene directly from legume nodules, thus eliminating the need of cultivation of the endosymbiont. This approach could be extended to a panel of diagnostic genes and constitute a powerful tool for studying the distribution of genes of interest in the environment, as well as for bacteria identification. PMID:16332784

  13. Xylella fastidiosa gene expression analysis by DNA microarrays

    PubMed Central

    2009-01-01

    Xylella fastidiosa genome sequencing has generated valuable data by identifying genes acting either on metabolic pathways or in associated pathogenicity and virulence. Based on available information on these genes, new strategies for studying their expression patterns, such as microarray technology, were employed. A total of 2,600 primer pairs were synthesized and then used to generate fragments using the PCR technique. The arrays were hybridized against cDNAs labeled during reverse transcription reactions and which were obtained from bacteria grown under two different conditions (liquid XDM2 and liquid BCYE). All data were statistically analyzed to verify which genes were differentially expressed. In addition to exploring conditions for X. fastidiosa genome-wide transcriptome analysis, the present work observed the differential expression of several classes of genes (energy, protein, amino acid and nucleotide metabolism, transport, degradation of substances, toxins and hypothetical proteins, among others). The understanding of expressed genes in these two different media will be useful in comprehending the metabolic characteristics of X. fastidiosa, and in evaluating how important certain genes are for the functioning and survival of these bacteria in plants. PMID:21637690

  14. Gene expression profiles in varicose veins using complementary DNA microarray.

    PubMed

    Lee, Seokjong; Lee, Wonchae; Choe, Yoonseok; Kim, Dowon; Na, Gunyeon; Im, Sanguk; Kim, Jinoh; Kim, Moonkyu; Kim, Jungchul; Cho, Joonyong

    2005-04-01

    There has been little information reported about the genetic event concerning the pathophysiology of varicose vein (VV). The purpose of this study was to examine the differentiation of gene expression in the wall of VV using complementary deoxyribonucleic acid (cDNA) microarrays. The study was performed with four pairs of VVs and control veins (CVs). cDNA specimens of VVs were prepared from the ribonucleic acid-isolated VVs of patients who underwent venous obliteration, using radiofrequency, as well as from CVs of those who underwent aortocoronary bypass grafting. Each set of VVs and CVs was hybridized with high-density microarray containing 3,063 human cDNAs. The finding of microarray hybridization were scanned, analyzed, and classified with the cluster program. Among 3,063 cDNA clones, 82 genes were up-regulated in VVs, and some of the up-regulated genes, which were detected by cDNA microarray, including transforming growth factor 3-induced gene (BIGH3), tubulin, lumican, actinin, collagen type I, versican, actin, and tropomyosin, belonged to extracelluar matrix molecules, cytoskeletal proteins, or myofibroblasts. Many up-regulated genes were found in Ws by applying cDNA microarray. These gene profiles suggested a pathway associated with fibrosis and that wound healing might be related to the pathophysiology of VVs.

  15. Gene expression profiling of mouse embryos with microarrays

    PubMed Central

    Sharov, Alexei A.; Piao, Yulan; Ko, Minoru S. H.

    2011-01-01

    Global expression profiling by DNA microarrays provides a snapshot of cell and tissue status and becomes an essential tool in biological and medical sciences. Typical questions that can be addressed by microarray analysis in developmental biology include: (1) to find a set of genes expressed in a specific cell type; (2) to identify genes expressed commonly in multiple cell types; (3) to follow the time-course changes of gene expression patterns; (4) to demonstrate cell’s identity by showing similarities or differences among two or multiple cell types; (5) to find regulatory pathways and/or networks affected by gene manipulations, such as overexpression or repression of gene expression; (6) to find downstream target genes of transcription factors; (7) to find downstream target genes of cell signaling; (8) to examine the effects of environmental manipulation of cells on gene expression patterns; and (9) to find the effects of genetic manipulation in embryos and adults. Here we describe strategies for executing these experiments and monitoring changes of cell state with gene expression microarrays in application to mouse embryology. Both statistical assessment and interpretation of data are discussed. We also present a protocol for performing microarray analysis on a small amount of embryonic materials. PMID:20699157

  16. Regularized gene selection in cancer microarray meta-analysis.

    PubMed

    Ma, Shuangge; Huang, Jian

    2009-01-01

    In cancer studies, it is common that multiple microarray experiments are conducted to measure the same clinical outcome and expressions of the same set of genes. An important goal of such experiments is to identify a subset of genes that can potentially serve as predictive markers for cancer development and progression. Analyses of individual experiments may lead to unreliable gene selection results because of the small sample sizes. Meta analysis can be used to pool multiple experiments, increase statistical power, and achieve more reliable gene selection. The meta analysis of cancer microarray data is challenging because of the high dimensionality of gene expressions and the differences in experimental settings amongst different experiments. We propose a Meta Threshold Gradient Descent Regularization (MTGDR) approach for gene selection in the meta analysis of cancer microarray data. The MTGDR has many advantages over existing approaches. It allows different experiments to have different experimental settings. It can account for the joint effects of multiple genes on cancer, and it can select the same set of cancer-associated genes across multiple experiments. Simulation studies and analyses of multiple pancreatic and liver cancer experiments demonstrate the superior performance of the MTGDR. The MTGDR provides an effective way of analyzing multiple cancer microarray studies and selecting reliable cancer-associated genes.

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

    PubMed

    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.

  18. Gene Expression Browser: large-scale and cross-experiment microarray data integration, management, search & visualization

    PubMed Central

    2010-01-01

    Background In the last decade, a large amount of microarray gene expression data has been accumulated in public repositories. Integrating and analyzing high-throughput gene expression data have become key activities for exploring gene functions, gene networks and biological pathways. Effectively utilizing these invaluable microarray data remains challenging due to a lack of powerful tools to integrate large-scale gene-expression information across diverse experiments and to search and visualize a large number of gene-expression data points. Results Gene Expression Browser is a microarray data integration, management and processing system with web-based search and visualization functions. An innovative method has been developed to define a treatment over a control for every microarray experiment to standardize and make microarray data from different experiments homogeneous. In the browser, data are pre-processed offline and the resulting data points are visualized online with a 2-layer dynamic web display. Users can view all treatments over control that affect the expression of a selected gene via Gene View, and view all genes that change in a selected treatment over control via treatment over control View. Users can also check the changes of expression profiles of a set of either the treatments over control or genes via Slide View. In addition, the relationships between genes and treatments over control are computed according to gene expression ratio and are shown as co-responsive genes and co-regulation treatments over control. Conclusion Gene Expression Browser is composed of a set of software tools, including a data extraction tool, a microarray data-management system, a data-annotation tool, a microarray data-processing pipeline, and a data search & visualization tool. The browser is deployed as a free public web service (http://www.ExpressionBrowser.com) that integrates 301 ATH1 gene microarray experiments from public data repositories (viz. the Gene

  19. Microarray and Functional Gene Analyses of Sulfate-Reducing Prokaryotes in Low-Sulfate, Acidic Fens Reveal Cooccurrence of Recognized Genera and Novel Lineages

    PubMed Central

    Loy, Alexander; Küsel, Kirsten; Lehner, Angelika; Drake, Harold L.; Wagner, Michael

    2004-01-01

    Low-sulfate, acidic (approximately pH 4) fens in the Lehstenbach catchment in the Fichtelgebirge mountains in Germany are unusual habitats for sulfate-reducing prokaryotes (SRPs) that have been postulated to facilitate the retention of sulfur and protons in these ecosystems. Despite the low in situ availability of sulfate (concentration in the soil solution, 20 to 200 μM) and the acidic conditions (soil and soil solution pHs, approximately 4 and 5, respectively), the upper peat layers of the soils from two fens (Schlöppnerbrunnen I and II) of this catchment displayed significant sulfate-reducing capacities. 16S rRNA gene-based oligonucleotide microarray analyses revealed stable diversity patterns for recognized SRPs in the upper 30 cm of both fens. Members of the family “Syntrophobacteraceae” were detected in both fens, while signals specific for the genus Desulfomonile were observed only in soils from Schlöppnerbrunnen I. These results were confirmed and extended by comparative analyses of environmentally retrieved 16S rRNA and dissimilatory (bi)sulfite reductase (dsrAB) gene sequences; dsrAB sequences from Desulfobacca-like SRPs, which were not identified by microarray analysis, were obtained from both fens. Hypotheses concerning the ecophysiological role of these three SRP groups in the fens were formulated based on the known physiological properties of their cultured relatives. In addition to these recognized SRP lineages, six novel dsrAB types that were phylogenetically unrelated to all known SRPs were detected in the fens. These dsrAB sequences had no features indicative of pseudogenes and likely represent novel, deeply branching, sulfate- or sulfite-reducing prokaryotes that are specialized colonists of low-sulfate habitats. PMID:15574893

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

    PubMed Central

    Peano, Clelia; Bicciato, Silvio; Corti, Giorgio; Ferrari, Francesco; Rizzi, Ermanno; Bonnal, Raoul JP; Bordoni, Roberta; Albertini, Alberto; Bernardi, Luigi Rossi; Donadio, Stefano; De Bellis, Gianluca

    2007-01-01

    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 organization of the chromosomes

  1. Comparison of gene coverage of mouse oligonucleotide microarray platforms

    PubMed Central

    Verdugo, Ricardo A; Medrano, Juan F

    2006-01-01

    Background The increasing use of DNA microarrays for genetical genomics studies generates a need for platforms with complete coverage of the genome. We have compared the effective gene coverage in the mouse genome of different commercial and noncommercial oligonucleotide microarray platforms by performing an in-house gene annotation of probes. We only used information about probes that is available from vendors and followed a process that any researcher may take to find the gene targeted by a given probe. In order to make consistent comparisons between platforms, probes in each microarray were annotated with an Entrez Gene id and the chromosomal position for each gene was obtained from the UCSC Genome Browser Database. Gene coverage was estimated as the percentage of Entrez Genes with a unique position in the UCSC Genome database that is tested by a given microarray platform. Results A MySQL relational database was created to store the mapping information for 25,416 mouse genes and for the probes in five microarray platforms (gene coverage level in parenthesis): Affymetrix430 2.0 (75.6%), ABI Genome Survey (81.24%), Agilent (79.33%), Codelink (78.09%), Sentrix (90.47%); and four array-ready oligosets: Sigma (47.95%), Operon v.3 (69.89%), Operon v.4 (84.03%), and MEEBO (84.03%). The differences in coverage between platforms were highly conserved across chromosomes. Differences in the number of redundant and unspecific probes were also found among arrays. The database can be queried to compare specific genomic regions using a web interface. The software used to create, update and query the database is freely available as a toolbox named ArrayGene. Conclusion The software developed here allows researchers to create updated custom databases by using public or proprietary information on genes for any organisms. ArrayGene allows easy comparisons of gene coverage between microarray platforms for any region of the genome. The comparison presented here reveals that the

  2. Systematic analysis of microarray datasets to identify Parkinson's disease-associated pathways and genes

    PubMed Central

    Feng, Yinling; Wang, Xuefeng

    2017-01-01

    In order to investigate commonly disturbed genes and pathways in various brain regions of patients with Parkinson's disease (PD), microarray datasets from previous studies were collected and systematically analyzed. Different normalization methods were applied to microarray datasets from different platforms. A strategy combining gene co-expression networks and clinical information was adopted, using weighted gene co-expression network analysis (WGCNA) to screen for commonly disturbed genes in different brain regions of patients with PD. Functional enrichment analysis of commonly disturbed genes was performed using the Database for Annotation, Visualization, and Integrated Discovery (DAVID). Co-pathway relationships were identified with Pearson's correlation coefficient tests and a hypergeometric distribution-based test. Common genes in pathway pairs were selected out and regarded as risk genes. A total of 17 microarray datasets from 7 platforms were retained for further analysis. Five gene coexpression modules were identified, containing 9,745, 736, 233, 101 and 93 genes, respectively. One module was significantly correlated with PD samples and thus the 736 genes it contained were considered to be candidate PD-associated genes. Functional enrichment analysis demonstrated that these genes were implicated in oxidative phosphorylation and PD. A total of 44 pathway pairs and 52 risk genes were revealed, and a risk gene pathway relationship network was constructed. Eight modules were identified and were revealed to be associated with PD, cancers and metabolism. A number of disturbed pathways and risk genes were unveiled in PD, and these findings may help advance understanding of PD pathogenesis. PMID:28098893

  3. Systematic analysis of microarray datasets to identify Parkinson's disease‑associated pathways and genes.

    PubMed

    Feng, Yinling; Wang, Xuefeng

    2017-03-01

    In order to investigate commonly disturbed genes and pathways in various brain regions of patients with Parkinson's disease (PD), microarray datasets from previous studies were collected and systematically analyzed. Different normalization methods were applied to microarray datasets from different platforms. A strategy combining gene co‑expression networks and clinical information was adopted, using weighted gene co‑expression network analysis (WGCNA) to screen for commonly disturbed genes in different brain regions of patients with PD. Functional enrichment analysis of commonly disturbed genes was performed using the Database for Annotation, Visualization, and Integrated Discovery (DAVID). Co‑pathway relationships were identified with Pearson's correlation coefficient tests and a hypergeometric distribution‑based test. Common genes in pathway pairs were selected out and regarded as risk genes. A total of 17 microarray datasets from 7 platforms were retained for further analysis. Five gene coexpression modules were identified, containing 9,745, 736, 233, 101 and 93 genes, respectively. One module was significantly correlated with PD samples and thus the 736 genes it contained were considered to be candidate PD‑associated genes. Functional enrichment analysis demonstrated that these genes were implicated in oxidative phosphorylation and PD. A total of 44 pathway pairs and 52 risk genes were revealed, and a risk gene pathway relationship network was constructed. Eight modules were identified and were revealed to be associated with PD, cancers and metabolism. A number of disturbed pathways and risk genes were unveiled in PD, and these findings may help advance understanding of PD pathogenesis.

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

    PubMed Central

    Kong, Wei; Mou, Xiaoyang; Liu, Qingzhong; Chen, Zhongxue; Vanderburg, Charles R; Rogers, Jack T; Huang, Xudong

    2009-01-01

    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 comparison to the PCA and support

  5. Microarray analysis of radiation response genes in primary human fibroblasts

    SciTech Connect

    Kis, Enikoe; Szatmari, Tuende; Keszei, Marton; Farkas, Robert; Esik, Olga; Lumniczky, Katalin; Falus, Andras; Safrany, Geza . E-mail: safrany@hp.osski.hu

    2006-12-01

    Purpose: To identify radiation-induced early transcriptional responses in primary human fibroblasts and understand cellular pathways leading to damage correction. Methods and Materials: Primary human fibroblast cell lines were irradiated with 2 Gy {gamma}-radiation and RNA isolated 2 h later. Radiation-induced transcriptional alterations were investigated with microarrays covering the entire human genome. Time- and dose dependent radiation responses were studied by quantitative real-time polymerase chain reaction (RT-PCR). Results: About 200 genes responded to ionizing radiation on the transcriptional level in primary human fibroblasts. The expression profile depended on individual genetic backgrounds. Thirty genes (28 up- and 2 down-regulated) responded to radiation in identical manner in all investigated cells. Twenty of these consensus radiation response genes were functionally categorized: most of them belong to the DNA damage response (GADD45A, BTG2, PCNA, IER5), regulation of cell cycle and cell proliferation (CDKN1A, PPM1D, SERTAD1, PLK2, PLK3, CYR61), programmed cell death (BBC3, TP53INP1) and signaling (SH2D2A, SLIC1, GDF15, THSD1) pathways. Four genes (SEL10, FDXR, CYP26B1, OR11A1) were annotated to other functional groups. Many of the consensus radiation response genes are regulated by, or regulate p53. Time- and dose-dependent expression profiles of selected consensus genes (CDKN1A, GADD45A, IER5, PLK3, CYR61) were investigated by quantitative RT-PCR. Transcriptional alterations depended on the applied dose, and on the time after irradiation. Conclusions: The data presented here could help in the better understanding of early radiation responses and the development of biomarkers to identify radiation susceptible individuals.

  6. Key aspects of analyzing microarray gene-expression data.

    PubMed

    Chen, James J

    2007-05-01

    One major challenge with the use of microarray technology is the analysis of massive amounts of gene-expression data for various applications. This review addresses the key aspects of the microarray gene-expression data analysis for the two most common objectives: class comparison and class prediction. Class comparison mainly aims to select which genes are differentially expressed across experimental conditions. Gene selection is separated into two steps: gene ranking and assigning a significance level. Class prediction uses expression profiling analysis to develop a prediction model for patient selection, diagnostic prediction or prognostic classification. Development of a prediction model involves two components: model building and performance assessment. It also describes two additional data analysis methods: gene-class testing and multiple ordering criteria.

  7. Do DNA Microarrays Tell the Story of Gene Expression?

    PubMed Central

    Rosenfeld, Simon

    2010-01-01

    Poor reproducibility of microarray measurements is a major obstacle to their application as an instrument for clinical diagnostics. In this paper, several aspects of poor reproducibility are analyzed. All of them belong to the category of interpretive weaknesses of DNA microarray technology. First, the attention is drawn to the fact that absence of the information regarding post-transcriptional mRNA stability makes it impossible to evaluate the level of gene activity from the relative mRNA abundances, the quantities available from microarray measurements. Second, irreducible intracellular variability with persistent patterns of stochasticity and burstiness put natural limits to reproducibility. Third, strong interactions within intracellular biomolecular networks make it highly problematic to build a bridge between transcription rates of individual genes and structural fidelity of their genetic codes. For these reasons, the microarray measurements of relative mRNA abundances are more appropriate in laboratory settings as a tool for scientific research, hypotheses generating and producing the leads for subsequent validation through more sophisticated technologies. As to clinical settings, where firm conclusive diagnoses, not the leads for further experimentation, are required, microarrays still have a long way to go until they become a reliable instrument in patient-related decision making. PMID:20628535

  8. Gene expression profiling in peanut using oligonucleotide microarrays

    USDA-ARS?s Scientific Manuscript database

    Transcriptome expression analysis in peanut to date has been limited to a relatively small set of genes and only recently have a moderately significant number of ESTs been released into the public domain. Utilization of these ESTs for the oligonucleotide microarrays provides a means to investigate l...

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

    PubMed Central

    Fu, Li M; Fu-Liu, Casey S

    2005-01-01

    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. PMID:15784140

  10. Development, Characterization and Experimental Validation of a Cultivated Sunflower (Helianthus annuus L.) Gene Expression Oligonucleotide Microarray

    PubMed Central

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

    2012-01-01

    Oligonucleotide-based microarrays with accurate gene coverage represent a key strategy for transcriptional studies in orphan species such as sunflower, H. annuus L., which lacks full genome sequences. The goal of this study was the development and functional annotation of a comprehensive sunflower unigene collection and the design and validation of a custom sunflower oligonucleotide-based microarray. A large scale EST (>130,000 ESTs) curation, assembly and sequence annotation was performed using Blast2GO (www.blast2go.de). The EST assembly comprises 41,013 putative transcripts (12,924 contigs and 28,089 singletons). The resulting Sunflower Unigen Resource (SUR version 1.0) was used to design an oligonucleotide-based Agilent microarray for cultivated sunflower. This microarray includes a total of 42,326 features: 1,417 Agilent controls, 74 control probes for sunflower replicated 10 times (740 controls) and 40,169 different non-control probes. Microarray performance was validated using a model experiment examining the induction of senescence by water deficit. Pre-processing and differential expression analysis of Agilent microarrays was performed using the Bioconductor limma package. The analyses based on p-values calculated by eBayes (p<0.01) allowed the detection of 558 differentially expressed genes between water stress and control conditions; from these, ten genes were further validated by qPCR. Over-represented ontologies were identified using FatiScan in the Babelomics suite. This work generated a curated and trustable sunflower unigene collection, and a custom, validated sunflower oligonucleotide-based microarray using Agilent technology. Both the curated unigene collection and the validated oligonucleotide microarray provide key resources for sunflower genome analysis, transcriptional studies, and molecular breeding for crop improvement. PMID:23110046

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

    PubMed

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

    2012-01-01

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

  12. Deoxyoligonucleotide microarrays for gene expression profiling in murine tooth germs.

    PubMed

    Osmundsen, Harald; Jevnaker, Anne-Marthe; Landin, Maria A

    2012-01-01

    The use of deoxyoligonucleotide microarrays facilitates rapid expression profiling of gene expression using samples of about 1 μg of total RNA. Here are described practical aspects of the procedures involved, including essential reagents. Analysis of results is discussed from a practical, experimental, point of view together with software required to carry out the required statistical analysis to isolate populations of differentially expressed genes.

  13. Identification of disease-causing genes using microarray data mining and Gene Ontology.

    PubMed

    Mohammadi, Azadeh; Saraee, Mohammad H; Salehi, Mansoor

    2011-01-26

    One of the best and most accurate methods for identifying disease-causing genes is monitoring gene expression values in different samples using microarray technology. One of the shortcomings of microarray data is that they provide a small quantity of samples with respect to the number of genes. This problem reduces the classification accuracy of the methods, so gene selection is essential to improve the predictive accuracy and to identify potential marker genes for a disease. Among numerous existing methods for gene selection, support vector machine-based recursive feature elimination (SVMRFE) has become one of the leading methods, but its performance can be reduced because of the small sample size, noisy data and the fact that the method does not remove redundant genes. We propose a novel framework for gene selection which uses the advantageous features of conventional methods and addresses their weaknesses. In fact, we have combined the Fisher method and SVMRFE to utilize the advantages of a filtering method as well as an embedded method. Furthermore, we have added a redundancy reduction stage to address the weakness of the Fisher method and SVMRFE. In addition to gene expression values, the proposed method uses Gene Ontology which is a reliable source of information on genes. The use of Gene Ontology can compensate, in part, for the limitations of microarrays, such as having a small number of samples and erroneous measurement results. The proposed method has been applied to colon, Diffuse Large B-Cell Lymphoma (DLBCL) and prostate cancer datasets. The empirical results show that our method has improved classification performance in terms of accuracy, sensitivity and specificity. In addition, the study of the molecular function of selected genes strengthened the hypothesis that these genes are involved in the process of cancer growth. The proposed method addresses the weakness of conventional methods by adding a redundancy reduction stage and utilizing Gene

  14. Identification of disease-causing genes using microarray data mining and Gene Ontology

    PubMed Central

    2011-01-01

    Background One of the best and most accurate methods for identifying disease-causing genes is monitoring gene expression values in different samples using microarray technology. One of the shortcomings of microarray data is that they provide a small quantity of samples with respect to the number of genes. This problem reduces the classification accuracy of the methods, so gene selection is essential to improve the predictive accuracy and to identify potential marker genes for a disease. Among numerous existing methods for gene selection, support vector machine-based recursive feature elimination (SVMRFE) has become one of the leading methods, but its performance can be reduced because of the small sample size, noisy data and the fact that the method does not remove redundant genes. Methods We propose a novel framework for gene selection which uses the advantageous features of conventional methods and addresses their weaknesses. In fact, we have combined the Fisher method and SVMRFE to utilize the advantages of a filtering method as well as an embedded method. Furthermore, we have added a redundancy reduction stage to address the weakness of the Fisher method and SVMRFE. In addition to gene expression values, the proposed method uses Gene Ontology which is a reliable source of information on genes. The use of Gene Ontology can compensate, in part, for the limitations of microarrays, such as having a small number of samples and erroneous measurement results. Results The proposed method has been applied to colon, Diffuse Large B-Cell Lymphoma (DLBCL) and prostate cancer datasets. The empirical results show that our method has improved classification performance in terms of accuracy, sensitivity and specificity. In addition, the study of the molecular function of selected genes strengthened the hypothesis that these genes are involved in the process of cancer growth. Conclusions The proposed method addresses the weakness of conventional methods by adding a redundancy

  15. Microarray analysis of differentially expressed genes and their functions in omental visceral adipose tissues of pregnant women with vs. without gestational diabetes mellitus.

    PubMed

    Qian, Yuan; Sun, Hao; Xiao, Hongli; Ma, Meirun; Xiao, Xue; Qu, Qinzai

    2017-05-01

    Increasing evidence has shown that insulin resistance in omental visceral adipose tissue (OVAT) is a characteristic of gestational diabetes mellitus (GDM). The present study aimed to identify differentially expressed genes (DEGs) and their associated functions and pathways involved in the pathogenesis of GDM by comparing the expression profiles of OVATs obtained from pregnant Chinese women with and without GDM during caesarian section. A total of 935 DEGs were identified, including 450 downregulated and 485 upregulated genes. In the gene ontology category cellular components, the DEGs were predominantly associated with functions of the extracellular region, while receptor binding was predominant in the molecular function category and biological process terms included antigen processing and presentation, extracellular matrix organization, positive regulation of cell-substrate adhesion, response to nutrients and response to dietary excess. Functional enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment were performed and a functional interaction network was constructed. Functions of downregulated genes included antigen processing and presentation as well as cell adhesion molecules, while those of upregulated genes included transforming growth factor (TGF)-β-signaling, focal adhesion, phosphoinositide-3 kinase-Akt-signaling, P53 signaling, extracellular matrix-receptor interaction and regulation of actin cytoskeleton pathway. The five main pathways associated with GDM were antigen processing and presentation, cell adhesion molecules, Type 1 diabetes mellitus, natural killer cell-mediated cytotoxicity and TGF-β signaling. These pathways were included in the KEGG pathway categories of 'signaling molecules and interaction', 'immune system' and 'inflammatory response', suggesting that these processes are involved in GDM. The results of the present study enhanced the present understanding of the mechanisms associated with insulin resistance in

  16. Gene expression analysis of perennial ryegrass (Lolium perenne) using cDNA microarrays

    NASA Astrophysics Data System (ADS)

    Ong, Eng-Kok; Sawbridge, Tim; Webster, Tracie; Emmerling, Michael; Nguyen, Nga; Nunan, Katrina; O'Neill, Matthew; O'Toole, Fiona; Rhodes, Carolyn; Simmonds, Jason; Tian, Pei; Wearne, Katherine; Winkworth, Amanda; Spangenberg, German

    2003-07-01

    Perennial ryegrass (Lolium perenne) is a major forage grass of temperate pastures. A genomics program has been undertaken generating over 52,000 expressed sequence tags (ESTs). Cluster analysis of the ESTs identified approximately 14,600 ryegrass unigenes. In this report, we described the application of ryegrass unigene cDNAs to produce ryegrass 15K microarray. Fifteen microarray hybridisations were performed with labeled total RNA isolated from a variety of plant organs and developmental stages. In a proof of concept, gene expression profiling of ryegrass ESTs using the 15K unigene microarrays has been established using several known genes and two cluster analysis approaches (parallel coordinate planes plot and hierarchical clustering). The expression profile of the known genes (e.g. rubisco and invertase) corresponds well with published data. The microarray expression profile of a ryegrass putative root specific kinase gene was also verified with Northern blotting. This combination of DNA microarray hybridisations and cluster analysis can be applied as a tool for the identification of novel sequences of unknown function.

  17. DFP: a Bioconductor package for fuzzy profile identification and gene reduction of microarray data

    PubMed Central

    Glez-Peña, Daniel; Álvarez, Rodrigo; Díaz, Fernando; Fdez-Riverola, Florentino

    2009-01-01

    Background Expression profiling assays done by using DNA microarray technology generate enormous data sets that are not amenable to simple analysis. The greatest challenge in maximizing the use of this huge amount of data is to develop algorithms to interpret and interconnect results from different genes under different conditions. In this context, fuzzy logic can provide a systematic and unbiased way to both (i) find biologically significant insights relating to meaningful genes, thereby removing the need for expert knowledge in preliminary steps of microarray data analyses and (ii) reduce the cost and complexity of later applied machine learning techniques being able to achieve interpretable models. Results DFP is a new Bioconductor R package that implements a method for discretizing and selecting differentially expressed genes based on the application of fuzzy logic. DFP takes advantage of fuzzy membership functions to assign linguistic labels to gene expression levels. The technique builds a reduced set of relevant genes (FP, Fuzzy Pattern) able to summarize and represent each underlying class (pathology). A last step constructs a biased set of genes (DFP, Discriminant Fuzzy Pattern) by intersecting existing fuzzy patterns in order to detect discriminative elements. In addition, the software provides new functions and visualisation tools that summarize achieved results and aid in the interpretation of differentially expressed genes from multiple microarray experiments. Conclusion DFP integrates with other packages of the Bioconductor project, uses common data structures and is accompanied by ample documentation. It has the advantage that its parameters are highly configurable, facilitating the discovery of biologically relevant connections between sets of genes belonging to different pathologies. This information makes it possible to automatically filter irrelevant genes thereby reducing the large volume of data supplied by microarray experiments. Based on

  18. DFP: a Bioconductor package for fuzzy profile identification and gene reduction of microarray data.

    PubMed

    Glez-Peña, Daniel; Alvarez, Rodrigo; Díaz, Fernando; Fdez-Riverola, Florentino

    2009-01-29

    Expression profiling assays done by using DNA microarray technology generate enormous data sets that are not amenable to simple analysis. The greatest challenge in maximizing the use of this huge amount of data is to develop algorithms to interpret and interconnect results from different genes under different conditions. In this context, fuzzy logic can provide a systematic and unbiased way to both (i) find biologically significant insights relating to meaningful genes, thereby removing the need for expert knowledge in preliminary steps of microarray data analyses and (ii) reduce the cost and complexity of later applied machine learning techniques being able to achieve interpretable models. DFP is a new Bioconductor R package that implements a method for discretizing and selecting differentially expressed genes based on the application of fuzzy logic. DFP takes advantage of fuzzy membership functions to assign linguistic labels to gene expression levels. The technique builds a reduced set of relevant genes (FP, Fuzzy Pattern) able to summarize and represent each underlying class (pathology). A last step constructs a biased set of genes (DFP, Discriminant Fuzzy Pattern) by intersecting existing fuzzy patterns in order to detect discriminative elements. In addition, the software provides new functions and visualisation tools that summarize achieved results and aid in the interpretation of differentially expressed genes from multiple microarray experiments. DFP integrates with other packages of the Bioconductor project, uses common data structures and is accompanied by ample documentation. It has the advantage that its parameters are highly configurable, facilitating the discovery of biologically relevant connections between sets of genes belonging to different pathologies. This information makes it possible to automatically filter irrelevant genes thereby reducing the large volume of data supplied by microarray experiments. Based on these contributions GENECBR, a

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

    PubMed Central

    He, Feng; Zeng, An-Ping

    2006-01-01

    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 interactions, including 443

  20. A 7872 cDNA microarray and its use in bovine functional genomics.

    PubMed

    Everts, Robin E; Band, Mark R; Liu, Z Lewis; Kumar, Charu G; Liu, Lei; Loor, Juan J; Oliveira, Rosane; Lewin, Harris A

    2005-05-15

    The strategy used to create and annotate a 7872 cDNA microarray from cattle placenta and spleen cDNA sequences is described. This microarray contains approximately 6300 unique genes, as determined by BLASTN and TBLASTX similarity search against the human and mouse UniGene and draft human genome sequence databases (build 34). Sequences on the array were annotated with gene ontology (GO) terms, thereby facilitating data analysis and interpretation. A total of 3244 genes were annotated with GO terms. The array is rich in sequences encoding transcription factors, signal transducers and cell cycle regulators. Current research being conducted with this array is described, and an overview of planned improvements in our microarray platform for cattle functional genomics is presented.

  1. Gene set analyses for interpreting microarray experiments on prokaryotic organisms.

    SciTech Connect

    Tintle, Nathan; Best, Aaron; Dejongh, Matthew; VanBruggen, Dirk; Heffron, Fred; Porwollik, Steffen; Taylor, Ronald C.

    2008-11-05

    Background: Recent advances in microarray technology have brought with them the need for enhanced methods of biologically interpreting gene expression data. Recently, methods like Gene Set Enrichment Analysis (GSEA) and variants of Fisher’s exact test have been proposed which utilize a priori biological information. Typically, these methods are demonstrated with a priori biological information from the Gene Ontology. Results: Alternative gene set definitions are presented based on gene sets inferred from the SEED: open-source software environment for comparative genome annotation and analysis of microbial organisms. Many of these gene sets are then shown to provide consistent expression across a series of experiments involving Salmonella Typhimurium. Implementation of the gene sets in an analysis of microarray data is then presented for the Salmonella Typhimurium data. Conclusions: SEED inferred gene sets can be naturally defined based on subsystems in the SEED. The consistent expression values of these SEED inferred gene sets suggest their utility for statistical analyses of gene expression data based on a priori biological information

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

    PubMed

    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.

  3. Implementation of GenePattern within the Stanford Microarray Database.

    PubMed

    Hubble, Jeremy; Demeter, Janos; Jin, Heng; Mao, Maria; Nitzberg, Michael; Reddy, T B K; Wymore, Farrell; Zachariah, Zachariah K; Sherlock, Gavin; Ball, Catherine A

    2009-01-01

    Hundreds of researchers across the world use the Stanford Microarray Database (SMD; http://smd.stanford.edu/) to store, annotate, view, analyze and share microarray data. In addition to providing registered users at Stanford access to their own data, SMD also provides access to public data, and tools with which to analyze those data, to any public user anywhere in the world. Previously, the addition of new microarray data analysis tools to SMD has been limited by available engineering resources, and in addition, the existing suite of tools did not provide a simple way to design, execute and share analysis pipelines, or to document such pipelines for the purposes of publication. To address this, we have incorporated the GenePattern software package directly into SMD, providing access to many new analysis tools, as well as a plug-in architecture that allows users to directly integrate and share additional tools through SMD. In this article, we describe our implementation of the GenePattern microarray analysis software package into the SMD code base. This extension is available with the SMD source code that is fully and freely available to others under an Open Source license, enabling other groups to create a local installation of SMD with an enriched data analysis capability.

  4. Nutrient control of gene expression in Drosophila: microarray analysis of starvation and sugar-dependent response

    PubMed Central

    Zinke, Ingo; Schütz, Christina S.; Katzenberger, Jörg D.; Bauer, Matthias; Pankratz, Michael J.

    2002-01-01

    We have identified genes regulated by starvation and sugar signals in Drosophila larvae using whole-genome microarrays. Based on expression profiles in the two nutrient conditions, they were organized into different categories that reflect distinct physiological pathways mediating sugar and fat metabolism, and cell growth. In the category of genes regulated in sugar-fed, but not in starved, animals, there is an upregulation of genes encoding key enzymes of the fat biosynthesis pathway and a downregulation of genes encoding lipases. The highest and earliest activated gene upon sugar ingestion is sugarbabe, a zinc finger protein that is induced in the gut and the fat body. Identification of potential targets using microarrays suggests that sugarbabe functions to repress genes involved in dietary fat breakdown and absorption. The current analysis provides a basis for studying the genetic mechanisms underlying nutrient signalling. PMID:12426388

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

    PubMed

    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

  6. Identifying new human oocyte marker genes: a microarray approach.

    PubMed

    Gasca, Stéphan; Pellestor, Franck; Assou, Saïd; Loup, Vanessa; Anahory, Tal; Dechaud, Hervé; De Vos, John; Hamamah, Samir

    2007-02-01

    The efficacy of classical IVF techniques is still impaired by poor implantation and pregnancy rates after embryo transfer. This is mainly due to a lack of reliable criteria for the selection of embryos with sufficient development potential. Several studies have provided evidence that some gene expression levels could be used as objective markers of oocyte and embryo competence and capacity to sustain a successful pregnancy. These analyses usually use reverse transcription-polymerase chain reaction to look at small sets of pre-selected genes. However, microarray approaches allow the identification of a wider range of cellular marker genes which could include additional and perhaps more suitable genes that could serve as embryo selection markers. Microarray screenings of around 30,000 genes on U133P Affymetrix gene chips made it possible to establish the expression profile of these genes as well as other related genes in human oocytes and cumulus cells. This study identifies new potential regulators and marker genes such as BARD1, RBL2, RBBP7, BUB3 or BUB1B, which are involved in oocyte maturation.

  7. MGFM: a novel tool for detection of tissue and cell specific marker genes from microarray gene expression data.

    PubMed

    El Amrani, Khadija; Stachelscheid, Harald; Lekschas, Fritz; Kurtz, Andreas; Andrade-Navarro, Miguel A

    2015-08-28

    Identification of marker genes associated with a specific tissue/cell type is a fundamental challenge in genetic and cell research. Marker genes are of great importance for determining cell identity, and for understanding tissue specific gene function and the molecular mechanisms underlying complex diseases. We have developed a new bioinformatics tool called MGFM (Marker Gene Finder in Microarray data) to predict marker genes from microarray gene expression data. Marker genes are identified through the grouping of samples of the same type with similar marker gene expression levels. We verified our approach using two microarray data sets from the NCBI's Gene Expression Omnibus public repository encompassing samples for similar sets of five human tissues (brain, heart, kidney, liver, and lung). Comparison with another tool for tissue-specific gene identification and validation with literature-derived established tissue markers established functionality, accuracy and simplicity of our tool. Furthermore, top ranked marker genes were experimentally validated by reverse transcriptase-polymerase chain reaction (RT-PCR). The sets of predicted marker genes associated with the five selected tissues comprised well-known genes of particular importance in these tissues. The tool is freely available from the Bioconductor web site, and it is also provided as an online application integrated into the CellFinder platform ( http://cellfinder.org/analysis/marker ). MGFM is a useful tool to predict tissue/cell type marker genes using microarray gene expression data. The implementation of the tool as an R-package as well as an application within CellFinder facilitates its use.

  8. Augmenting Microarray Data with Literature-Based Knowledge to Enhance Gene Regulatory Network Inference

    PubMed Central

    Kilicoglu, Halil; Shin, Dongwook; Rindflesch, Thomas C.

    2014-01-01

    Gene regulatory networks are a crucial aspect of systems biology in describing molecular mechanisms of the cell. Various computational models rely on random gene selection to infer such networks from microarray data. While incorporation of prior knowledge into data analysis has been deemed important, in practice, it has generally been limited to referencing genes in probe sets and using curated knowledge bases. We investigate the impact of augmenting microarray data with semantic relations automatically extracted from the literature, with the view that relations encoding gene/protein interactions eliminate the need for random selection of components in non-exhaustive approaches, producing a more accurate model of cellular behavior. A genetic algorithm is then used to optimize the strength of interactions using microarray data and an artificial neural network fitness function. The result is a directed and weighted network providing the individual contribution of each gene to its target. For testing, we used invasive ductile carcinoma of the breast to query the literature and a microarray set containing gene expression changes in these cells over several time points. Our model demonstrates significantly better fitness than the state-of-the-art model, which relies on an initial random selection of genes. Comparison to the component pathways of the KEGG Pathways in Cancer map reveals that the resulting networks contain both known and novel relationships. The p53 pathway results were manually validated in the literature. 60% of non-KEGG relationships were supported (74% for highly weighted interactions). The method was then applied to yeast data and our model again outperformed the comparison model. Our results demonstrate the advantage of combining gene interactions extracted from the literature in the form of semantic relations with microarray analysis in generating contribution-weighted gene regulatory networks. This methodology can make a significant contribution to

  9. Identifying new human oocyte marker genes: a microarray approach

    PubMed Central

    Gasca, Stephan; Pellestor, Franck; Assou, Said; Loup, Vanessa; Anahory, Tal; Dechaud, Hervé; De Vos, John; Hamamah, Samir

    2007-01-01

    Efficiency in classical IVF (cIVF) techniques is still impaired by poor implantation and pregnancy rates after embryo transfer. This is mostly due to a lack of reliable criteria for the selection of embryos with sufficient development potential. Several studies have provided evidence that some genes’ expression levels could be used as objective markers of oocytes and embryos competence and of their capacity to sustain a successful pregnancy. These analyses usually used reverse transcription-polymerase chain reaction to look at small sets of pre-selected genes. However, microarray approaches permit to identify a wider range of cellular marker genes. Thus they allow the identification of additional and perhaps more suited genes that could serve as embryo selection markers. Microarray screenings of circa 30 000 genes on U133P Affymetrix™ gene chips made it possible to establish the expression profile of these genes as well as other related genes in human oocytes and cumulus cells. In this study, we identified new potential regulators and marker genes such as BARD1, RBL2, RBBP7, BUB3 or BUB1B, which are involved in oocyte maturation. PMID:17298719

  10. Microarray analysis of gene expression in medicinal plant research.

    PubMed

    Youns, M; Efferth, T; Hoheisel, J D

    2009-10-01

    Expression profiling analysis offers great opportunities for the identification of novel molecular targets, drug discovery, development, and validation. The beauty of microarray analysis of gene expression is that it can be used to screen the expression of tens of thousands of genes in parallel and to identify appropriate molecular targets for therapeutic intervention. Toward identifying novel therapeutic options, natural products, notably from medicinal plants used in traditional Chinese medicine (TCM), have been thoroughly investigated. Increased knowledge of the molecular mechanisms of TCM-derived drugs could be achieved through application of modern molecular technologies including transcript profiling. In the present review, we introduce a brief introduction to the field of microarray technology and disclose its role in target identification and validation. Moreover, we provide examples for applications regarding molecular target discovery in medicinal plants derived TCM. This could be an attractive strategy for the development of novel and improved therapeutics.

  11. Microarray characterization of gene expression changes in blood during acute ethanol exposure

    PubMed Central

    2013-01-01

    Background As part of the civil aviation safety program to define the adverse effects of ethanol on flying performance, we performed a DNA microarray analysis of human whole blood samples from a five-time point study of subjects administered ethanol orally, followed by breathalyzer analysis, to monitor blood alcohol concentration (BAC) to discover significant gene expression changes in response to the ethanol exposure. Methods Subjects were administered either orange juice or orange juice with ethanol. Blood samples were taken based on BAC and total RNA was isolated from PaxGene™ blood tubes. The amplified cDNA was used in microarray and quantitative real-time polymerase chain reaction (RT-qPCR) analyses to evaluate differential gene expression. Microarray data was analyzed in a pipeline fashion to summarize and normalize and the results evaluated for relative expression across time points with multiple methods. Candidate genes showing distinctive expression patterns in response to ethanol were clustered by pattern and further analyzed for related function, pathway membership and common transcription factor binding within and across clusters. RT-qPCR was used with representative genes to confirm relative transcript levels across time to those detected in microarrays. Results Microarray analysis of samples representing 0%, 0.04%, 0.08%, return to 0.04%, and 0.02% wt/vol BAC showed that changes in gene expression could be detected across the time course. The expression changes were verified by qRT-PCR. The candidate genes of interest (GOI) identified from the microarray analysis and clustered by expression pattern across the five BAC points showed seven coordinately expressed groups. Analysis showed function-based networks, shared transcription factor binding sites and signaling pathways for members of the clusters. These include hematological functions, innate immunity and inflammation functions, metabolic functions expected of ethanol metabolism, and pancreatic

  12. Microarray analysis of R-gene-mediated resistance to viruses.

    PubMed

    Ishihara, Takeaki; Sato, Yukiyo; Takahashi, Hideki

    2015-01-01

    The complex process for host-plant resistance to viruses is precisely regulated by a number of genes and signaling compounds. Thus, global gene expression analysis can provide a powerful tool to grasp the complex molecular network for resistance to viruses. The procedures for comparative global gene expression profiling of virus-resistant and control plants by microarray analysis include RNA extraction, cDNA synthesis, cRNA labeling, hybridization, array scanning, and data mining steps. There are several platforms for the microarray analysis. Commercial services for the steps from cDNA synthesis to array scanning are now widely available; however, the data manipulation step is highly dependent on the experimental design and research focus. The protocols presented here are optimized for analyzing global gene expression during the R gene-conferred defense response using commercial oligonucleotide-based arrays. We also demonstrate a technique to screen for differentially expressed genes using Excel software and a simple Internet tool-based data mining approach for characterizing the identified genes.

  13. Automated target preparation for microarray-based gene expression analysis.

    PubMed

    Raymond, Frédéric; Metairon, Sylviane; Borner, Roland; Hofmann, Markus; Kussmann, Martin

    2006-09-15

    DNA microarrays have rapidly evolved toward a platform for massively paralleled gene expression analysis. Despite its widespread use, the technology has been criticized to be vulnerable to technical variability. Addressing this issue, recent comparative, interplatform, and interlaboratory studies have revealed that, given defined procedures for "wet lab" experiments and data processing, a satisfactory reproducibility and little experimental variability can be achieved. In view of these advances in standardization, the requirement for uniform sample preparation becomes evident, especially if a microarray platform is used as a facility, i.e., by different users working in the laboratory. While one option to reduce technical variability is to dedicate one laboratory technician to all microarray studies, we have decided to automate the entire RNA sample preparation implementing a liquid handling system coupled to a thermocycler and a microtiter plate reader. Indeed, automated RNA sample preparation prior to chip analysis enables (1) the reduction of experimentally caused result variability, (2) the separation of (important) biological variability from (undesired) experimental variation, and (3) interstudy comparison of gene expression results. Our robotic platform can process up to 24 samples in parallel, using an automated sample preparation method that produces high-quality biotin-labeled cRNA ready to be hybridized on Affymetrix GeneChips. The results show that the technical interexperiment variation is less pronounced than with manually prepared samples. Moreover, experiments using the same starting material showed that the automated process yields a good reproducibility between samples.

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

    PubMed

    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

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

    PubMed Central

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

    2009-01-01

    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 Component Runtime

  16. Challenges of microarray applications for microbial detection and gene expression profiling in food

    USDA-ARS?s Scientific Manuscript database

    Microarray technology represents one of the latest advances in molecular biology. The diverse types of microarrays have been applied to clinical and environmental microbiology, microbial ecology, and in human, veterinary, and plant diagnostics. Since multiple genes can be analyzed simultaneously, ...

  17. Dimension reduction for classification with gene expression microarray data.

    PubMed

    Dai, Jian J; Lieu, Linh; Rocke, David

    2006-01-01

    An important application of gene expression microarray data is classification of biological samples or prediction of clinical and other outcomes. One necessary part of multivariate statistical analysis in such applications is dimension reduction. This paper provides a comparison study of three dimension reduction techniques, namely partial least squares (PLS), sliced inverse regression (SIR) and principal component analysis (PCA), and evaluates the relative performance of classification procedures incorporating those methods. A five-step assessment procedure is designed for the purpose. Predictive accuracy and computational efficiency of the methods are examined. Two gene expression data sets for tumor classification are used in the study.

  18. Whole Genome Microarray Analysis of Gene Expression in Prader–Willi Syndrome

    PubMed Central

    Bittel, Douglas C.; Kibiryeva, Nataliya; Sell, Susan M.; Strong, Theresa V.; Butler, Merlin G.

    2017-01-01

    Prader–Willi syndrome (PWS) is caused by loss of function of paternally expressed genes in the 15q11-q13 region and a paucity of data exists on transcriptome variation. To further characterize genetic alterations in this classic obesity syndrome using whole genome microarrays to analyze gene expression, microarray and quantitative RT-PCR analysis were performed using RNA isolated from lymphoblastoid cells from PWS male subjects (four with 15q11-q13 deletion and three with UPD) and three age and cognition matched nonsyndromic comparison males. Of more than 47,000 probes examined in the microarray, 23,383 were detectable and 323 had significantly different expression in the PWS lymphoblastoid cells relative to comparison cells, 14 of which were related to neurodevelopment and function. As expected, there was no evidence of expression of paternally expressed genes from the 15q11-q13 region (e.g., SNRPN) in the PWS cells. Alterations in expression of serotonin receptor genes (e.g., HTR2B) and genes involved in eating behavior and obesity (ADIPOR2, MC2R, HCRT, OXTR) were noted. Other genes of interest with reduced expression in PWS subjects included STAR (a key regulator of steroid synthesis) and SAG (an arrestin family member which desensitizes G-protein-coupled receptors). Quantitative RT-PCR for SAG, OXTR, STAR, HCRT, and HTR2B using RNA isolated from their lymphoblastoid cells and available brain tissue (frontal cortex) from separate individuals with PWS and control subjects and normalized to GAPD gene expression levels validated our microarray gene expression data. Our analysis identified previously unappreciated changes in gene expression which may contribute to the clinical manifestations seen in PWS. PMID:17236194

  19. Exhaustive Search for Fuzzy Gene Networks from Microarray Data

    SciTech Connect

    Sokhansanj, B A; Fitch, J P; Quong, J N; Quong, A A

    2003-07-07

    Recent technological advances in high-throughput data collection allow for the study of increasingly complex systems on the scale of the whole cellular genome and proteome. Gene network models are required to interpret large and complex data sets. Rationally designed system perturbations (e.g. gene knock-outs, metabolite removal, etc) can be used to iteratively refine hypothetical models, leading to a modeling-experiment cycle for high-throughput biological system analysis. We use fuzzy logic gene network models because they have greater resolution than Boolean logic models and do not require the precise parameter measurement needed for chemical kinetics-based modeling. The fuzzy gene network approach is tested by exhaustive search for network models describing cyclin gene interactions in yeast cell cycle microarray data, with preliminary success in recovering interactions predicted by previous biological knowledge and other analysis techniques. Our goal is to further develop this method in combination with experiments we are performing on bacterial regulatory networks.

  20. Analysis of recursive gene selection approaches from microarray data.

    PubMed

    Li, Fan; Yang, Yiming

    2005-10-01

    Finding a small subset of most predictive genes from microarray for disease prediction is a challenging problem. Support vector machines (SVMs) have been found to be successful with a recursive procedure in selecting important genes for cancer prediction. However, it is not well understood how much of the success depends on the choice of the specific classifier and how much on the recursive procedure. We answer this question by examining multiple classifers [SVM, ridge regression (RR) and Rocchio] with feature selection in recursive and non-recursive settings on three DNA microarray datasets (ALL-AML Leukemia data, Breast Cancer data and GCM data). We found recursive RR most effective. On the AML-ALL dataset, it achieved zero error rate on the test set using only three genes (selected from over 7000), which is more encouraging than the best published result (zero error rate using 8 genes by recursive SVM). On the Breast Cancer dataset and the two largest categories of the GCM dataset, the results achieved by recursive RR are also very encouraging. A further analysis of the experimental results shows that different classifiers penalize redundant features to different extent and this property plays an important role in the recursive feature selection process. RR classifier tends to penalize redundant features to a much larger extent than the SVM does. This may be the reason why recursive RR has a better performance in selecting genes.

  1. Gene expression profiling of in Moniezia expansa at different developmental proglottids using cDNA microarray.

    PubMed

    Bo, Xinwen; Zhao, Wenjuan; Zhang, Hui; Kang, Lichao; Wang, Xinhua

    2012-04-01

    Gene expression profiles of Moniezia expansa proglottids at varying developmental stages were analysed using cDNA microarray. A total of 4,056 spots, including full length and partial complementary DNAs that represent novel, known, and control genes, were studied. Results indicated an up-regulation of 55 genes in immature proglottids, 134 genes in mature proglottids and 103 genes in gravid proglottids were up-regulated, and a down-regulation of 7 genes in immature proglottids, 68 genes in mature proglottids and 78 genes in gravid proglottids compared to controls (scolex-neck proglottids). Many of these genes were identified as transcription factors and were involved in functions such as metabolism, transport, protein biosynthesis, apoptosis, cell differentiation, cell communication and nucleic acid binding. Expression level alterations in UBE2A, Cavβ, RAD51, DAZ, PKAc and 2 unknown genes were confirmed by real-time quantitative polymerase chain reaction (RT-PCR). The complete microarray data set has been deposited in the NCBI Gene Expression Omnibus, GEO Series accession number GSE13982. Results provide a gene expression profile at various development stages of M. expansa proglottids, which prove invaluable in understanding the pathogenesis of the tapeworm and studying the genes concerned with reproductive organ development.

  2. Microarray gene expression profiling analysis combined with bioinformatics in multiple sclerosis.

    PubMed

    Liu, Mingyuan; Hou, Xiaojun; Zhang, Ping; Hao, Yong; Yang, Yiting; Wu, Xiongfeng; Zhu, Desheng; Guan, Yangtai

    2013-05-01

    Multiple sclerosis (MS) is the most prevalent demyelinating disease and the principal cause of neurological disability in young adults. Recent microarray gene expression profiling studies have identified several genetic variants contributing to the complex pathogenesis of MS, however, expressional and functional studies are still required to further understand its molecular mechanism. The present study aimed to analyze the molecular mechanism of MS using microarray analysis combined with bioinformatics techniques. We downloaded the gene expression profile of MS from Gene Expression Omnibus (GEO) and analysed the microarray data using the differentially coexpressed genes (DCGs) and links package in R and Database for Annotation, Visualization and Integrated Discovery. The regulatory impact factor (RIF) algorithm was used to measure the impact factor of transcription factor. A total of 1,297 DCGs between MS patients and healthy controls were identified. Functional annotation indicated that these DCGs were associated with immune and neurological functions. Furthermore, the RIF result suggested that IKZF1, BACH1, CEBPB, EGR1, FOS may play central regulatory roles in controlling gene expression in the pathogenesis of MS. Our findings confirm the presence of multiple molecular alterations in MS and indicate the possibility for identifying prognostic factors associated with MS pathogenesis.

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

    PubMed

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

    2014-06-01

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

  4. Microarray analysis of differentially expressed genes in preeclamptic and normal placental tissues.

    PubMed

    Ma, K; Lian, Y; Zhou, S; Hu, R; Xiong, Y; Ting, P; Xiong, Y; Li, X; Wang, X

    2014-01-01

    To detect the candidate genes for preeclampsia (PE). The gene expression profiles in preeclamptic and normal placental tissues were analyzed using cDNA microarray approach and the altered expression of important genes were further confirmed by real-time RT-PCR (reverse transcription polymerase chain reaction) technique. Total RNA was extracted from placental tissues of three cases with severe PE and from three cases with normal pregnancy. After scanning, differentially expressed genes were detected by software. In two experiments (the fluorescent labels were exchanged), a total of 111 differentially expressed genes were detected. In placental tissue ofpreeclamptic pregnancy, 68 differentially expressed genes were up-regulated, and 44 differentially expressed genes were down-regulated. Of these genes, 16 highly differentially expressed genes were confirmed by real-time fluorescent quantitative RT-PCR, and the result showed that the ratio of gene expression differences was comparable to that detected by cDNA microarray. The results of bioinformatic analysis showed that encoding products of differentially expressed genes were correlated to infiltration of placenta trophoblastic cells, immunomodulatory factors, pregnancy-associated plasma protein, signal transduction pathway, and cell adhesion. Further studies on the biological function and regulating mechanism of these genes will provide new clues for better understanding of etiology and pathogenesis of PE.

  5. ChipInfo: software for extracting gene annotation and gene ontology information for microarray analysis

    PubMed Central

    Zhong, Sheng; Li, Cheng; Wong, Wing Hung

    2003-01-01

    To date, assembling comprehensive annotation information for all probe sets of any Affymetrix microarrays remains a time-consuming, error-prone and challenging task. ChipInfo is designed for retrieving annotation information from online databases such as NetAffx and Gene Ontology and organizing such information into easily interpretable tabular format outputs. As companion software to dChip and GoSurfer, ChipInfo enables users to independently update the information resource files of these software packages. It also has functions for computing related summary statistics of probe sets and Gene Ontology terms. ChipInfo is available at http://biosun1.harvard.edu/complab/chipinfo/. PMID:12824349

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

    PubMed

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

    2012-11-15

    Microarray analysis is a technique that can be employed to provide expression profiles of single genes and new insights to elucidate the biological mechanisms responsible for fruit development. To evaluate expression of genes mostly engaged in fruit development between Prunus mume and Prunus armeniaca, we first identified differentially expressed transcripts along the entire fruit life cycle by using microarrays spotted with 10,641 ESTs collected from P. mume and other Prunus EST sequences. A total of 1418 ESTs were selected after quality control of microarray spots and analysis for differential gene expression patterns during fruit development of P. mume and P. Armeniaca. From these, 707 up-regulated and 711 down-regulated genes showing more than two-fold differences in expression level were annotated by GO based on biological processes, molecular functions and cellular components. These differentially expressed genes were found to be involved in several important pathways of carbohydrate, galactose, and starch and sucrose metabolism as well as in biosynthesis of other secondary metabolites via KEGG. This could provide detailed information on the fruit quality differences during development and ripening of these two species. With the results obtained, we provide a practical database for comprehensive understanding of molecular events during fruit development and also lay a theoretical foundation for the cloning of genes regulating in a series of important rate-limiting enzymes involved in vital metabolic pathways during fruit development. Copyright © 2012 Elsevier GmbH. All rights reserved.

  7. Monitoring of dnaK gene expression in Porphyromonas gingivalis by oxygen stress using DNA microarray.

    PubMed

    Araki, Makoto; Hiratsuka, Koichi; Kiyama-Kishikawa, Michiko; Abiko, Yoshimitsu

    2004-06-01

    Porphyromonas gingivalis, a Gram-negative anaerobe associated with adult periodontitis, expresses numerous potential virulence factors. dnaK, a member of the heat shock protein family, functions as a molecular chaperone and plays a role in microbial pathogenicity. However, little is known regarding its gene expression caused by oxygen stress in P. gingivalis. In the present study, a custom-made DNA microarray was designed and used to monitor dnaK gene expression in P. gingivalis caused by oxygen stress. The results demonstrated that dnaK mRNA was up-regulated in a short time, and the DNA microarray results were confirmed by real-time polymerase chain reaction analysis. These findings suggest that oxygen stress stimulates gene expression of dnaK and may have a relationship to the aerotolerance activity of this organism as well as its expression of pathogenesis.

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

    PubMed Central

    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

  9. Gene Expression Signature in Endemic Osteoarthritis by Microarray Analysis

    PubMed Central

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

    2015-01-01

    Kashin-Beck Disease (KBD) is an endemic osteochondropathy with an unknown pathogenesis. Diagnosis of KBD is effective only in advanced cases, which eliminates the possibility of early treatment and leads to an inevitable exacerbation of symptoms. Therefore, we aim to identify an accurate blood-based gene signature for the detection of KBD. Previously published gene expression profile data on cartilage and peripheral blood mononuclear cells (PBMCs) from adults with KBD were compared to select potential target genes. Microarray analysis was conducted to evaluate the expression of the target genes in a cohort of 100 KBD patients and 100 healthy controls. A gene expression signature was identified using a training set, which was subsequently validated using an independent test set with a minimum redundancy maximum relevance (mRMR) algorithm and support vector machine (SVM) algorithm. Fifty unique genes were differentially expressed between KBD patients and healthy controls. A 20-gene signature was identified that distinguished between KBD patients and controls with 90% accuracy, 85% sensitivity, and 95% specificity. This study identified a 20-gene signature that accurately distinguishes between patients with KBD and controls using peripheral blood samples. These results promote the further development of blood-based genetic biomarkers for detection of KBD. PMID:25997002

  10. Grouping Gene Ontology terms to improve the assessment of gene set enrichment in microarray data.

    PubMed

    Lewin, Alex; Grieve, Ian C

    2006-10-03

    Gene Ontology (GO) terms are often used to assess the results of microarray experiments. The most common way to do this is to perform Fisher's exact tests to find GO terms which are over-represented amongst the genes declared to be differentially expressed in the analysis of the microarray experiment. However, due to the high degree of dependence between GO terms, statistical testing is conservative, and interpretation is difficult. We propose testing groups of GO terms rather than individual terms, to increase statistical power, reduce dependence between tests and improve the interpretation of results. We use the publicly available package POSOC to group the terms. Our method finds groups of GO terms significantly over-represented amongst differentially expressed genes which are not found by Fisher's tests on individual GO terms. Grouping Gene Ontology terms improves the interpretation of gene set enrichment for microarray data.

  11. GEPAS, an experiment-oriented pipeline for the analysis of microarray gene expression data

    PubMed Central

    Vaquerizas, Juan M.; Conde, Lucía; Yankilevich, Patricio; Cabezón, Amaya; Minguez, Pablo; Díaz-Uriarte, Ramón; Al-Shahrour, Fátima; Herrero, Javier; Dopazo, Joaquín

    2005-01-01

    The Gene Expression Profile Analysis Suite, GEPAS, has been running for more than three years. With >76 000 experiments analysed during the last year and a daily average of almost 300 analyses, GEPAS can be considered a well-established and widely used platform for gene expression microarray data analysis. GEPAS is oriented to the analysis of whole series of experiments. Its design and development have been driven by the demands of the biomedical community, probably the most active collective in the field of microarray users. Although clustering methods have obviously been implemented in GEPAS, our interest has focused more on methods for finding genes differentially expressed among distinct classes of experiments or correlated to diverse clinical outcomes, as well as on building predictors. There is also a great interest in CGH-arrays which fostered the development of the corresponding tool in GEPAS: InSilicoCGH. Much effort has been invested in GEPAS for developing and implementing efficient methods for functional annotation of experiments in the proper statistical framework. Thus, the popular FatiGO has expanded to a suite of programs for functional annotation of experiments, including information on transcription factor binding sites, chromosomal location and tissues. The web-based pipeline for microarray gene expression data, GEPAS, is available at . PMID:15980548

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

    PubMed

    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.

  13. Development of an oligonucleotide-based DNA microarray for transcriptional analysis of Choristoneura fumiferana nucleopolyhedrovirus (CfMNPV) genes.

    PubMed

    Yang, Dan-Hui; Barari, Mehrnoosh; Arif, Basil M; Krell, Peter J

    2007-08-01

    A modified oligonucleotide-based two-channel DNA microarray was developed for characterization of temporal expression profiles of select Choristoneura fumiferana nucleopolyhedrovirus (CfMNPV) ORFs including its 7 unique ORFs. The microarray chip contained oligonucleotide probes for 23 CfMNPV ORFs and their complements as well as five host genes. Total RNA was isolated at different times post infection from Cf203 insect cells infected with CfMNPV. The cDNA was synthesized, fluorescent labelled with Cy3, and co-hybridized to the microarray chips along with Cy5-labelled viral genomic DNA, which served as equimolar reference standards for each probe. Transcription of the 7 CfMNPV unique ORFs was detected using DNA microarray analysis and their temporal expression profiles suggest that they are functional genes. The expression levels of three host genes varied throughout virus infection and therefore were unsuitable for normalization between microarrays. The DNA microarray results were compared to quantitative RT-PCR (qRT-PCR). Transcription of the non-coding (antisense) strands of some of the CfMNPV select genes including the polyhedrin gene, was also detected by array analysis and confirmed by qRT-PCR. The polyhedrin antisense transcript, based on long-range RT-PCR analysis, appeared to be a read-through product of an adjacent ORF in the same orientation as the antisense transcript.

  14. Functional protein microarrays by electrohydrodynamic jet printing.

    PubMed

    Shigeta, Kazuyo; He, Ying; Sutanto, Erick; Kang, Somi; Le, An-Phong; Nuzzo, Ralph G; Alleyne, Andrew G; Ferreira, Placid M; Lu, Yi; Rogers, John A

    2012-11-20

    This paper reports the use of advanced forms of electrohydrodynamic jet (e-jet) printing for creating micro- and nanoscale patterns of proteins on various surfaces ranging from flat silica substrates to structured plasmonic crystals, suitable for micro/nanoarray analysis and other applications in both fluorescent and plasmonic detection modes. The approaches function well with diverse classes of proteins, including streptavidin, IgG, fibrinogen, and γ-globulin. Detailed study reveals that the printing process does not adversely alter the protein structure or function, as demonstrated in the specific case of streptavidin through measurements of its binding specificity to biotin-modified DNA. Multinozzle printing systems enable several types of proteins (up to four currently) to be patterned on a single substrate, in rapid fashion and with excellent control over spatial dimensions and registration. High-speed, pulsed operational modes allow large-area printing, with narrow statistical distributions of drop size and spacing in patterns that include millions of droplets. The process is also compatible with the structured surfaces of plasmonic crystal substrates to enable detection without fluorescence. These collective characteristics suggest potential utility of e-jet techniques in wide-ranging areas of biotechnology, where its compatibility with various biomaterials and substrates with different topographies and surface chemistries, and ability to form deposits that range from thick films to submonolayer coatings, derive from the remote, noncontacting physical material transfer mode of operation.

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

    PubMed Central

    Koop, Ben F; von Schalburg, Kristian R; Leong, Jong; Walker, Neil; Lieph, Ryan; Cooper, Glenn A; Robb, Adrienne; Beetz-Sargent, Marianne; Holt, Robert A; Moore, Richard; Brahmbhatt, Sonal; Rosner, Jamie; Rexroad, Caird E; McGowan, Colin R; Davidson, William S

    2008-01-01

    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 consistent with an ancestral

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

    PubMed

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

    2012-01-01

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

  17. Evaluating methods for ranking differentially expressed genes applied to microArray quality control data

    PubMed Central

    2011-01-01

    Background Statistical methods for ranking differentially expressed genes (DEGs) from gene expression data should be evaluated with regard to high sensitivity, specificity, and reproducibility. In our previous studies, we evaluated eight gene ranking methods applied to only Affymetrix GeneChip data. A more general evaluation that also includes other microarray platforms, such as the Agilent or Illumina systems, is desirable for determining which methods are suitable for each platform and which method has better inter-platform reproducibility. Results We compared the eight gene ranking methods using the MicroArray Quality Control (MAQC) datasets produced by five manufacturers: Affymetrix, Applied Biosystems, Agilent, GE Healthcare, and Illumina. The area under the curve (AUC) was used as a measure for both sensitivity and specificity. Although the highest AUC values can vary with the definition of "true" DEGs, the best methods were, in most cases, either the weighted average difference (WAD), rank products (RP), or intensity-based moderated t statistic (ibmT). The percentages of overlapping genes (POGs) across different test sites were mainly evaluated as a measure for both intra- and inter-platform reproducibility. The POG values for WAD were the highest overall, irrespective of the choice of microarray platform. The high intra- and inter-platform reproducibility of WAD was also observed at a higher biological function level. Conclusion These results for the five microarray platforms were consistent with our previous ones based on 36 real experimental datasets measured using the Affymetrix platform. Thus, recommendations made using the MAQC benchmark data might be universally applicable. PMID:21639945

  18. A focused microarray to study human mitochondrial and nuclear gene expression.

    PubMed

    Voss, Joachim G; Raju, Raghavan; Logun, Carolea; Danner, Robert L; Munson, Peter J; Rangel, Zoila; Dalakas, Marinos C

    2008-04-01

    A focused microarray (huMITOchip) was developed to study alterations of human mitochondrial and nuclear gene expression in health and disease. The huMITOchip contains 4,774 probe sets identical to the Affymetrix U 133 plus 2.0 chip covering genes affecting mitochondrial, lipid, cytokine, apoptosis, and muscle function transcripts. Unlike other gene chips, the huMITOchip has 51 probe sets that interrogate 37 genes of the mitochondrial genome. The human mitochondrial gene chip was validated against the Affymetrix U133 plus 2.0 array using an in vitro system of CCL136 muscle cell line stimulated with or without interferon gamma (IFN-gamma). The 37 genes from the mtDNA demonstrated absolute gene expression levels ranging from 0.1 to 3,182. The comparison of the two gene chips yielded an excellent Pearson's correlation coefficient (r = 0.98). At least 17 probe sets were differentially expressed in response to IFN-gamma on both chips, with a high degree of concordance. This is the first report on the development of a focused oligonucleotide microarray containing genes of the mitochondrial genome.

  19. A Focused Microarray to Study Human Mitochondrial and Nuclear Gene Expression

    PubMed Central

    Voss, Joachim G.; Raju, Raghavan; Logun, Carolea; Danner, Robert L.; Munson, Peter J.; Rangel, Zoila; Dalakas, Marinos C.

    2016-01-01

    A focused microarray (huMITOchip) was developed to study alterations of human mitochondrial and nuclear gene expression in health and disease. The huMITOchip contains 4,774 probe sets identical to the Affymetrix U 133 plus 2.0 chip covering genes affecting mitochondrial, lipid, cytokine, apoptosis, and muscle function transcripts. Unlike other gene chips, the huMITOchip has 51 probe sets that interrogate 37 genes of the mitochondrial genome. The human mitochondrial gene chip was validated against the Affymetrix U133 plus 2.0 array using an in vitro system of CCL136 muscle cell line stimulated with or without interferon gamma (IFN-γ). The 37 genes from the mtDNA demonstrated absolute gene expression levels ranging from 0.1 to 3,182. The comparison of the two gene chips yielded an excellent Pearson’s correlation coefficient (r = 0.98). At least 17 probe sets were differentially expressed in response to IFN-γ on both chips, with a high degree of concordance. This is the first report on the development of a focused oligonucleotide microarray containing genes of the mitochondrial genome. PMID:18398222

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

    PubMed

    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.

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

    PubMed

    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.

  2. Gene set analyses for interpreting microarray experiments on prokaryotic organisms.

    PubMed

    Tintle, Nathan L; Best, Aaron A; DeJongh, Matthew; Van Bruggen, Dirk; Heffron, Fred; Porwollik, Steffen; Taylor, Ronald C

    2008-11-05

    Despite the widespread usage of DNA microarrays, questions remain about how best to interpret the wealth of gene-by-gene transcriptional levels that they measure. Recently, methods have been proposed which use biologically defined sets of genes in interpretation, instead of examining results gene-by-gene. Despite a serious limitation, a method based on Fisher's exact test remains one of the few plausible options for gene set analysis when an experiment has few replicates, as is typically the case for prokaryotes. We extend five methods of gene set analysis from use on experiments with multiple replicates, for use on experiments with few replicates. We then use simulated and real data to compare these methods with each other and with the Fisher's exact test (FET) method. As a result of the simulation we find that a method named MAXMEAN-NR, maintains the nominal rate of false positive findings (type I error rate) while offering good statistical power and robustness to a variety of gene set distributions for set sizes of at least 10. Other methods (ABSSUM-NR or SUM-NR) are shown to be powerful for set sizes less than 10. Analysis of three sets of experimental data shows similar results. Furthermore, the MAXMEAN-NR method is shown to be able to detect biologically relevant sets as significant, when other methods (including FET) cannot. We also find that the popular GSEA-NR method performs poorly when compared to MAXMEAN-NR. MAXMEAN-NR is a method of gene set analysis for experiments with few replicates, as is common for prokaryotes. Results of simulation and real data analysis suggest that the MAXMEAN-NR method offers increased robustness and biological relevance of findings as compared to FET and other methods, while maintaining the nominal type I error rate.

  3. Gene set analyses for interpreting microarray experiments on prokaryotic organisms

    PubMed Central

    Tintle, Nathan L; Best, Aaron A; DeJongh, Matthew; Van Bruggen, Dirk; Heffron, Fred; Porwollik, Steffen; Taylor, Ronald C

    2008-01-01

    Background Despite the widespread usage of DNA microarrays, questions remain about how best to interpret the wealth of gene-by-gene transcriptional levels that they measure. Recently, methods have been proposed which use biologically defined sets of genes in interpretation, instead of examining results gene-by-gene. Despite a serious limitation, a method based on Fisher's exact test remains one of the few plausible options for gene set analysis when an experiment has few replicates, as is typically the case for prokaryotes. Results We extend five methods of gene set analysis from use on experiments with multiple replicates, for use on experiments with few replicates. We then use simulated and real data to compare these methods with each other and with the Fisher's exact test (FET) method. As a result of the simulation we find that a method named MAXMEAN-NR, maintains the nominal rate of false positive findings (type I error rate) while offering good statistical power and robustness to a variety of gene set distributions for set sizes of at least 10. Other methods (ABSSUM-NR or SUM-NR) are shown to be powerful for set sizes less than 10. Analysis of three sets of experimental data shows similar results. Furthermore, the MAXMEAN-NR method is shown to be able to detect biologically relevant sets as significant, when other methods (including FET) cannot. We also find that the popular GSEA-NR method performs poorly when compared to MAXMEAN-NR. Conclusion MAXMEAN-NR is a method of gene set analysis for experiments with few replicates, as is common for prokaryotes. Results of simulation and real data analysis suggest that the MAXMEAN-NR method offers increased robustness and biological relevance of findings as compared to FET and other methods, while maintaining the nominal type I error rate. PMID:18986519

  4. An efficient ensemble learning method for gene microarray classification.

    PubMed

    Osareh, Alireza; Shadgar, Bita

    2013-01-01

    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.

  5. Gene regulatory network clustering for graph layout based on microarray gene expression data.

    PubMed

    Kojima, Kaname; Imoto, Seiya; Nagasaki, Masao; Miyano, Satoru

    2010-01-01

    We propose a statistical model realizing simultaneous estimation of gene regulatory network and gene module identification from time series gene expression data from microarray experiments. Under the assumption that genes in the same module are densely connected, the proposed method detects gene modules based on the variational Bayesian technique. The model can also incorporate existing biological prior knowledge such as protein subcellular localization. We apply the proposed model to the time series data from a synthetically generated network and verified the effectiveness of the proposed model. The proposed model is also applied the time series microarray data from HeLa cell. Detected gene module information gives the great help on drawing the estimated gene network.

  6. Gene expression microarray data from human microvascular endothelial cells supplemented with a low concentration of niacin

    PubMed Central

    Hughes-Large, Jennifer M.; Borradaile, Nica M.

    2016-01-01

    The systemic lipid modifying drug, niacin, can directly improve human microvascular endothelial cell angiogenic function under lipotoxic conditions, possibly through activation of niacin receptors “Niacin receptor activation improves human microvascular endothelial cell angiogenic function during lipotoxicity” (Hughes-Large et al. 2014). Here we provide accompanying data collected using Affymetrix GeneChip microarrays to identify changes in gene expression in human microvascular endothelial cells treated with 10 μM niacin. Statistical analyses of robust multi-array average (RMA) values revealed that only 16 genes exhibited greater than 1.3-fold differential expression. Of these 16, only 5 were identified protein coding genes, while 3 of the remaining 11 genes appeared to be small nuclear/nucleolar RNAs. Altered expression of EFCAB4B, NAP1L2, and OR13C8 was confirmed by real time quantitative PCR. PMID:26937468

  7. Gene expression microarray data from human microvascular endothelial cells supplemented with a low concentration of niacin.

    PubMed

    Hughes-Large, Jennifer M; Borradaile, Nica M

    2016-03-01

    The systemic lipid modifying drug, niacin, can directly improve human microvascular endothelial cell angiogenic function under lipotoxic conditions, possibly through activation of niacin receptors "Niacin receptor activation improves human microvascular endothelial cell angiogenic function during lipotoxicity" (Hughes-Large et al. 2014). Here we provide accompanying data collected using Affymetrix GeneChip microarrays to identify changes in gene expression in human microvascular endothelial cells treated with 10 μM niacin. Statistical analyses of robust multi-array average (RMA) values revealed that only 16 genes exhibited greater than 1.3-fold differential expression. Of these 16, only 5 were identified protein coding genes, while 3 of the remaining 11 genes appeared to be small nuclear/nucleolar RNAs. Altered expression of EFCAB4B, NAP1L2, and OR13C8 was confirmed by real time quantitative PCR.

  8. Identification of conserved core xylem gene sets: conifer cDNA microarray development, transcript profiling and computational analyses.

    PubMed

    Pavy, Nathalie; Boyle, Brian; Nelson, Colleen; Paule, Charles; Giguère, Isabelle; Caron, Sébastien; Parsons, Lee S; Dallaire, Nancy; Bedon, Frank; Bérubé, Hugo; Cooke, Janice; Mackay, John

    2008-01-01

    One approach for investigating the molecular basis of wood formation is to integrate microarray profiling data sets and sequence analyses, comparing tree species with model plants such as Arabidopsis. Conifers may be included in comparative studies thanks to large-scale expressed sequence tag (EST) analyses, which enable the development of cDNA microarrays with very significant genome coverage. A microarray of 10,400 low-redundancy sequences was designed starting from white spruce (Picea glauca (Moench.) Voss) cDNAs. Computational procedures that were developed to ensure broad transcriptome coverage and efficient PCR amplification were used to select cDNA clones, which were re-sequenced in the microarray manufacture process. White spruce transcript profiling experiments that compared secondary xylem to phloem and needles identified 360 xylem-preferential gene sequences. The functional annotations of all differentially expressed sequences were highly consistent with the results of similar analyses carried out in angiosperm trees and herbaceous plants. Computational analyses comparing the spruce microarray sequences and core xylem gene sets from Arabidopsis identified 31 transcripts that were highly conserved in angiosperms and gymnosperms, in terms of both sequence and xylem expression. Several other spruce sequences have not previously been linked to xylem differentiation (including genes encoding TUBBY-like domain proteins (TLPs) and a gibberellin insensitive (gai) gene sequence) or were shown to encode proteins of unknown function encompassing diverse conserved domains of unknown function.

  9. Predicting microRNA targets in time-series microarray experiments via functional data analysis.

    PubMed

    Parker, Brian J; Wen, Jiayu

    2009-01-30

    MicroRNA (miRNA) target prediction is an important component in understanding gene regulation. One approach is computational: searching nucleotide sequences for miRNA complementary base pairing. An alternative approach explored in this paper is the use of gene expression profiles from time-series microarray experiments to aid in miRNA target prediction. This requires distinguishing genuine targets from genes that are secondarily down-regulated as part of the same regulatory module. We use a functional data analytic (FDA) approach, FDA being a subfield of statistics that extends standard multivariate techniques to datasets with predictor and/or response variables that are functional. In a miR-124 transfection experiment spanning 120 hours, for genes with measurably down-regulated mRNA, exploratory functional data analysis showed differences in expression profiles over time between directly and indirectly down-regulated genes, such as response latency and biphasic response for direct miRNA targets. For prediction, an FDA approach was shown to effectively classify direct miR-124 targets from time-series microarray data (accuracy 88%; AUC 0.96), providing better performance than multivariate approaches. Exploratory FDA analysis can reveal interesting aspects of dynamic microarray miRNA studies. Predictive FDA models can be applied where computational miRNA target predictors fail or are unreliable, e.g. when there is a lack of evolutionary conservation, and can provide posterior probabilities to provide additional confirmatory evidence to validate candidate miRNA targets computationally predicted using sequence information. This approach would be applicable to the investigation of other miRNAs and suggests that dynamic microarray studies at a higher time resolution could reveal further details on miRNA regulation.

  10. Microarray analysis of altered gene expression in ERbeta-overexpressing HEK293 cells.

    PubMed

    Zhao, Chunyan; Putnik, Milica; Gustafsson, Jan-Ake; Dahlman-Wright, Karin

    2009-10-01

    Estrogen receptors (ERs), ERalpha and ERbeta, mediate estrogen actions in a broad range of target tissues. With the introduction of microarray techniques, a significant understanding has been gained regarding the interplay between the ERalpha and ERbeta in breast cancer cell lines. To gain a more comprehensive understanding of ERbeta-dependent gene regulation independent of ERalpha, we performed microarray analysis on HEK293/mock and HEK293/ERbeta cells. A total of 332 genes was identified as ERbeta-upregulated genes and 210 identified as ERbeta-downregulated genes. ERbeta-induced and ERbeta-repressed genes were involved in cell-cell signaling, morphogenesis, and cell proliferation. The ERbeta repressive effect on genes related to proliferation was further studied by proliferation assays, where ERbeta expression resulted in a significant decrease in cell proliferation. To identify primary ERbeta target genes, we examined a number of ERbeta-regulated genes using chromatin immunoprecipitation assays for regions bound by ERbeta. Our results showed that ERbeta recruitment was significant to regions associated with 12 genes (IL1RAP, TMSB4X, COLEC12, ENPP2, KLRC1, RERG, RGS16, TNNT2, CYR61, FER1L3, FAM108A1, and CYP4X1), suggesting that these genes are likely to be ERbeta primary target genes. This study has provided novel information on the gene regulatory function of ERbeta independent of ERalpha and identified a number of ERbeta primary target genes. The results of Gene Ontology analysis and proliferation assays are consistent with an antiproliferative role of ERbeta independent of ERalpha.

  11. Differentially expressed genes identified by cross-species microarray in the blind cavefish Astyanax.

    PubMed

    Strickler, Allen G; Jeffery, William R

    2009-03-01

    Changes in gene expression were examined by microarray analysis during development of the eyed surface dwelling (surface fish) and blind cave-dwelling (cavefish) forms of the teleost Astyanax mexicanus De Filippi, 1853. The cross-species microarray used surface and cavefish RNA hybridized to a DNA chip prepared from a closely related species, the zebrafish Danio rerio Hamilton, 1822. We identified a total of 67 differentially expressed probe sets at three days post-fertilization: six upregulated and 61 downregulated in cavefish relative to surface fish. Many of these genes function either in eye development and/or maintenance, or in programmed cell death. The upregulated probe set showing the highest mean fold change was similar to the human ubiquitin specific protease 53 gene. The downregulated probe sets showing some of the highest fold changes corresponded to genes with roles in eye development, including those encoding gamma crystallins, the guanine nucleotide binding proteins Gnat1 and Gant2, a BarH-like homeodomain transcription factor, and rhodopsin. Downregulation of gamma-crystallin and rhodopsin was confirmed by in situ hybridization and immunostaining with specific antibodies. Additional downregulated genes encode molecules that inhibit or activate programmed cell death. The results suggest that cross-species microarray can be used for identifying differentially expressed genes in cavefish, that many of these genes might be involved in eye degeneration via apoptotic processes, and that more genes are downregulated than upregulated in cavefish, consistent with the predominance of morphological losses over gains during regressive evolution. © 2009 ISZS, Blackwell Publishing and IOZ/CAS.

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

    PubMed Central

    2010-01-01

    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, and it may also be used to

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

    PubMed

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

    2016-11-01

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

  14. Optimization Based Tumor Classification from Microarray Gene Expression Data

    PubMed Central

    Dagliyan, Onur; Uney-Yuksektepe, Fadime; Kavakli, I. Halil; Turkay, Metin

    2011-01-01

    Background An important use of data obtained from microarray measurements is the classification of tumor types with respect to genes that are either up or down regulated in specific cancer types. A number of algorithms have been proposed to obtain such classifications. These algorithms usually require parameter optimization to obtain accurate results depending on the type of data. Additionally, it is highly critical to find an optimal set of markers among those up or down regulated genes that can be clinically utilized to build assays for the diagnosis or to follow progression of specific cancer types. In this paper, we employ a mixed integer programming based classification algorithm named hyper-box enclosure method (HBE) for the classification of some cancer types with a minimal set of predictor genes. This optimization based method which is a user friendly and efficient classifier may allow the clinicians to diagnose and follow progression of certain cancer types. Methodology/Principal Findings We apply HBE algorithm to some well known data sets such as leukemia, prostate cancer, diffuse large B-cell lymphoma (DLBCL), small round blue cell tumors (SRBCT) to find some predictor genes that can be utilized for diagnosis and prognosis in a robust manner with a high accuracy. Our approach does not require any modification or parameter optimization for each data set. Additionally, information gain attribute evaluator, relief attribute evaluator and correlation-based feature selection methods are employed for the gene selection. The results are compared with those from other studies and biological roles of selected genes in corresponding cancer type are described. Conclusions/Significance The performance of our algorithm overall was better than the other algorithms reported in the literature and classifiers found in WEKA data-mining package. Since it does not require a parameter optimization and it performs consistently very high prediction rate on different type of

  15. Electrosonic ejector microarray for drug and gene delivery.

    PubMed

    Zarnitsyn, Vladimir G; Meacham, J Mark; Varady, Mark J; Hao, Chunhai; Degertekin, F Levent; Fedorov, Andrei G

    2008-04-01

    We report on development and experimental characterization of a novel cell manipulation device-the electrosonic ejector microarray-which establishes a pathway for drug and/or gene delivery with control of biophysical action on the length scale of an individual cell. The device comprises a piezoelectric transducer for ultrasound wave generation, a reservoir for storing the sample mixture and a set of acoustic horn structures that form a nozzle array for focused application of mechanical energy. The nozzles are micromachined in silicon or plastic using simple and economical batch fabrication processes. When the device is driven at a particular resonant frequency of the acoustic horn structures, the sample mixture of cells and desired transfection agents/molecules suspended in culture medium is ejected from orifices located at the nozzle tips. During sample ejection, focused mechanical forces (pressure and shear) are generated on a microsecond time scale (dictated by nozzle size/geometry and ejection velocity) resulting in identical "active" microenvironments for each ejected cell. This process enables a number of cellular bioeffects, from uptake of small molecules and gene delivery/transfection to cell lysis. Specifically, we demonstrate successful calcein uptake and transfection of DNA plasmid encoding green fluorescent protein (GFP) into human malignant glioma cells (cell line LN443) using electrosonic microarrays with 36, 45 and 50 mum diameter nozzle orifices and operating at ultrasound frequencies between 0.91 and 0.98 MHz. Our results suggest that efficacy and the extent of bioeffects are mainly controlled by nozzle orifice size and the localized intensity of the applied acoustic field.

  16. Identification of Iron Homeostasis Genes Dysregulation Potentially Involved in Retinopathy of Prematurity Pathogenicity by Microarray Analysis

    PubMed Central

    Luo, Xian-qiong; Zhang, Chun-yi; Zhang, Jia-wen; Jiang, Jing-bo; Yin, Ai-hua; Guo, Li; Nie, Chuan; Lu, Xu-zai; Deng, Hua; Zhang, Liang

    2015-01-01

    Retinopathy of prematurity (ROP) is a serious disease of preterm neonates and there are limited systematic studies of the molecular mechanisms underlying ROP. Therefore, here we performed global gene expression profiling in human fetal retinal microvascular endothelial cells (RMECs) under hypoxic conditions in vitro. Aborted fetuses were enrolled and primary RMECs were isolated from eyeballs. Cultivated cells were treated with CoCl2 to induce hypoxia. The dual-color microarray approach was adopted to compare gene expression profiling between treated RMECs and the paired untreated control. The one-class algorithm in significance analysis of microarray (SAM) software was used to screen the differentially expressed genes (DEGs) and quantitative RT-PCR (qRT-PCR) was conducted to validate the results. Gene Ontology was employed for functional enrichment analysis. There were 326 DEGs between the hypoxia-induced group and untreated group. Of these genes, 198 were upregulated in hypoxic RMECs, while the other 128 hits were downregulated. In particular, genes in the iron ion homeostasis pathway were highly enriched under hypoxic conditions. Our study indicates that dysregulation of genes involved in iron homeostasis mediating oxidative damage may be responsible for the mechanisms underlying ROP. The “oxygen plus iron” hypothesis may improve our understanding of ROP pathogenesis. PMID:26557385

  17. DEVELOPMENT AND VALIDATION OF A 2,000 GENE MICROARRAY FOR THE FATHEAD MINNOW, PIMEPHALES PROMELAS

    EPA Science Inventory

    The development of the gene microarray has provided the field of ecotoxicology a new tool to identify modes of action (MOA) of chemicals and chemical mixtures. Herein we describe the development and application of a 2,000 gene oligonucleotide microarray for the fathead minnow (P...

  18. DEVELOPMENT AND VALIDATION OF A 2,000 GENE MICROARRAY FOR THE FATHEAD MINNOW, PIMEPHALES PROMELAS

    EPA Science Inventory

    The development of the gene microarray has provided the field of ecotoxicology a new tool to identify modes of action (MOA) of chemicals and chemical mixtures. Herein we describe the development and application of a 2,000 gene oligonucleotide microarray for the fathead minnow (P...

  19. Partial least squares dimension reduction for microarray gene expression data with a censored response.

    PubMed

    Nguyen, Danh V

    2005-01-01

    An important application of DNA microarray technologies involves monitoring the global state of transcriptional program in tumor cells. One goal in cancer microarray studies is to compare the clinical outcome, such as relapse-free or overall survival, for subgroups of patients defined by global gene expression patterns. A method of comparing patient survival, as a function of gene expression, was recently proposed in [Bioinformatics 18 (2002) 1625] by Nguyen and Rocke. Due to the (a) high-dimensionality of microarray gene expression data and (b) censored survival times, a two-stage procedure was proposed to relate survival times to gene expression profiles. The first stage involves dimensionality reduction of the gene expression data by partial least squares (PLS) and the second stage involves prediction of survival probability using proportional hazard regression. In this paper, we provide a systematic assessment of the performance of this two-stage procedure. PLS dimension reduction involves complex non-linear functions of both the predictors and the response data, rendering exact analytical study intractable. Thus, we assess the methodology under a simulation model for gene expression data with a censored response variable. In particular, we compare the performance of PLS dimension reduction relative to dimension reduction via principal components analysis (PCA) and to a modified PLS (MPLS) approach. PLS performed substantially better relative to dimension reduction via PCA when the total predictor variance explained is low to moderate (e.g. 40%-60%). It performed similar to MPLS and slightly better in some cases. Additionally, we examine the effect of censoring on dimension reduction stage. The performance of all methods deteriorates for a high censoring rate, although PLS-PH performed relatively best overall.

  20. Microarray Analysis Identifies Cerebellar Genes Sensitive to Chronic Ethanol Treatment in PKCγ Mice

    PubMed Central

    Bowers, Barbara J.; Radcliffe, Richard A.; Smith, Amy M.; Miyamoto-Ditmon, Jill; Wehner, Jeanne M.

    2007-01-01

    Neuroadaptive changes that occur in the development of ethanol tolerance may be the result of alterations in gene expression. We have shown that PKCγ wild-type mice develop tolerance to the sedative-hypnotic effects of ethanol after chronic ethanol treatment; whereas, mutant mice do not, making these genotypes a suitable model for identifying changes in gene expression related to tolerance development. Using a two-stage process, several genes were initially identified using microarray analyses of cerebellar tissue from ethanol-treated PKCγ mutant and wild-type mice. Subsequent confirmation of a subset of these genes using qRT-PCR was done to verify gene expression changes. A total of 109 genes from different functional classifications were identified in these groups on the microarrays. Eight genes were selected for verification: three, Twik-1, Plp, and Adk2, were chosen as genes related to tolerance; another three, Hsp70.2, Bdnf, and Th, were chosen as genes related to resistance to tolerance; and two genes, JunB and Nur77, were selected as candidate genes sensitive to chronic ethanol. The results from the verification experiments indicated that Twik-1, which codes for a potassium channel, was associated with tolerance and appeared to be dependent on the presence of PKCγ. No genes were confirmed to be related to resistance to tolerance; however, expression of two of these, Hsp70.2 and Th, were found to be sensitive to chronic ethanol and were added to the transcription factors, JunB and Nur77, confirmed by qRT-PCR, as a subset of genes that respond to chronic ethanol. PMID:17157717

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

    PubMed Central

    2011-01-01

    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. PMID:21261946

  2. SoFoCles: feature filtering for microarray classification based on gene ontology.

    PubMed

    Papachristoudis, Georgios; Diplaris, Sotiris; Mitkas, Pericles A

    2010-02-01

    Marker gene selection has been an important research topic in the classification analysis of gene expression data. Current methods try to reduce the "curse of dimensionality" by using statistical intra-feature set calculations, or classifiers that are based on the given dataset. In this paper, we present SoFoCles, an interactive tool that enables semantic feature filtering in microarray classification problems with the use of external, well-defined knowledge retrieved from the Gene Ontology. The notion of semantic similarity is used to derive genes that are involved in the same biological path during the microarray experiment, by enriching a feature set that has been initially produced with legacy methods. Among its other functionalities, SoFoCles offers a large repository of semantic similarity methods that are used in order to derive feature sets and marker genes. The structure and functionality of the tool are discussed in detail, as well as its ability to improve classification accuracy. Through experimental evaluation, SoFoCles is shown to outperform other classification schemes in terms of classification accuracy in two real datasets using different semantic similarity computation approaches.

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

    PubMed

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

    2013-01-01

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

  4. Discovering monotonic stemness marker genes from time-series stem cell microarray data.

    PubMed

    Wang, Hsei-Wei; Sun, Hsing-Jen; Chang, Ting-Yu; Lo, Hung-Hao; Cheng, Wei-Chung; Tseng, George C; Lin, Chin-Teng; Chang, Shing-Jyh; Pal, Nikhil; Chung, I-Fang

    2015-01-01

    Identification of genes with ascending or descending monotonic expression patterns over time or stages of stem cells is an important issue in time-series microarray data analysis. We propose a method named Monotonic Feature Selector (MFSelector) based on a concept of total discriminating error (DEtotal) to identify monotonic genes. MFSelector considers various time stages in stage order (i.e., Stage One vs. other stages, Stages One and Two vs. remaining stages and so on) and computes DEtotal of each gene. MFSelector can successfully identify genes with monotonic characteristics. We have demonstrated the effectiveness of MFSelector on two synthetic data sets and two stem cell differentiation data sets: embryonic stem cell neurogenesis (ESCN) and embryonic stem cell vasculogenesis (ESCV) data sets. We have also performed extensive quantitative comparisons of the three monotonic gene selection approaches. Some of the monotonic marker genes such as OCT4, NANOG, BLBP, discovered from the ESCN dataset exhibit consistent behavior with that reported in other studies. The role of monotonic genes found by MFSelector in either stemness or differentiation is validated using information obtained from Gene Ontology analysis and other literature. We justify and demonstrate that descending genes are involved in the proliferation or self-renewal activity of stem cells, while ascending genes are involved in differentiation of stem cells into variant cell lineages. We have developed a novel system, easy to use even with no pre-existing knowledge, to identify gene sets with monotonic expression patterns in multi-stage as well as in time-series genomics matrices. The case studies on ESCN and ESCV have helped to get a better understanding of stemness and differentiation. The novel monotonic marker genes discovered from a data set are found to exhibit consistent behavior in another independent data set, demonstrating the utility of the proposed method. The MFSelector R function and data

  5. Microarray-based mutation detection in the dystrophin gene.

    PubMed

    Hegde, Madhuri R; Chin, Ephrem L H; Mulle, Jennifer G; Okou, David T; Warren, Stephen T; Zwick, Michael E

    2008-09-01

    Duchenne and Becker muscular dystrophies (DMD and BMD) are X-linked recessive neuromuscular disorders caused by mutations in the dystrophin gene affecting approximately 1 in 3,500 males. The human dystrophin gene spans>2,200 kb, or roughly 0.1% of the genome, and is composed of 79 exons. The mutational spectrum of disease-causing alleles, including exonic copy number variations (CNVs), is complex. Deletions account for approximately 65% of DMD mutations and 85% of BMD mutations. Duplications occur in approximately 6 to 10% of males with either DMD or BMD. The remaining 30 to 35% of mutations consist of small deletions, insertions, point mutations, or splicing mutations, most of which introduce a premature stop codon. Laboratory analysis of dystrophin can be used to confirm a clinical diagnosis of DMD, characterize the type of dystrophin mutation, and perform prenatal testing and carrier testing for females. Current dystrophin diagnostic assays involve a variety of methodologies, including multiplex PCR, Southern blot analysis, multiplex ligation-dependent probe amplification (MLPA), detection of virtually all mutations-SSCP (DOVAM-S), and single condition amplification/internal primer sequencing (SCAIP); however, these methods are time-consuming, laborious, and do not accurately detect duplication mutations in the dystrophin gene. Furthermore, carrier testing in females is often difficult when a related affected male is unavailable. Here we describe the development, design, validation, and implementation of a high-resolution comparative genomic hybridization (CGH) microarray-based approach capable of accurately detecting both deletions and duplications in the dystrophin gene. This assay can be readily adopted by clinical molecular testing laboratories and represents a rapid, cost-effective approach for screening a large gene, such as dystrophin.

  6. Microarray-based mutation detection in the dystrophin gene

    PubMed Central

    Hegde, Madhuri R.; Chin, Ephrem L.H.; Mulle, Jennifer G.; Okou, David T.; Warren, Stephen T.; Zwick, Michael E.

    2008-01-01

    Duchenne and Becker muscular dystrophies (DMD and BMD) are X-linked recessive neuromuscular disorders caused by mutations in the dystrophin gene affecting approximately 1 in 3,500 males. The human dystrophin gene spans > 2,200 kb, or roughly 0.1% of the genome, and is composed of 79 exons. The mutational spectrum of disease-causing alleles, including exonic copy number variations (CNVs), is complex. Deletions account for approximately 65% of DMD mutations and 85% of BMD mutations. Duplications occur in approximately 6–10% of males with either DMD or BMD. The remaining 30–35% of mutations consist of small deletions, insertions, point mutations, or splicing mutations, most of which introduce a premature stop codon. Laboratory analysis of dystrophin can be used to confirm a clinical diagnosis of DMD, characterize the type of dystrophin mutation, and perform prenatal testing and carrier testing for females. Current dystrophin diagnostic assays involve a variety of methodologies, including multiplex PCR, Southern blot analysis, MLPA, DOVAM-S, and SCAIP; however, these methods are time-consuming, laborious, and do not accurately detect duplication mutations in the dystrophin gene. Furthermore, carrier testing in females is often difficult when a related affected male is unavailable. Here we describe the development, design, validation, and implementation of a high-resolution CGH microarray-based approach capable of accurately detecting both deletions and duplications in the dystrophin gene. This assay can be readily adopted by clinical molecular testing laboratories and represents a rapid, cost-effective approach for screening a large gene, such as dystrophin. PMID:18663755

  7. Use of Microarray to Analyze Gene Expression Profiles of Acute Effects of Prochloraz on Fathead Minnows Pimephales promelas

    EPA Science Inventory

    Microarray technology is a powerful tool to investigate the gene expression profiles for thousands of genes simultaneously. In recent years, microarrays have been used to characterize environmental pollutants and identify molecular mode(s) of action of chemicals including endocri...

  8. Use of Microarray to Analyze Gene Expression Profiles of Acute Effects of Prochloraz on Fathead Minnows Pimephales promelas

    EPA Science Inventory

    Microarray technology is a powerful tool to investigate the gene expression profiles for thousands of genes simultaneously. In recent years, microarrays have been used to characterize environmental pollutants and identify molecular mode(s) of action of chemicals including endocri...

  9. Microarray analysis of genes differentially expressed in HepG2 cells cultured in simulated microgravity: preliminary report

    NASA Technical Reports Server (NTRS)

    Khaoustov, V. I.; Risin, D.; Pellis, N. R.; Yoffe, B.; McIntire, L. V. (Principal Investigator)

    2001-01-01

    Developed at NASA, the rotary cell culture system (RCCS) allows the creation of unique microgravity environment of low shear force, high-mass transfer, and enables three-dimensional (3D) cell culture of dissimilar cell types. Recently we demonstrated that a simulated microgravity is conducive for maintaining long-term cultures of functional hepatocytes and promote 3D cell assembly. Using deoxyribonucleic acid (DNA) microarray technology, it is now possible to measure the levels of thousands of different messenger ribonucleic acids (mRNAs) in a single hybridization step. This technique is particularly powerful for comparing gene expression in the same tissue under different environmental conditions. The aim of this research was to analyze gene expression of hepatoblastoma cell line (HepG2) during early stage of 3D-cell assembly in simulated microgravity. For this, mRNA from HepG2 cultured in the RCCS was analyzed by deoxyribonucleic acid microarray. Analyses of HepG2 mRNA by using 6K glass DNA microarray revealed changes in expression of 95 genes (overexpression of 85 genes and downregulation of 10 genes). Our preliminary results indicated that simulated microgravity modifies the expression of several genes and that microarray technology may provide new understanding of the fundamental biological questions of how gravity affects the development and function of individual cells.

  10. Microarray analysis of genes differentially expressed in HepG2 cells cultured in simulated microgravity: preliminary report.

    PubMed

    Khaoustov, V I; Risin, D; Pellis, N R; Yoffe, B

    2001-02-01

    Developed at NASA, the rotary cell culture system (RCCS) allows the creation of unique microgravity environment of low shear force, high-mass transfer, and enables three-dimensional (3D) cell culture of dissimilar cell types. Recently we demonstrated that a simulated microgravity is conducive for maintaining long-term cultures of functional hepatocytes and promote 3D cell assembly. Using deoxyribonucleic acid (DNA) microarray technology, it is now possible to measure the levels of thousands of different messenger ribonucleic acids (mRNAs) in a single hybridization step. This technique is particularly powerful for comparing gene expression in the same tissue under different environmental conditions. The aim of this research was to analyze gene expression of hepatoblastoma cell line (HepG2) during early stage of 3D-cell assembly in simulated microgravity. For this, mRNA from HepG2 cultured in the RCCS was analyzed by deoxyribonucleic acid microarray. Analyses of HepG2 mRNA by using 6K glass DNA microarray revealed changes in expression of 95 genes (overexpression of 85 genes and downregulation of 10 genes). Our preliminary results indicated that simulated microgravity modifies the expression of several genes and that microarray technology may provide new understanding of the fundamental biological questions of how gravity affects the development and function of individual cells.

  11. Microarray analysis of genes differentially expressed in HepG2 cells cultured in simulated microgravity: preliminary report

    NASA Technical Reports Server (NTRS)

    Khaoustov, V. I.; Risin, D.; Pellis, N. R.; Yoffe, B.; McIntire, L. V. (Principal Investigator)

    2001-01-01

    Developed at NASA, the rotary cell culture system (RCCS) allows the creation of unique microgravity environment of low shear force, high-mass transfer, and enables three-dimensional (3D) cell culture of dissimilar cell types. Recently we demonstrated that a simulated microgravity is conducive for maintaining long-term cultures of functional hepatocytes and promote 3D cell assembly. Using deoxyribonucleic acid (DNA) microarray technology, it is now possible to measure the levels of thousands of different messenger ribonucleic acids (mRNAs) in a single hybridization step. This technique is particularly powerful for comparing gene expression in the same tissue under different environmental conditions. The aim of this research was to analyze gene expression of hepatoblastoma cell line (HepG2) during early stage of 3D-cell assembly in simulated microgravity. For this, mRNA from HepG2 cultured in the RCCS was analyzed by deoxyribonucleic acid microarray. Analyses of HepG2 mRNA by using 6K glass DNA microarray revealed changes in expression of 95 genes (overexpression of 85 genes and downregulation of 10 genes). Our preliminary results indicated that simulated microgravity modifies the expression of several genes and that microarray technology may provide new understanding of the fundamental biological questions of how gravity affects the development and function of individual cells.

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

    PubMed

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

    2017-09-01

    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

  13. Microarray analysis identifies Salmonella genes belonging to the low-shear modeled microgravity regulon

    NASA Technical Reports Server (NTRS)

    Wilson, James W.; Ramamurthy, Rajee; Porwollik, Steffen; McClelland, Michael; Hammond, Timothy; Allen, Pat; Ott, C. Mark; Pierson, Duane L.; Nickerson, Cheryl A.

    2002-01-01

    The low-shear environment of optimized rotation suspension culture allows both eukaryotic and prokaryotic cells to assume physiologically relevant phenotypes that have led to significant advances in fundamental investigations of medical and biological importance. This culture environment has also been used to model microgravity for ground-based studies regarding the impact of space flight on eukaryotic and prokaryotic physiology. We have previously demonstrated that low-shear modeled microgravity (LSMMG) under optimized rotation suspension culture is a novel environmental signal that regulates the virulence, stress resistance, and protein expression levels of Salmonella enterica serovar Typhimurium. However, the mechanisms used by the cells of any species, including Salmonella, to sense and respond to LSMMG and identities of the genes involved are unknown. In this study, we used DNA microarrays to elucidate the global transcriptional response of Salmonella to LSMMG. When compared with identical growth conditions under normal gravity (1 x g), LSMMG differentially regulated the expression of 163 genes distributed throughout the chromosome, representing functionally diverse groups including transcriptional regulators, virulence factors, lipopolysaccharide biosynthetic enzymes, iron-utilization enzymes, and proteins of unknown function. Many of the LSMMG-regulated genes were organized in clusters or operons. The microarray results were further validated by RT-PCR and phenotypic analyses, and they indicate that the ferric uptake regulator is involved in the LSMMG response. The results provide important insight about the Salmonella LSMMG response and could provide clues for the functioning of known Salmonella virulence systems or the identification of uncharacterized bacterial virulence strategies.

  14. Microarray analysis identifies Salmonella genes belonging to the low-shear modeled microgravity regulon

    NASA Technical Reports Server (NTRS)

    Wilson, James W.; Ramamurthy, Rajee; Porwollik, Steffen; McClelland, Michael; Hammond, Timothy; Allen, Pat; Ott, C. Mark; Pierson, Duane L.; Nickerson, Cheryl A.

    2002-01-01

    The low-shear environment of optimized rotation suspension culture allows both eukaryotic and prokaryotic cells to assume physiologically relevant phenotypes that have led to significant advances in fundamental investigations of medical and biological importance. This culture environment has also been used to model microgravity for ground-based studies regarding the impact of space flight on eukaryotic and prokaryotic physiology. We have previously demonstrated that low-shear modeled microgravity (LSMMG) under optimized rotation suspension culture is a novel environmental signal that regulates the virulence, stress resistance, and protein expression levels of Salmonella enterica serovar Typhimurium. However, the mechanisms used by the cells of any species, including Salmonella, to sense and respond to LSMMG and identities of the genes involved are unknown. In this study, we used DNA microarrays to elucidate the global transcriptional response of Salmonella to LSMMG. When compared with identical growth conditions under normal gravity (1 x g), LSMMG differentially regulated the expression of 163 genes distributed throughout the chromosome, representing functionally diverse groups including transcriptional regulators, virulence factors, lipopolysaccharide biosynthetic enzymes, iron-utilization enzymes, and proteins of unknown function. Many of the LSMMG-regulated genes were organized in clusters or operons. The microarray results were further validated by RT-PCR and phenotypic analyses, and they indicate that the ferric uptake regulator is involved in the LSMMG response. The results provide important insight about the Salmonella LSMMG response and could provide clues for the functioning of known Salmonella virulence systems or the identification of uncharacterized bacterial virulence strategies.

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

    PubMed Central

    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

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

    PubMed

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

    2015-06-01

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

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

    SciTech Connect

    William Grundy; Manuel Ares, Jr.; David Haussler

    2001-06-18

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

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

    PubMed

    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.

  19. An Agent-Based Clustering Approach for Gene Selection in Gene Expression Microarray.

    PubMed

    Ramos, Juan; Castellanos-Garzón, José A; González-Briones, Alfonso; de Paz, Juan F; Corchado, Juan M

    2017-03-09

    Gene selection is a major research area in microarray analysis, which seeks to discover differentially expressed genes for a particular target annotation. Such genes also often called informative genes are able to differentiate tissue samples belonging to different classes of the studied disease. Despite the fact that there is a wide number of proposals, the complexity imposed by this problem remains a challenge today. This research proposes a gene selection approach by means of a clustering-based multi-agent system. This proposal manages different filter methods and gene clustering through coordinated agents to discover informative gene subsets. To assess the reliability of our approach, we have used four important and public gene expression datasets, two Lung cancer datasets, Colon and Leukemia cancer dataset. The achieved results have been validated through cluster validity measures, visual analytics, a classifier and compared with other gene selection methods, proving the reliability of our proposal.

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

    PubMed

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

    2015-01-01

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

  1. Identification of key genes associated with the effect of estrogen on ovarian cancer using microarray analysis.

    PubMed

    Zhang, Shi-tao; Zuo, Chao; Li, Wan-nan; Fu, Xue-qi; Xing, Shu; Zhang, Xiao-ping

    2016-02-01

    To identify key genes related to the effect of estrogen on ovarian cancer. Microarray data (GSE22600) were downloaded from Gene Expression Omnibus. Eight estrogen and seven placebo treatment samples were obtained using a 2 × 2 factorial designs, which contained 2 cell lines (PEO4 and 2008) and 2 treatments (estrogen and placebo). Differentially expressed genes were identified by Bayesian methods, and the genes with P < 0.05 and |log2FC (fold change)| ≥0.5 were chosen as cut-off criterion. Differentially co-expressed genes (DCGs) and differentially regulated genes (DRGs) were, respectively, identified by DCe function and DRsort function in DCGL package. Topological structure analysis was performed on the important transcriptional factors (TFs) and genes in transcriptional regulatory network using tYNA. Functional enrichment analysis was, respectively, performed for DEGs and the important genes using Gene Ontology and KEGG databases. In total, 465 DEGs were identified. Functional enrichment analysis of DEGs indicated that ACVR2B, LTBP1, BMP7 and MYC involved in TGF-beta signaling pathway. The 2285 DCG pairs and 357 DRGs were identified. Topological structure analysis showed that 52 important TFs and 65 important genes were identified. Functional enrichment analysis of the important genes showed that TP53 and MLH1 participated in DNA damage response and the genes (ACVR2B, LTBP1, BMP7 and MYC) involved in TGF-beta signaling pathway. TP53, MLH1, ACVR2B, LTBP1 and BMP7 might participate in the pathogenesis of ovarian cancer.

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

    USDA-ARS?s Scientific Manuscript database

    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. Microarray analysis of gene expression in acaricide-exposed Rhipcephalus (Boophilus) microplus larvae.

    USDA-ARS?s Scientific Manuscript database

    Acaricide-inducible differential gene expression was studied in larvae of Rhipicephalus (Boophilus) microplus using a microarray-based approach. The acaricides used were: coumaphos, permethrin, ivermectin, and amitraz. The microarrays contained over 13,000 probes, having been derived from a previous...

  4. Microarray analysis of acaricide inducible gene expression in the southern cattle tick, Rhipicephalus (Boophilus) microplus

    USDA-ARS?s Scientific Manuscript database

    Acaricide-inducible differential gene expression was studied in larvae of Rhipicephalus (Boophilus) microplus using a microarray-based approach. The acaricides used were: coumaphos, permethrin, ivermectin, and amitraz. The microarrays contained over 13,000 probes, having been derived from a previous...

  5. Ossification of the posterior longitudinal ligament related genes identification using microarray gene expression profiling and bioinformatics analysis.

    PubMed

    He, Hailong; Mao, Lingzhou; Xu, Peng; Xi, Yanhai; Xu, Ning; Xue, Mingtao; Yu, Jiangming; Ye, Xiaojian

    2014-01-10

    Ossification of the posterior longitudinal ligament (OPLL) is a kind of disease with physical barriers and neurological disorders. The objective of this study was to explore the differentially expressed genes (DEGs) in OPLL patient ligament cells and identify the target sites for the prevention and treatment of OPLL in clinic. Gene expression data GSE5464 was downloaded from Gene Expression Omnibus; then DEGs were screened by limma package in R language, and changed functions and pathways of OPLL cells compared to normal cells were identified by DAVID (The Database for Annotation, Visualization and Integrated Discovery); finally, an interaction network of DEGs was constructed by string. A total of 1536 DEGs were screened, with 31 down-regulated and 1505 up-regulated genes. Response to wounding function and Toll-like receptor signaling pathway may involve in the development of OPLL. Genes, such as PDGFB, PRDX2 may involve in OPLL through response to wounding function. Toll-like receptor signaling pathway enriched genes such as TLR1, TLR5, and TLR7 may involve in spine cord injury in OPLL. PIK3R1 was the hub gene in the network of DEGs with the highest degree; INSR was one of the most closely related genes of it. OPLL related genes screened by microarray gene expression profiling and bioinformatics analysis may be helpful for elucidating the mechanism of OPLL.

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

    PubMed Central

    Warnat, Patrick; Eils, Roland; Brors, Benedikt

    2005-01-01

    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 microarray technologies

  7. Large scale comparison of gene expression levels by microarrays and RNAseq using TCGA data.

    PubMed

    Guo, Yan; Sheng, Quanhu; Li, Jiang; Ye, Fei; Samuels, David C; Shyr, Yu

    2013-01-01

    RNAseq and microarray methods are frequently used to measure gene expression level. While similar in purpose, there are fundamental differences between the two technologies. Here, we present the largest comparative study between microarray and RNAseq methods to date using The Cancer Genome Atlas (TCGA) data. We found high correlations between expression data obtained from the Affymetrix one-channel microarray and RNAseq (Spearman correlations coefficients of ∼0.8). We also observed that the low abundance genes had poorer correlations between microarray and RNAseq data than high abundance genes. As expected, due to measurement and normalization differences, Agilent two-channel microarray and RNAseq data were poorly correlated (Spearman correlations coefficients of only ∼0.2). By examining the differentially expressed genes between tumor and normal samples we observed reasonable concordance in directionality between Agilent two-channel microarray and RNAseq data, although a small group of genes were found to have expression changes reported in opposite directions using these two technologies. Overall, RNAseq produces comparable results to microarray technologies in term of expression profiling. The RNAseq normalization methods RPKM and RSEM produce similar results on the gene level and reasonably concordant results on the exon level. Longer exons tended to have better concordance between the two normalization methods than shorter exons.

  8. Large Scale Comparison of Gene Expression Levels by Microarrays and RNAseq Using TCGA Data

    PubMed Central

    Li, Jiang; Ye, Fei; Samuels, David C.; Shyr, Yu

    2013-01-01

    RNAseq and microarray methods are frequently used to measure gene expression level. While similar in purpose, there are fundamental differences between the two technologies. Here, we present the largest comparative study between microarray and RNAseq methods to date using The Cancer Genome Atlas (TCGA) data. We found high correlations between expression data obtained from the Affymetrix one-channel microarray and RNAseq (Spearman correlations coefficients of ∼0.8). We also observed that the low abundance genes had poorer correlations between microarray and RNAseq data than high abundance genes. As expected, due to measurement and normalization differences, Agilent two-channel microarray and RNAseq data were poorly correlated (Spearman correlations coefficients of only ∼0.2). By examining the differentially expressed genes between tumor and normal samples we observed reasonable concordance in directionality between Agilent two-channel microarray and RNAseq data, although a small group of genes were found to have expression changes reported in opposite directions using these two technologies. Overall, RNAseq produces comparable results to microarray technologies in term of expression profiling. The RNAseq normalization methods RPKM and RSEM produce similar results on the gene level and reasonably concordant results on the exon level. Longer exons tended to have better concordance between the two normalization methods than shorter exons. PMID:23977046

  9. Unsupervised Bayesian linear unmixing of gene expression microarrays.

    PubMed

    Bazot, Cécile; Dobigeon, Nicolas; Tourneret, Jean-Yves; Zaas, Aimee K; Ginsburg, Geoffrey S; Hero, Alfred O

    2013-03-19

    This paper introduces a new constrained model and the corresponding algorithm, called unsupervised Bayesian linear unmixing (uBLU), to identify biological signatures from high dimensional assays like gene expression microarrays. The basis for uBLU is a Bayesian model for the data samples which are represented as an additive mixture of random positive gene signatures, called factors, with random positive mixing coefficients, called factor scores, that specify the relative contribution of each signature to a specific sample. The particularity of the proposed method is that uBLU constrains the factor loadings to be non-negative and the factor scores to be probability distributions over the factors. Furthermore, it also provides estimates of the number of factors. A Gibbs sampling strategy is adopted here to generate random samples according to the posterior distribution of the factors, factor scores, and number of factors. These samples are then used to estimate all the unknown parameters. Firstly, the proposed uBLU method is applied to several simulated datasets with known ground truth and compared with previous factor decomposition methods, such as principal component analysis (PCA), non negative matrix factorization (NMF), Bayesian factor regression modeling (BFRM), and the gradient-based algorithm for general matrix factorization (GB-GMF). Secondly, we illustrate the application of uBLU on a real time-evolving gene expression dataset from a recent viral challenge study in which individuals have been inoculated with influenza A/H3N2/Wisconsin. We show that the uBLU method significantly outperforms the other methods on the simulated and real data sets considered here. The results obtained on synthetic and real data illustrate the accuracy of the proposed uBLU method when compared to other factor decomposition methods from the literature (PCA, NMF, BFRM, and GB-GMF). The uBLU method identifies an inflammatory component closely associated with clinical symptom scores

  10. Analysis of Temporal-spatial Co-variation within Gene Expression Microarray Data in an Organogenesis Model

    NASA Astrophysics Data System (ADS)

    Ehler, Martin; Rajapakse, Vinodh; Zeeberg, Barry; Brooks, Brian; Brown, Jacob; Czaja, Wojciech; Bonner, Robert F.

    The gene networks underlying closure of the optic fissure during vertebrate eye development are poorly understood. We used a novel clustering method based on Laplacian Eigenmaps, a nonlinear dimension reduction method, to analyze microarray data from laser capture microdissected (LCM) cells at the site and developmental stages (days 10.5 to 12.5) of optic fissure closure. Our new method provided greater biological specificity than classical clustering algorithms in terms of identifying more biological processes and functions related to eye development as defined by Gene Ontology at lower false discovery rates. This new methodology builds on the advantages of LCM to isolate pure phenotypic populations within complex tissues and allows improved ability to identify critical gene products expressed at lower copy number. The combination of LCM of embryonic organs, gene expression microarrays, and extracting spatial and temporal co-variations appear to be a powerful approach to understanding the gene regulatory networks that specify mammalian organogenesis.

  11. Microarray Analysis of Gene Expression in Soybean Roots Susceptible to the Soybean Cyst Nematode Two Days Post Invasion

    PubMed Central

    Khan, R.; Alkharouf, N.; Beard, H.; MacDonald, M.; Chouikha, I.; Meyer, S.; Grefenstette, J.; Knap, H.; Matthews, B.

    2004-01-01

    Soybean root cells undergo dramatic morphological and biochemical changes during the establishment of a feeding site in a compatible interaction with the soybean cyst nematode (SCN). We constructed a cDNA microarray with approximately 1,300 cDNA inserts targeted to identify differentially expressed genes during the compatible interaction of SCN with soybean roots 2 days after infection. Three independent biological replicates were grown and inoculated with SCN, and 2 days later RNA was extracted for hybridization to microarrays and compared to noninoculated controls. Statistical analysis indicated that approximately 8% of the genes monitored were induced and more than 50% of these were genes of unknown function. Notable genes that were more highly expressed 2 days after inoculation with SCN as compared to noninoculated roots included the repetitive proline-rich glycoprotein, the stress-induced gene SAM22, ß-1,3-endoglucanase, peroxidase, and those involved in carbohydrate metabolism, plant defense, and signaling. PMID:19262812

  12. Use of a bacterial antimicrobial resistance gene microarray for the identification of resistant Staphylococcus aureus.

    PubMed

    Garneau, P; Labrecque, O; Maynard, C; Messier, S; Masson, L; Archambault, M; Harel, J

    2010-11-01

    As diagnostic and surveillance activities are vital to determine measures needed to control antimicrobial resistance (AMR), new and rapid laboratory methods are necessary to facilitate this important effort. DNA microarray technology allows the detection of a large number of genes in a single reaction. This technology is simple, specific and high-throughput. We have developed a bacterial antimicrobial resistance gene DNA microarray that will allow rapid antimicrobial resistance gene screening for all Gram-positive and Gram-negative bacteria. A prototype microarray was designed using a 70-mer based oligonucleotide set targeting AMR genes of Gram-negative and Gram-positive bacteria. In the present version, the microarray consists of 182 oligonucleotides corresponding to 166 different acquired AMR gene targets, covering most of the resistance genes found in both Gram-negative and -positive bacteria. A test study was performed on a collection of Staphylococcus aureus isolates from milk samples from dairy farms in Québec, Canada. The reproducibility of the hybridizations was determined, and the microarray results were compared with those obtained by phenotypic resistance tests (either MIC or Kirby-Bauer). The microarray genotyping demonstrated a correlation between penicillin, tetracycline and erythromycin resistance phenotypes with the corresponding acquired resistance genes. The hybridizations showed that the 38 antimicrobial resistant S. aureus isolates possessed at least one AMR gene. © 2010 Blackwell Verlag GmbH.

  13. Relationship between codon biased genes, microarray expression values and physiological characteristics of Streptococcus pneumoniae.

    PubMed

    Martín-Galiano, Antonio J; Wells, Jerry M; de la Campa, Adela G

    2004-07-01

    A codon-profile strategy was used to predict gene expression levels in Streptococcus pneumoniae. Predicted highly expressed (PHE) genes included those encoding glycolytic and fermentative enzymes, sugar-conversion systems and carbohydrate-transporters. Additionally, some genes required for infection that are involved in oxidative metabolism and hydrogen peroxide production were PHE. Low expression values were predicted for genes encoding specific regulatory proteins like two-component systems and competence genes. Correspondence analysis localized 484 ORFs which shared a distinctive codon profile in the right horn. These genes had a mean G+C content (33.4 %) that was lower than the bulk of the genome coding sequences (39.7 %), suggesting that many of them were acquired by horizontal transfer. Half of these genes (242) were pseudogenes, ORFs shorter than 80 codons or without assigned function. The remaining genes included several virulence factors, such as capsular genes, iga, lytB, nanB, pspA, choline-binding proteins, and functions related to DNA acquisition, such as restriction-modification systems and comDE. In order to compare predicted translation rate with the relative amounts of mRNA for each gene, the codon adaptation index (CAI) values were compared with microarray fluorescence intensity values following hybridization of labelled RNA from laboratory-grown cultures. High mRNA amounts were observed in 32.5 % of PHE genes and in 64 % of the 25 genes with the highest CAI values. However, high relative amounts of RNA were also detected in 10.4 % of non-PHE genes, such as those encoding fatty acid metabolism enzymes and proteases, suggesting that their expression might also be regulated at the level of transcription or mRNA stability under the conditions tested. The effects of codon bias and mRNA amount on different gene groups in S. pneumoniae are discussed.

  14. Gene microarray assessment of multiple genes and signal pathways involved in androgen-dependent prostate cancer becoming androgen independent.

    PubMed

    Liu, Jun-Bao; Dai, Chun-Mei; Su, Xiao-Yun; Cao, Lu; Qin, Rui; Kong, Qing-Bo

    2014-01-01

    To study the gene expression change and possible signal pathway during androgen-dependent prostate cancer (ADPC) becoming androgen-independent prostate cancer (AIPC), an LNCaP cell model of AIPC was established using flutamide in combination with androgen-free environment inducement, and differential expression genes were screened by microarray. Then the biological process, molecular function and KEGG pathway of differential expression genes are analyzed by Molecule Annotation System (MAS). By comparison of 12,207 expression genes, 347 expression genes were acquired, of which 156 were up-ragulated and 191 down-regulated. After analyzing the biological process and molecule function of differential expression genes, these genes are found to play crucial roles in cell proliferation, differntiation, cell cycle control, protein metabolism and modification and other biological process, serve as signal molecules, enzymes, peptide hormones, cytokines, cytoskeletal proteins and adhesion molecules. The analysis of KEGG show that the relevant genes of AIPC transformation participate in glutathione metabolism, cell cycle, P53 signal pathway, cytochrome P450 metabolism, Hedgehog signal pathway, MAPK signal pathway, adipocytokines signal pathway, PPAR signal pathway, TGF-β signal pathway and JAK-STAT signal pathway. In conclusion, during the process of ADPC becoming AIPC, it is not only one specific gene or pathway, but multiple genes and pathways that change. The findings above lay the foundation for study of AIPC mechanism and development of AIPC targeting drugs.

  15. Effect of leucine uptake on hepatic and skeletal muscle gene expression in rats: a microarray analysis

    PubMed Central

    Cheon, Wookwang

    2015-01-01

    [Purpose] This study was performed to explore the physiological functions of leucine by exploring genes with leucine-dependent variability using DNA microarray. [Methods] Sprague-Dawley rats (n = 20) were separated into a HPD (30% High Protein Diet, n = 10) group and a NPD (0% Non Protein Diet, n = 10) group and fed a protein diet for 2 weeks. At the end of the 2-week period, the rats were fasted for 12-16 hours, further separated into subgroups within the HPD (Saline, n = 5, Leucine, n = 5) and NPD (Saline, n = 5, Leucine, n = 5) groups and administered with a leucine solution. The liver and muscles were harvested after 2 hours for RNA extraction. RNA purification from the isolated muscles and target gene identification using DNA chip were performed. The target gene was determined based on the results of the DNA chip experiment, and mRNA expression of the target gene was analyzed using Real-Time PCR. [Results] In the skeletal muscle, 27 genes were upregulated while 52 genes were down regulated after leucine administration in the NPD group. In the liver, 160 genes were up-regulated while 126 were down-regulated. The per2 gene was one of the genes with leucine-dependent induction in muscles and liver. [Conclusion] This study was performed to explore the physiological functions of leucine, however, a large number of genes showed variability. Therefore, it was difficult to definitively identify the genes linked with a particular physiological function. Various nutritional effects of leucine were observed. High variability in cytokines, receptors, and various membrane proteins were observed, which suggests that leucine functions as more than a nutrient. The interpretation may depend on investigators’ perspectives, therefore, discussion with relevant experts and the BCAA (Branched-Chain Amino Acids) society may be needed for effective utilization of this data. PMID:26244133

  16. Development and validation of a 2,000-gene microarray for the fathead minnow (Pimephales promelas)

    SciTech Connect

    Larkin, Patrick; Villeneuve, Daniel L.; Knoebl, Iris; Miracle, Ann L.; Carter, Barbara J.; Liu, Li; Denslow, Nancy D.; Ankley, Gerald T.

    2007-07-01

    Gene microarrays provide the field of ecotoxicology new tools to identify mechanisms of action of chemicals and chemical mixtures. Herein we describe the development and application of a 2,000-gene oligonucleotide microarray for the fathead minnow Pimephales promelas, a species commonly used in ecological risk assessments in North America. The microarrays were developed from various cDNA and subtraction libraries that we constructed. Consistency and reproducibility of the microarrays were documented by examining multiple technical replicates. To test application of the fathead minnow microarrays, gene expression profiles of fish exposed to 17-estradiol, a well-characterized estrogen receptor (ER) agonist, were examined. For these experiments, adult male fathead minnows were exposed for 24 h to waterborne 17-estradiol (40 or 100 ng/L) in a flow-through system, and gene expression in liver samples was characterized. Seventy-one genes were identified as differentially regulated by estradiol exposure. Examination of the gene ontology designations of these genes revealed patterns consistent with estradiol’s expected mechanisms of action and also provided novel insights as to molecular effects of the estrogen. Our studies indicate the feasibility and utility of microarrays as a basis for understanding biological responses to chemical exposure in a model ecotoxicology test species.

  17. Power of deep sequencing and agilent microarray for gene expression profiling study.

    PubMed

    Feng, Lin; Liu, Hang; Liu, Yu; Lu, Zhike; Guo, Guangwu; Guo, Suping; Zheng, Hongwei; Gao, Yanning; Cheng, Shujun; Wang, Jian; Zhang, Kaitai; Zhang, Yong

    2010-06-01

    Next-generation sequencing-based Digital Gene Expression tag profiling (DGE) has been used to study the changes in gene expression profiling. To compare the quality of the data generated by microarray and DGE, we examined the gene expression profiles of an in vitro cell model with these platforms. In this study, 17,362 and 15,938 genes were detected by microarray and DGE, respectively, with 13,221 overlapping genes. The correlation coefficients between the technical replicates were >0.99 and the detection variance was <9% for both platforms. The dynamic range of microarray was fixed with four orders of magnitude, whereas that of DGE was extendable. The consistency of the two platforms was high, especially for those abundant genes. It was more difficult for the microarray to distinguish the expression variation of less abundant genes. Although microarrays might be eventually replaced by DGE or transcriptome sequencing (RNA-seq) in the near future, microarrays are still stable, practical, and feasible, which may be useful for most biological researchers.

  18. SPERM RNA AMPLIFICATION FOR GENE EXPRESSION PROFILING BY DNA MICROARRAY TECHNOLOGY

    EPA Science Inventory

    Sperm RNA Amplification for Gene Expression Profiling by DNA Microarray Technology
    Hongzu Ren, Kary E. Thompson, Judith E. Schmid and David J. Dix, Reproductive Toxicology Division, NHEERL, Office of Research and Development, US Environmental Protection Agency, Research Triang...

  19. SPERM RNA AMPLIFICATION FOR GENE EXPRESSION PROFILING BY DNA MICROARRAY TECHNOLOGY

    EPA Science Inventory

    Sperm RNA Amplification for Gene Expression Profiling by DNA Microarray Technology
    Hongzu Ren, Kary E. Thompson, Judith E. Schmid and David J. Dix, Reproductive Toxicology Division, NHEERL, Office of Research and Development, US Environmental Protection Agency, Research Triang...

  20. Screening miRNA and their target genes related to tetralogy of Fallot with microarray.

    PubMed

    Wang, Xian-min; Zhang, Kui; Li, Yan; Shi, Kun; Liu, Yi-ling; Yang, Yan-feng; Fang, Yu; Mao, Meng

    2014-06-01

    Our aim is to screen miRNAs and genes related to tetralogy of Fallot and construct a co-expression network based on integrating miRNA and gene microarrays. We downloaded the gene expression profile GSE35490 (miRNA) and GSE35776 (mRNA) of tetralogy of Fallot from the Gene Expression Omnibus database, which includes eight normal and 15 disease samples from infants, and screened differentially expressed miRNAs and genes between normal and disease samples (cut-off: p < 0.05; FDR < 0.05; and log FC > 2 or log FC < -2); in addition, we downloaded human miRNA and their targets, which were collected in the miRNA targets prediction database TargetScan, and selected ones that also appeared in our differentially expressed miRNAs and their predicted targets (score >0.9) and then made a relationship of diff_miRNAs and diff_genes of our results. Finally, we uploaded all the diff_target genes into String, constructed a co-expression network regulated by diff_miRNAs, and performed functional analysis with the software DAVID. Comparing normal and disease lesion tissue, we got 32 and 875 differentially expressed miRNAs and genes, respectively, and found hsa-miR-124 with 34 diff_target genes and hsa-miR-138 with two diff_target genes. Then we constructed a co-expression network that contains 231 pairs of genes. Genes in the network were enriched into 14 function clusters, and the most significant one is protein localisation. We screened the tetralogy of Fallot-related hsa-miR-124 and hsa-miR-138 with their direct and indirect differentially expressed target genes, and found that protein localisation is the significant cause affecting tetralogy of Fallot. Our approach may provide the groundwork for a new therapy approach to treating tetralogy of Fallot.

  1. Functional genomics resources for the North Atlantic copepod, Calanus finmarchicus: EST database and physiological microarray

    PubMed Central

    Lenz, Petra H.; Unal, Ebru; Hassett, R. Patrick; Smith, Christine M.; Bucklin, Ann; Christie, Andrew E.; Towle, David W.

    2012-01-01

    The copepod, Calanus finmarchicus is a keystone species for the North Atlantic. Because of recent changes in the geographic distribution of this species, there are questions as to how this organism responds physiologically to environmental cues. Molecular techniques allow for examination and new understanding of these physiological changes. Here, we describe the development of a microarray for high-throughput studies of the physiological ecology of C. finmarchicus. An EST database was generated for this species using a normalized cDNA library derived from adult and sub-adult individuals. Sequence data were clustered into contigs and annotated using Blastx. Target transcripts were selected, and unique, 50 base-pair, oligomer probes were generated for 995 genes. Blast2GO processing provided detailed information on gene function. The selected targets included broad representation of biological processes, cellular components, and molecular functions. The microarray was tested in two sets of comparisons: adult females maintained at different food concentrations and field-caught sub-adults showing differences in lipid storage. Up-regulated and down-regulated transcripts were identified for both comparisons. Only a small subset of the genes up-regulated in low food individuals were also up-regulated in lipid-poor animals; no overlap was seen between the genes down-regulated in the two comparisons. PMID:22277925

  2. Circular RNA and gene expression profiles in gastric cancer based on microarray chip technology.

    PubMed

    Sui, Weiguo; Shi, Zhoufang; Xue, Wen; Ou, Minglin; Zhu, Ying; Chen, Jiejing; Lin, Hua; Liu, Fuhua; Dai, Yong

    2017-03-01

    The aim of the present study was to screen gastric cancer (GC) tissue and adjacent tissue for differences in mRNA and circular (circRNA) expression, to analyze the differences in circRNA and mRNA expression, and to investigate the circRNA expression in gastric carcinoma and its mechanism. circRNA and mRNA differential expression profiles generated using Agilent microarray technology were analyzed in the GC tissues and adjacent tissues. qRT-PCR was used to verify the differential expression of circRNAs and mRNAs according to the interactions between circRNAs and miRNAs as well as the possible existence of miRNA and mRNA interactions. We found that: i) the circRNA expression profile revealed 1,285 significant differences in circRNA expression, with circRNA expression downregulated in 594 samples and upregulated in 691 samples via interactions with miRNAs. The qRT-PCR validation experiments showed that hsa_circRNA_400071, hsa_circRNA_000543 and hsa_circRNA_001959 expression was consistent with the microarray analysis results. ii) 29,112 genes were found in the GC tissues and adjacent tissues, including 5,460 differentially expressed genes. Among them, 2,390 differentially expressed genes were upregulated and 3,070 genes were downregulated. Gene Ontology (GO) analysis of the differentially expressed genes revealed these genes involved in biological process classification, cellular component classification and molecular function classification. Pathway analysis of the differentially expressed genes identified 83 significantly enriched genes, including 28 upregulated genes and 55 downregulated genes. iii) 69 differentially expressed circRNAs were found that might adsorb specific miRNAs to regulate the expression of their target gene mRNAs. The conclusions are: i) differentially expressed circRNAs had corresponding miRNA binding sites. These circRNAs regulated the expression of target genes through interactions with miRNAs and might become new molecular biomarkers for GC

  3. Microarray and differential display identify genes involved in jasmonate-dependent anther development.

    PubMed

    Mandaokar, Ajin; Kumar, V Dinesh; Amway, Matt; Browse, John

    2003-07-01

    Jasmonate (JA) is a signaling compound essential for anther development and pollen fertility in Arabidopsis. Mutations that block the pathway of JA synthesis result into male sterility. To understand the processes of anther and pollen maturation, we used microarray and differential display approaches to compare gene expression pattern in anthers of wild-type Arabidopsis and the male-sterile mutant, opr3. Microarray experiment revealed 25 genes that were up-regulated more than 1.8-fold in wild-type anthers as compared to mutant anthers. Experiments based on differential display identified 13 additional genes up-regulated in wild-type anthers compared to opr3 for a total of 38 differentially expressed genes. Searches of the Arabidopsis and non-redundant databases disclosed known or likely functions for 28 of the 38 genes identified, while 10 genes encode proteins of unknown function. Northern blot analysis of eight representative clones as probes confirmed low expression in opr3 anthers compared with wild-type anthers. JA responsiveness of these same genes was also investigated by northern blot analysis of anther RNA isolated from wild-type and opr3 plants, In these experiments, four genes were induced in opr3 anthers within 0.5-1 h of JA treatment while the remaining genes were up-regulated only 1-8 h after JA application. None of these genes was induced by JA in anthers of the coil mutant that is deficient in JA responsiveness. The four early-induced genes in opr3 encode lipoxygenase, a putative bHLH transcription factor, epithiospecifier protein and an unknown protein. We propose that these and other early components may be involved in JA signaling and in the initiation of developmental processes. The four late genes encode an extensin-like protein, a peptide transporter and two unknown proteins, which may represent components required later in anther and pollen maturation. Transcript profiling has provided a successful approach to identify genes involved in

  4. An attempt for combining microarray data sets by adjusting gene expressions.

    PubMed

    Kim, Ki-Yeol; Kim, Se Hyun; Ki, Dong Hyuk; Jeong, Jaeheon; Jeong, Ha Jin; Jeung, Hei-Cheul; Chung, Hyun Cheol; Rha, Sun Young

    2007-06-01

    The diverse experimental environments in microarray technology, such as the different platforms or different RNA sources, can cause biases in the analysis of multiple microarrays. These systematic effects present a substantial obstacle for the analysis of microarray data, and the resulting information may be inconsistent and unreliable. Therefore, we introduced a simple integration method for combining microarray data sets that are derived from different experimental conditions, and we expected that more reliable information can be detected from the combined data set rather than from the separated data sets. This method is based on the distributions of the gene expression ratios among the different microarray data sets and it transforms, gene by gene, the gene expression ratios into the form of the reference data set. The efficiency of the proposed integration method was evaluated using two microarray data sets, which were derived from different RNA sources, and a newly defined measure, the mixture score. The proposed integration method intermixed the two data sets that were obtained from different RNA sources, which in turn reduced the experimental bias between the two data sets, and the mixture score increased by 24.2%. A data set combined by the proposed method preserved the inter-group relationship of the separated data sets. The proposed method worked well in adjusting systematic biases, including the source effect. The ability to use an effectively integrated microarray data set yields more reliable results due to the larger sample size and this also decreases the chance of false negatives.

  5. DNA Microarray Analysis of Human Monocytes Early Response Genes upon Infection with Rickettsia rickettsii

    DTIC Science & Technology

    2004-11-15

    DNA Microarray Analysis of Human Monocytes Early Response Genes upon Infection with Rickettsia rickettsii Chien-Chung Chao Rickettsiae Diseases...TITLE AND SUBTITLE DNA Microarray Analysis of Human Monocytes Early Response Genes upon Infection with Rickettsia rickettsii 5a. CONTRACT NUMBER 5b...ANSI Std Z39-18 Rickettsiae • Gram negative coccobacillary bacteria • Obligate intracellular organisms • Arthropod-borne • Cause febrile diseases (mild

  6. The MicroArray Quality Control (MAQC) project shows inter- and intraplatform reproducibility of gene expression measurements

    EPA Science Inventory

    Over the last decade, the introduction of microarray technology has had a profound impact on gene expression research. The publication of studies with dissimilar or altogether contradictory results, obtained using different microarray platforms to analyze identical RNA samples, ...

  7. MICROARRAY QUALITY CONTROL PROJECT: A COMPREHENSIVE GENE EXPRESSION TECHNOLOGY SURVEY DEMONSTRATES MEASURABLE CONSISTENCY AND CONCORDANT RESULTS BETWEEN PLATFORMS

    EPA Science Inventory

    Over the last decade, the introduction of microarray technology has had a profound impact on gene expression research. The publication of studies with dissimilar or altogether contradictory results, obtained using different microarray platforms to analyze identical RNA samples, h...

  8. MICROARRAY QUALITY CONTROL PROJECT: A COMPREHENSIVE GENE EXPRESSION TECHNOLOGY SURVEY DEMONSTRATES MEASURABLE CONSISTENCY AND CONCORDANT RESULTS BETWEEN PLATFORMS

    EPA Science Inventory

    Over the last decade, the introduction of microarray technology has had a profound impact on gene expression research. The publication of studies with dissimilar or altogether contradictory results, obtained using different microarray platforms to analyze identical RNA samples, h...

  9. The MicroArray Quality Control (MAQC) project shows inter- and intraplatform reproducibility of gene expression measurements

    EPA Science Inventory

    Over the last decade, the introduction of microarray technology has had a profound impact on gene expression research. The publication of studies with dissimilar or altogether contradictory results, obtained using different microarray platforms to analyze identical RNA samples, ...

  10. Microarray-based characterization of differential gene expression during vocal fold wound healing in rats.

    PubMed

    Welham, Nathan V; Ling, Changying; Dawson, John A; Kendziorski, Christina; Thibeault, Susan L; Yamashita, Masaru

    2015-03-01

    The vocal fold (VF) mucosa confers elegant biomechanical function for voice production but is susceptible to scar formation following injury. Current understanding of VF wound healing is hindered by a paucity of data and is therefore often generalized from research conducted in skin and other mucosal systems. Here, using a previously validated rat injury model, expression microarray technology and an empirical Bayes analysis approach, we generated a VF-specific transcriptome dataset to better capture the system-level complexity of wound healing in this specialized tissue. We measured differential gene expression at 3, 14 and 60 days post-injury compared to experimentally naïve controls, pursued functional enrichment analyses to refine and add greater biological definition to the previously proposed temporal phases of VF wound healing, and validated the expression and localization of a subset of previously unidentified repair- and regeneration-related genes at the protein level. Our microarray dataset is a resource for the wider research community and has the potential to stimulate new hypotheses and avenues of investigation, improve biological and mechanistic insight, and accelerate the identification of novel therapeutic targets.

  11. Identification of novel TCDD-regulated genes by microarray analysis

    SciTech Connect

    Hanlon, Paul R.; Zheng, Wenchao; Ko, Alex Y.; Jefcoate, Colin R. . E-mail: jefcoate@facstaff.wisc.edu

    2005-02-01

    TCDD exposure of multipotential C3H10T1/2 fibroblasts for 72 h altered the expression of over 1000 genes, including coordinated changes across large functionally similar gene clusters. TCDD coordinately induced 23 cell cycle-related genes similar to epidermal growth factor (EGF)-induced levels but without any affect on the major mitogenic signaling pathway (extracellular signal-regulated kinase, ERK). TCDD treatment also decreased glycolytic and ribosomal clusters. Most of these TCDD-induced changes were attenuated by the presence of EGF or an adipogenic stimulus, each added during the final 24 h. TCDD prevented 10% of EGF-induced gene responses and 40% of adipogenic responses. Over 100 other genes responded to TCDD during adipogenesis. This group of responses included complete suppression of three proliferins and stimulations of several cytokine receptors. Despite these varied secondary effects of TCDD, direct AhR activation measured by integrated AhR-responsive luciferase reporters was similar under quiescent, EGF-stimulated or adipogenic conditions. Only 23 genes were similarly induced by TCDD regardless of conditions and 10 were suppressed. These 23 genes include: 4 genes previously recognized to contain AhR response elements (cytochrome P450 (CYP) 1B1, CYP1A1, NAD(P)H quinone reductase 1 (NQO1), and aldehyde dehydrogenase 3A1); two novel oxidative genes (alcohol dehydrogenase 3 and superoxide dismutase 3); and glypican 1, a plasma membrane proteoglycan that affects cell signaling. Further experiments demonstrated that TCDD maximally induced NQO1, glypican 1 and alcohol dehydrogenase 3 by 6 h. Glypican 1 activates the actions of many growth factors and therefore may contribute to secondary effects on gene expression.

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

    PubMed

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

    2015-09-30

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

  13. A Meta-Analysis of Microarray Gene Expression in Mouse Stem Cells: Redefining Stemness

    PubMed Central

    Edwards, Yvonne J. K.; Bryson, Kevin; Jones, David T.

    2008-01-01

    Background While much progress has been made in understanding stem cell (SC) function, a complete description of the molecular mechanisms regulating SCs is not yet established. This lack of knowledge is a major barrier holding back the discovery of therapeutic uses of SCs. We investigated the value of a novel meta-analysis of microarray gene expression in mouse SCs to aid the elucidation of regulatory mechanisms common to SCs and particular SC types. Methodology/Principal Findings We added value to previously published microarray gene expression data by characterizing the promoter type likely to regulate transcription. Promoters of up-regulated genes in SCs were characterized in terms of alternative promoter (AP) usage and CpG-richness, with the aim of correlating features known to affect transcriptional control with SC function. We found that SCs have a higher proportion of up-regulated genes using CpG-rich promoters compared with the negative controls. Comparing subsets of SC type with the controls a slightly different story unfolds. The differences between the proliferating adult SCs and the embryonic SCs versus the negative controls are statistically significant. Whilst the difference between the quiescent adult SCs compared with the negative controls is not. On examination of AP usage, no difference was observed between SCs and the controls. However, comparing the subsets of SC type with the controls, the quiescent adult SCs are found to up-regulate a larger proportion of genes that have APs compared to the controls and the converse is true for the proliferating adult SCs and the embryonic SCs. Conclusions/Significance These findings suggest that looking at features associated with control of transcription is a promising future approach for characterizing “stemness” and that further investigations of stemness could benefit from separate considerations of different SC states. For example, “proliferating-stemness” is shown here, in terms of promoter

  14. Identification of Novel Tissue-Specific Genes by Analysis of Microarray Databases: A Human and Mouse Model

    PubMed Central

    Suh, Yeunsu; Davis, Michael E.; Lee, Kichoon

    2013-01-01

    Understanding the tissue-specific pattern of gene expression is critical in elucidating the molecular mechanisms of tissue development, gene function, and transcriptional regulations of biological processes. Although tissue-specific gene expression information is available in several databases, follow-up strategies to integrate and use these data are limited. The objective of the current study was to identify and evaluate novel tissue-specific genes in human and mouse tissues by performing comparative microarray database analysis and semi-quantitative PCR analysis. We developed a powerful approach to predict tissue-specific genes by analyzing existing microarray data from the NCBI′s Gene Expression Omnibus (GEO) public repository. We investigated and confirmed tissue-specific gene expression in the human and mouse kidney, liver, lung, heart, muscle, and adipose tissue. Applying our novel comparative microarray approach, we confirmed 10 kidney, 11 liver, 11 lung, 11 heart, 8 muscle, and 8 adipose specific genes. The accuracy of this approach was further verified by employing semi-quantitative PCR reaction and by searching for gene function information in existing publications. Three novel tissue-specific genes were discovered by this approach including AMDHD1 (amidohydrolase domain containing 1) in the liver, PRUNE2 (prune homolog 2) in the heart, and ACVR1C (activin A receptor, type IC) in adipose tissue. We further confirmed the tissue-specific expression of these 3 novel genes by real-time PCR. Among them, ACVR1C is adipose tissue-specific and adipocyte-specific in adipose tissue, and can be used as an adipocyte developmental marker. From GEO profiles, we predicted the processes in which AMDHD1 and PRUNE2 may participate. Our approach provides a novel way to identify new sets of tissue-specific genes and to predict functions in which they may be involved. PMID:23741331

  15. Identification of novel tissue-specific genes by analysis of microarray databases: a human and mouse model.

    PubMed

    Song, Yan; Ahn, Jinsoo; Suh, Yeunsu; Davis, Michael E; Lee, Kichoon

    2013-01-01

    Understanding the tissue-specific pattern of gene expression is critical in elucidating the molecular mechanisms of tissue development, gene function, and transcriptional regulations of biological processes. Although tissue-specific gene expression information is available in several databases, follow-up strategies to integrate and use these data are limited. The objective of the current study was to identify and evaluate novel tissue-specific genes in human and mouse tissues by performing comparative microarray database analysis and semi-quantitative PCR analysis. We developed a powerful approach to predict tissue-specific genes by analyzing existing microarray data from the NCBI's Gene Expression Omnibus (GEO) public repository. We investigated and confirmed tissue-specific gene expression in the human and mouse kidney, liver, lung, heart, muscle, and adipose tissue. Applying our novel comparative microarray approach, we confirmed 10 kidney, 11 liver, 11 lung, 11 heart, 8 muscle, and 8 adipose specific genes. The accuracy of this approach was further verified by employing semi-quantitative PCR reaction and by searching for gene function information in existing publications. Three novel tissue-specific genes were discovered by this approach including AMDHD1 (amidohydrolase domain containing 1) in the liver, PRUNE2 (prune homolog 2) in the heart, and ACVR1C (activin A receptor, type IC) in adipose tissue. We further confirmed the tissue-specific expression of these 3 novel genes by real-time PCR. Among them, ACVR1C is adipose tissue-specific and adipocyte-specific in adipose tissue, and can be used as an adipocyte developmental marker. From GEO profiles, we predicted the processes in which AMDHD1 and PRUNE2 may participate. Our approach provides a novel way to identify new sets of tissue-specific genes and to predict functions in which they may be involved.

  16. Feature Selection and Classification of MAQC-II Breast Cancer and Multiple Myeloma Microarray Gene Expression Data

    PubMed Central

    Liu, Qingzhong; Sung, Andrew H.; Chen, Zhongxue; Liu, Jianzhong; Huang, Xudong; Deng, Youping

    2009-01-01

    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 AUC errors. PMID

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

    PubMed

    Liu, Qingzhong; Sung, Andrew H; Chen, Zhongxue; Liu, Jianzhong; Huang, Xudong; Deng, Youping

    2009-12-11

    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 AUC errors.

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

    PubMed Central

    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 value<0.01. Based on a functional analysis, L1 larvae have a larger number of genes putatively involved in transcription (p = 0.004), and L3i larvae have biased expression of putative heat shock proteins (such as hsp-90). Genes with products known to be immunoreactive in S. stercoralis-infected humans (such as SsIR and NIE) had L3i biased expression. Abundantly expressed L3i contigs of interest included S. stercoralis orthologs of cytochrome oxidase ucr 2.1 and hsp-90, which may be potential chemotherapeutic targets. The S. stercoralis ortholog of fatty acid and retinol binding protein-1, successfully used in a vaccine against Ancylostoma ceylanicum, was identified among the 25 most highly expressed L3i genes. The sperm-containing glycoprotein domain, utilized in a vaccine against the nematode Cooperia punctata, was exclusively found in L3i biased genes and may be a valuable S. stercoralis target of interest. Conclusions A new DNA microarray tool for the examination of S. stercoralis biology has been developed and provides new and valuable insights regarding

  19. Improved detection of differentially expressed genes in microarray experiments through multiple scanning and image integration

    PubMed Central

    Romualdi, Chiara; Trevisan, Silvia; Celegato, Barbara; Costa, Germano; Lanfranchi, Gerolamo

    2003-01-01

    The variability of results in microarray technology is in part due to the fact that independent scans of a single hybridised microarray give spot images that are not quite the same. To solve this problem and turn it to our advantage, we introduced the approach of multiple scanning and of image integration of microarrays. To this end, we have developed specific software that creates a virtual image that statistically summarises a series of consecutive scans of a microarray. We provide evidence that the use of multiple imaging (i) enhances the detection of differentially expressed genes; (ii) increases the image homogeneity; and (iii) reveals false-positive results such as differentially expressed genes that are detected by a single scan but not confirmed by successive scanning replicates. The increase in the final number of differentially expressed genes detected in a microarray experiment with this approach is remarkable; 50% more for microarrays hybridised with targets labelled by reverse transcriptase, and 200% more for microarrays developed with the tyramide signal amplification (TSA) technique. The results have been confirmed by semi-quantitative RT–PCR tests. PMID:14627839

  20. GeneXplorer: an interactive web application for microarray data visualization and analysis.

    PubMed

    Rees, Christian A; Demeter, Janos; Matese, John C; Botstein, David; Sherlock, Gavin

    2004-10-01

    When publishing large-scale microarray datasets, it is of great value to create supplemental websites where either the full data, or selected subsets corresponding to figures within the paper, can be browsed. We set out to create a CGI application containing many of the features of some of the existing standalone software for the visualization of clustered microarray data. We present GeneXplorer, a web application for interactive microarray data visualization and analysis in a web environment. GeneXplorer allows users to browse a microarray dataset in an intuitive fashion. It provides simple access to microarray data over the Internet and uses only HTML and JavaScript to display graphic and annotation information. It provides radar and zoom views of the data, allows display of the nearest neighbors to a gene expression vector based on their Pearson correlations and provides the ability to search gene annotation fields. The software is released under the permissive MIT Open Source license, and the complete documentation and the entire source code are freely available for download from CPAN http://search.cpan.org/dist/Microarray-GeneXplorer/.

  1. A microarray study indicates high-amylose resistant starch increases hormones and improves structure and function of the GI tract

    PubMed Central

    Keenan, Michael J; Martin, Roy J; Raggio, Anne M; McCutcheon, Kathleen L; Brown, Ian L; Birkett, Anne; Newman, Susan S; Skaf, Jihad; Hegsted, Maren; Tulley, Richard T; Blair, Eric; Zhou, June

    2014-01-01

    Background/Aims Type 2 resistant starch from high-amylose maize (HAM-RS2) is associated with increased fermentation, increased expression of proglucagon (gene for GLP-1) and peptide YY (PYY) genes in the large intestine, and improved health. To determine what other genes are up- or down-regulated with feeding of HAM-RS2 a microarray was performed. Methods Adult, male SD rats were fed one of the following three diets for a four week study period: cornstarch control (CC, 3.74 kcal/g), dietary energy density control (EC, 3.27kcal/g), and 30% HAM-RS2 (RS, 3.27 kcal/g). Rat microarray with ∼27,000 genes and validation of 94 representative genes with multiple qPCR were used to determine gene expression in total RNA extracts of cecal cells from rats. The RS vs. EC comparison tested effects of fermentation as energy density of the diet was controlled. Results For the RS vs. EC comparison, 86% of the genes were validated from the microarray and the expression indicates promotion of cell growth, proliferation, differentiation, and apoptosis. Gut hormones GLP-1 and PYY were increased. Conclusions Gene expression results predict improved structure and function of the GI tract and production of gut hormones may promote healthy functions beyond the GI tract. PMID:22516953

  2. Integrative meta-analysis of differentially expressed genes in osteoarthritis using microarray technology.

    PubMed

    Wang, Xi; Ning, Yujie; Guo, Xiong

    2015-09-01

    The aim of the present study was to identify differentially expressed (DE) genes in patients with osteoarthritis (OA), and biological processes associated with changes in gene expression that occur in this disease. Using the INMEX (integrative meta‑analysis of expression data) software tool, a meta‑analysis of publicly available microarray Gene Expression Omnibus (GEO) datasets of OA was performed. Gene ontology (GO) enrichment analysis was performed in order to detect enriched functional attributes based on gene‑associated GO terms. Three GEO datasets, containing 137 patients with OA and 52 healthy controls, were included in the meta‑analysis. The analysis identified 85 genes that were consistently differentially expressed in OA (30 genes were upregulated and 55 genes were downregulated). The upregulated gene with the lowest P‑value (P=5.36E‑07) was S‑phase kinase‑associated protein 2, E3 ubiquitin protein ligase (SKP2). The downregulated gene with the lowest P‑value (P=4.42E‑09) was Proline rich 5 like (PRR5L). Among the 210 GO terms that were associated with the set of DE genes, the most significant two enrichments were observed in the GO categories of 'Immune response', with a P‑value of 0.000129438, and 'Immune effectors process', with a P‑value of 0.000288619. The current meta‑analysis identified genes that were consistently DE in OA, in addition to biological pathways associated with changes in gene expression that occur during OA, which may provide insight into the molecular mechanisms underlying the pathogenesis of this disease.

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

    SciTech Connect

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

    2008-04-25

    Human metapneumovirus (hMPV) is a major cause of lower respiratory tract infections in infants, elderly and immunocompromised patients. Little is known about the response to hMPV infection of airway epithelial cells, which play a pivotal role in initiating and shaping innate and adaptive immune responses. In this study, we analyzed the transcriptional profiles of airway epithelial cells infected with hMPV using high-density oligonucleotide microarrays. Of the 47,400 transcripts and variants represented on the Affimetrix GeneChip Human Genome HG-U133 plus 2 array, 1601 genes were significantly altered following hMPV infection. Altered genes were then assigned to functional categories and mapped to signaling pathways. Many up-regulated genes are involved in the initiation of pro-inflammatory and antiviral immune responses, including chemokines, cytokines, type I interferon and interferon-inducible proteins. Other important functional classes up-regulated by hMPV infection include cellular signaling, gene transcription and apoptosis. Notably, genes associated with antioxidant and membrane transport activity, several metabolic pathways and cell proliferation were down-regulated in response to hMPV infection. Real-time PCR and Western blot assays were used to confirm the expression of genes related to several of these functional groups. The overall result of this study provides novel information on host gene expression upon infection with hMPV and also serves as a foundation for future investigations of genes and pathways involved in the pathogenesis of this important viral infection. Furthermore, it can facilitate a comparative analysis of other paramyxoviral infections to determine the transcriptional changes that are conserved versus the one that are specific to individual pathogens.

  4. A microarray analysis of gene expression patterns during early phases of newt lens regeneration

    PubMed Central

    Sousounis, Konstantinos; Michel, Christian S.; Bruckskotten, Marc; Maki, Nobuyasu; Borchardt, Thilo; Braun, Thomas; Tsonis, Panagiotis A.

    2013-01-01

    Purpose Notophthalmus viridescens, the red-spotted newt, possesses tremendous regenerative capabilities. Among the tissues and organs newts can regenerate, the lens is regenerated via transdifferentiation of the pigment epithelial cells of the dorsal iris, following complete removal (lentectomy). Under normal conditions, the same cells from the ventral iris are not capable of regenerating. This study aims to further understand the initial signals of lens regeneration. Methods We performed microarray analysis using RNA from a dorsal or ventral iris isolated 1, 3, and 5 days after lentectomy and compared to RNA isolated from an intact iris. This analysis was supported with quantitative real-time polymerase chain reaction (qRT-PCR) of selected genes. Results Microarrays showed 804 spots were differentially regulated 1, 3, and 5 days post-lentectomy in the dorsal and ventral iris. Functional annotation using Gene Ontology revealed interesting terms. Among them, factors related to cell cycle and DNA repair were mostly upregulated, in the microarray, 3 and 5 days post-lentectomy. qRT-PCR for rad1 and vascular endothelial growth factor receptor 1 showed upregulation for the dorsal iris 3 and 5 days post- lentectomy and for the ventral iris 5 days post-lentectomy. Rad1 was also upregulated twofold more in the dorsal iris than in the ventral iris 5 days post-lentectomy (p<0.001). Factors related to redox homeostasis were mostly upregulated in the microarray in all time points and samples. qRT-PCR for glutathione peroxidase 1 also showed upregulation in all time points for the ventral and dorsal iris. For the most part, mitochondrial enzymes were downregulated with the notable exception of cytochrome c–related oxidases that were mostly upregulated at all time points. qRT-PCR for cytochrome c oxidase subunit 2 showed upregulation especially 3 days post-lentectomy for the dorsal and ventral iris (p<0.001). Factors related to extracellular matrix and tissue remodeling showed

  5. CGO: utilizing and integrating gene expression microarray data in clinical research and data management.

    PubMed

    Bumm, Klaus; Zheng, Mingzhong; Bailey, Clyde; Zhan, Fenghuang; Chiriva-Internati, M; Eddlemon, Paul; Terry, Julian; Barlogie, Bart; Shaughnessy, John D

    2002-02-01

    Clinical GeneOrganizer (CGO) is a novel windows-based archiving, organization and data mining software for the integration of gene expression profiling in clinical medicine. The program implements various user-friendly tools and extracts data for further statistical analysis. This software was written for Affymetrix GeneChip *.txt files, but can also be used for any other microarray-derived data. The MS-SQL server version acts as a data mart and links microarray data with clinical parameters of any other existing database and therefore represents a valuable tool for combining gene expression analysis and clinical disease characteristics.

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

    PubMed

    Hoeschele, Ina; Li, Hua

    2005-04-01

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

  7. Modulation of gene expression in Leishmania drug resistant mutants as determined by targeted DNA microarrays

    PubMed Central

    Guimond, Chantal; Trudel, Nathalie; Brochu, Christian; Marquis, Nathalie; Fadili, Amal El; Peytavi, Régis; Briand, Guylaine; Richard, Dave; Messier, Nadine; Papadopoulou, Barbara; Corbeil, Jacques; Bergeron, Michel G.; Légaré, Danielle; Ouellette, Marc

    2003-01-01

    In the protozoan parasite Leishmania, drug resistance can be a complex phenomenon. Several metabolic pathways and membrane transporters are implicated in the resistance phenotype. To monitor the expression of these genes, we generated custom DNA microarrays with PCR fragments corresponding to 44 genes involved with drug resistance. Transcript profiling of arsenite and antimony resistant mutants with these arrays pinpointed a number of genes overexpressed in mutants, including the ABC transporter PGPA, the glutathione biosynthesis genes γ-glutamylcysteine synthetase (GSH1) and the glutathione synthetase (GSH2). Competitive hybridisations with total RNA derived from sensitive and methotrexate resistant cells revealed the overexpression of genes coding for dihydrofolate reductase (DHFR-TS), pteridine reductase (PTR1) and S-adenosylmethionine synthase (MAT2) and a down regulation of one gene of the folate transporter (FT) family. By labelling the DNA of sensitive and resistant parasites we could also detect several gene amplification events using DNA microarrays including the amplification of the S-adenosyl homocysteine hydrolase gene (SAHH). Alteration in gene expression detected by microarrays was validated by northern blot analysis, while Southern blots indicated that most genes overexpressed were also amplified, although other mechanisms were also present. The microarrays were useful in the study of resistant parasites to pinpoint several genes linked to drug resistance. PMID:14530437

  8. Modulation of gene expression in Leishmania drug resistant mutants as determined by targeted DNA microarrays.

    PubMed

    Guimond, Chantal; Trudel, Nathalie; Brochu, Christian; Marquis, Nathalie; El Fadili, Amal; Peytavi, Régis; Briand, Guylaine; Richard, Dave; Messier, Nadine; Papadopoulou, Barbara; Corbeil, Jacques; Bergeron, Michel G; Légaré, Danielle; Ouellette, Marc

    2003-10-15

    In the protozoan parasite Leishmania, drug resistance can be a complex phenomenon. Several metabolic pathways and membrane transporters are implicated in the resistance phenotype. To monitor the expression of these genes, we generated custom DNA microarrays with PCR fragments corresponding to 44 genes involved with drug resistance. Transcript profiling of arsenite and antimony resistant mutants with these arrays pinpointed a number of genes overexpressed in mutants, including the ABC transporter PGPA, the glutathione biosynthesis genes gamma-glutamylcysteine synthetase (GSH1) and the glutathione synthetase (GSH2). Competitive hybridisations with total RNA derived from sensitive and methotrexate resistant cells revealed the overexpression of genes coding for dihydrofolate reductase (DHFR-TS), pteridine reductase (PTR1) and S-adenosylmethionine synthase (MAT2) and a down regulation of one gene of the folate transporter (FT) family. By labelling the DNA of sensitive and resistant parasites we could also detect several gene amplification events using DNA microarrays including the amplification of the S-adenosyl homocysteine hydrolase gene (SAHH). Alteration in gene expression detected by microarrays was validated by northern blot analysis, while Southern blots indicated that most genes overexpressed were also amplified, although other mechanisms were also present. The microarrays were useful in the study of resistant parasites to pinpoint several genes linked to drug resistance.

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

    PubMed Central

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

    2010-01-01

    As public microarray repositories rapidly accumulate gene expression data, these resources contain increasingly valuable information about cellular processes in human biology. This presents a unique opportunity for intelligent data mining methods to extract information about the transcriptional modules underlying these biological processes. Modeling cellular gene expression as a combination of functional modules, we use independent component analysis (ICA) to derive 423 fundamental components of human biology from a 9,395-array compendium of heterogeneous expression data. Annotation using the Gene Ontology (GO) suggests that while some of these components represent known biological modules, others may describe biology not well characterized by existing manually-curated ontologies. In order to understand the biological functions represented by these modules, we investigate the mechanism of the preclinical anticancer drug parthenolide (PTL) by analyzing the differential expression of our fundamental components. Our method correctly identifies known pathways and predicts that N-glycan biosynthesis and T-cell receptor signaling may contribute to PTL response. The fundamental gene modules we describe have the potential to provide pathway-level insight into new gene expression datasets. PMID:20619355

  10. Parvalbumin-Neurons of the Ventrolateral Hypothalamic Parvafox Nucleus Receive a Glycinergic Input: A Gene-Microarray Study

    PubMed Central

    Szabolcsi, Viktoria; Albisetti, Gioele W.; Celio, Marco R.

    2017-01-01

    The ventrolateral hypothalamic parvafox (formerly called PV1-Foxb1) nucleus is an anatomical entity of recent discovery and unknown function. With a view to gaining an insight into its putative functional role(s), we conducted a gene-microarray analysis and, armed with the forthcoming data, controlled the results with the Allen databases and the murine BrainStars (B*) database. The parvafox nucleus was specifically sampled by laser-capture microdissection and the transcriptome was subjected to a microarray analysis on Affymetrix chips. Eighty-two relevant genes were found to be potentially more expressed in this brain region than in either the cerebral cortex or the hippocampus. When the expression patterns of these genes were counterchecked in the Allen-Database of in-situ hybridizations and in the B*-microarray database, their localization in the parvafox region was confirmed for thirteen. For nine novel genes, which are particularly interesting because of their possible involvement in neuromodulation, the expression was verified by quantitative real time-PCR. Of particular functional importance may be the occurrence of glycine receptors, the presence of which indicates that the activity of the parvafox nucleus is under ascending inhibitory control. PMID:28167900

  11. Analysis of gene expression profile induced by EMP-1 in esophageal cancer cells using cDNA Microarray

    PubMed Central

    Wang, Hai-Tao; Kong, Jian-Ping; Ding, Fang; Wang, Xiu-Qin; Wang, Ming-Rong; Liu, Lian-Xin; Wu, Min; Liu, Zhi-Hua

    2003-01-01

    AIM: To obtain human esophageal cancer cell EC9706 stably expressed epithelial membrane protein-1 (EMP-1) with integrated eukaryotic plasmid harboring the open reading frame (ORF) of human EMP-1, and then to study the mechanism by which EMP-1 exerts its diverse cellular action on cell proliferation and altered gene profile by exploring the effect of EMP-1. METHODS: The authors first constructed pcDNA3.1/myc-his expression vector harboring the ORF of EMP-1 and then transfected it into human esophageal carcinoma cell line EC9706. The positive clones were analyzed by Western blot and RT-PCR. Moreover, the cell growth curve was observed and the cell cycle was checked by FACS technique. Using cDNA microarray technology, the authors compared the gene expression pattern in positive clones with control. To confirm the gene expression profile, semi-quantitative RT-PCR was carried out for 4 of the randomly picked differentially expressed genes. For those differentially expressed genes, classification was performed according to their function and cellular component. RESULTS: Human EMP-1 gene can be stably expressed in EC9706 cell line transfected with human EMP-1. The authors found the cell growth decreased, among which S phase was arrested and G1 phase was prolonged in the transfected positive clones. By cDNA microarray analysis, 35 genes showed an over 2.0 fold change in expression level after transfection, with 28 genes being consistently up-regulated and 7 genes being down-regulated. Among the classified genes, almost half of the induced genes (13 out of 28 genes) were related to cell signaling, cell communication and particularly to adhesion. CONCLUSION: Overexpression of human EMP-1 gene can inhibit the proliferation of EC9706 cell with S phase arrested and G1 phase prolonged. The cDNA microarray analysis suggested that EMP-1 may be one of regulators involved in cell signaling, cell communication and adhesion regulators. PMID:12632483

  12. Analysis of gene expression profile induced by EMP-1 in esophageal cancer cells using cDNA Microarray.

    PubMed

    Wang, Hai-Tao; Kong, Jian-Ping; Ding, Fang; Wang, Xiu-Qin; Wang, Ming-Rong; Liu, Lian-Xin; Wu, Min; Liu, Zhi-Hua

    2003-03-01

    To obtain human esophageal cancer cell EC9706 stably expressed epithelial membrane protein-1 (EMP-1) with integrated eukaryotic plasmid harboring the open reading frame (ORF) of human EMP-1, and then to study the mechanism by which EMP-1 exerts its diverse cellular action on cell proliferation and altered gene profile by exploring the effect of EMP-1. The authors first constructed pcDNA3.1/myc-his expression vector harboring the ORF of EMP-1 and then transfected it into human esophageal carcinoma cell line EC9706. The positive clones were analyzed by Western blot and RT-PCR. Moreover, the cell growth curve was observed and the cell cycle was checked by FACS technique. Using cDNA microarray technology, the authors compared the gene expression pattern in positive clones with control. To confirm the gene expression profile, semi-quantitative RT-PCR was carried out for 4 of the randomly picked differentially expressed genes. For those differentially expressed genes, classification was performed according to their function and cellular component. Human EMP-1 gene can be stably expressed in EC9706 cell line transfected with human EMP-1. The authors found the cell growth decreased, among which S phase was arrested and G1 phase was prolonged in the transfected positive clones. By cDNA microarray analysis, 35 genes showed an over 2.0 fold change in expression level after transfection, with 28 genes being consistently up-regulated and 7 genes being down-regulated. Among the classified genes, almost half of the induced genes (13 out of 28 genes) were related to cell signaling, cell communication and particularly to adhesion. Overexpression of human EMP-1 gene can inhibit the proliferation of EC9706 cell with S phase arrested and G1 phase prolonged. The cDNA microarray analysis suggested that EMP-1 may be one of regulators involved in cell signaling, cell communication and adhesion regulators.

  13. From single gene to integrative molecular concept MAPS: pitfalls and potentials of microarray technology.

    PubMed

    Chiorino, G; Mello Grand, M; Scatolini, M; Ostano, P

    2008-01-01

    Microarray experiments have a large variety of applications and several important achievements have been obtained by means of this technology, especially within the field of whole genome expression profiling, which undoubtedly is the most diffused world-wide. Nevertheless, care must be taken in unconditionally applying such high-throughput techniques and in extracting/interpreting their results. Both the validity and the reproducibility of microarray-based clinical research have recently been challenged. Pitfalls and potentials of the microarray technology for gene expression profiling are critically reviewed in this paper.

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

    SciTech Connect

    SacconePhD, Scott F; Chesler, Elissa J; Bierut, Laura J; Kalivas, Peter J; Lerman, Caryn; Saccone, Nancy L; Uhl, George R; Li, Chuan-Yun; Philip, Vivek M; Edenberg, Howard; Sherry, Steven; Feolo, Michael; Moyzis, Robert K; Rutter, Joni L

    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.

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

    PubMed Central

    Saccone, Scott F.; Bierut, Laura J.; Chesler, Elissa J.; Kalivas, Peter W.; Lerman, Caryn; Saccone, Nancy L.; Uhl, George R.; Li, Chuan-Yun; Philip, Vivek M.; Edenberg, Howard J.; Sherry, Stephen T.; Feolo, Michael; Moyzis, Robert K.; Rutter, Joni L.

    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. PMID:19381300

  16. Microarray Analysis of Differential Gene Expression Profile in Peripheral Blood Cells of Patients with Human Essential Hypertension

    PubMed Central

    Korkor, Melvin T.; Meng, Fan Bo; Xing, Shen Yang; Zhang, Mu Chun; Guo, Jin Rui; Zhu, Xiao Xue; Yang, Ping

    2011-01-01

    The polygenic nature of essential hypertension and its dependence on environmental factors pose a challenge for biomedical research. We hypothesized that the analysis of gene expression profiles from peripheral blood cells would distinguish patients with hypertension from normotensives. In order to test this, total RNA from peripheral blood cells was isolated. RNA was reversed-transcribed and labeled and gene expression analyzed using significance Analysis Microarrays (Stanford University, CA, USA). Briefly, Significance Analysis Microarrays (SAM) thresholding identified 31 up-regulated and 18 down-regulated genes with fold changes of ≥2 or≤0.5 and q-value ≤5 % in expression. Statistically significantly gene ontology (GO) function and biological process differentially expressed in essential hypertension were MHC class II receptor activity and immune response respectively. Biological pathway analysis identified several related pathways which are associated with immune/inflammatory responses. Quantitative Real- Time RT-PCR results were consistent with the microarray results. The levels of C - reactive protein were higher in hypertensive patients than normotensives and inflammation-related genes were increased as well. In conclusion, genes enriched for “immune/inflammatory responses” may be associated with essential hypertension. In addition, there is a correlation between systemic inflammation and hypertension. It is anticipated that these findings may provide accurate and efficient strategies for prevention, diagnosis and control of this disorder. PMID:21369372

  17. GeneAnalytics: An Integrative Gene Set Analysis Tool for Next Generation Sequencing, RNAseq and Microarray Data.

    PubMed

    Ben-Ari Fuchs, Shani; Lieder, Iris; Stelzer, Gil; Mazor, Yaron; Buzhor, Ella; Kaplan, Sergey; Bogoch, Yoel; Plaschkes, Inbar; Shitrit, Alina; Rappaport, Noa; Kohn, Asher; Edgar, Ron; Shenhav, Liraz; Safran, Marilyn; Lancet, Doron; Guan-Golan, Yaron; Warshawsky, David; Shtrichman, Ronit

    2016-03-01

    Postgenomics data are produced in large volumes by life sciences and clinical applications of novel omics diagnostics and therapeutics for precision medicine. To move from "data-to-knowledge-to-innovation," a crucial missing step in the current era is, however, our limited understanding of biological and clinical contexts associated with data. Prominent among the emerging remedies to this challenge are the gene set enrichment tools. This study reports on GeneAnalytics™ ( geneanalytics.genecards.org ), a comprehensive and easy-to-apply gene set analysis tool for rapid contextualization of expression patterns and functional signatures embedded in the postgenomics Big Data domains, such as Next Generation Sequencing (NGS), RNAseq, and microarray experiments. GeneAnalytics' differentiating features include in-depth evidence-based scoring algorithms, an intuitive user interface and proprietary unified data. GeneAnalytics employs the LifeMap Science's GeneCards suite, including the GeneCards®--the human gene database; the MalaCards-the human diseases database; and the PathCards--the biological pathways database. Expression-based analysis in GeneAnalytics relies on the LifeMap Discovery®--the embryonic development and stem cells database, which includes manually curated expression data for normal and diseased tissues, enabling advanced matching algorithm for gene-tissue association. This assists in evaluating differentiation protocols and discovering biomarkers for tissues and cells. Results are directly linked to gene, disease, or cell "cards" in the GeneCards suite. Future developments aim to enhance the GeneAnalytics algorithm as well as visualizations, employing varied graphical display items. Such attributes make GeneAnalytics a broadly applicable postgenomics data analyses and interpretation tool for translation of data to knowledge-based innovation in various Big Data fields such as precision medicine, ecogenomics, nutrigenomics, pharmacogenomics, vaccinomics

  18. CDNA microarray analysis of gene expression patterns in blood mononuclear cells of SLA-DRB1-defined Yorkshire pigs.

    PubMed

    Nino-Soto, M I; Jozani, R J; Bridle, B; Mallard, B A

    2008-01-01

    Three lines of commercialYorkshire pigs with defined SLA-DRB1 alleles were developed at the University of Guelph for xenotransplantation and immune response studies. Two of the SLA-DRB1 alleles have been previously reported (SLA-DRB1*0502 and *0701), whereas the third one is a new allele. The influence of defined SLA-DRB1 alleles on transcriptional patterns of immune-related genes in blood mononuclear cells (BMCs) of pigs was explored using cDNA microarray. Microarray analysis showed significant differential expression of inflammatory genes in association with the various SLA-DRB1 alleles. A better understanding of the association between SLA genotypes and gene activity can increase the knowledge of the function of these molecules, as well as define new strategies to control animal health and optimize animal production.

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

    PubMed Central

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

    2016-01-01

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

  20. Development and application of the active surveillance of pathogens microarray to monitor bacterial gene flux

    PubMed Central

    Stabler, Richard A; Dawson, Lisa F; Oyston, Petra CF; Titball, Richard W; Wade, Jim; Hinds, Jason; Witney, Adam A; Wren, Brendan W

    2008-01-01

    Background Human and animal health is constantly under threat by emerging pathogens that have recently acquired genetic determinants that enhance their survival, transmissibility and virulence. We describe the construction and development of an Active Surveillance of Pathogens (ASP) oligonucleotide microarray, designed to 'actively survey' the genome of a given bacterial pathogen for virulence-associated genes. Results The microarray consists of 4958 reporters from 151 bacterial species and include genes for the identification of individual bacterial species as well as mobile genetic elements (transposons, plasmid and phage), virulence genes and antibiotic resistance genes. The ASP microarray was validated with nineteen bacterial pathogens species, including Francisella tularensis, Clostridium difficile, Staphylococcus aureus, Enterococcus faecium and Stenotrophomonas maltophilia. The ASP microarray identified these bacteria, and provided information on potential antibiotic resistance (eg sufamethoxazole resistance and sulfonamide resistance) and virulence determinants including genes likely to be acquired by horizontal gene transfer (e.g. an alpha-haemolysin). Conclusion The ASP microarray has potential in the clinic as a diagnostic tool, as a research tool for both known and emerging pathogens, and as an early warning system for pathogenic bacteria that have been recently modified either naturally or deliberately. PMID:18844996

  1. Monitoring of gene expression profiles and isolation of candidate genes involved in pollination and fertilization in rice ( Oryza sativa L.) with a 10K cDNA microarray.

    PubMed

    Lan, Lefu; Chen, Wei; Lai, Ying; Suo, Jinfeng; Kong, Zhaosheng; Li, Can; Lu, Ying; Zhang, Yujun; Zhao, Xiangyu; Zhang, Xiansheng; Zhang, Yansheng; Han, Bin; Cheng, Jing; Xue, Yongbiao

    2004-03-01

    To monitor gene expression profiles during pollination and fertilization in rice at a genome scale, we generated 73,424 high-quality expressed sequence tags (ESTs) derived from the green/etiolated shoot and pistil (0-5 h after pollination, 5hP) of rice, which were subsequently used to construct a cDNA microarray containing ca. 10 000 unique rice genes. This microarray was used to analyze gene expression in pistil unpollinated (UP), 5hP and 5DAP(5 days after pollination), anther, shoot, root, 10-day-old embryo (10EM) and 10-day-old endosperm (10EN). Clustering analysis revealed that the anther has a gene-expression profile more similar to root than to pistil and most pistil-preferentially expressed genes respond to pollination and/or fertilization. There are 253 ESTs exhibiting differential expression (e +/- 2-fold changes) during pollination and fertilization, and about 70% of them can be assigned a putative function. We also recovered 20 genes similar to pollination-related and/or fertility-related genes previously identified as well as genes that were not implicated previously. Microarray and real-time PCR analyses showed that the array sensitivity was estimated at 1-5 copies of mRNA per cell, and the differentially expressed genes showed a high correlation between the two methods. Our results indicated that this cDNA microarray constructed here is reliable and can be used for monitoring gene expression profiles in rice. In addition, the genes that differentially expressed during pollination represent candidate genes for dissecting molecular mechanism of this important biological process in rice.

  2. Identification of differentially expressed genes in shrimp (Penaeus stylirostris) infected with White spot syndrome virus by cDNA microarrays.

    PubMed

    Dhar, A K; Dettori, A; Roux, M M; Klimpel, K R; Read, B

    2003-12-01

    White spot syndrome virus (WSSV) is currently the most important viral pathogen infecting penaeid shrimp worldwide. Although considerable progress has been made in characterizing the WSSV genome and developing detection methods, information pertaining to host genes involved in WSSV pathogenesis is limited. We examined the potential of cDNA microarray analysis to study gene expression in WSSV-infected shrimp. Shrimp cDNAs were printed as low-density arrays on glass slides and were hybridized with Cy3/Cy5 labeled probes derived from RNA isolated from healthy and WSSV-infected shrimp. Genes that code for proteins that are relevant to crustacean immunity, structural proteins, as well as proteins of unknown function were among those whose mRNA expression was altered upon WSSV infection. To validate the microarray data, the temporal expression of three differentially expressed genes, an immune gene (C-type lectin-1), a structural gene (40S ribosomal protein), and a gene involved in lipid metabolism (fatty acid binding protein) was measured in healthy and WSSV-infected shrimp by real-time RT-PCR. The data suggest that WSSV infection alters the expression of a wide array of cellular genes, and provides a framework for further studies aimed at identifying genes whose function may provide insight into the mechanism of WSSV infection in shrimp.

  3. TTCA: an R package for the identification of differentially expressed genes in time course microarray data.

    PubMed

    Albrecht, Marco; Stichel, Damian; Müller, Benedikt; Merkle, Ruth; Sticht, Carsten; Gretz, Norbert; Klingmüller, Ursula; Breuhahn, Kai; Matthäus, Franziska

    2017-01-14

    The analysis of microarray time series promises a deeper insight into the dynamics of the cellular response following stimulation. A common observation in this type of data is that some genes respond with quick, transient dynamics, while other genes change their expression slowly over time. The existing methods for detecting significant expression dynamics often fail when the expression dynamics show a large heterogeneity. Moreover, these methods often cannot cope with irregular and sparse measurements. The method proposed here is specifically designed for the analysis of perturbation responses. It combines different scores to capture fast and transient dynamics as well as slow expression changes, and performs well in the presence of low replicate numbers and irregular sampling times. The results are given in the form of tables including links to figures showing the expression dynamics of the respective transcript. These allow to quickly recognise the relevance of detection, to identify possible false positives and to discriminate early and late changes in gene expression. An extension of the method allows the analysis of the expression dynamics of functional groups of genes, providing a quick overview of the cellular response. The performance of this package was tested on microarray data derived from lung cancer cells stimulated with epidermal growth factor (EGF). Here we describe a new, efficient method for the analysis of sparse and heterogeneous time course data with high detection sensitivity and transparency. It is implemented as R package TTCA (transcript time course analysis) and can be installed from the Comprehensive R Archive Network, CRAN. The source code is provided with the Additional file 1.

  4. GeneAnalytics: An Integrative Gene Set Analysis Tool for Next Generation Sequencing, RNAseq and Microarray Data

    PubMed Central

    Ben-Ari Fuchs, Shani; Lieder, Iris; Mazor, Yaron; Buzhor, Ella; Kaplan, Sergey; Bogoch, Yoel; Plaschkes, Inbar; Shitrit, Alina; Rappaport, Noa; Kohn, Asher; Edgar, Ron; Shenhav, Liraz; Safran, Marilyn; Lancet, Doron; Guan-Golan, Yaron; Warshawsky, David; Shtrichman, Ronit

    2016-01-01

    Abstract Postgenomics data are produced in large volumes by life sciences and clinical applications of novel omics diagnostics and therapeutics for precision medicine. To move from “data-to-knowledge-to-innovation,” a crucial missing step in the current era is, however, our limited understanding of biological and clinical contexts associated with data. Prominent among the emerging remedies to this challenge are the gene set enrichment tools. This study reports on GeneAnalytics™ (geneanalytics.genecards.org), a comprehensive and easy-to-apply gene set analysis tool for rapid contextualization of expression patterns and functional signatures embedded in the postgenomics Big Data domains, such as Next Generation Sequencing (NGS), RNAseq, and microarray experiments. GeneAnalytics' differentiating features include in-depth evidence-based scoring algorithms, an intuitive user interface and proprietary unified data. GeneAnalytics employs the LifeMap Science's GeneCards suite, including the GeneCards®—the human gene database; the MalaCards—the human diseases database; and the PathCards—the biological pathways database. Expression-based analysis in GeneAnalytics relies on the LifeMap Discovery®—the embryonic development and stem cells database, which includes manually curated expression data for normal and diseased tissues, enabling advanced matching algorithm for gene–tissue association. This assists in evaluating differentiation protocols and discovering biomarkers for tissues and cells. Results are directly linked to gene, disease, or cell “cards” in the GeneCards suite. Future developments aim to enhance the GeneAnalytics algorithm as well as visualizations, employing varied graphical display items. Such attributes make GeneAnalytics a broadly applicable postgenomics data analyses and interpretation tool for translation of data to knowledge-based innovation in various Big Data fields such as precision medicine, ecogenomics, nutrigenomics

  5. Estrogen receptor biomarker genes and microarray accession numbers used in Ryan et al.

    EPA Pesticide Factsheets

    List of biomarker genes used to predict estrogen receptor activity in MCF-7 cells; list of microarray accession numbers used in the study.This dataset is associated with the following publication:Vanduyn, N., B. Chorley , R. Tice, R. Judson , and C. Corton. Moving Toward Integrating Gene Expression Profiling into High-throughput Testing:A Gene Expression Biomarker Accurately Predicts Estrogen Receptor α Modulation in a Microarray Compendium. PLoS ONE. Public Library of Science, San Francisco, CA, USA, 151(1): 88-103, (2016).

  6. Profiling of differentially expressed genes in human gingival epithelial cells and fibroblasts by DNA microarray.

    PubMed

    Abiko, Yoshimitsu; Hiratsuka, Koichi; Kiyama-Kishikawa, Michiko; Tsushima, Katsumasa; Ohta, Mitsuhiro; Sasahara, Hiroshige

    2004-03-01

    Gingival epithelial cells and fibroblasts play important roles and have a harmonious relationship under normal and disease conditions, but the precise differences between theses cells remain unknown. To study the differences in gene expression between human gingival epithelial cells (HGE) and human gingival fibroblasts (HGF), mRNA was recovered from primary cultured cells and analyzed using cDNA microarray technology. The cDNA retro-transcribed from equal quantities of mRNA was labeled with the fluorescent dyes Cy5 and Cy3. The mixed probes were then hybridized with 7276 genes on the DNA microarray, after which fluorescence signals were scanned and further analyzed using GeneSpring software. Of the 7276 genes screened, 469 showed expression levels that were more than 2-fold greater in HGE than in HGF, while 293 showed expression levels that were more than 2-fold greater in HGF than in HGE. To confirm the reliability of the microarray results, keratin K5 and desmocolin, and vimentin and gp130, which showed higher mRNA levels in HGE and HGF, respectively, were selected and their mRNA levels were further analyzed by RT-PCR. The results of RT-PCR correlated well with those of microarray analysis. The present findings using a DNA microarray to detect differences in the gene expression profiles of HGE and HGF may be beneficial for genetic diagnosis of periodontal tissue metabolism and periodontal diseases.

  7. Gene co-expression analyses: an overview from microarray collections in Arabidopsis thaliana.

    PubMed

    Di Salle, Pasquale; Incerti, Guido; Colantuono, Chiara; Chiusano, Maria Luisa

    2017-03-01

    Bioinformatics web-based resources and databases are precious references for most biological laboratories worldwide. However, the quality and reliability of the information they provide depends on them being used in an appropriate way that takes into account their specific features. Huge collections of gene expression data are currently publicly available, ready to support the understanding of gene and genome functionalities. In this context, tools and resources for gene co-expression analyses have flourished to exploit the 'guilty by association' principle, which assumes that genes with correlated expression profiles are functionally related. In the case of Arabidopsis thaliana, the reference species in plant biology, the resources available mainly consist of microarray results. After a general overview of such resources, we tested and compared the results they offer for gene co-expression analysis. We also discuss the effect on the results when using different data sets, as well as different data normalization approaches and parameter settings, which often consider different metrics for establishing co-expression. A dedicated example analysis of different gene pools, implemented by including/excluding mutant samples in a reference data set, showed significant variation of gene co-expression occurrence, magnitude and direction. We conclude that, as the heterogeneity of the resources and methods may produce different results for the same query genes, the exploration of more than one of the available resources is strongly recommended. The aim of this article is to show how best to integrate data sources and/or merge outputs to achieve robust analyses and reliable interpretations, thereby making use of diverse data resources an opportunity for added value. © The Author 2016. Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

  8. Improving gene set analysis of microarray data by SAM-GS

    PubMed Central

    Dinu, Irina; Potter, John D; Mueller, Thomas; Liu, Qi; Adewale, Adeniyi J; Jhangri, Gian S; Einecke, Gunilla; Famulski, Konrad S; Halloran, Philip; Yasui, Yutaka

    2007-01-01

    Background Gene-set analysis evaluates the expression of biological pathways, or a priori defined gene sets, rather than that of individual genes, in association with a binary phenotype, and is of great biologic interest in many DNA microarray studies. Gene Set Enrichment Analysis (GSEA) has been applied widely as a tool for gene-set analyses. We describe here some critical problems with GSEA and propose an alternative method by extending the individual-gene analysis method, Significance Analysis of Microarray (SAM), to gene-set analyses (SAM-GS). Results Using a mouse microarray dataset with simulated gene sets, we illustrate that GSEA gives statistical significance to gene sets that have no gene associated with the phenotype (null gene sets), and has very low power to detect gene sets in which half the genes are moderately or strongly associated with the phenotype (truly-associated gene sets). SAM-GS, on the other hand, performs very well. The two methods are also compared in the analyses of three real microarray datasets and relevant pathways, the diverging results of which clearly show advantages of SAM-GS over GSEA, both statistically and biologically. In a microarray study for identifying biological pathways whose gene expressions are associated with p53 mutation in cancer cell lines, we found biologically relevant performance differences between the two methods. Specifically, there are 31 additional pathways identified as significant by SAM-GS over GSEA, that are associated with the presence vs. absence of p53. Of the 31 gene sets, 11 actually involve p53 directly as a member. A further 6 gene sets directly involve the extrinsic and intrinsic apoptosis pathways, 3 involve the cell-cycle machinery, and 3 involve cytokines and/or JAK/STAT signaling. Each of these 12 gene sets, then, is in a direct, well-established relationship with aspects of p53 signaling. Of the remaining 8 gene sets, 6 have plausible, if less well established, links with p53. Conclusion We

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

    PubMed

    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.

  10. Use of a DNA Microarray for Simultaneous Detection of Antibiotic Resistance Genes among Staphylococcal Clinical Isolates▿

    PubMed Central

    Zhu, Ling-Xiang; Zhang, Zhi-Wei; Wang, Can; Yang, Hua-Wei; Jiang, Di; Zhang, Qiong; Mitchelson, Keith; Cheng, Jing

    2007-01-01

    We developed a multiplex asymmetric PCR (MAPCR)-based DNA microarray assay for characterization of the clinically relevant antibiotic resistance genes leading to penicillin, methicillin, aminoglycoside, macrolide, lincosamide, and streptogramin B (MLSB) resistance in staphylococci. The DNA-based assay involves detection of specific conserved regions of the mecA, blaZ (methicillin and penicillin resistance), aac(6′)-Ie-aph(2‴) (aminoglycoside resistance), ermA and ermC genes (MLSB resistance), and the msrA gene (macrolide and streptogramin B resistance). The microarray uses a variable sequence region of the 16S rRNA gene to broadly differentiate between Staphylococcus aureus and other coagulase-negative staphylococci (CoNS). The performance of the microarray was validated with a total of 178 clinically important S. aureus and 237 CoNS isolates, with correlations of 100% for S. aureus to CoNS discrimination and more than 90% for antibiotic resistance between the genotypic analysis determined by the microarray and the phenotype determined by standard methods of species identification and susceptibility testing. The major discrepant results were 17 mecA-positive CoNS and 60 aac(6′)-Ie-aph(2‴)-positive CoNS isolates measured by microarray that were susceptible to the corresponding antibiotics based on disk diffusion assay. Overall, this microarray-based assay offers a simultaneous, fast (≤5 h), and accurate identification of antibiotic resistance genes from a single colony, as well as species classification. Our extensive validation of the microarray suggests that it may be a useful tool to complement phenotypic susceptibility testing in clinical laboratories and to survey the spread of antibiotic resistance determinants in epidemiological studies. PMID:17728472

  11. Gene expression profiling of NB4 cells following knockdown of nucleostemin using DNA microarrays.

    PubMed

    Sun, Xiaoli; Jia, Yu; Wei, Yuanyu; Liu, Shuai; Yue, Baohong

    2016-07-01

    Nucleostemin (NS) is mainly expressed in stem and tumor cells, and is necessary for the maintenance of their self-renewal and proliferation. Originally, NS was thought to exert its effects through inhibiting p53, while recent studies have revealed that NS is also able to function independently of p53. The present study performed a gene expression profiling analysis of p53‑mutant NB4 leukeima cells following knockdown of NS in order to elucidate the p53‑independent NS pathway. NS expression was silenced using lentivirus‑mediated RNA interference technology, and gene expression profiling of NB4 cells was performed by DNA microarray analysis. A total of 1,953 genes were identified to be differentially expressed (fold change ≥2 or ≤0.5) following knockdown of NS expression. Furthermore, reverse‑transcription quantitative polymerase chain reaction analysis was used to detect the expression of certain candidate genes, and the results were in agreement with the micaroarray data. Pathway analysis indicated that aberrant genes were enhanced in endoplasmic, c‑Jun N‑terminal kinase and mineral absorption pathways. The present study shed light on the mechanisms of the p54‑independent NS pathway in NB4 cells and provided a foundation for the discovery of promising targets for the treatment of p53-mutant leukemia.

  12. Microarray Analysis of Antimicrobial Resistance Genes in Salmonella enterica from Preharvest Poultry Environment

    USDA-ARS?s Scientific Manuscript database

    Rapid detection of drug resistance profiles in Salmonella can be critical in treatment of salmonellosis. A 70-mer oligonucleotide microarray chip with 775 gene probes was used to detect antimicrobial resistance genes in 34 Salmonella isolates from a turkey production facility. The phenotypic antim...

  13. Microarray-Based Detection of 90 Antibiotic Resistance Genes of Gram-Positive Bacteria

    PubMed Central

    Perreten, Vincent; Vorlet-Fawer, Lorianne; Slickers, Peter; Ehricht, Ralf; Kuhnert, Peter; Frey, Joachim

    2005-01-01

    A disposable microarray was developed for detection of up to 90 antibiotic resistance genes in gram-positive bacteria by hybridization. Each antibiotic resistance gene is represented by two specific oligonucleotides chosen from consensus sequences of gene families, except for nine genes for which only one specific oligonucleotide could be developed. A total of 137 oligonucleotides (26 to 33 nucleotides in length with similar physicochemical parameters) were spotted onto the microarray. The microarrays (ArrayTubes) were hybridized with 36 strains carrying specific antibiotic resistance genes that allowed testing of the sensitivity and specificity of 125 oligonucleotides. Among these were well-characterized multidrug-resistant strains of Enterococcus faecalis, Enterococcus faecium, and Lactococcus lactis and an avirulent strain of Bacillus anthracis harboring the broad-host-range resistance plasmid pRE25. Analysis of two multidrug-resistant field strains allowed the detection of 12 different antibiotic resistance genes in a Staphylococcus haemolyticus strain isolated from mastitis milk and 6 resistance genes in a Clostridium perfringens strain isolated from a calf. In both cases, the microarray genotyping corresponded to the phenotype of the strains. The ArrayTube platform presents the advantage of rapidly screening bacteria for the presence of antibiotic resistance genes known in gram-positive bacteria. This technology has a large potential for applications in basic research, food safety, and surveillance programs for antimicrobial resistance. PMID:15872258

  14. Identification of target genes of cediranib in alveolar soft part sarcoma using a gene microarray.

    PubMed

    Jiang, Wenhua; Liu, Pengfei; Li, Xiaodong; Wang, Ping

    2017-04-01

    The aim of the present study was to identify the target genes of cediranib and the associated signaling pathways in alveolar soft part sarcoma (ASPS). A microarray dataset (GSE32569) was obtained from the Gene Expression Omnibus database. The R software package was used for data normalization and screening of differentially expressed genes (DEGs). The Database for Annotation, Visualization and Integrated Discovery was used to perform Gene Ontology analysis. Gene Set Enrichment Analysis was performed to obtain the up- and downregulated pathways in ASPS. The Distant Regulatory Elements of co-regulated genes database was used to identify the transcription factors (TFs) that were enriched in the signaling pathways. A protein-protein interaction (PPI) network was constructed using the Search Tool for the Retrieval of Interacting Genes/Proteins database and was visualized using Cytoscape software. A total of 71 DEGs, including 59 upregulated genes and 12 downregulated genes, were identified. Gene sets associated with ASPS were enriched primarily in four signaling pathways: The phenylalanine metabolism pathway, the mitogen-activated protein kinase (MAPK) signaling pathway, the taste transduction pathway and the intestinal immune network for the production of immunoglobulin A. Furthermore, 107 TFs were identified to be enriched in the MAPK signaling pathway. Certain genes, including those coding for Fms-like tyrosine kinase 1, kinase insert domain receptor, E-selectin and platelet-derived growth factor receptor D, that were associated with other genes in the PPI network, were identified. The present study identified certain potential target genes and the associated signaling pathways of cediranib action in ASPS, which may be helpful in understanding the efficacy of cediranib and the development of new targets for cediranib.

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

    PubMed Central

    Hu, Simin; Rao, J. Sunil

    2007-01-01

    In gene selection for cancer classification 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 eigenvalue-ratio 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. PMID:19455233

  16. Melatonin or ramelteon therapy differentially affects hepatic gene expression profiles after haemorrhagic shock in rat--A microarray analysis.

    PubMed

    Kleber, Astrid; Ruf, Christian G; Wolf, Alexander; Fink, Tobias; Glas, Michael; Wolf, Beate; Volk, Thomas; Abend, Michael; Mathes, Alexander M

    2015-10-01

    Melatonin has been demonstrated to reduce liver damage in different models of stress. However, there is only limited information on the impact of this hormone on hepatic gene expression. The aim of this study was, to investigate the influence of melatonin or the melatonergic agonist ramelteon on hepatic gene expression profiles after haemorrhagic shock using a whole genome microarray analysis. Male Sprague-Dawley rats (200-300 g, n=4/group) underwent haemorrhagic shock (mean arterial pressure 35±5 mmHg). After 90 min of shock, animals were resuscitated with shed blood and Ringer's and treated with vehicle (5% dimethyl sulfoxide), melatonin or ramelteon (each 1.0 mg/kg intravenously). Sham-operated animals were treated likewise but did not undergo haemorrhage. After 2 h of reperfusion, the liver was harvested, and a whole genome microarray analysis was performed. Functional gene expression profiles were determined using the Panther® classification system; promising candidate genes were evaluated by quantitative polymerase chain reaction (PCR). Microarray and PCR data showed a good correlation (r(2)=0.84). A strong influence of melatonin on receptor mediated signal transduction was revealed using the functional gene expression profile analysis, whereas ramelteon mainly influenced transcription factors. Shock-induced upregulation of three candidate genes with relevant functions for hepatocytes (ppp1r15a, dusp5, rhoB) was significantly reduced by melatonin (p<0.05 vs. shock/vehicle), but not by ramelteon. Two genes previously known as haemorrhage-induced (il1b, s100a8) were transcriptionally repressed by both drugs. Melatonin and ramelteon appear to induce specific hepatic gene expression profiles after haemorrhagic shock in rats. The observed differences between both substances are likely to be attributable to a distinct mechanism of action in these agents. Copyright © 2015 Elsevier Inc. All rights reserved.

  17. Removing batch effects from purified plasma cell gene expression microarrays with modified ComBat.

    PubMed

    Stein, Caleb K; Qu, Pingping; Epstein, Joshua; Buros, Amy; Rosenthal, Adam; Crowley, John; Morgan, Gareth; Barlogie, Bart

    2015-02-25

    Gene expression profiling (GEP) via microarray analysis is a widely used tool for assessing risk and other patient diagnostics in clinical settings. However, non-biological factors such as systematic changes in sample preparation, differences in scanners, and other potential batch effects are often unavoidable in long-term studies and meta-analysis. In order to reduce the impact of batch effects on microarray data, Johnson, Rabinovic, and Li developed ComBat for use when combining batches of gene expression microarray data. We propose a modification to ComBat that centers data to the location and scale of a pre-determined, 'gold-standard' batch. This modified ComBat (M-Combat) is designed specifically in the context of meta-analysis and batch effect adjustment for use with predictive models that are validated and fixed on historical data from a 'gold-standard' batch. We combined data from MIRT across two batches ('Old' and 'New' Kit sample preparation) as well as external data sets from the HOVON-65/GMMG-HD4 and MRC-IX trials into a combined set, first without transformation and then with both ComBat and M-ComBat transformations. Fixed and validated gene risk signatures developed at MIRT on the Old Kit standard (GEP5, GEP70, and GEP80 risk scores) were compared across these combined data sets. Both ComBat and M-ComBat eliminated all of the differences among probes caused by systematic batch effects (over 98% of all untransformed probes were significantly different by ANOVA with 0.01 q-value threshold reduced to zero significant probes with ComBat and M-ComBat). The agreement in mean and distribution of risk scores, as well as the proportion of high-risk subjects identified, coincided with the 'gold-standard' batch more with M-ComBat than with ComBat. The performance of risk scores improved overall using either ComBat or M-Combat; however, using M-ComBat and the original, optimal risk cutoffs allowed for greater ability in our study to identify smaller cohorts of

  18. Functional genomics in chickens: development of integrated-systems microarrays for transcriptional profiling and discovery of regulatory pathways.

    PubMed

    Cogburn, L A; Wang, X; Carre, W; Rejto, L; Aggrey, S E; Duclos, M J; Simon, J; Porter, T E

    2004-01-01

    The genetic networks that govern the differentiation and growth of major tissues of economic importance in the chicken are largely unknown. Under a functional genomics project, our consortium has generated 30 609 expressed sequence tags (ESTs) and developed several chicken DNA microarrays, which represent the Chicken Metabolic/Somatic (10 K) and Neuroendocrine/Reproductive (8 K) Systems (http://udgenome.ags.udel.edu/cogburn/). One of the major challenges facing functional genomics is the development of mathematical models to reconstruct functional gene networks and regulatory pathways from vast volumes of microarray data. In initial studies with liver-specific microarrays (3.1 K), we have examined gene expression profiles in liver during the peri-hatch transition and during a strong metabolic perturbation-fasting and re-feeding-in divergently selected broiler chickens (fast vs. slow-growth lines). The expression of many genes controlling metabolic pathways is dramatically altered by these perturbations. Our analysis has revealed a large number of clusters of functionally related genes (mainly metabolic enzymes and transcription factors) that control major metabolic pathways. Currently, we are conducting transcriptional profiling studies of multiple tissues during development of two sets of divergently selected broiler chickens (fast vs. slow growing and fat vs. lean lines). Transcriptional profiling across multiple tissues should permit construction of a detailed genetic blueprint that illustrates the developmental events and hierarchy of genes that govern growth and development of chickens. This review will briefly describe the recent acquisition of chicken genomic resources (ESTs and microarrays) and our consortium's efforts to help launch the new era of functional genomics in the chicken.

  19. Transcription factor regulation can be accurately predicted from the presence of target gene signatures in microarray gene expression data

    PubMed Central

    Essaghir, Ahmed; Toffalini, Federica; Knoops, Laurent; Kallin, Anders; van Helden, Jacques; Demoulin, Jean-Baptiste

    2010-01-01

    Deciphering transcription factor networks from microarray data remains difficult. This study presents a simple method to infer the regulation of transcription factors from microarray data based on well-characterized target genes. We generated a catalog containing transcription factors associated with 2720 target genes and 6401 experimentally validated regulations. When it was available, a distinction between transcriptional activation and inhibition was included for each regulation. Next, we built a tool (www.tfacts.org) that compares submitted gene lists with target genes in the catalog to detect regulated transcription factors. TFactS was validated with published lists of regulated genes in various models and compared to tools based on in silico promoter analysis. We next analyzed the NCI60 cancer microarray data set and showed the regulation of SOX10, MITF and JUN in melanomas. We then performed microarray experiments comparing gene expression response of human fibroblasts stimulated by different growth factors. TFactS predicted the specific activation of Signal transducer and activator of transcription factors by PDGF-BB, which was confirmed experimentally. Our results show that the expression levels of transcription factor target genes constitute a robust signature for transcription factor regulation, and can be efficiently used for microarray data mining. PMID:20215436

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

    PubMed

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

    2008-01-01

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

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

    NASA Astrophysics Data System (ADS)

    Chatziioannou, Aristotelis; Moulos, Panagiotis

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

  2. Gene profiling of the rat medial collateral ligament during early healing using microarray analysis

    PubMed Central

    Chamberlain, Connie S.; Brounts, Sabrina H.; Sterken, David G.; Rolnick, Kevin I.; Baer, Geoffrey S.

    2011-01-01

    Ligament heals in a synchronized and complex series of events. The remodeling process may last months or years. Experimental evidence suggests the damaged ligament does not recover its normal functional properties. Specific mechanisms to prevent scar formation and to regenerate the original mechanical function remain elusive but likely involve regulation of creeping substitution. Creeping substitution creates a larger hypercellular, hypervascular, and disorganized granulation tissue mass that results in an inefficient and nonregenerative wound healing process for the ligament. Control of creeping substitution may limit the extent of this tissue compromise and reduce the time necessary for healing. The objective of this study is to better understand the mechanism behind scar formation by identifying the extracellular matrix factors and other unique genes of interest differentially expressed during rat ligament healing via microarray. For this study, rat medial collateral ligaments were either surgically transected or left intact. Ligaments were collected at day 3 or 7 postinjury and used for microarray, quantitative PCR, and/or immunohistochemistry. Results were compared with the normal intact ligament. We demonstrate that early ligament healing is characterized by the modulation of several inflammatory and extracellular matrix factors during the first week of injury. Specifically, a number of matrix metalloproteinases and collagens are differentially and significantly expressed during early ligament healing. Additionally, we demonstrate the modulation of three novel genes, periostin, collagen-triple helix repeat containing-1, and serine protease 35 in our ligament healing model. Together, control of granulation tissue creeping substitution and subsequent downstream scar formation is likely to involve these factors. PMID:21596919

  3. geneCommittee: a web-based tool for extensively testing the discriminatory power of biologically relevant gene sets in microarray data classification.

    PubMed

    Reboiro-Jato, Miguel; Arrais, Joel P; Oliveira, José Luis; Fdez-Riverola, Florentino

    2014-01-30

    The diagnosis and prognosis of several diseases can be shortened through the use of different large-scale genome experiments. In this context, microarrays can generate expression data for a huge set of genes. However, to obtain solid statistical evidence from the resulting data, it is necessary to train and to validate many classification techniques in order to find the best discriminative method. This is a time-consuming process that normally depends on intricate statistical tools. geneCommittee is a web-based interactive tool for routinely evaluating the discriminative classification power of custom hypothesis in the form of biologically relevant gene sets. While the user can work with different gene set collections and several microarray data files to configure specific classification experiments, the tool is able to run several tests in parallel. Provided with a straightforward and intuitive interface, geneCommittee is able to render valuable information for diagnostic analyses and clinical management decisions based on systematically evaluating custom hypothesis over different data sets using complementary classifiers, a key aspect in clinical research. geneCommittee allows the enrichment of microarrays raw data with gene functional annotations, producing integrated datasets that simplify the construction of better discriminative hypothesis, and allows the creation of a set of complementary classifiers. The trained committees can then be used for clinical research and diagnosis. Full documentation including common use cases and guided analysis workflows is freely available at http://sing.ei.uvigo.es/GC/.

  4. cDNA Microarray Analysis Revealing Candidate Biomineralization Genes of the Pearl Oyster, Pinctada fucata martensii.

    PubMed

    Shi, Yaohua; Zheng, Xing; Zhan, Xin; Wang, Aimin; Gu, Zhifeng

    2016-06-01

    Biomineralization is a common biological phenomenon resulting in strong tissue, such as bone, tooth, and shell. Pinctada fucata martensii is an ideal animal for the study of biomineralization. Here, microarray technique was used to identify biomineralization gene in mantle edge (ME), mantle center (MC), and both ME and MC (ME-MC) for this pearl oyster. Results revealed that 804, 306, and 1127 contigs expressed at least three times higher in ME, MC, and ME-MC as those in other tissues. Blast against non-redundant database showed that 130 contigs (16.17 %), 53 contigs (17.32 %), and 248 contigs (22.01 %) hit reference genes (E ≤ -10), among which 91 contigs, 48 contigs, and 168 contigs could be assigned to 32, 26, and 63 biomineralization genes in tissue of ME, MC, and ME-MC at a threshold of 3 times upregulated expression level. The ratios of biomineralization contigs to homologous contigs were similar at 3 times, 10 times, and 100 times of upregulated expression level in either ME, MC, or ME-MC. Moreover, the ratio of biomineralization contigs was highest in MC. Although mRNA distribution characters were similar to those in other studies for eight biomineralization genes of PFMG3, Pif, nacrein, MSI7, mantle gene 6, Pfty1, prismin, and the shematrin, most biomineralization genes presented different expression profiles from existing reports. These results provided massive fundamental information for further study of biomineralization gene function, and it may be helpful for revealing gene nets of biomineralization and the molecular mechanisms underlining formation of shell and pearl for the oyster.

  5. Adaptive filtering of microarray gene expression data based on Gaussian mixture decomposition

    PubMed Central

    2013-01-01

    Background DNA microarrays are used for discovery of genes expressed differentially between various biological conditions. In microarray experiments the number of analyzed samples is often much lower than the number of genes (probe sets) which leads to many false discoveries. Multiple testing correction methods control the number of false discoveries but decrease the sensitivity of discovering differentially expressed genes. Concerning this problem, filtering methods for improving the power of detection of differentially expressed genes were proposed in earlier papers. These techniques are two-step procedures, where in the first step some pool of non-informative genes is removed and in the second step only the pool of the retained genes is used for searching for differentially expressed genes. Results A very important parameter to choose is the proportion between the sizes of the pools of removed and retained genes. A new method, which we propose, allow to determine close to optimal threshold values for sample means and sample variances for gene filtering. The method is adaptive and based on the decomposition of the histogram of gene expression means or variances into mixture of Gaussian components. Conclusions By performing analyses of several publicly available datasets and simulated datasets we demonstrate that our adaptive method increases sensitivity of finding differentially expressed genes compared to previous methods of filtering microarray data based on using fixed threshold values. PMID:23510016

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

    PubMed

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

    2015-11-10

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

  7. Analysis of gene expression on anodic porous alumina microarrays

    PubMed Central

    Nicolini, Claudio; Singh, Manjul; Spera, Rosanna; Felli, Lamberto

    2013-01-01

    This paper investigates the application of anodic porous alumina as an advancement on chip laboratory for gene expressions. The surface was prepared by a suitable electrolytic process to obtain a regular distribution of deep micrometric holes and printed bypen robot tips under standard conditions. The gene expression within the Nucleic Acid Programmable Protein Array (NAPPA) is realized in a confined environment of 16 spots, containing circular DNA plasmids expressed using rabbit reticulocyte lysate. Authors demonstrated the usefulness of APA in withholding the protein expression by detecting with a CCD microscope the photoluminescence signal emitted from the complex secondary antibody anchored to Cy3 and confined in the pores. Friction experiments proved the mechanical resistance under external stresses by the robot tip pens printing. So far, no attempts have been made to directly compare APA with any other surface/substrate; the rationale for pursuing APA as a potential surface coating is that it provides advantages over the simple functionalization of a glass slide, overcoming concerns about printing and its ability to generate viable arrays. PMID:23783000

  8. Modeling the temporal evolution of the Drosophila gene expression from DNA microarray time series

    NASA Astrophysics Data System (ADS)

    Haye, Alexandre; Dehouck, Yves; Kwasigroch, Jean Marc; Bogaerts, Philippe; Rooman, Marianne

    2009-03-01

    The time evolution of gene expression across the developmental stages of the host organism can be inferred from appropriate DNA microarray time series. Modeling this evolution aims eventually at improving the understanding and prediction of the complex phenomena that are the basis of life. We focus on the embryonic-to-adult development phases of Drosophila melanogaster, and chose to model the expression network with the help of a system of differential equations with constant coefficients, which are nonlinear in the transcript concentrations but linear in their logarithms. To reduce the dimensionality of the problem, genes having similar expression profiles are grouped into 17 clusters. We show that a simple linear model is able to reproduce the experimental data with very good precision, owing to the large number of parameters that represent the connections between the clusters. Remarkably, the parameter reduction allowed elimination of up to 80-85% of these connections while keeping fairly good precision. This result supports the low-connectivity hypothesis of gene expression networks, with about three connections per cluster, without introducing a priori hypotheses. The core of the network shows a few gene clusters with negative self-regulation, and some highly connected clusters involving proteins with crucial functions.

  9. Effects of Oxidized Phospholipids on Gene Expression in RAW 264.7 Macrophages: A Microarray Study

    PubMed Central

    Koller, Daniel; Hackl, Hubert; Bogner-Strauß, Juliane Gertrude; Hermetter, Albin

    2014-01-01

    Oxidized phospholipids (oxPLs) are components of oxidized LDL (oxLDL). It is known that oxLDL activates expression of a series of atherogenic genes and their oxPLs contribute to their biological activities. In this study we present the effects of 1-palmitoyl-2-glutaroyl-sn-glycero-3-phosphocholine (PGPC) and 1-palmitoyl-2-(5-oxovaleroyl)-sn-glycero-3-phosphocholine (POVPC) on gene expression in RAW 264.7 macrophages using cDNA microarrays. PGPC affected the regulation of 146 genes, whereas POVPC showed only very minor effects. PGPC preferentially influenced expression of genes related to cell death, angiogenesis, cholesterol efflux, procoagulant mechanisms, atherogenesis, inflammation, and cell cycle. Many of these effects are known from studies with oxLDL or oxidized 1-hexadecanoyl-2-eicosatetra-5′,8′,11′,14′-enoyl-sn-glycero-3-phosphocholine (oxPAPC), containing PGPC in addition to other oxPL species. It is known that POVPC efficiently reacts with proteins by Schiff base formation, whereas PGPC only physically interacts with its biological targets. POVPC seems to affect cell physiology to a great extent on the protein level, whereas PGPC gives rise to both the modulation of protein function and regulation on the transcriptional level. PMID:25333283

  10. Insights into the Sigma-1 receptor chaperone’s cellular functions: a microarray report

    PubMed Central

    Tsai, Shang-Yi; Rothman, Richard Kyle; Su, Tsung-Ping

    2013-01-01

    We previously demonstrated that Sig-1Rs are critical regulators in neuronal morphogenesis and development via the regulation of oxidative stress and mitochondrial functions. In the present study, we sought to identify pathways and genes that are affected by Sig-1R. Gene expression profiles were examined in rat hippocampal neurons that had been cultured for18 days in vitro (DIV). The cells were transduced with AAV siRNA targeting Sig-1R on DIV 10 for 7 days, followed by gene expression analysis using a rat genome cDNA array. The gene array results indicated that Sig-1R knockdown hampered cellular functions including steroid biogenesis, protein ubiquitination, actin cytoskeleton network, and Nrf-2 mediated oxidative stress. Many of the cellular components important for actin polymerization and synapse plasticity, including F-actin capping protein and neurofilaments, were significantly changed in AAV-siSig-1R neurons. Further, cytochrome c was reduced in AAV-Sig-1R neurons whereas free-radical generating enzymes including cytochrome p450 and cytochrome b-245 were increased. The microarray results also suggest that Sig-1Rs may regulate genes that are involved in the pathogenesis of many CNS diseases including Alzheimer’s disease and Parkinson’s disease. These data further confirmed that Sig-1Rs play critical roles in the CNS and thus these findings may aid in future development of therapeutic treatments targeting neurodegenerative disorders. PMID:21905129

  11. Hierarchical Gene Selection and Genetic Fuzzy System for Cancer Microarray Data Classification

    PubMed Central

    Nguyen, Thanh; Khosravi, Abbas; Creighton, Douglas; Nahavandi, Saeid

    2015-01-01

    This paper introduces a novel approach to gene selection based on a substantial modification of analytic hierarchy process (AHP). The modified AHP systematically integrates outcomes of individual filter methods to select the most informative genes for microarray classification. Five individual ranking methods including t-test, entropy, receiver operating characteristic (ROC) curve, Wilcoxon and signal to noise ratio are employed to rank genes. These ranked genes are then considered as inputs for the modified AHP. Additionally, a method that uses fuzzy standard additive model (FSAM) for cancer classification based on genes selected by AHP is also proposed in this paper. Traditional FSAM learning is a hybrid process comprising unsupervised structure learning and supervised parameter tuning. Genetic algorithm (GA) is incorporated in-between unsupervised and supervised training to optimize the number of fuzzy rules. The integration of GA enables FSAM to deal with the high-dimensional-low-sample nature of microarray data and thus enhance the efficiency of the classification. Experiments are carried out on numerous microarray datasets. Results demonstrate the performance dominance of the AHP-based gene selection against the single ranking methods. Furthermore, the combination of AHP-FSAM shows a great accuracy in microarray data classification compared to various competing classifiers. The proposed approach therefore is useful for medical practitioners and clinicians as a decision support system that can be implemented in the real medical practice. PMID:25823003

  12. Differential modulation of Bordetella pertussis virulence genes as evidenced by DNA microarray analysis.

    PubMed

    Hot, D; Antoine, R; Renauld-Mongénie, G; Caro, V; Hennuy, B; Levillain, E; Huot, L; Wittmann, G; Poncet, D; Jacob-Dubuisson, F; Guyard, C; Rimlinger, F; Aujame, L; Godfroid, E; Guiso, N; Quentin-Millet, M-J; Lemoine, Y; Locht, C

    2003-07-01

    The production of most factors involved in Bordetella pertussis virulence is controlled by a two-component regulatory system termed BvgA/S. In the Bvg+ phase virulence-activated genes (vags) are expressed, and virulence-repressed genes (vrgs) are down-regulated. The expression of these genes can also be modulated by MgSO(4) or nicotinic acid. In this study we used microarrays to analyse the influence of BvgA/S or modulation on the expression of nearly 200 selected genes. With the exception of one vrg, all previously known vags and vrgs were correctly assigned as such, and the microarray analyses identified several new vags and vrgs, including genes coding for putative autotransporters, two-component systems, extracellular sigma factors, the adenylate cyclase accessory genes cyaBDE, and two genes coding for components of a type III secretion system. For most of the new vrgs and vags the results of the microarray analyses were confirmed by RT-PCR analysis and/or lacZfusions. The degree of regulation and modulation varied between genes, and showed a continuum from strongly BvgA/S-activated genes to strongly BvgA/S-repressed genes. The microarray analyses also led to the identification of a subset of vags and vrgs that are differentially regulated and modulated by MgSO(4) or nicotinic acid, indicating that these genes may be targets for multiple regulatory circuits. For example, the expression of bilA, a gene predicted to encode an intimin-like protein, was found to be activated by BvgA/S and up-modulated by nicotinic acid. Furthermore, surprisingly, in the strain analysed here, which produces only type 2 fimbriae, the fim3 gene was identified as a vrg, while fim2 was confirmed to be a vag.

  13. Computerized system for recognition of autism on the basis of gene expression microarray data.

    PubMed

    Latkowski, Tomasz; Osowski, Stanislaw

    2015-01-01

    The aim of this paper is to provide a means to recognize a case of autism using gene expression microarrays. The crucial task is to discover the most important genes which are strictly associated with autism. The paper presents an application of different methods of gene selection, to select the most representative input attributes for an ensemble of classifiers. The set of classifiers is responsible for distinguishing autism data from the reference class. Simultaneous application of a few gene selection methods enables analysis of the ill-conditioned gene expression matrix from different points of view. The results of selection combined with a genetic algorithm and SVM classifier have shown increased accuracy of autism recognition. Early recognition of autism is extremely important for treatment of children and increases the probability of their recovery and return to normal social communication. The results of this research can find practical application in early recognition of autism on the basis of gene expression microarray analysis.

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

    PubMed Central

    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

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

    PubMed

    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.

  16. Tetrahymena Gene Expression Database (TGED): a resource of microarray data and co-expression analyses for Tetrahymena.

    PubMed

    Xiong, Jie; Lu, XingYi; Lu, YuMing; Zeng, HongHui; Yuan, DongXia; Feng, LiFang; Chang, Yue; Bowen, Josephine; Gorovsky, Martin; Fu, ChengJie; Miao, Wei

    2011-01-01

    Tetrahymena thermophila is a model eukaryotic organism. Functional genomic analyses in Tetrahymena present rich opportunities to address fundamental questions of cell and molecular biology. The Tetrahymena Gene Expression Database (TGED; available at http://tged.ihb.ac.cn) is the first expression database of a ciliated protozoan. It covers three major physiological and developmental states: growth, starvation, and conjugation, and can be accessed through a user-friendly web interface. The gene expression profiles and candidate co-expressed genes for each gene can be retrieved using Gene ID or Gene description searches. Descriptions of standardized methods of sample preparation and the opportunity to add new Tetrahymena microarray data will be of great interest to the Tetrahymena research community. TGED is intended to be a resource for all members of the scientific research community who are interested in Tetrahymena and other ciliates.

  17. Parameter Estimation for Gene Regulatory Networks from Microarray Data: Cold Shock Response in Saccharomyces cerevisiae.

    PubMed

    Dahlquist, Kam D; Fitzpatrick, Ben G; Camacho, Erika T; Entzminger, Stephanie D; Wanner, Nathan C

    2015-08-01

    We investigated the dynamics of a gene regulatory network controlling the cold shock response in budding yeast, Saccharomyces cerevisiae. The medium-scale network, derived from published genome-wide location data, consists of 21 transcription factors that regulate one another through 31 directed edges. The expression levels of the individual transcription factors were modeled using mass balance ordinary differential equations with a sigmoidal production function. Each equation includes a production rate, a degradation rate, weights that denote the magnitude and type of influence of the connected transcription factors (activation or repression), and a threshold of expression. The inverse problem of determining model parameters from observed data is our primary interest. We fit the differential equation model to published microarray data using a penalized nonlinear least squares approach. Model predictions fit the experimental data well, within the 95% confidence interval. Tests of the model using randomized initial guesses and model-generated data also lend confidence to the fit. The results have revealed activation and repression relationships between the transcription factors. Sensitivity analysis indicates that the model is most sensitive to changes in the production rate parameters, weights, and thresholds of Yap1, Rox1, and Yap6, which form a densely connected core in the network. The modeling results newly suggest that Rap1, Fhl1, Msn4, Rph1, and Hsf1 play an important role in regulating the early response to cold shock in yeast. Our results demonstrate that estimation for a large number of parameters can be successfully performed for nonlinear dynamic gene regulatory networks using sparse, noisy microarray data.

  18. Genes regulated by thyrotropin and iodide in cultured human thyroid follicles: analysis by cDNA microarray.

    PubMed

    Yamazaki, Kazuko; Yamada, Emiko; Kanaji, Yoshio; Yanagisawa, Tetsuo; Kato, Yoshiyuki; Takano, Kazue; Obara, Takao; Sato, Kanji

    2003-02-01

    Thyrotropin (TSH) regulates a number of genes in thyrocytes, leading to iodide uptake, de novo synthesis and release of thyroid hormones, and cell proliferation, accompanied by increased blood flow. At higher doses of iodide, however, the TSH-induced increases in thyroid hormone release and blood flow are downregulated, and high iodide intake occasionally worsens autoimmune thyroiditis. To elucidate the genes involved in such effects, we cultured human thyrocytes and examined genes modulated by TSH and iodide, using a cDNA microarray study, which can analyze 2400 genes in each run. When thyroid follicles were cultured with TSH for 2 days, more than 100 genes were upregulated. These genes included those for enzymes involved in carbohydrate and lipid metabolism, adenylate and guanylate cyclases, and enzyme involved in cell proliferation. When thyroid follicles were cultured with high iodide concentrations (10(-5) M) for 24 hours, more than 100 genes were upregulated. Interesting genes were interleukin-8, IFP53, 90-kd heat shock protein, osteopontin, and intercellular adhesion molecule-1. These results were confirmed by reverse transcription-polymerase chain reaction (RT-PCR) followed by Southern blot hybridization. In summary, TSH upregulated a number of genes regulating thyroid functions. It is intriguing that thyroid follicles cultured with a high iodide concentration (10(-5) M) increased the expression levels of genes capable of modulating lymphocyte functions, even though immunocompetent cells were extensively removed by the present experimental culture conditions. Although we have analyzed only approximately 6%-8% of all human genes, the cDNA microarray study is a powerful tool to elucidate the effects of TSH and iodide on thyroid function.

  19. Global gene expression analysis of two Streptococcus thermophilus bacteriophages using DNA microarray.

    PubMed

    Duplessis, Martin; Russell, W Michael; Romero, Dennis A; Moineau, Sylvain

    2005-09-30

    A custom microarray was developed to study the temporal gene expression of the two groups of phages infecting the Gram-positive lactic acid bacterium Streptococcus thermophilus. The complete genomic sequence of the virulent cos-type phage DT1 (34,815 bp) and the pac-type phage 2972 (34,704 bp) were used for the construction of the microarray. Gene expression was measured at nine time intervals (0, 2, 7, 12, 17, 22, 27, 32 and 37 min) during phage infection and an expression curve was determined for each gene. Each phage gene was then classified into one of the three traditional transcription classes and these data were used to generate the complete transcriptional map of DT1 and 2972. Phage DT1 possesses 18 early genes, 12 middle genes and 12 late-expressed genes whereas 2972 has 16 early, 11 middle and 14 late genes. The trends of the phage gene expression profiles were also confirmed by slot blot hybridizations. Significant differences were observed when comparing the transcriptional maps of DT1 and 2972 with those already available for the S. thermophilus phages Sfi19 and Sfi21. To our knowledge, this report presents the first complete transcription analysis of bacteriophages infecting Gram-positive bacteria using the DNA microarray technology.

  20. Covariance Structure Models for Gene Expression Microarray Data

    ERIC Educational Resources Information Center

    Xie, Jun; Bentler, Peter M.

    2003-01-01

    Covariance structure models are applied to gene expression data using a factor model, a path model, and their combination. The factor model is based on a few factors that capture most of the expression information. A common factor of a group of genes may represent a common protein factor for the transcript of the co-expressed genes, and hence, it…

  1. Covariance Structure Models for Gene Expression Microarray Data

    ERIC Educational Resources Information Center

    Xie, Jun; Bentler, Peter M.

    2003-01-01

    Covariance structure models are applied to gene expression data using a factor model, a path model, and their combination. The factor model is based on a few factors that capture most of the expression information. A common factor of a group of genes may represent a common protein factor for the transcript of the co-expressed genes, and hence, it…

  2. Identification of Cytokinin-Responsive Genes Using Microarray Meta-Analysis and RNA-Seq in Arabidopsis1[C][W][OA

    PubMed Central

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

    2013-01-01

    Cytokinins are N6-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. PMID:23524861

  3. Screening of differentially expressed genes in pathological scar tissues using expression microarray.

    PubMed

    Huang, L P; Mao, Z; Zhang, L; Liu, X X; Huang, C; Jia, Z S

    2015-09-09

    Pathological scar tissues and normal skin tissues were differentiated by screening for differentially expressed genes in pathologic scar tissues via gene expression microarray. The differentially expressed gene data was analyzed by gene ontology and pathway analyses. There were 5001 up- or down-regulated genes in 2-fold differentially expressed genes, 956 up- or down-regulated genes in 5-fold differentially expressed genes, and 114 up- or down-regulated genes in 20-fold differentially expressed genes. Therefore, significant differences were observed in the gene expression in pathological scar tissues and normal foreskin tissues. The development of pathological scar tissues has been correlated to changes in multiple genes and pathways, which are believed to form a dynamic network connection.

  4. cDNA microarray reveals the alterations of cytoskeleton-related genes in osteoblast under high magneto-gravitational environment.

    PubMed

    Qian, Airong; Di, Shengmeng; Gao, Xiang; Zhang, Wei; Tian, Zongcheng; Li, Jingbao; Hu, Lifang; Yang, Pengfei; Yin, Dachuan; Shang, Peng

    2009-07-01

    The diamagnetic levitation as a novel ground-based model for simulating a reduced gravity environment has been widely applied in many fields. In this study, a special designed superconducting magnet, which can produce three apparent gravity levels (0, 1, and 2 g), namely high magneto-gravitational environment (HMGE), was used to simulate space gravity environment. The effects of HMGE on osteoblast gene expression profile were investigated by microarray. Genes sensitive to diamagnetic levitation environment (0 g), gravity changes, and high magnetic field changes were sorted on the basis of typical cell functions. Cytoskeleton, as an intracellular load-bearing structure, plays an important role in gravity perception. Therefore, 13 cytoskeleton-related genes were chosen according to the results of microarray analysis, and the expressions of these genes were found to be altered under HMGE by real-time PCR. Based on the PCR results, the expressions of WASF2 (WAS protein family, member 2), WIPF1 (WAS/WASL interacting protein family, member 1), paxillin, and talin 1 were further identified by western blot assay. Results indicated that WASF2 and WIPF1 were more sensitive to altered gravity levels, and talin 1 and paxillin were sensitive to both magnetic field and gravity changes. Our findings demonstrated that HMGE can affect osteoblast gene expression profile and cytoskeleton-related genes expression. The identification of mechanosensitive genes may enhance our understandings to the mechanism of bone loss induced by microgravity and may provide some potential targets for preventing and treating bone loss or osteoporosis.

  5. Screening for key genes associated with atopic dermatitis with DNA microarrays.

    PubMed

    Zhang, Zhong-Kui; Yang, Yong; Bai, Shu-Rong; Zhang, Gui-Zhen; Liu, Tai-Hua; Zhou, Zhou; Wang, Chun-Mei; Tang, Li-Jun; Wang, Jun; He, Si-Xian

    2014-03-01

    The aim of the present study was to identify key genes associated with atopic dermatitis (AD) using microarray data and bioinformatic analyses. The dataset GSE6012, downloaded from the Gene Expression Omnibus (GEO) database, contains gene expression data from 10 AD skin samples and 10 healthy skin samples. Following data preprocessing, differentially expressed genes (DEGs) were identified using the limma package of the R project. Interaction networks were constructed comprising DEGs that showed a degree of node of >3, >5 and >10, using the Osprey software. Functional enrichment and pathway enrichment analysis of the network comprising all DEGs and of the network comprising DEGs with a high degree of node, were performed with the DAVID and WebGestalt toolkits, respectively. A total of 337 DEGs were identified. The functional enrichment analysis revealed that the list of DEGs was significantly enriched for proteins related to epidermis development (P=2.95E-07), including loricrin (LOR), keratin 17 (KRT17), small proline-rich repeat proteins (SPRRs) and involucrin (IVL). The chemokine signaling pathway was the most significantly enriched pathway (P=0.0490978) in the network of all DEGs and in the network consisting of high degree‑node DEGs (>10), which comprised the genes coding for chemokine receptor 7 (CCR7), chemokine ligand (CCL19), signal transducer and activator of transcription 1 (STAT1), and phosphoinositide-3-kinase regulatory subunit 1 (PIK3R1). In conclusion, the list of AD-associated proteins identified in this study, including LOR, KRT17, SPRRs, IVL, CCR7, CCL19, PIK3R1 and STAT1 may prove useful for the development of methods to treat AD. From these proteins, PIK3R1 and KRT17 are novel and promising targets for AD therapy.

  6. Use of a 15 k gene microarray to determine gene expression changes in response to acute and chronic methylmercury exposure in the fathead minnow Pimephales promelas Rafinesque

    USGS Publications Warehouse

    Klaper, R.; Carter, Barbara J.; Richter, C.A.; Drevnick, P.E.; Sandheinrich, M.B.; Tillitt, D.E.

    2008-01-01

    This study describes the use of a 15 000 gene microarray developed for the toxicological model species, Pimephales promelas, in investigating the impact of acute and chronic methylmercury exposures in male gonad and liver tissues. The results show significant differences in the individual genes that were differentially expressed in response to each treatment. In liver, a total of 650 genes exhibited significantly (P < 0.05) altered expression with greater than two-fold differences from the controls in response to acute exposure and a total of 267 genes were differentially expressed in response to chronic exposure. A majority of these genes were downregulated rather than upregulated. Fewer genes were altered in gonad than in liver at both timepoints. A total of 212 genes were differentially expressed in response to acute exposure and 155 genes were altered in response to chronic exposure. Despite the differences in individual genes expressed across treatments, the functional categories that altered genes were associated with showed some similarities. Of interest in light of other studies involving the effects of methylmercury on fish, several genes associated with apoptosis were upregulated in response to both acute and chronic exposures. Induction of apoptosis has been associated with effects on reproduction seen in the previous studies. This study demonstrates the utility of microarray analysis for investigations of the physiological effects of toxicants as well as the time-course of effects that may take place. In addition, it is the first publication to demonstrate the use of this new 15 000 gene microarray for fish biology and toxicology. ?? 2008 The Authors.

  7. Very Important Pool (VIP) genes – an application for microarray-based molecular signatures

    PubMed Central

    Su, Zhenqiang; Hong, Huixiao; Fang, Hong; Shi, Leming; Perkins, Roger; Tong, Weida

    2008-01-01

    Background Advances in DNA microarray technology portend that molecular signatures from which microarray will eventually be used in clinical environments and personalized medicine. Derivation of biomarkers is a large step beyond hypothesis generation and imposes considerably more stringency for accuracy in identifying informative gene subsets to differentiate phenotypes. The inherent nature of microarray data, with fewer samples and replicates compared to the large number of genes, requires identifying informative genes prior to classifier construction. However, improving the ability to identify differentiating genes remains a challenge in bioinformatics. Results A new hybrid gene selection approach was investigated and tested with nine publicly available microarray datasets. The new method identifies a Very Important Pool (VIP) of genes from the broad patterns of gene expression data. The method uses a bagging sampling principle, where the re-sampled arrays are used to identify the most informative genes. Frequency of selection is used in a repetitive process to identify the VIP genes. The putative informative genes are selected using two methods, t-statistic and discriminatory analysis. In the t-statistic, the informative genes are identified based on p-values. In the discriminatory analysis, disjoint Principal Component Analyses (PCAs) are conducted for each class of samples, and genes with high discrimination power (DP) are identified. The VIP gene selection approach was compared with the p-value ranking approach. The genes identified by the VIP method but not by the p-value ranking approach are also related to the disease investigated. More importantly, these genes are part of the pathways derived from the common genes shared by both the VIP and p-ranking methods. Moreover, the binary classifiers built from these genes are statistically equivalent to those built from the top 50 p-value ranked genes in distinguishing different types of samples. Conclusion The

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

    PubMed Central

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

    2008-01-01

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

  9. Gene selection algorithms for microarray data based on least squares support vector machine

    PubMed Central

    Tang, E Ke; Suganthan, PN; Yao, Xin

    2006-01-01

    Background In discriminant analysis of microarray data, usually a small number of samples are expressed by a large number of genes. It is not only difficult but also unnecessary to conduct the discriminant analysis with all the genes. Hence, gene selection is usually performed to select important genes. Results A gene selection method searches for an optimal or near optimal subset of genes with respect to a given evaluation criterion. In this paper, we propose a new evaluation criterion, named the leave-one-out calculation (LOOC, A list of abbreviations appears just above the list of references) measure. A gene selection method, named leave-one-out calculation sequential forward selection (LOOCSFS) algorithm, is then presented by combining the LOOC measure with the sequential forward selection scheme. Further, a novel gene selection algorithm, the gradient-based leave-one-out gene selection (GLGS) algorithm, is also proposed. Both of the gene selection algorithms originate from an efficient and exact calculation of the leave-one-out cross-validation error of the least squares support vector machine (LS-SVM). The proposed approaches are applied to two microarray datasets and compared to other well-known gene selection methods using codes available from the second author. Conclusion The proposed gene selection approaches can provide gene subsets leading to more accurate classification results, while their computational complexity is comparable to the existing methods. The GLGS algorithm can also better scale to datasets with a very large number of genes. PMID:16504159

  10. Microarray analysis of gene expression in olive flounder liver infected with viral haemorrhagic septicaemia virus (VHSV).

    PubMed

    Cho, Hyun Kook; Kim, Julan; Moon, Ji Young; Nam, Bo-Hye; Kim, Young-Ok; Kim, Woo-Jin; Park, Jung Youn; An, Cheul Min; Cheong, Jaehun; Kong, Hee Jeong

    2016-02-01

    The most fatal viral pathogen in olive flounder Paralichthys olivaceus, is viral hemorrhagic septicemia virus, which afflicts over 48 species of freshwater and marine fish. Here, we performed gene expression profiling on transcripts isolated from VHSV-infected olive flounder livers using a 13 K cDNA microarray chip. A total of 1832 and 1647 genes were upregulated and down-regulated over two-fold, respectively, after infection. A variety of immune-related genes showing significant changes in gene expression were identified in upregulated genes through gene ontology annotation. These genes were grouped into categories such as antibacterial peptide, antigen-recognition and adhesion molecules, apoptosis, cytokine-related pathway, immune system, stress response, and transcription factor and regulatory factors. To verify the cDNA microarray data, we performed quantitative real-time PCR, and the results were similar to the microarray data. In conclusion, these results may be useful for the identification of specific genes or for the diagnosis of VHSV infection in flounder.

  11. Borrowing information across genes and experiments for improved error variance estimation in microarray data analysis.

    PubMed

    Ji, Tieming; Liu, Peng; Nettleton, Dan

    2012-01-01

    Statistical inference for microarray experiments usually involves the estimation of error variance for each gene. Because the sample size available for each gene is often low, the usual unbiased estimator of the error variance can be unreliable. Shrinkage methods, including empirical Bayes approaches that borrow information across genes to produce more stable estimates, have been developed in recent years. Because the same microarray platform is often used for at least several experiments to study similar biological systems, there is an opportunity to improve variance estimation further by borrowing information not only across genes but also across experiments. We propose a lognormal model for error variances that involves random gene effects and random experiment effects. Based on the model, we develop an empirical Bayes estimator of the error variance for each combination of gene and experiment and call this estimator BAGE because information is Borrowed Across Genes and Experiments. A permutation strategy is used to make inference about the differential expression status of each gene. Simulation studies with data generated from different probability models and real microarray data show that our method outperforms existing approaches.

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

    PubMed Central

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

    2016-01-01

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

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

    PubMed

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

    2016-03-01

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

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

    EPA Science Inventory

    GENE EXPRESSION IN THE TESTES OF NORMOSPERMIC VERSUS TERATOSPERMIC DOMESTIC CATS USING HUMAN cDNA MICROARRAY ANALYSES

    B.S. Pukazhenthi1, J. C. Rockett2, M. Ouyang3, D.J. Dix2, J.G. Howard1, P. Georgopoulos4, W.J. J. Welsh3 and D. E. Wildt1

    1Department of Reproductiv...

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

    EPA Science Inventory


    MICROARRAY ANALYSIS OF DICHLOROACETIC ACID-INDUCED CHANGES IN GENE EXPRESSION

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

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

    EPA Science Inventory

    GENE EXPRESSION IN THE TESTES OF NORMOSPERMIC VERSUS TERATOSPERMIC DOMESTIC CATS USING HUMAN cDNA MICROARRAY ANALYSES

    B.S. Pukazhenthi1, J. C. Rockett2, M. Ouyang3, D.J. Dix2, J.G. Howard1, P. Georgopoulos4, W.J. J. Welsh3 and D. E. Wildt1

    1Department of Reproductiv...

  17. USING DNA MICROARRAYS TO CHARACTERIZE GENE EXPRESSION IN TESTES OF FERTILE AND INFERTILE HUMANS AND MICE

    EPA Science Inventory

    USING DNA MICROARRAYS TO CHARACTERIZE GENE EXPRESSION
    IN TESTES OF FERTILE AND INFERTILE HUMANS AND MICE

    John C. Rockett1, J. Christopher Luft1, J. Brian Garges1, M. Stacey Ricci2, Pasquale Patrizio2, Norman B. Hecht2 and David J. Dix1
    Reproductive Toxicology Divisio...

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

    PubMed

    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.

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

    PubMed

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

    2014-08-01

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

  20. USING DNA MICROARRAYS TO CHARACTERIZE GENE EXPRESSION IN TESTES OF FERTILE AND INFERTILE HUMANS AND MICE

    EPA Science Inventory

    USING DNA MICROARRAYS TO CHARACTERIZE GENE EXPRESSION
    IN TESTES OF FERTILE AND INFERTILE HUMANS AND MICE

    John C. Rockett1, J. Christopher Luft1, J. Brian Garges1, M. Stacey Ricci2, Pasquale Patrizio2, Norman B. Hecht2 and David J. Dix1
    Reproductive Toxicology Divisio...

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

    EPA Science Inventory


    MICROARRAY ANALYSIS OF DICHLOROACETIC ACID-INDUCED CHANGES IN GENE EXPRESSION

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

  2. Comparison of microarray and sage techniques in gene expression analysis of human glioblastoma.

    PubMed

    Kavsan, V M; Dmitrenko, V V; Shostak, K O; Bukreieva, T V; Vitak, N Y; Simirenko, O E; Malisheva, T A; Shamayev, M I; Rozumenko, V D; Zozulya, Y A

    2007-01-01

    To enhance glioblastoma (GB) marker discovery we compared gene expression in GB with human normal brain (NB) by accessing SAGE Genie web site and compared obtained results with published data. Nine GB and five NB SAGE-libraries were analyzed using the Digital Gene Expression Displayer (DGED), the results of DGED were tested by Northern blot analysis and RT-PCR of arbitrary selected genes. Review of available data from the articles on gene expression profiling by microarray-based hybridization showed as few as 35 overlapped genes with increased expression in GB. Some of them were identified in four articles, but most genes in three or even in two investigations. There was found also some differences between SAGE results of GB analysis. Digital Gene Expression Displayer approach revealed 676 genes differentially expressed in GB vs. NB with cut-off ratio: twofold change and P < or = 0.05. Differential expression of selectedgenes obtained by DGED was confirmed by Northern analysis and RT-PCR. Altogether, only 105 of 955 genes presented in published investigations were among the genes obtained by DGED. Comparison of the results obtained by microarrays and SAGE is very complicated because authors present only the most prominent differentially expressed genes. However, even available data give quite poor overlapping of genes revealed by microarrays. Some differences between results obtained by SAGE in different investigations can be explained by high dependence on the statistical methods used. As for now, the best solution to search for molecular tumor markers is to compare all available results and to select only those genes, which significant expression in tumor combined with very low expression in normal tissues was reproduced in several articles. 105 differentially expressed genes, common to both methods, can be included in the list of candidates for the molecular typing of GBs. Some genes, encoded cell surface or extra-cellular proteins may be useful for targeting

  3. Microarray analysis of hepatic gene expression identifies new genes involved in steatotic liver

    PubMed Central

    Guillén, Natalia; Navarro, María A.; Arnal, Carmen; Noone, Enda; Arbonés-Mainar, José M.; Acín, Sergio; Surra, Joaquín C.; Muniesa, Pedro; Roche, Helen M.; Osada, Jesús

    2009-01-01

    Trans-10, cis-12-conjugated linoleic acid (CLA)-enriched diets promote fatty liver in mice, while cis-9, trans-11-CLA ameliorates this effect, suggesting regulation of multiple genes. To test this hypothesis, apoE-deficient mice were fed a Western-type diet enriched with linoleic acid isomers, and their hepatic gene expression was analyzed with DNA microarrays. To provide an initial screening of candidate genes, only 12 with remarkably modified expression between both CLA isomers were considered and confirmed by quantitative RT-PCR. Additionally mRNA expression of 15 genes involved in lipid metabolism was also studied. Ten genes (Fsp27, Aqp4, Cd36, Ly6d, Scd1, Hsd3b5, Syt1, Cyp7b1, and Tff3) showed significant associations among their expressions and the degree of hepatic steatosis. Their involvement was also analyzed in other models of steatosis. In hyperhomocysteinemic mice lacking Cbs gene, only Fsp27, Cd36, Scd1, Syt1, and Hsd3b5 hepatic expressions were associated with steatosis. In apoE-deficient mice consuming olive-enriched diet displaying reduction of the fatty liver, only Fsp27 and Syt1 expressions were found associated. Using this strategy, we have shown that expression of these genes is highly associated with hepatic steatosis in a genetic disease such as Cbs deficiency and in two common situations such as Western diets containing CLA isomers or a Mediterranean-type diet. Conclusion: The results highlight new processes involved in lipid handling in liver and will help to understand the complex human pathology providing new proteins and new strategies to cope with hepatic steatosis. PMID:19258494

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

    PubMed Central

    2010-01-01

    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 designs and target tissues

  5. A Novel Strategy for Gene Selection of Microarray Data Based on Gene-to-Class Sensitivity Information

    PubMed Central

    Han, Fei; Sun, Wei; Ling, Qing-Hua

    2014-01-01

    To obtain predictive genes with lower redundancy and better interpretability, a hybrid gene selection method encoding prior information is proposed in this paper. To begin with, the prior information referred to as gene-to-class sensitivity (GCS) of all genes from microarray data is exploited by a single hidden layered feedforward neural network (SLFN). Then, to select more representative and lower redundant genes, all genes are grouped into some clusters by K-means method, and some low sensitive genes are filtered out according to their GCS values. Finally, a modified binary particle swarm optimization (BPSO) encoding the GCS information is proposed to perform further gene selection from the remainder genes. For considering the GCS information, the proposed method selects those genes highly correlated to sample classes. Thus, the low redundant gene subsets obtained by the proposed method also contribute to improve classification accuracy on microarray data. The experiments results on some open microarray data verify the effectiveness and efficiency of the proposed approach. PMID:24844313

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

    PubMed Central

    2010-01-01

    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 PMID:21047384

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

    USDA-ARS?s Scientific Manuscript database

    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 wide...

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

    PubMed Central

    2011-01-01

    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. PMID:22369383

  9. VAMPIRE microarray suite: a web-based platform for the interpretation of gene expression data

    PubMed Central

    Hsiao, Albert; Ideker, Trey; Olefsky, Jerrold M.; Subramaniam, Shankar

    2005-01-01

    Microarrays are invaluable high-throughput tools used to snapshot the gene expression profiles of cells and tissues. Among the most basic and fundamental questions asked of microarray data is whether individual genes are significantly activated or repressed by a particular stimulus. We have previously presented two Bayesian statistical methods for this level of analysis, collectively known as variance-modeled posterior inference with regional exponentials (VAMPIRE). These methods each require a sophisticated modeling step followed by integration of a posterior probability density. We present here a publicly available, web-based platform that allows users to easily load data, associate related samples and identify differentially expressed features using the VAMPIRE statistical framework. In addition, this suite of tools seamlessly integrates a novel gene annotation tool, known as GOby, which identifies statistically overrepresented gene groups. Unlike other tools in this genre, GOby can localize enrichment while respecting the hierarchical structure of annotation systems like Gene Ontology (GO). By identifying statistically significant enrichment of GO terms, Kyoto Encyclopedia of Genes and Genomes pathways, and TRANSFAC transcription factor binding sites, users can gain substantial insight into the physiological significance of sets of differentially expressed genes. The VAMPIRE microarray suite can be accessed at . PMID:15980550

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

    PubMed

    Liu, Qingzhong; Sung, Andrew H; Chen, Zhongxue; Liu, Jianzhong; Chen, Lei; Qiao, Mengyu; Wang, Zhaohui; Huang, Xudong; Deng, Youping

    2011-12-23

    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. 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. 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.

  11. Use of Microarray Datasets to generate Caco-2-dedicated Networks and to identify Reporter Genes of Specific Pathway Activity.

    PubMed

    Venkatasubramanian, Prashanna Balaji; Toydemir, Gamze; de Wit, Nicole; Saccenti, Edoardo; Martins Dos Santos, Vitor A P; van Baarlen, Peter; Wells, Jerry M; Suarez-Diez, Maria; Mes, Jurriaan J

    2017-07-28

    Intestinal epithelial cells, like Caco-2, are commonly used to study the interaction between food, other luminal factors and the host, often supported by microarray analysis to study the changes in gene expression as a result of the exposure. However, no compiled dataset for Caco-2 has ever been initiated and Caco-2-dedicated gene expression networks are barely available. Here, 341 Caco-2-specific microarray samples were collected from public databases and from in-house experiments pertaining to Caco-2 cells exposed to pathogens, probiotics and several food compounds. Using these datasets, a gene functional association network specific for Caco-2 was generated containing 8937 nodes 129711 edges. Two in silico methods, a modified version of biclustering and the new Differential Expression Correlation Analysis, were developed to identify Caco-2-specific gene targets within a pathway of interest. These methods were subsequently applied to the AhR and Nrf2 signalling pathways and altered expression of the predicted target genes was validated by qPCR in Caco-2 cells exposed to coffee extracts, known to activate both AhR and Nrf2 pathways. The datasets and in silico method(s) to identify and predict responsive target genes can be used to more efficiently design experiments to study Caco-2/intestinal epithelial-relevant biological processes.

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

    PubMed

    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.

  13. Multivariate analysis of low-dose radiation-associated changes in cytokine gene expression profiles using microarray technology.

    PubMed

    Albanese, Joseph; Martens, Kelly; Karanitsa, Leonid V; Karkanitsa, Leonid V; Schreyer, Suzanne K; Dainiak, Nicholas

    2007-04-01

    The availability of microarray technology, which permits evaluation of the entire cellular transcriptome in a single experiment, has provided new insights on the function of the genome under normal and pathological conditions, as well as in response to genotoxic stimuli, including ionizing radiation. The aims of this study were to: 1) determine whether specific cytokine gene expression profiles can be delineated in individuals exposed to chronic, low-dose radiation; and 2) compare analyses from three multivariate analytic methodologies, hierarchical clustering analysis (HCA), principal component analysis (PCA), and projection pursuit (PP), in evaluating transcriptional responses in human mononuclear cells to low doses of ionizing radiation (IR), as determined by cDNA microarrays. Total RNA isolated from mononuclear cells of 19 apparently healthy adult individuals exposed to low doses of IR ranging from 0.18 mSv to 49 mSv over a period of 11 to 13 years, as a result of the Chernobyl Nuclear Power Plant catastrophe, was reverse transcribed in the presence of radioactive dATP to generate radiolabeled complementary cDNA. Target cDNA was hybridized to human cytokine and receptor arrays and mRNA transcriptional patterns were evaluated using HCA, PCA, and PP. Statistical analyses of the data generated from 19 microarrays revealed distinct gene expression patterns in mononuclear cells of individuals exposed to radiation doses of greater than 10 mSv or less than 10 mSv. Genes encompassed within clusters discerned by HCA, PCA, and PP varied depending on the methodology used to analyze the microarray data. The most frequently expressed genes across all radiation doses were serine/threonine protein kinase receptor (11/19), transforming growth factor (TGF) receptor (11/19), EB13 (10/19), and CD40 ligand. Although our findings suggest that it may be possible to assign gene expression profiles to low-dose-irradiated individuals, we show that gene expression profiles vary

  14. Targeted cellular process profiling approach for uterine leiomyoma using cDNA microarray, proteomics and gene ontology analysis

    PubMed Central

    Ahn, Woong Shick; Kim, Ko-Woon; Bae, Su Mi; Yoon, Joo Hee; Lee, Joon Mo; Namkoong, Sung Eun; Kim, Jin Hong; Kim, Chong Kook; Lee, Young Joo; Kim, Yong-Wan

    2003-01-01

    This study utilized both cDNA microarray and two-dimensional protein gel electrophoresis technology to investigate the multiple interactions of genes and proteins involved in uterine leiomyoma pathophysiology. Also, the gene ontology analysis was used to systematically characterize the global expression profiles at cellular process levels. We profiled differentially expressed transcriptome and proteome in six-paired leiomyoma and normal myometrium. Screening up to 17 000 genes identified 21 upregulated and 50 downregulated genes. The gene-expression profiles were classified into mutually dependent 420 functional sets, resulting in 611 cellular processes according to the gene ontology. Also, protein analysis using two-dimensional gel electrophoresis identified 33 proteins (17 upregulated and 16 downregulated) of more than 500 total spots, which was classified into 302 cellular processes. Of these functional profilings, downregulations of transcriptomes and proteoms were shown in cell adhesion, cell motility, organogenesis, enzyme regulator, structural molecule activity and response to external stimulus functional activities that are supposed to play important roles in pathophysiology. In contrast, the upregulation was only shown in nucleic acid-binding activity. Taken together, potentially significant pathogenetic cellular processes were identified and showed that the downregulated functional profiling has a significant impact on the discovery of pathogenic pathway in leiomyoma. Also, the gene ontology analysis can overcome the complexity of expression profiles of cDNA microarray and two-dimensional protein analysis via its cellular process-level approach. Therefore, a valuable prognostic candidate gene with relevance to disease-specific pathogenesis can be found at cellular process levels. PMID:14748746

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

    PubMed Central

    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

  16. Microarray-based gene expression profiling to elucidate effectiveness of fermented Codonopsis lanceolata in mice.

    PubMed

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

    2014-04-08

    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.

  17. Development and validation of a flax (Linum usitatissimum L.) gene expression oligo microarray.

    PubMed

    Fenart, Stéphane; Ndong, Yves-Placide Assoumou; Duarte, Jorge; Rivière, Nathalie; Wilmer, Jeroen; van Wuytswinkel, Olivier; Lucau, Anca; Cariou, Emmanuelle; Neutelings, Godfrey; Gutierrez, Laurent; Chabbert, Brigitte; Guillot, Xavier; Tavernier, Reynald; Hawkins, Simon; Thomasset, Brigitte

    2010-10-21

    Flax (Linum usitatissimum L.) has been cultivated for around 9,000 years and is therefore one of the oldest cultivated species. Today, flax is still grown for its oil (oil-flax or linseed cultivars) and its cellulose-rich fibres (fibre-flax cultivars) used for high-value linen garments and composite materials. Despite the wide industrial use of flax-derived products, and our actual understanding of the regulation of both wood fibre production and oil biosynthesis more information must be acquired in both domains. Recent advances in genomics are now providing opportunities to improve our fundamental knowledge of these complex processes. In this paper we report the development and validation of a high-density oligo microarray platform dedicated to gene expression analyses in flax. Nine different RNA samples obtained from flax inner- and outer-stems, seeds, leaves and roots were used to generate a collection of 1,066,481 ESTs by massive parallel pyrosequencing. Sequences were assembled into 59,626 unigenes and 48,021 sequences were selected for oligo design and high-density microarray (Nimblegen 385K) fabrication with eight, non-overlapping 25-mers oligos per unigene. 18 independent experiments were used to evaluate the hybridization quality, precision, specificity and accuracy and all results confirmed the high technical quality of our microarray platform. Cross-validation of microarray data was carried out using quantitative qRT-PCR. Nine target genes were selected on the basis of microarray results and reflected the whole range of fold change (both up-regulated and down-regulated genes in different samples). A statistically significant positive correlation was obtained comparing expression levels for each target gene across all biological replicates both in qRT-PCR and microarray results. Further experiments illustrated the capacity of our arrays to detect differential gene expression in a variety of flax tissues as well as between two contrasted flax varieties

  18. Development and validation of a flax (Linum usitatissimum L.) gene expression oligo microarray

    PubMed Central

    2010-01-01

    Background Flax (Linum usitatissimum L.) has been cultivated for around 9,000 years and is therefore one of the oldest cultivated species. Today, flax is still grown for its oil (oil-flax or linseed cultivars) and its cellulose-rich fibres (fibre-flax cultivars) used for high-value linen garments and composite materials. Despite the wide industrial use of flax-derived products, and our actual understanding of the regulation of both wood fibre production and oil biosynthesis more information must be acquired in both domains. Recent advances in genomics are now providing opportunities to improve our fundamental knowledge of these complex processes. In this paper we report the development and validation of a high-density oligo microarray platform dedicated to gene expression analyses in flax. Results Nine different RNA samples obtained from flax inner- and outer-stems, seeds, leaves and roots were used to generate a collection of 1,066,481 ESTs by massive parallel pyrosequencing. Sequences were assembled into 59,626 unigenes and 48,021 sequences were selected for oligo design and high-density microarray (Nimblegen 385K) fabrication with eight, non-overlapping 25-mers oligos per unigene. 18 independent experiments were used to evaluate the hybridization quality, precision, specificity and accuracy and all results confirmed the high technical quality of our microarray platform. Cross-validation of microarray data was carried out using quantitative qRT-PCR. Nine target genes were selected on the basis of microarray results and reflected the whole range of fold change (both up-regulated and down-regulated genes in different samples). A statistically significant positive correlation was obtained comparing expression levels for each target gene across all biological replicates both in qRT-PCR and microarray results. Further experiments illustrated the capacity of our arrays to detect differential gene expression in a variety of flax tissues as well as between two contrasted

  19. Oligonucleotide Microarray Analysis of Dietary-Induced Hyperlipidemia Gene Expression Profiles in Miniature Pigs

    PubMed Central

    Takahashi, Junko; Waki, Shiori; Matsumoto, Rena; Odake, Junji; Miyaji, Takayuki; Tottori, Junichi; Iwanaga, Takehiro; Iwahashi, Hitoshi

    2012-01-01

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

  20. Unique gene expression profile in osteoarthritis synovium compared with cartilage: analysis of publicly accessible microarray datasets.

    PubMed

    Park, Robin; Ji, Jong Dae

    2016-06-01

    The purpose of this study was to identify a gene expression signature in osteoarthritis (OA) synovium and genomic pathways likely to be involved in the pathogenesis of OA. Four publicly accessible microarray studies from synovium of OA patients were integrated, and a transcriptomic and network-based meta-analysis was performed. Based on pathways according to the Kyoto Encyclopedia of Genes and Genomes, functional enrichment analysis was performed. Meta-analysis results of OA synovium were compared to two previously published studies of OA cartilage to determine the relative number of common and specific DEGs of the cartilage and synovium. According to our meta-analysis, a total of 1350 genes were found to be differentially expressed in the synovium of OA patients as compared to that of healthy controls. Pathway analysis found 41 significant pathways in the total DEGs, and 22 and 16 pathways in the upregulated and downregulated DEGs, respectively. Cell adhesion molecules and cytokine-cytokine receptor interaction were the most significant pathway in the upregulated and downregulated DEGs, respectively. Comparison of meta-analysis results of OA synovium with results of two previous studies of OA cartilage identified 85 common genes and 1632 cartilage-specific DEGs and 1265 synovium-specific DEGs in the first study; and 142 common genes, and 856 cartilage-specific DEGs and 1208 synovium-specific DEGs in the second study. Our results show a small overlap between the DEGs of the synovium compared to DEGs of the cartilage, suggesting different pathogenic mechanisms that are specific to the synovium.

  1. Gene profile in the spleen under massive partial hepatectomy using complementary DNA microarray and pathway analysis.

    PubMed

    Arakawa, Yusuke; Shimada, Mitsuo; Utsunomiya, Tohru; Imura, Satoru; Morine, Yuji; Ikemoto, Tetsuya; Mori, Hiroki; Kanamoto, Mami; Iwahashi, Shuichi; Saito, Yu; Takasu, Chie

    2014-08-01

    In general, the spleen is one of the abdominal organs connected by the portal system, and a splenectomy improves hepatic functions in the settings of partial hepatectomy (Hx) for portal hypertensive cases or living donor liver transplantation with excessive portal vein flow. Those precise mechanisms remain still unclear; therefore, we investigated the DNA expression profile in the spleen after 90% Hx in rats using complementary DNA microarray and pathway analysis. Messenger RNAs (mRNAs) were prepared from three rat spleens at each time point (0, 3, and 6 h after 90% Hx). Using the gene chip, mRNA was hybridized to Affymetrix GeneChip Rat Genome 230 2.0 Array (Affymetrix®) and pathway analysis was done with Ingenuity Pathway Analysis (IPA®). We determined the 3-h or 6-h/0-h ratio to assess the influence of Hx, and cut-off values were set at more than 2.0-fold or less than 1/2 (0.5)-fold. Chemokine activity-related genes including Cxcl1 (GRO1) and Cxcl2 (MIP-2) related pathway were upregulated in the spleen. Also, immediate early response genes including early growth response-1 (EGR1), FBJ murine osteosarcoma (FOS) and activating transcription factor 3 (ATF3) related pathway were upregulated in the spleen. We concluded that in the spleen the expression of numerous inflammatory-related genes would occur after 90% Hx. The spleen could take a harmful role and provide a negative impact during post Hx phase due to the induction of chemokine and transcription factors including GRO1 and EGR1. © 2014 Journal of Gastroenterology and Hepatology Foundation and Wiley Publishing Asia Pty Ltd.

  2. Interpreting the gene expression microarray results: a user-based experience.

    PubMed

    Melissari, Erika; Di Russo, Manuela; Mariotti, Veronica; Righi, Marco; Iofrida, Caterina; Pellegrini, Silvia

    2013-06-01

    In recent years many tools have been developed to cope with the interpretation of gene expression results from microarray experiments. The effectiveness of these tools largely depends on their ease of use by biomedical researchers. Tools based on effective computational methods, indeed, cannot be fully exploited by users if they are not supported by an intuitive interface, a large set of utilities and effective outputs. In this paper, 10 tools for the interpretation of gene expression microarray results have been tested on 11 microarray datasets and evaluated according to eight assessment criteria: 1. interface design and usability, 2. easiness of input submission, 3. effectiveness of output representation and 4. of the downloaded outputs, 5. possibility to submit multiple gene IDs, 6. sources of information, 7. provision of different statistical tests and 8. of multiple test correction methods. Strengths and weaknesses of each tool are highlighted to: a. provide useful tips to users dealing with the biological interpretation of microarray results; b. draw the attention of software developers on the usability of their tools.

  3. A comparative analytical assay of gene regulatory networks inferred using microarray and RNA-seq datasets

    PubMed Central

    Izadi, Fereshteh; Zarrini, Hamid Najafi; Kiani, Ghaffar; Jelodar, Nadali Babaeian

    2016-01-01

    A Gene Regulatory Network (GRN) is a collection of interactions between molecular regulators and their targets in cells governing gene expression level. Omics data explosion generated from high-throughput genomic assays such as microarray and RNA-Seq technologies and the emergence of a number of pre-processing methods demands suitable guidelines to determine the impact of transcript data platforms and normalization procedures on describing associations in GRNs. In this study exploiting publically available microarray and RNA-Seq datasets and a gold standard of transcriptional interactions in Arabidopsis, we performed a comparison between six GRNs derived by RNA-Seq and microarray data and different normalization procedures. As a result we observed that compared algorithms were highly data-specific and Networks reconstructed by RNA-Seq data revealed a considerable accuracy against corresponding networks captured by microarrays. Topological analysis showed that GRNs inferred from two platforms were similar in several of topological features although we observed more connectivity in RNA-Seq derived genes network. Taken together transcriptional regulatory networks obtained by Robust Multiarray Averaging (RMA) and Variance-Stabilizing Transformed (VST) normalized data demonstrated predicting higher rate of true edges over the rest of methods used in this comparison. PMID:28293077

  4. A Comparison of Fuzzy Clustering Approaches for Quantification of Microarray Gene Expression

    PubMed Central

    WANG, YU-PING; GUNAMPALLY, MAHESWAR; CHEN, JIE; BITTEL, DOUGLAS; BUTLER, MERLIN G.; CAI, WEI-WEN

    2016-01-01

    Despite the widespread application of microarray imaging for biomedical imaging research, barriers still exist regarding its reliability for clinical use. A critical major problem lies in accurate spot segmentation and the quantification of gene expression level (mRNA) from the microarray images. A variety of commercial and research freeware packages are available, but most cannot handle array spots with complex shapes such as donuts and scratches. Clustering approaches such as k-means and mixture models were introduced to overcome this difficulty, which use the hard labeling of each pixel. In this paper, we apply fuzzy clustering approaches for spot segmentation, which provides soft labeling of the pixel. We compare several fuzzy clustering approaches for microarray analysis and provide a comprehensive study of these approaches for spot segmentation. We show that possiblistic c-means clustering (PCM) provides the best performance in terms of stability criterion when testing on both a variety of simulated and real microarray images. In addition, we compared three statistical criteria in measuring gene expression levels and show that a new asymptotically unbiased statistic is able to quantify the gene expression level more accurately. PMID:28163819

  5. Alternations in genes expression of pathway signaling in esophageal tissue with atresia: results of expression microarray profiling.

    PubMed

    Smigiel, R; Lebioda, A; Blaszczyński, M; Korecka, K; Czauderna, P; Korlacki, W; Jakubiak, A; Bednarczyk, D; Maciejewski, H; Wizinska, P; Sasiadek, M M; Patkowski, D

    2015-04-01

    Esophageal atresia (EA) is a congenital defect of the esophagus involving the interruption of the esophagus with or without connection to the trachea (tracheoesophageal fistula [TEF]). EA/TEF may occur as an isolated anomaly, may be part of a complex of congenital defects (syndromic), or may develop within the context of a known syndrome or association. The molecular mechanisms underlying the development of EA are poorly understood. It is supposed that a combination of multigenic factors and epigenetic modification of genes play a role in its etiology. The aim of our work was to assess the human gene expression microarray study in esophageal tissue samples. Total RNA was extracted from 26 lower pouches of esophageal tissue collected during thoracoscopic EA repair in neonates with the isolated (IEA) and the syndromic form (SEA). We identified 787 downregulated and 841 upregulated transcripts between SEA and controls, and about 817 downregulated and 765 upregulated probes between IEA and controls. Fifty percent of these genes showed differential expression specific for either IEA or SEA. Functional pathway analysis revealed substantial enrichment for Wnt and Sonic hedgehog, as well as cytokine and chemokine signaling pathways. Moreover, we performed reverse transcription polymerase chain reaction study in a group of SHH and Wnt pathways genes with differential expression in microarray profiling to confirm the microarray expression results. We verified the altered expression in SFRP2 gene from the Wnt pathway as well as SHH, GLI1, GLI2, and GLI3 from the Sonic hedgehog pathway. The results suggest an important role of these pathways and genes for EA/TEF etiology. © 2014 International Society for Diseases of the Esophagus.

  6. Single exon-resolution targeted chromosomal microarray analysis of known and candidate intellectual disability genes

    PubMed Central

    Tucker, Tracy; Zahir, Farah R; Griffith, Malachi; Delaney, Allen; Chai, David; Tsang, Erica; Lemyre, Emmanuelle; Dobrzeniecka, Sylvia; Marra, Marco; Eydoux, Patrice; Langlois, Sylvie; Hamdan, Fadi F; Michaud, Jacques L; Friedman, Jan M

    2014-01-01

    Intellectual disability affects about 3% of individuals globally, with∼50% idiopathic. We designed an exonic-resolution array targeting all known submicroscopic chromosomal intellectual disability syndrome loci, causative genes for intellectual disability, and potential candidate genes, all genes encoding glutamate receptors and epigenetic regulators. Using this platform, we performed chromosomal microarray analysis on 165 intellectual disability trios (affected child and both normal parents). We identified and independently validated 36 de novo copy-number changes in 32 trios. In all, 67% of the validated events were intragenic, involving only exon 1 (which includes the promoter sequence according to our design), exon 1 and adjacent exons, or one or more exons excluding exon 1. Seventeen of the 36 copy-number variants involve genes known to cause intellectual disability. Eleven of these, including seven intragenic variants, are clearly pathogenic (involving STXBP1, SHANK3 (3 patients), IL1RAPL1, UBE2A, NRXN1, MEF2C, CHD7, 15q24 and 9p24 microdeletion), two are likely pathogenic (PI4KA, DCX), two are unlikely to be pathogenic (GRIK2, FREM2), and two are unclear (ARID1B, 15q22 microdeletion). Twelve individuals with genomic imbalances identified by our array were tested with a clinical microarray, and six had a normal result. We identified de novo copy-number variants within genes not previously implicated in intellectual disability and uncovered pathogenic variation of known intellectual disability genes below the detection limit of standard clinical diagnostic chromosomal microarray analysis. PMID:24253858

  7. Single exon-resolution targeted chromosomal microarray analysis of known and candidate intellectual disability genes.

    PubMed

    Tucker, Tracy; Zahir, Farah R; Griffith, Malachi; Delaney, Allen; Chai, David; Tsang, Erica; Lemyre, Emmanuelle; Dobrzeniecka, Sylvia; Marra, Marco; Eydoux, Patrice; Langlois, Sylvie; Hamdan, Fadi F; Michaud, Jacques L; Friedman, Jan M

    2014-06-01

    Intellectual disability affects about 3% of individuals globally, with∼50% idiopathic. We designed an exonic-resolution array targeting all known submicroscopic chromosomal intellectual disability syndrome loci, causative genes for intellectual disability, and potential candidate genes, all genes encoding glutamate receptors and epigenetic regulators. Using this platform, we performed chromosomal microarray analysis on 165 intellectual disability trios (affected child and both normal parents). We identified and independently validated 36 de novo copy-number changes in 32 trios. In all, 67% of the validated events were intragenic, involving only exon 1 (which includes the promoter sequence according to our design), exon 1 and adjacent exons, or one or more exons excluding exon 1. Seventeen of the 36 copy-number variants involve genes known to cause intellectual disability. Eleven of these, including seven intragenic variants, are clearly pathogenic (involving STXBP1, SHANK3 (3 patients), IL1RAPL1, UBE2A, NRXN1, MEF2C, CHD7, 15q24 and 9p24 microdeletion), two are likely pathogenic (PI4KA, DCX), two are unlikely to be pathogenic (GRIK2, FREM2), and two are unclear (ARID1B, 15q22 microdeletion). Twelve individuals with genomic imbalances identified by our array were tested with a clinical microarray, and six had a normal result. We identified de novo copy-number variants within genes not previously implicated in intellectual disability and uncovered pathogenic variation of known intellectual disability genes below the detection limit of standard clinical diagnostic chromosomal microarray analysis.

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

    PubMed

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

    2013-01-01

    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). 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. 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 priorities, detect disease outbreaks, and evaluate control programs.

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

    PubMed Central

    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

  10. Microarray profile of differentially expressed genes in a monkey model of allergic asthma

    PubMed Central

    Zou, Jun; Young, Simon; Zhu, Feng; Gheyas, Ferdous; Skeans, Susan; Wan, Yuntao; Wang, Luquan; Ding, Wei; Billah, Motasim; McClanahan, Terri; Coffman, Robert L; Egan, Robert; Umland, Shelby

    2002-01-01

    Background Inhalation of Ascaris suum antigen by allergic monkeys causes an immediate bronchoconstriction and delayed allergic reaction, including a pulmonary inflammatory infiltrate. To identify genes involved in this process, the gene-expression pattern of allergic monkey lungs was profiled by microarrays. Monkeys were challenged by inhalation of A. suum antigen or given interleukin-4 (IL-4) treatment; lung tissue was collected at 4, 18 or 24 h after antigen challenge or 24 h after IL-4. Each challenged monkey lung was compared to a pool of normal, unchallenged monkey lungs. Results Of the approximately 40,000 cDNAs represented on the microarray, expression levels of 169 changed by more than 2.5-fold in at least one of the pairwise probe comparisons; these cDNAs encoded 149 genes, of which two thirds are known genes. The largest number of regulated genes was observed 4 h after challenge. Confirmation of differential expression in the original tissue was obtained for 95% of a set of these genes using real-time PCR. Cluster analysis revealed at least five groups of genes with unique expression patterns. One cluster contained genes for several chemokine mediators including eotaxin, PARC, MCP-1 and MCP-3. Genes involved in tissue remodeling and antioxidant responses were also identified as regulated by antigen and IL-4 or by antigen only. Conclusion This study provides a large-scale profile of gene expression in the primate lung following allergen or IL-4 challenge. It shows that microarrays, with real-time PCR, are a powerful tool for identifying and validating differentially expressed genes in a disease model. PMID:12049661

  11. Type I interferon related genes are common genes on the early stage after vaccination by meta-analysis of microarray data.

    PubMed

    Zhang, Junnan; Shao, Jie; Wu, Xing; Mao, Qunying; Wang, Yiping; Gao, Fan; Kong, Wei; Liang, Zhenglun

    2015-01-01

    The objective of this study was to find common immune mechanism across different kinds of vaccines. A meta-analysis of microarray datasets was performed using publicly available microarray Gene Expression Omnibus (GEO) and Array Express data sets of vaccination records. Seven studies (out of 35) were selected for this meta-analysis. A total of 447 chips (145 pre-vaccination and 302 post-vaccination) were included. Significance analysis of microarrays (SAM) program was used for screening differentially expressed genes (DEGs). Functional pathway enrichment for the DEGs was conducted in DAVID Gene Ontology (GO) database. Twenty DEGs were identified, of which 10 up-regulated genes involved immune response. Six of which were type I interferon (IFN) related genes, including LY6E, MX1, OAS3, IFI44L, IFI6 and IFITM3. Ten down-regulated genes mainly mediated negative regulation of cell proliferation and cell motion. Results of a subgroup analysis showed that although the kinds of genes varied widely between days 3 and 7 post vaccination, the pathways between them are basically the same, such as immune response and response to viruses, etc. For an independent verification of these 6 type I IFN related genes, peripheral blood mononuclear cells (PBMCs) were collected at baseline and day 3 after the vaccination from 8 Enterovirus 71(EV71) vaccinees and were assayed by RT-PCR. Results showed that the 6 DEGs were also upregulated in EV71 vaccinees. In summary, meta-analysis methods were used to explore the immune mechanism of vaccines and results indicated that the type I IFN related genes and corresponding pathways were common in early immune responses for different kinds of vaccines.

  12. Fusarium verticillioides gene expression profiling by microarray analysis

    USDA-ARS?s Scientific Manuscript database

    Fusarium verticillioides is a pathogen of maize and it can produce the toxic polyketide derived secondary metabolites called fumonisins. Fumonisins have been shown to cause animal diseases and are epidemiologically correlated to esophageal cancer and neural tube defects in humans. The genes necess...

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

    PubMed

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

    2011-12-01

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

  14. Differential gene expression in recombinant Pichia pastoris analysed by heterologous DNA microarray hybridisation

    PubMed Central

    Sauer, Michael; Branduardi, Paola; Gasser, Brigitte; Valli, Minoska; Maurer, Michael; Porro, Danilo; Mattanovich, Diethard

    2004-01-01

    Background Pichia pastoris is a well established yeast host for heterologous protein expression, however, the physiological and genetic information about this yeast remains scanty. The lack of a published genome sequence renders DNA arrays unavailable, thereby hampering more global investigations of P. pastoris from the beginning. Here, we examine the suitability of Saccharomyces cerevisiae DNA microarrays for heterologous hybridisation with P. pastoris cDNA. Results We could show that it is possible to obtain new and valuable information about transcriptomic regulation in P. pastoris by probing S. cerevisiae DNA microarrays. The number of positive signals was about 66 % as compared to homologous S. cerevisiae hybridisation, and both the signal intensities and gene regulations correlated with high significance between data obtained from P. pastoris and S. cerevisiae samples. The differential gene expression patterns upon shift from glycerol to methanol as carbon source were investigated in more detail. Downregulation of TCA cycle genes and a decrease of genes related to ribonucleotide and ribosome synthesis were among the major effects identified. Conclusions We could successfully demonstrate that heterologous microarray hybridisations allow deep insights into the transcriptomic regulation processes of P. pastoris. The observed downregulation of TCA cycle and ribosomal synthesis genes correlates to a significantly lower specific growth rate during the methanol feed phase. PMID:15610561

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

    PubMed

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

    2016-01-01

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

  16. Microarray analysis of Ewing's sarcoma family of tumours reveals characteristic gene expression signatures associated with metastasis and resistance to chemotherapy.

    PubMed

    Schaefer, Karl-Ludwig; Eisenacher, Martin; Braun, Yvonne; Brachwitz, Kristin; Wai, Daniel H; Dirksen, Uta; Lanvers-Kaminsky, Claudia; Juergens, Heribert; Herrero, David; Stegmaier, Sabine; Koscielniak, Ewa; Eggert, Angelika; Nathrath, Michaela; Gosheger, Georg; Schneider, Dominik T; Bury, Carsten; Diallo-Danebrock, Raihanatou; Ottaviano, Laura; Gabbert, Helmut E; Poremba, Christopher

    2008-03-01

    In Ewing's sarcoma family of tumours (ESFT), the clinically most adverse prognostic parameters are the presence of tumour metastasis at time of diagnosis and poor response to neoadjuvant chemotherapy. To identify genes differentially regulated between metastatic and localised tumours, we analysed 27 ESFT specimens using Affymetrix microarrays. Functional annotation of differentially regulated genes revealed 29 over-represented pathways including PDGF, TP53, NOTCH, and WNT1-signalling. Regression of primary tumours (n=20) induced by polychemotherapy was found to be correlated with the expression of genes involved in angiogenesis, apoptosis, ubiquitin proteasome pathway, and PI3 kinase and p53 pathways. These findings could be confirmed by in vitro cytotoxicity assays. A set of 46 marker genes correctly classifies these 20 tumours as responding versus non-responding. We conclude that expression signatures of initial tumour biopsies can help to identify ESFT patients at high risk to develop tumour metastasis or to suffer from a therapy refractory cancer.

  17. Global gene expression profiling of dimethylnitrosamine-induced liver fibrosis: from pathological and biochemical data to microarray analysis.

    PubMed

    Su, Li-Jen; Hsu, Shih-Lan; Yang, Jyh-Shyue; Tseng, Huei-Hun; Huang, Shiu-Feng; Huang, Chi-Ying F

    2006-01-01

    The development of hepatocellular carcinoma (HCC) is generally preceded by cirrhosis, which occurs at the end stage of fibrosis. This is a common and potentially lethal problem of chronic liver disease in Asia. The development of microarrays permits us to monitor transcriptomes on a genome-wide scale; this has dramatically speeded up a comprehensive understanding of the disease process. Here we used dimethylnitrosamine (DMN), a nongenotoxic hepatotoxin, to induce rat necroinflammatory and hepatic fibrosis. During the 6-week time course, histopathological, biochemical, and quantitative RT-PCR analyses confirmed the incidence of necroinflammatory and hepatic fibrosis in this established rat model system. Using the Affymetrix microarray chip, 256 differentially expressed genes were identified from the liver injury samples. Hierarchical clustering of gene expression using a gene ontology database allowed the identification of several stage-specific characters and functionally related clusters that encode proteins related to metabolism, cell growth/maintenance, and response to external challenge. Among these genes, we classified 44 potential necroinflammatory-related genes and 62 potential fibrosis-related markers or drug targets based on histopathological scores. We also compared the results with other data on well-known markers and various other microarray datasets that are available. In conclusion, we believe that the molecular picture of necroinflammatory and hepatic fibrosis from this study may provide novel biological insights into the development of early liver damage molecular classifiers than can be used for basic research and in clinical applications. A public accessible website is available at http://LiverFibrosis.nchc.org.tw:8080/LF.

  18. Development of a microarray chip for gene expression in rabbit ocular research.

    PubMed

    Popp, Michael P; Liu, Li; Timmers, Adrian; Esson, Douglas W; Shiroma, Lineu; Meyers, Craig; Berceli, Scott; Tao, Ming; Wistow, Graeme; Schultz, Gregory S; Sherwood, Mark B

    2007-02-02

    To develop a microarray for the rabbit that can be used for ocular gene expression research. Messenger RNA was isolated from anterior segment tissues (cornea, conjunctiva, and iris) and posterior segment tissues (lens, retina, and sclera) of rabbit eyes and used to create two independent cDNA libraries through the NEIBank project. Clones from each of these libraries were sequenced from both the 5' and 3' ends. These sequences and those from the National Center for Biotechnology Information (NCBI) taxonomy database for rabbit were combined and electronically assembled into a set of unique nonoverlapping continuous sequences (contigs). For each contig, a homology search was performed using BLASTX and BLASTN against both the NCBI NR and NT databases to provide gene annotation. Unique contigs were sent to Agilent Technologies, where 60 base oligonucleotide probes were designed and synthesized, in situ, on two different arrays in an 8 array x 1900 element format. Glaucoma filtration surgery was performed on one eye of six rabbits. After 14 days, tissue was harvested from the conjunctiva and Tenon's capsule of both the surgically treated and untreated control eyes. Total RNA from each sample was labeled with cyanine dyes and hybridized to our custom microarrays. Of the 3,154 total probes present on the two arrays, 2,522 had a signal value above the background. The expression of 315 genes was significantly altered by glaucoma filtration surgery. Genes whose expression was altered included proteins associated with inflammatory response, defense response, and proteins involved in synthesis of the extracellular matrix. The results of this rabbit microarray study are consistent with those from other wound healing studies, indicating that this array can provide valid information on broad patterns of gene expression. This is the first microarray available for rabbit studies and is a valuable tool that can be used to study molecular events in the eye.

  19. Chromatin immunoprecipitation microarrays for identification of genes silenced by histone H3 lysine 9 methylation.

    PubMed

    Kondo, Yutaka; Shen, Lanlan; Yan, Pearlly S; Huang, Tim Hui-Ming; Issa, Jean-Pierre J

    2004-05-11

    Switching from acetylation to methylation at histone H3 lysine 9 (K9) has recently been shown to contribute to euchromatin gene silencing. To identify genes silenced by K9 modifications, we probed a human CpG island microarray with DNA obtained by chromatin immunoprecipitation (ChIP) in a cancer cell line using an anti-H3-K9 methylated antibody or an anti-H3-K9 acetylated antibody. Of the 27 clones with the highest signal ratio of K9 methylation over acetylation (Me/Ac), 13 contained repetitive sequences. Among 14 nonrepetitive clones, we identified 11 genes (seven known and four previously undescribed), one EST, and two unknown fragments. Using ChIP-PCR, all 18 examined clones showed higher ratios of H3-K9 Me/Ac than the active gene control, P21, thus confirming the microarray data. In addition, we found a strong correlation between the K9 Me/Ac ratio and CpG island DNA methylation (R = 0.92, P < 0.01), and five of seven genes examined (megalin, thrombospondin-4, KR18, latrophilin-3, and phosphatidylinositol-3-OH kinase P101 subunit) showed lack of expression by RT-PCR and reactivation by DNA methylation and/or histone deacetylase inhibition, suggesting that these genes are true targets of silencing through histone modifications. All five genes also showed significant DNA methylation in a cell line panel and in primary colon cancers. Our data suggest that CpG island microarray coupled with ChIP can identify novel targets of gene silencing in cancer. This unbiased approach confirms the tight coupling between DNA methylation and histone modifications in cancer and could be used to probe gene silencing in nonneoplastic conditions as well.

  20. Verification of gene expression profiles for colorectal cancer using 12 internet public microarray datasets

    PubMed Central

    Chang, Yu-Tien; Yao, Chung-Tay; Su, Sui-Lung; Chou, Yu-Ching; Chu, Chi-Ming; Huang, Chi-Shuan; Terng, Harn-Jing; Chou, Hsiu-Ling; Wetter, Thomas; Chen, Kang-Hua; Chang, Chi-Wen; Shih, Yun-Wen; Lai, Ching-Huang

    2014-01-01

    AIM: To verify gene expression profiles for colorectal cancer using 12 internet public microarray datasets. METHODS: Logistic regression analysis was performed, and odds ratios for each gene were determined between colorectal cancer (CRC) and controls. Twelve public microarray datasets of GSE 4107, 4183, 8671, 9348, 10961, 13067, 13294, 13471, 14333, 15960, 17538, and 18105, which included 519 cases of adenocarcinoma and 88 normal mucosa controls, were pooled and used to verify 17 selective genes from 3 published studies and estimate the external generality. RESULTS: We validated the 17 CRC-associated genes from studies by Chang et al (Model 1: 5 genes), Marshall et al (Model 2: 7 genes) and Han et al (Model 3: 5 genes) and performed the multivariate logistic regression analysis using the pooled 12 public microarray datasets as well as the external validation. The goodness-of-fit test of Hosmer-Lemeshow (H-L) showed statistical significance (P = 0.044) for Model 2 of Marshall et al in which observed event rates did not match expected event rates in subgroups of the model population. Expected and observed event rates in subgroups were similar, which are called well calibrated, in Models 1, 3 and 4 with non-significant P values of 0.460, 0.194 and 1.000 for H-L tests, respectively. A 7-gene model of CPEB4, EIF2S3, MGC20553, MS4A1, ANXA3, TNFAIP6 and IL2RB was pairwise selected, which showed the best results in logistic regression analysis (H-L P = 1.000, R2 = 0.951, areas under the curve = 0.999, accuracy = 0.968, specificity = 0.966 and sensitivity = 0.994). CONCLUSION: A novel gene expression profile was associated with CRC and can potentially be applied to blood-based detection assays. PMID:25516661

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

    PubMed Central

    Dheilly, Nolwenn M.; Lelong, Christophe; Huvet, Arnaud; Kellner, Kristell; Dubos, Marie-Pierre; Riviere, Guillaume; Boudry, Pierre; Favrel, Pascal

    2012-01-01

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

  2. Microarrays in the 2010s: the contribution of microarray-based gene expression profiling to breast cancer classification, prognostication and prediction

    PubMed Central

    2011-01-01

    Breast cancer comprises a collection of diseases with distinctive clinical, histopathological, and molecular features. Importantly, tumors with similar histological features may display disparate clinical behaviors. Gene expression profiling using microarray technologies has improved our understanding of breast cancer biology and has led to the development of a breast cancer molecular taxonomy and of multigene 'signatures' to predict outcome and response to systemic therapies. The use of these prognostic and predictive signatures in routine clinical decision-making remains controversial. Here, we review the clinical relevance of microarray-based profiling of breast cancer and discuss its impact on patient management. PMID:21787441

  3. Transcriptome-Wide High-Density Microarray Analysis Reveals Differential Gene Transcription in Periprosthetic Tissue From Hips With Chronic Periprosthetic Joint Infection vs Aseptic Loosening.

    PubMed

    Omar, Mohamed; Klawonn, Frank; Brand, Stephan; Stiesch, Meike; Krettek, Christian; Eberhard, Jörg

    2017-01-01

    Differentiating between periprosthetic hip infection and aseptic hip prosthesis loosening can be challenging, especially in patients with chronic infections. This study used whole-genome microarray analysis to investigate the transcriptomes of periprosthetic hip tissues to identify genes that are differentially transcripted between chronic periprosthetic hip infection and aseptic hip prosthesis loosening. In this pilot study, a total of 24 patients with either chronic periprosthetic hip infection (n = 12) or aseptic hip prosthesis loosening (n = 12) were analyzed. Periprosthetic hip infection was diagnosed based on modified criteria of the Musculoskeletal Infection Society. To evaluate differences in gene transcription, whole-genome microarray analysis was performed on the mRNA of periprosthetic tissue. Microarray analysis revealed differential gene transcription in periprosthetic hip tissue affected by chronic hip infection vs aseptic hip prosthesis loosening. A total of 39 genes had area under the curve values greater than 0.9 for diagnosing chronic periprosthetic hip infection; 5 genes had annotations relevant to infection and metabolism. The 39 genes also included 7 genes that were differentially transcribed but that have no apparent connection to immune response processes plus 27 genes with unknown function. Differences in gene transcription profiles might represent novel diagnostic targets that can be used to differentiate between chronic periprosthetic hip infections and aseptic hip prosthesis loosening. Secondary metabolites of differentially transcripted genes might serve as easily accessible markers for detecting chronic periprosthetic joint infection in future. Copyright © 2016 Elsevier Inc. All rights reserved.

  4. Transfection microarrays for high-throughput phenotypic screening of genes involved in cell migration.

    PubMed

    Onuki-Nagasaki, Reiko; Nagasaki, Akira; Hakamada, Kazumi; Uyeda, Taro Q P; Fujita, Satoshi; Miyake, Masato; Miyake, Jun

    2010-01-01

    Cell migration is important in several biological phenomena, such as cancer metastasis. Therefore, the identification of genes involved in cell migration might facilitate the discovery of antimetastatic drugs. However, screening of genes by the current methods can be complicated by factors related to cell stimulation, for example, abolition of contact inhibition and the release inflammatory cytokines from wounded cells during examinations of wound healing in vitro. To overcome these problems and identify genes involved in cell migration, in this chapter we describe the use of transfection microarrays for high-throughput phenotypic screening.

  5. Quantitative Monitoring of Gene Expression Patterns with a Complementary DNA Microarray

    NASA Astrophysics Data System (ADS)

    Schena, Mark; Shalon, Dari; Davis, Ronald W.; Brown, Patrick O.

    1995-10-01

    A high-capacity system was developed to monitor the expression of many genes in parallel. Microarrays prepared by high-speed robotic printing of complementary DNAs on glass were used for quantitative expression measurements of the corresponding genes. Because of the small format and high density of the arrays, hybridization volumes of 2 microliters could be used that enabled detection of rare transcripts in probe mixtures derived from 2 micrograms of total cellular messenger RNA. Differential expression measurements of 45 Arabidopsis genes were made by means of simultaneous, two-color fluorescence hybridization.

  6. Comparison and Validation of Putative Pathogenicity-Related Genes Identified by T-DNA Insertional Mutagenesis and Microarray Expression Profiling in Magnaporthe oryzae

    PubMed Central

    Wáng, Ying; Tan, Qi; Gao, Ying Nv; Li, Yan

    2017-01-01

    High-throughput technologies of functional genomics such as T-DNA insertional mutagenesis and microarray expression profiling have been employed to identify genes related to pathogenicity in Magnaporthe oryzae. However, validation of the functions of individual genes identified by these high-throughput approaches is laborious. In this study, we compared two published lists of genes putatively related to pathogenicity in M. oryzae identified by T-DNA insertional mutagenesis (comprising 1024 genes) and microarray expression profiling (comprising 236 genes), respectively, and then validated the functions of some overlapped genes between the two lists by knocking them out using the method of target gene replacement. Surprisingly, only 13 genes were overlapped between the two lists, and none of the four genes selected from the overlapped genes exhibited visible phenotypic changes on vegetative growth, asexual reproduction, and infection ability in their knockout mutants. Our results suggest that both of the lists might contain large proportions of unrelated genes to pathogenicity and therefore comparing the two gene lists is hardly helpful for the identification of genes that are more likely to be involved in pathogenicity as we initially expected. PMID:28286772

  7. Comparison and Validation of Putative Pathogenicity-Related Genes Identified by T-DNA Insertional Mutagenesis and Microarray Expression Profiling in Magnaporthe oryzae.

    PubMed

    Wang, Ying; Wáng, Ying; Tan, Qi; Gao, Ying Nv; Li, Yan; Bao, Da Peng

    2017-01-01

    High-throughput technologies of functional genomics such as T-DNA insertional mutagenesis and microarray expression profiling have been employed to identify genes related to pathogenicity in Magnaporthe oryzae. However, validation of the functions of individual genes identified by these high-throughput approaches is laborious. In this study, we compared two published lists of genes putatively related to pathogenicity in M. oryzae identified by T-DNA insertional mutagenesis (comprising 1024 genes) and microarray expression profiling (comprising 236 genes), respectively, and then validated the functions of some overlapped genes between the two lists by knocking them out using the method of target gene replacement. Surprisingly, only 13 genes were overlapped between the two lists, and none of the four genes selected from the overlapped genes exhibited visible phenotypic changes on vegetative growth, asexual reproduction, and infection ability in their knockout mutants. Our results suggest that both of the lists might contain large proportions of unrelated genes to pathogenicity and therefore comparing the two gene lists is hardly helpful for the identification of genes that are more likely to be involved in pathogenicity as we initially expected.

  8. Identification of differentially expressed genes in cutaneous squamous cell carcinoma by microarray expression profiling

    PubMed Central

    Nindl, Ingo; Dang, Chantip; Forschner, Tobias; Kuban, Ralf J; Meyer, Thomas; Sterry, Wolfram; Stockfleth, Eggert

    2006-01-01

    Background Carcinogenesis is a multi-step process indicated by several genes up- or down-regulated during tumor progression. This study examined and identified differentially expressed genes in cutaneous squamous cell carcinoma (SCC). Results Three different biopsies of 5 immunosuppressed organ-transplanted recipients each normal skin (all were pooled), actinic keratosis (AK) (two were pooled), and invasive SCC and additionally 5 normal skin tissues from immunocompetent patients were analyzed. Thus, total RNA of 15 specimens were used for hybridization with Affymetrix HG-U133A microarray technology containing 22,283 genes. Data analyses were performed by prediction analysis of microarrays using nearest shrunken centroids with the threshold 3.5 and ANOVA analysis was independently performed in order to identify differentially expressed genes (p < 0.05). Verification of 13 up- or down-regulated genes was performed by quantitative real-time reverse transcription (RT)-PCR and genes were additionally confirmed by sequencing. Broad coherent patterns in normal skin vs. AK and SCC were observed for 118 genes. Conclusion The majority of identified differentially expressed genes in cutaneous SCC were previously not described. PMID:16893473

  9. Microarray expression profiling identifies genes with altered expression in HDL-deficient mice

    SciTech Connect

    Callow, Matthew J.; Dudoit, Sandrine; Gong, Elaine L.; Speed, Terence P.; Rubin, Edward M.

    2000-05-05

    Based on the assumption that severe alterations in the expression of genes known to be involved in HDL metabolism may affect the expression of other genes we screened an array of over 5000 mouse expressed sequence tags (ESTs) for altered gene expression in the livers of two lines of mice with dramatic decreases in HDL plasma concentrations. Labeled cDNA from livers of apolipoprotein AI (apo AI) knockout mice, Scavenger Receptor BI (SR-BI) transgenic mice and control mice were co-hybridized to microarrays. Two-sample t-statistics were used to identify genes with altered expression levels in the knockout or transgenic mice compared with the control mice. In the SR-BI group we found 9 array elements representing at least 5 genes to be significantly altered on the basis of an adjusted p value of less than 0.05. In the apo AI knockout group 8 array elements representing 4 genes were altered compared with the control group (p < 0.05). Several of the genes identified in the SR-BI transgenic suggest altered sterol metabolism and oxidative processes. These studies illustrate the use of multiple-testing methods for the identification of genes with altered expression in replicated microarray experiments of apo AI knockout and SR-BI transgenic mice.

  10. Differential gene expression profiling of vocal fold polyps and Reinke's edema by complementary DNA microarray.

    PubMed

    Duflo, Suzy M; Thibeault, Susan L; Li, Wenhua; Smith, Marshall E; Schade, Goetz; Hess, Markus M

    2006-09-01

    Our purpose was to determine whether complementary DNA (cDNA) microarray analysis (MA) can establish distinct gene expression profiles for 2 phenotypically similar vocal fold lesions: Reinke's edema (RE) and polyps. Established transcript profiles can provide insight into the molecular and cellular processes involved in these diseases. Eleven RE specimens and 17 polyps were analyzed with MA for 8,745 genes. Further MA profiling was attempted within each lesion group to identify molecular markers for reflux exposure and smoking. Prediction analysis was used to predict lesion classification for 2 unclassified samples. A real-time polymerase chain reaction was performed to corroborate MA transcript levels for selected significant genes. Sixty-five genes were found to differentiate RE and polyps (p = .0088). For RE, 19 genes were differentiated for reflux exposure (p = .016). No genes were found to differentiate smokers from nonsmokers. For polyps, no genes were found to differentiate for reflux (p = .16) and smoking (p = .565). Categorization of unclassified lesions was possible with a minimum of 13 genes. We demonstrate the feasibility of benign lesion classification based on MA. Microarray analysis is useful not only for improving diagnosis and classification of such lesions, but also for potentially generating prognostic indicators and targets for therapy.

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

    PubMed

    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.

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

    PubMed Central

    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. PMID:25961028

  13. Microarray gene expression analysis of the human airway in patients exposed to sulfur mustard.

    PubMed

    Najafi, Ali; Masoudi-Nejad, Ali; Imani Fooladi, Abbas Ali; Ghanei, Mostafa; Nourani, Mohamad Reza

    2014-08-01

    There is much data about the acute effects of sulfur mustard gas on humans, animals and cells. But less is known regarding the molecular basics of chronic complications in humans. Basically, mustard gas, as an alkylating agent, causes several chronic problems in the eyes, skin and more importantly in the pulmonary system which is the main cause of death. Although recent proteomic research has been carried out on bronchoalveolar lavage (BAL) and serum, but high-throughput transcriptomics have not yet been applied to chronic airway remodeling. This is the first cDNA-microarray report on the chronic human mustard lung disease, 25 years after exposure during the Iran-Iraq war. Microarray transcriptional profiling indicated that a total of 122 genes were significantly dysregulated in tissues located in the airway of patients. These genes are associated with the extracellular matrix components, apoptosis, stress response, inflammation and mucus secretion.

  14. Use of microarray technology to profile gene expression patterns important for reproduction in cattle.

    PubMed

    Evans, A C O; Forde, N; O'Gorman, G M; Zielak, A E; Lonergan, P; Fair, T

    2008-07-01

    Fertility in cattle is a major component of many agricultural enterprises and there is pressure to devise methods to improve this. A number of approaches are ongoing, one of which is to better understand the cellular and molecular events of the development of reproductive tissues and to use these as targets for developing new strategies. Microarray technologies now allow us the potential to determine the transcriptional profile of expressed genes in a given tissue. This review focuses on the types of microarrays available for studies in cattle and concludes that genes associated with one or more of the cellular processes of cell survival/death, intracellular signalling, transcription and translation, cell division and proliferation and cellular metabolism are the main transcriptional pathways that control the development of ovarian follicles, oocytes, early embryos and the uterine endometrium about the time of the establishment of pregnancy.

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

    PubMed Central

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

    2012-01-01

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

  16. Identification of estrogen-associated intrinsic aging genes in Chinese Han female skin by cDNA microarray technology.

    PubMed

    Yan, Wei; Zhao, ZhenMin; Zhang, LiLi; Wang, DunMei; Yan, Li; Yin, NingBei; Wu, Di; Zhang, Feng

    2011-08-01

    Estrogens play an important role in intrinsic skin aging. The associated changes in global gene expression are poorly understood. We used the Illumina microarray platform to obtain comprehensive gene expression profiles in female Chinese Han skin, and confirmed the data by quantitative real-time PCR (Q-RT-PCR). We found 244 genes significantly related to estrogen-associated intrinsic skin aging, and some of these genes were confirmed by Q-RT-PCR. We also performed functional analysis by both Gene Ontology annotation and enrichment of the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways database. The functional analysis revealed 11 biological pathways (including the KEGG pathways, the mitogen-activated protein kinase signaling pathway and metabolic pathways), that were associated with multiple cellular functions which may be involved in intrinsic skin aging. This study suggests that estrogen-associated intrinsic skin aging is a complicated biological process involving many genes and pathways. Copyright © 2011 The Editorial Board of Biomedical and Environmental Sciences. Published by Elsevier B.V. All rights reserved.

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

    PubMed Central

    Efferth, Thomas; Greten, Henry Johannes

    2012-01-01

    Withania somnifera (L.) Dunal (Indian ginseng, winter cherry, Solanaceae) is widely used in traditional medicine. Roots are either chewed or used to prepare beverages (aqueous decocts). The major secondary metabolites of Withania somnifera are the withanolides, which are C-28-steroidal lactone triterpenoids. Withania somnifera extracts exert chemopreventive and anticancer activities in vitro and in vivo. The aims of the present in silico study were, firstly, to investigate whether tumor cells develop cross-resistance between standard anticancer drugs and withanolides and, secondly, to elucidate the molecular determinants of sensitivity and resistance of tumor cells towards withanolides. Using IC50 concentrations of eight different withanolides (withaferin A, withaferin A diacetate, 3-azerininylwithaferin A, withafastuosin D diacetate, 4-B-hydroxy-withanolide E, isowithanololide E, withafastuosin E, and withaperuvin) and 19 established anticancer drugs, we analyzed the cross-resistance profile of 60 tumor cell lines. The cell lines revealed cross-resistance between the eight withanolides. Consistent cross-resistance between withanolides and nitrosoureas (carmustin, lomustin, and semimustin) was also observed. Then, we performed transcriptomic microarray-based COMPARE and hierarchical cluster analyses of mRNA expression to identify mRNA expression profiles predicting sensitivity or resistance towards withanolides. Genes from diverse functional groups were significantly associated with response of tumor cells to withaferin A diacetate, e.g. genes functioning in DNA damage and repair, stress response, cell growth regulation, extracellular matrix components, cell adhesion and cell migration, constituents of the ribosome, cytoskeletal organization and regulation, signal transduction, transcription factors, and others. PMID:27605335

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

    NASA Astrophysics Data System (ADS)

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

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

  19. Microarray analysis of gene expression during early development: a cautionary overview.

    PubMed

    Robert, Claude

    2010-12-01

    The rise of the 'omics' technologies started nearly a decade ago and, among them, transcriptomics has been used successfully to contrast gene expression in mammalian oocytes and early embryos. The scarcity of biological material that early developmental stages provide is the prime reason why the field of transcriptomics is becoming more and more popular with reproductive biologists. The potential to amplify scarce mRNA samples and generate the necessary amounts of starting material enables the relative measurement of RNA abundance of thousands of candidates simultaneously. So far, microarrays have been the most commonly used high-throughput method in this field. Microarray platforms can be found in a wide variety of formats, from cDNA collections to long or short oligo probe sets. These platforms generate large amounts of data that require the integration of comparative RNA abundance values in the physiological context of early development for their full benefit to be appreciated. Unfortunately, significant discrepancies between datasets suggest that direct comparison between studies is difficult and often not possible. We have investigated the sample-handling steps leading to the generation of microarray data produced from prehatching embryo samples and have identified key steps that significantly impact the downstream results. This review provides a discussion on the best methods for the preparation of samples from early embryos for microarray analysis and focuses on the challenges that impede dataset comparisons from different platforms and the reasons why methodological benchmarking performed using somatic cells may not apply to the atypical nature of prehatching development.

  20. Gene expression profiling in Salmonella Choleraesuis-infected porcine lung using a long oligonucleotide microarray.

    PubMed

    Zhao, Shu-Hong; Kuhar, Daniel; Lunney, Joan K; Dawson, Harry; Guidry, Catherine; Uthe, Jolita J; Bearson, Shawn M D; Recknor, Justin; Nettleton, Dan; Tuggle, Christopher K

    2006-07-01

    Understanding the transcriptional response to pathogenic bacterial infection within food animals is of fundamental and applied interest. To determine the transcriptional response to Salmonella enterica serovar Choleraesuis (SC) infection, a 13,297-oligonucleotide swine array was used to analyze RNA from control, 24-h postinoculation (hpi), and 48-hpi porcine lung tissue from pigs infected with SC. In total, 57 genes showed differential expression (p < 0.001; false discovery rate = 12%). Quantitative real-time PCR (qRT-PCR) of 61 genes was used to confirm the microarray results and to identify pathways responding to infection. Of the 33 genes identified by microarray analysis as differentially expressed, 23 were confirmed by qRT-PCR results. A novel finding was that two transglutaminase family genes (TGM1 and TGM3) showed dramatic increases in expression postinoculation; combined with several other apoptotic genes, they indicated the induction of apoptotic pathways during SC infection. A predominant T helper 1-type immune response occurred during infection, with interferon gamma (IFNG) significantly increased at 48 hpi. Genes induced by IFNs (GBP1, GBP2, C1S, C1R, MHC2TA, PSMB8, TAP1, TAP2) showed increased expression during porcine lung infection. These data represent the first thorough investigation of gene regulation pathways that control an important porcine respiratory and foodborne bacterial infection.

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

    PubMed

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

    2013-01-01

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

  2. Cross-species microarray hybridization to identify developmentally regulated genes in the filamentous fungus Sordaria macrospora.

    PubMed

    Nowrousian, Minou; Ringelberg, Carol; Dunlap, Jay C; Loros, Jennifer J; Kück, Ulrich

    2005-04-01

    The filamentous fungus Sordaria macrospora forms complex three-dimensional fruiting bodies that protect the developing ascospores and ensure their proper discharge. Several regulatory genes essential for fruiting body development were previously isolated by complementation of the sterile mutants pro1, pro11 and pro22. To establish the genetic relationships between these genes and to identify downstream targets, we have conducted cross-species microarray hybridizations using cDNA arrays derived from the closely related fungus Neurospora crassa and RNA probes prepared from wild-type S. macrospora and the three developmental mutants. Of the 1,420 genes which gave a signal with the probes from all the strains used, 172 (12%) were regulated differently in at least one of the three mutants compared to the wild type, and 17 (1.2%) were regulated differently in all three mutant strains. Microarray data were verified by Northern analysis or quantitative real time PCR. Among the genes that are up- or down-regulated in the mutant strains are genes encoding the pheromone precursors, enzymes involved in melanin biosynthesis and a lectin-like protein. Analysis of gene expression in double mutants revealed a complex network of interaction between the pro gene products.

  3. Microarray analysis of differentially expressed genes regulating lipid metabolism during melanoma progression.

    PubMed

    Sumantran, Venil N; Mishra, Pratik; Sudhakar, N

    2015-04-01

    A new hallmark of cancer involves acquisition of a lipogenic phenotype which promotes tumorigenesis. Little is known about lipid metabolism in melanomas. Therefore, we used BRB (Biometrics Research Branch) class comparison tool with multivariate analysis to identify differentially expressed genes in human cutaneous melanomas, compared with benign nevi and normal skin derived from the microarray dataset (GDS1375). The methods were validated by identifying known melanoma biomarkers (CITED1, FGFR2, PTPRF, LICAM, SPP1 and PHACTR1) in our results. Eighteen genes regulating metabolism of fatty acids, lipid second messengers and gangliosides were 2-9 fold upregulated in melanomas of GDS-1375. Out of the 18 genes, 13 were confirmed by KEGG pathway analysis and 10 were also significantly upregulated in human melanoma cell lines of NCI-60 Cell Miner database. Results showed that melanomas upregulated PPARGC1A transcription factor and its target genes regulating synthesis of fatty acids (SCD) and complex lipids (FABP3 and ACSL3). Melanoma also upregulated genes which prevented lipotoxicity (CPT2 and ACOT7) and regulated lipid second messengers, such as phosphatidic acid (AGPAT-4, PLD3) and inositol triphosphate (ITPKB, ITPR3). Genes for synthesis of pro-tumorigenic GM3 and GD3 gangliosides (UGCG, HEXA, ST3GAL5 and ST8SIA1) were also upregulated in melanoma. Overall, the microarray analysis of GDS-1375 dataset indicated that melanomas can become lipogenic by upregulating genes, leading to increase in fatty acid metabolism, metabolism of specific lipid second messengers, and ganglioside synthesis.

  4. Extreme value distribution based gene selection criteria for discriminant microarray data analysis using logistic regression.

    PubMed

    Li, Wentian; Sun, Fengzhu; Grosse, Ivo

    2004-01-01

    One important issue commonly encountered in the analysis of microarray data is to decide which and how many genes should be selected for further studies. For discriminant microarray data analyses based on statistical models, such as the logistic regression models, gene selection can be accomplished by a comparison of the maximum likelihood of the model given the real data, L(D|M), and the expected maximum likelihood of the model given an ensemble of surrogate data with randomly permuted label, L(D(0)|M). Typically, the computational burden for obtaining L(D(0)M) is immense, often exceeding the limits of available computing resources by orders of magnitude. Here, we propose an approach that circumvents such heavy computations by mapping the simulation problem to an extreme-value problem. We present the derivation of an asymptotic distribution of the extreme-value as well as its mean, median, and variance. Using this distribution, we propose two gene selection criteria, and we apply them to two microarray datasets and three classification tasks for illustration.

  5. A microarray gene analysis of peripheral whole blood in normal adult male rats after long-term GH gene therapy.

    PubMed

    Qin, Ying; Tian, Ya-Ping

    2010-06-01

    The main aims of this study were to determine the effects of GH gene abuse/misuse in normal animals and to discover genes that could be used as candidate biomarkers for the detection of GH gene therapy abuse/misuse in humans. We determined the global gene expression profile of peripheral whole blood from normal adult male rats after long-term GH gene therapy using CapitalBio 27 K Rat Genome Oligo Arrays. Sixty one genes were found to be differentially expressed in GH gene-treated rats 24 weeks after receiving GH gene therapy, at a two-fold higher or lower level compared to the empty vector group (p < 0.05). These genes were mainly associated with angiogenesis, oncogenesis, apoptosis, immune networks, signaling pathways, general metabolism, type I diabetes mellitus, carbon fixation, cell adhesion molecules, and cytokine-cytokine receptor interaction. The results imply that exogenous GH gene expression in normal subjects is likely to induce cellular changes in the metabolism, signal pathways and immunity. A real-time qRT-PCR analysis of a selection of the genes confirmed the microarray data. Eight differently expressed genes were selected as candidate biomarkers from among these 61 genes. These 8 showed five-fold higher or lower expression levels after the GH gene transduction (p < 0.05). They were then validated in real-time PCR experiments using 15 single-treated blood samples and 10 control blood samples. In summary, we detected the gene expression profiles of rat peripheral whole blood after long-term GH gene therapy and screened eight genes as candidate biomarkers based on the microarray data. This will contribute to an increased mechanistic understanding of the effects of chronic GH gene therapy abuse/misuse in normal subjects.

  6. [Study of generational risk in deafness inflicted couples using deafness gene microarray technique].

    PubMed

    Wang, Ping; Zhao, Jia; Yu, Shu-yuan; Jin, Peng; Zhu, Wei; DU, Bo

    2011-06-01

    To explored the significance of screening the gene mutations of deafness related in deaf-mute (deaf & dumb) family using DNA microarray. Total of 52 couples of deaf-mute were recruited from Changchun deaf-mute community. With an average age of (58.3 ± 6.7) years old (x(-) ± s). Blood samples were obtained with informed consent. Their genomic DNA was extracted from peripheral blood and PCR was performed. Nine of hot spot mutations in four most common deafness pathologic gene were examined with the DNA microarray, including GJB2, GJB3, PDS and mtDNA 12S rRNA genes. At the same time, the results were verified with the traditional methods of sequencing. Fifty of normal people served as a control group. All patients were diagnosed non-syndromic sensorineural hearing loss by subjective pure tone audiometry. Thirty-two of 104 cases appeared GJB2 gene mutation (30.7%), the mutation sites included 35delG, 176del16, 235delC and 299delAT. Eighteen of 32 cases of GJB2 mutations were 235delC (59.1%). Seven of 104 cases appeared SLC26A4 gene IVS7-2 A > G mutation. Questionnaire survey and gene diagnosis revealed that four of 52 families have deaf offspring (7.6%). When a couple carries the same gene mutation, the risk of their children deafness was 100%. The results were confirmed with the traditional methods of sequencing. There is a high risk of deafness if a deaf-mute family is planning to have a new baby. It is very important and helpful to avoid deaf newborns again in deaf-mute family by DNA microarray.

  7. Gene expression in breast muscle associated with feed efficiency in a single male broiler line using a chicken 44K oligo microarray. I. Top differentially expressed genes.

    PubMed

    Kong, B-W; Song, J J; Lee, J Y; Hargis, B M; Wing, T; Lassiter, K; Bottje, W

    2011-11-01

    Global RNA expression in breast muscle obtained from a male broiler line phenotyped for high or low feed efficiency (FE) was investigated. Pooled RNA samples (n = 6/phenotype) labeled with cyanine 3 or cyanine 5 fluorescent dyes to generate cRNA probes were hybridized on a 4 × 44K chicken oligo microarray. Local polynomial regression normalization was applied to background-corrected red and green intensities with a moderated t-statistic. Corresponding P-values were computed and adjusted for multiple testing by false discovery rate to identify differentially expressed genes. Microarray validation was carried out by comparing findings with quantitative reverse-transcription PCR. A 1.3-fold difference in gene expression was set as a cutoff value, which encompassed 20% (782 of 4,011) of the total number of genes that were differentially expressed between FE phenotypes. Using an online software program (Ingenuity Pathway Analysis), the top 10 upregulated genes identified by Ingenuity Pathway Analysis in the high-FE group were generally associated with anabolic processes. In contrast, 7 of the top 10 downregulated genes in the high-FE phenotype (upregulated in the low-FE phenotype) were associated with muscle fiber development, muscle function, and cytoskeletal organization, with the remaining 3 genes associated with self-recognition or stress-responding genes. The results from this study focusing on only the top differentially expressed genes suggest that the high-FE broiler phenotype is derived from the upregulation of genes associated with anabolic processes as well as a downregulation of genes associated with muscle fiber development, muscle function, cytoskeletal organization, and stress response.

  8. Interactive Exploration of Microarray Gene Expression Patterns in a Reduced Dimensional Space

    PubMed Central

    Misra, Jatin; Schmitt, William; Hwang, Daehee; Hsiao, Li-Li; Gullans, Steve; Stephanopoulos, George; Stephanopoulos, Gregory

    2002-01-01

    The very high dimensional space of gene expression measurements obtained by DNA microarrays impedes the detection of underlying patterns in gene expression data and the identification of discriminatory genes. In this paper we show the use of projection methods such as principal components analysis (PCA) to obtain a direct link between patterns in the genes and patterns in samples. This feature is useful in the initial interactive pattern exploration of gene expression data and data-driven learning of the nature and types of samples. Using oligonucleotide microarray measurements of 40 samples from different normal human tissues, we show that distinct patterns are obtained when the genes are projected on a two-dimensional plane spanned by the loadings of the two major principal components. These patterns define the particular genes associated with a sample class (i.e., tissue). When used separately from the other genes, these class-specific (i.e., tissue-specific) genes in turn define distinct tissue patterns in the projection space spanned by the scores of the two major principal components. In this study, PCA projection facilitated discriminatory gene selection for different tissues and identified tissue-specific gene expression signatures for liver, skeletal muscle, and brain samples. Furthermore, it allowed the classification of nine new samples belonging to these three types using the linear combination of the expression levels of the tissue-specific genes determined from the first set of samples. The application of the technique to other published data sets is also discussed. [Online supplementary material available at www.genome.org.] PMID:12097349

  9. A dynamic, web-accessible resource to process raw microarray scan data into consolidated gene expression values: importance of replication

    PubMed Central

    Le Meur, Nolwenn; Lamirault, Guillaume; Bihouée, Audrey; Steenman, Marja; Bédrine-Ferran, Hélène; Teusan, Raluca; Ramstein, Gérard; Léger, Jean J.

    2004-01-01

    We propose a freely accessible web-based pipeline, which processes raw microarray scan data to obtain experimentally consolidated gene expression values. The tool MADSCAN, which stands for MicroArray Data Suites of Computed ANalysis, makes a practical choice among the numerous methods available for filtering, normalizing and scaling of raw microarray expression data in a dynamic and automatic way. Different statistical methods have been adapted to extract reliable information from replicate gene spots as well as from replicate microarrays for each biological situation under study. A carefully constructed experimental design thus allows to detect outlying expression values and to identify statistically significant expression values, together with a list of quality controls with proposed threshold values. The integrated processing procedure described here, based on multiple measurements per gene, is decisive for reliably monitoring subtle gene expression changes typical for most biological events. PMID:15475389

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

    PubMed Central

    Raman, Tina; O'Connor, Timothy P; Hackett, Neil R; Wang, Wei; Harvey, Ben-Gary; Attiyeh, Marc A; Dang, David T; Teater, Matthew; Crystal, Ronald G

    2009-01-01

    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 < 0.0001) than correlation coefficients for pairwise comparisons between arrays that passed the QC criteria (average Pearson r = 0.97 ± 0.01). Inter-array variability was significantly decreased (p < 0.0001) among samples passing the QC criteria compared with samples failing the QC criteria. 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. PMID:19852842

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

    PubMed Central

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

    2015-01-01

    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. PMID:26981356

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

    PubMed Central

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

    2015-01-01

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

  13. High-throughput proteomics integrated with gene microarray for discovery of colorectal cancer potential biomarkers

    PubMed Central

    Zhong, Chenhan; Li, Dan; Zhai, Xiaohui; Hu, Wangxiong; Guo, Cheng; Yuan, Ying; Zheng, Shu

    2016-01-01

    Proteins, as executives of genes' instructions, are responsible for cellular phenotypes. Integrating proteomics with gene microarray, we conducted this study to identify potential protein biomarkers of colorectal cancer (CRC). Isobaric tags with related and absolute quantitation (iTRAQ) labeling mass spectrometry (MS) was applied to screen and identify differentially expressed proteins between paired CRC and adjacent normal mucosa. Meanwhile, Affymetrix U133plus2.0 microarrays were used to perform gene microarray analysis. Verification experiments included immunohistochemistry (IHC), western blot and enzyme-linked immunosorbent assay (ELISA) of selected proteins. Overall, 5469 differentially expressed proteins were detected with iTRAQ-MS from 24 matched CRC and adjacent normal tissues. And gene microarray identified 39859 differential genes from 52 patients. Of these, 3083 differential proteins had corresponding differentially expressed genes, with 245 proteins and their genes showed >1.5-fold change in expression level. Gene ontology enrichment analysis revealed that up-regulated proteins were more involved in cell adhesion and motion than down-regulated proteins. In addition, up-regulated proteins were more likely to be located in nucleus and vesicles. Further verification experiments with IHC confirmed differential expression levels of 5 proteins (S100 calcium-binding protein A9, annexin A3, nicotinamide phosphoribosyltransferase, carboxylesterase 2 and calcium activated chloride channel A1) between CRC and normal tissues. Besides, western blot showed a stepwise increase of annexin A3 abundance in normal colorectal mucosa, adenoma and CRC tissues. ELISA results revealed significantly higher serum levels of S100 calcium-binding protein A9 and annexin A3 in CRC patients than healthy controls, validating diagnostic value of these proteins. Cell experiments showed that inhibition of annexin A3 could suppress CRC cell proliferation and aggressiveness. S100 calcium

  14. Microarray based gene expression analysis of murine brown and subcutaneous adipose tissue: significance with human.

    PubMed

    Baboota, Ritesh K; Sarma, Siddhartha M; Boparai, Ravneet K; Kondepudi, Kanthi Kiran; Mantri, Shrikant; Bishnoi, Mahendra

    2015-01-01

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

  15. Sex-related gene expression profiles in the adrenal cortex in the mature rat: Microarray analysis with emphasis on genes involved in steroidogenesis

    PubMed Central

    TREJTER, MARCIN; HOCHOL, ANNA; TYCZEWSKA, MARIANNA; ZIOLKOWSKA, AGNIESZKA; JOPEK, KAROL; SZYSZKA, MARTA; MALENDOWICZ, LUDWIK K; RUCINSKI, MARCIN

    2015-01-01

    Notable sex-related differences exist in mammalian adrenal cortex structure and function. In adult rats, the adrenal weight and the average volume of zona fasciculata cells of females are larger and secrete greater amounts of corticosterone than those of males. The molecular bases of these sex-related differences are poorly understood. In this study, to explore the molecular background of these differences, we defined zone- and sex-specific transcripts in adult male and female (estrous cycle phase) rats. Twelve-week-old rats of both genders were used and samples were taken from the zona glomerulosa (ZG) and zona fasciculata/reticularis (ZF/R) zones. Transcriptome identification was carried out using the Affymetrix® Rat Gene 1.1 ST Array. The microarray data were compared by fold change with significance according to moderated t-statistics. Subsequently, we performed functional annotation clustering using the Gene Ontology (GO) and Database for Annotation, Visualization and Integrated Discovery (DAVID). In the first step, we explored differentially expressed transcripts in the adrenal ZG and ZF/R. The number of differentially expressed transcripts was notably higher in the female than in the male rats (702 vs. 571). The differentially expressed genes which were significantly enriched included genes involved in steroid hormone metabolism, and their expression levels in the ZF/R of adult female rats were significantly higher compared with those in the male rats. In the female ZF/R, when compared with that of the males, prevailing numbers of genes linked to cell fraction, oxidation/reduction processes, response to nutrients and to extracellular stimuli or steroid hormone stimuli were downregulated. The microarray data for key genes involved directly in steroidogenesis were confirmed by qPCR. Thus, when compared with that of the males, in the female ZF/R, higher expression levels of genes involved directly in steroid hormone synthesis were accompanied by lower

  16. Sex-related gene expression profiles in the adrenal cortex in the mature rat: microarray analysis with emphasis on genes involved in steroidogenesis.

    PubMed

    Trejter, Marcin; Hochol, Anna; Tyczewska, Marianna; Ziolkowska, Agnieszka; Jopek, Karol; Szyszka, Marta; Malendowicz, Ludwik K; Rucinski, Marcin

    2015-03-01

    Notable sex-related differences exist in mammalian adrenal cortex structure and function. In adult rats, the adrenal weight and the average volume of zona fasciculata cells of females are larger and secrete greater amounts of corticosterone than those of males. The molecular bases of these sex-related differences are poorly understood. In this study, to explore the molecular background of these differences, we defined zone- and sex-specific transcripts in adult male and female (estrous cycle phase) rats. Twelve-week-old rats of both genders were used and samples were taken from the zona glomerulosa (ZG) and zona fasciculata/reticularis (ZF/R) zones. Transcriptome identification was carried out using the Affymetrix(®) Rat Gene 1.1 ST Array. The microarray data were compared by fold change with significance according to moderated t-statistics. Subsequently, we performed functional annotation clustering using the Gene Ontology (GO) and Database for Annotation, Visualization and Integrated Discovery (DAVID). In the first step, we explored differentially expressed transcripts in the adrenal ZG and ZF/R. The number of differentially expressed transcripts was notably higher in the female than in the male rats (702 vs. 571). The differentially expressed genes which were significantly enriched included genes involved in steroid hormone metabolism, and their expression levels in the ZF/R of adult female rats were significantly higher compared with those in the male rats. In the female ZF/R, when compared with that of the males, prevailing numbers of genes linked to cell fraction, oxidation/reduction processes, response to nutrients and to extracellular stimuli or steroid hormone stimuli were downregulated. The microarray data for key genes involved directly in steroidogenesis were confirmed by qPCR. Thus, when compared with that of the males, in the female ZF/R, higher expression levels of genes involved directly in steroid hormone synthesis were accompanied by lower

  17. A combined analysis of microarray gene expression studies of the human prefrontal cortex identifies genes implicated in schizophrenia.

    PubMed

    Pérez-Santiago, Josué; Diez-Alarcia, Rebeca; Callado, Luis F; Zhang, Jin X; Chana, Gursharan; White, Cory H; Glatt, Stephen J; Tsuang, Ming T; Everall, Ian P; Meana, J Javier; Woelk, Christopher H

    2012-11-01

    Small cohort sizes and modest levels of gene expression changes in brain tissue have plagued the statistical approaches employed in microarray studies investigating the mechanism of schizophrenia. To combat these problems a combined analysis of six prior microarray studies was performed to facilitate the robust statistical analysis of gene expression data from the dorsolateral prefrontal cortex of 107 patients with schizophrenia and 118 healthy subjects. Multivariate permutation tests identified 144 genes that were differentially expressed between schizophrenia and control groups. Seventy of these genes were identified as differentially expressed in at least one component microarray study but none of these individual studies had the power to identify the remaining 74 genes, demonstrating the utility of a combined approach. Gene ontology terms and biological pathways that were significantly enriched for differentially expressed genes were related to neuronal cell-cell signaling, mesenchymal induction, and mitogen-activated protein kinase signaling, which have all previously been associated with the etiopathogenesis of schizophrenia. The differential expression of BAG3, C4B, EGR1, MT1X, NEUROD6, SST and S100A8 was confirmed by real-time quantitative PCR in an independent cohort using postmortem human prefrontal cortex samples. Comparison of gene expression between schizophrenic subjects with and without detectable levels of antipsychotics in their blood suggests that the modulation of MT1X and S100A8 may be the result of drug exposure. In conclusion, this combined analysis has resulted in a statistically robust identification of genes whose dysregulation may contribute to the mechanism of schizophrenia.

  18. Acid-induced gene expression in Helicobacter pylori: study in genomic scale by microarray.

    PubMed

    Ang, S; Lee, C Z; Peck, K; Sindici, M; Matrubutham, U; Gleeson, M A; Wang, J T

    2001-03-01

    To understand the RNA expression in response to acid stress of Helicobacter pylori in genomic scale, a microarray membrane containing 1,534 open reading frames (ORFs) from strain 26695 was used. Total RNAs of H. pylori under growth conditions of pH 7.2 and 5.5 were extracted, reverse transcribed into cDNA, and labeled with biotin. Each microarray membrane was hybridized with cDNA probe from the same strain under two different pH conditions and developed by a catalyzed reporter deposition method. Gene expression of all ORFs was measured by densitometry. Among the 1,534 ORFs, 53 ORFs were highly expressed (> or = 30% of rRNA control in densitometry ratios). There were 445 ORFs which were stably expressed (<30% of rRNA in densitometry) under both pH conditions without significant variation. A total of 80 ORFs had significantly increased expression levels at low pH, while expressions of 4 ORFs were suppressed under acidic condition. The remaining 952 ORFs were not detectable under either pH condition. These data were highly reproducible and comparable to those obtained by the RNA slot blot method. Our results suggest that microarray can be used in monitoring prokaryotic gene expression in genomic scale.

  19. Direct Detection of Soil mRNAs using Targeted Microarrays for Genes Associated with Lignin Degradation

    SciTech Connect

    Bailey, Vanessa L.; Fansler, Sarah J.; Bandyopadhyay, Somnath; Smith, Jeff L.; Waters, Katrina M.; Bolton, Harvey

    2010-07-04

    Microarrays have become established tools for describing microbial systems, however the assessment of expression profiles for environmental microbial communities still presents unique challenges. Notably, the concentration of particular transcripts are likely very dilute relative to the pool of total RNA, and PCR-based amplification strategies are vulnerable to amplification biases and the appropriate primer selection. Thus, we apply a signal amplification approach, rather than template amplification, to analyze the expression of genes encoding selected lignin-degrading enzymes in soil. Controls in the form of known amplicons and cDNA from Phanerochaete chrysosporium were included and mixed with the soil cDNA both before and after the signal amplification in order to assess the dynamic range of the microarray. We demonstrate that restored prairie soil expresses a diverse range of genes encoding lignin-degrading enzymes following incubation with lignin substrate, while farmed agricultural soil does not. The mixed additions of control cDNA with soil cDNA does interfere with detection of the low abundance transcripts, nevertheless this microarray approach consistently reports the higher-abundance transcripts which present more robust signals.

  20. A mixture model-based strategy for selecting sets of genes in multiclass response microarray experiments.

    PubMed

    Broët, Philippe; Lewin, Alex; Richardson, Sylvia; Dalmasso, Cyril; Magdelenat, Henri

    2004-11-01

    Multiclass response (MCR) experiments are those in which there are more than two classes to be compared. In these experiments, though the null hypothesis is simple, there are typically many patterns of gene expression changes across the different classes that led to complex alternatives. In this paper, we propose a new strategy for selecting genes in MCR that is based on a flexible mixture model for the marginal distribution of a modified F-statistic. Using this model, false positive and negative discovery rates can be estimated and combined to produce a rule for selecting a subset of genes. Moreover, the method proposed allows calculation of these rates for any predefined subset of genes. We illustrate the performance our approach using simulated datasets and a real breast cancer microarray dataset. In this latter study, we investigate predefined subset of genes and point out interesting differences between three distinct biological pathways. http://www.bgx.org.uk/software.html

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

    PubMed

    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.

  2. Microarray analysis of active cardiac remodeling genes in a familial hypertrophic cardiomyopathy mouse model rescued by a phospholamban knockout

    PubMed Central

    Rajan, Sudarsan; Pena, James R.; Jegga, Anil G.; Aronow, Bruce J.; Wolska, Beata M.

    2013-01-01

    Familial hypertrophic cardiomyopathy (FHC) is a disease characterized by ventricular hypertrophy, fibrosis, and aberrant systolic and/or diastolic function. Our laboratories have previously developed two mouse models that affect cardiac performance. One mouse model encodes an FHC-associated mutation in α-tropomyosin: Glu → Gly at amino acid 180, designated as Tm180. These mice display a phenotype that is characteristic of FHC, including severe cardiac hypertrophy with fibrosis and impaired physiological performance. The other model was a gene knockout of phospholamban (PLN KO), a regulator of calcium uptake in the sarcoplasmic reticulum of cardiomyocytes; these hearts exhibit hypercontractility with no pathological abnormalities. Previous work in our laboratories shows that when mice were genetically crossed between the PLN KO and Tm180, the progeny (PLN KO/Tm180) display a rescued hypertrophic phenotype with improved morphology and cardiac function. To understand the changes in gene expression that occur in these models undergoing cardiac remodeling (Tm180, PLN KO, PLN KO/Tm180, and nontransgenic control mice), we conducted microarray analyses of left ventricular tissue at 4 and 12 mo of age. Expression profiling reveals that 1,187 genes changed expression in direct response to the three genetic models. With these 1,187 genes, 11 clusters emerged showing normalization of transcript expression in the PLN KO/Tm180 hearts. In addition, 62 transcripts are highly involved in suppression of the hypertrophic phenotype. Confirmation of the microarray analysis was conducted by quantitative RT-PCR. These results provide insight into genes that alter expression during cardiac remodeling and are active during modulation of the cardiomyopathic phenotype. PMID:23800848

  3. Development of a prostate cDNA microarray and statistical gene expression analysis package.

    PubMed

    Carlisle, A J; Prabhu, V V; Elkahloun, A; Hudson, J; Trent, J M; Linehan, W M; Williams, E D; Emmert-Buck, M R; Liotta, L A; Munson, P J; Krizman, D B

    2000-05-01

    A cDNA microarray comprising 5184 different cDNAs spotted onto nylon membrane filters was developed for prostate gene expression studies. The clones used for arraying were identified by cluster analysis of > 35 000 prostate cDNA library-derived expressed sequence tags (ESTs) present in the dbEST database maintained by the National Center for Biotechnology Information. Total RNA from two cell lines, prostate line 8.4 and melanoma line UACC903, was used to make radiolabeled probe for filter hybridizations. The absolute intensity of each individual cDNA spot was determined by phosphorimager scanning and evaluated by a bioinformatics package developed specifically for analysis of cDNA microarray experimentation. Results indicated 89% of the genes showed intensity levels above background in prostate cells compared with only 28% in melanoma cells. Replicate probe preparations yielded results with correlation values ranging from r = 0.90 to 0.93 and coefficient of variation ranging from 16 to 28%. Findings indicate that among others, the keratin 5 and vimentin genes were differentially expressed between these two divergent cell lines. Follow-up northern blot analysis verified these two expression changes, thereby demonstrating the reliability of this system. We report the development of a cDNA microarray system that is sensitive and reliable, demonstrates a low degree of variability, and is capable of determining verifiable gene expression differences between two distinct human cell lines. This system will prove useful for differential gene expression analysis in prostate-derived cells and tissue.

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

    PubMed

    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.

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

    PubMed Central

    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

  6. Screening insertion libraries for mutations in many genes simultaneously using DNA microarrays

    PubMed Central

    Mahalingam, Ramamurthy; Fedoroff, Nina

    2001-01-01

    We describe a method to screen pools of DNA from multiple transposon lines for insertions in many genes simultaneously. We use thermal asymmetric interlaced–PCR, a hemispecific PCR amplification protocol that combines nested, insertion-specific primers with degenerate primers, to amplify DNA flanking the transposons. In reconstruction experiments with previously characterized Arabidopsis lines carrying insertions of the maize Dissociation (Ds) transposon, we show that fluorescently labeled, transposon-flanking fragments overlapping ORFs hybridize to cognate expressed sequence tags (ESTs) on a DNA microarray. We further show that insertions can be detected in DNA pools from as many as 100 plants representing different transposon lines and that all of the tested, transposon-disrupted genes whose flanking fragments can be amplified individually also can be detected when amplified from the pool. The ability of a transposon-flanking fragment to hybridize declines rapidly with decreasing homology to the spotted DNA fragment, so that only ESTs with >90% homology to the transposon-disrupted gene exhibit significant cross-hybridization. Because thermal asymmetric interlaced–PCR fragments tend to be short, use of the present method favors recovery of insertions in and near genes. We apply the technique to screening pools of new Ds lines using cDNA microarrays containing ESTs for ≈1,000 stress-induced and -repressed Arabidopsis genes. PMID:11416215

  7. Classification of microarrays; synergistic effects between normalization, gene selection and machine learning

    PubMed Central

    2011-01-01

    Background Machine learning is a powerful approach for describing and predicting classes in microarray data. Although several comparative studies have investigated the relative performance of various machine learning methods, these often do not account for the fact that performance (e.g. error rate) is a result of a series of analysis steps of which the most important are data normalization, gene selection and machine learning. Results In this study, we used seven previously published cancer-related microarray data sets to compare the effects on classification performance of five normalization methods, three gene selection methods with 21 different numbers of selected genes and eight machine learning methods. Performance in term of error rate was rigorously estimated by repeatedly employing a double cross validation approach. Since performance varies greatly between data sets, we devised an analysis method that first compares methods within individual data sets and then visualizes the comparisons across data sets. We discovered both well performing individual methods and synergies between different methods. Conclusion Support Vector Machines with a radial basis kernel, linear kernel or polynomial kernel of degree 2 all performed consistently well across data sets. We show that there is a synergistic relationship between these methods and gene selection based on the T-test and the selection of a relatively high number of genes. Also, we find that these methods benefit significantly from using normalized data, although it is hard to draw general conclusions about the relative performance of different normalization procedures. PMID:21982277

  8. Using control genes to correct for unwanted variation in microarray data

    PubMed Central

    Gagnon-Bartsch, Johann A.; Speed, Terence P.

    2012-01-01

    Microarray expression studies suffer from the problem of batch effects and other unwanted variation. Many methods have been proposed to adjust microarray data to mitigate the problems of unwanted variation. Several of these methods rely on factor analysis to infer the unwanted variation from the data. A central problem with this approach is the difficulty in discerning the unwanted variation from the biological variation that is of interest to the researcher. We present a new method, intended for use in differential expression studies, that attempts to overcome this problem by restricting the factor analysis to negative control genes. Negative control genes are genes known a priori not to be differentially expressed with respect to the biological factor of interest. Variation in the expression levels of these genes can therefore be assumed to be unwanted variation. We name this method “Remove Unwanted Variation, 2-step” (RUV-2). We discuss various techniques for assessing the performance of an adjustment method and compare the performance of RUV-2 with that of other commonly used adjustment methods such as Combat and Surrogate Variable Analysis (SVA). We present several example studies, each concerning genes differentially expressed with respect to gender in the brain and find that RUV-2 performs as well or better than other methods. Finally, we discuss the possibility of adapting RUV-2 for use in studies not concerned with differential expression and conclude that there may be promise but substantial challenges remain. PMID:22101192

  9. A microarray whole-genome gene expression dataset in a rat model of inflammatory corneal angiogenesis.

    PubMed

    Mukwaya, Anthony; Lindvall, Jessica M; Xeroudaki, Maria; Peebo, Beatrice; Ali, Zaheer; Lennikov, Anton; Jensen, Lasse Dahl Ejby; Lagali, Neil

    2016-11-22

    In angiogenesis with concurrent inflammation, many pathways are activated, some linked to VEGF and others largely VEGF-independent. Pathways involving inflammatory mediators, chemokines, and micro-RNAs may play important roles in maintaining a pro-angiogenic environment or mediating angiogenic regression. Here, we describe a gene expression dataset to facilitate exploration of pro-angiogenic, pro-inflammatory, and remodelling/normalization-associated genes during both an active capillary sprouting phase, and in the restoration of an avascular phenotype. The dataset was generated by microarray analysis of the whole transcriptome in a rat model of suture-induced inflammatory corneal neovascularisation. Regions of active capillary sprout growth or regression in the cornea were harvested and total RNA extracted from four biological replicates per group. High quality RNA was obtained for gene expression analysis using microarrays. Fold change of selected genes was validated by qPCR, and protein expression was evaluated by immunohistochemistry. We provide a gene expression dataset that may be re-used to investigate corneal neovascularisation, and may also have implications in other contexts of inflammation-mediated angiogenesis.

  10. Histopathology of melanosis coli and determination of its associated genes by comparative analysisof expression microarrays

    PubMed Central

    LI, XIAO-AN; ZHOU, YAN; ZHOU, SHU-XIAN; LIU, HAI-RONG; XU, JIN-MEI; GAO, LONG; YU, XIAN-JING; LI, XIAO-HUI

    2015-01-01

    Melanosis coli (MC) refers to the condition characterized by abnormal brown or black pigmentation deposits on the colonic mucosa. However, the histopathological findings and genes associated with the pathogenesis of melanosis coli remain to be fully elucidated. The present study aimed to examine the histopathological features and differentially expressed genes of MC. This involved performing hematoxylin and eosin staining, specific staining and immunohistochemistry on tissues sections, which were isolated from patients diagnosed with MC. DNA expression microarray analysis, western blotting and immunofluorescence assays were performed to analyze the differentially expressed genes of melanosis coli. The results demonstrated that the pigment deposits in MC consisted of lipofuscin. A TUNEL assay revealed that a substantial number of apoptotic cells were present within the macrophages and superficial lamina propria of the colonic epithelium. Expression microarray analysis revealed that the significantly downregulated genes were CYP3A4, CYP3A7, UGT2B11 and UGT2B15 in melanosis coli. Western blotting and immunofluorescence assays indicated that the expression of CYP3A4 in the normal tissue was higher than in the MC tissue. The results of the present study provided a comprehensive description of the histopathological characteristics and pathogenesis of MC and for the first time, to the best of our knowledge, demonstrated that the cytochrome P450-associated genes were significantly downregulated in melanosis coli. This novel information can be used to assist in further investigations of melanosis coli. PMID:26238215

  11. A microarray whole-genome gene expression dataset in a rat model of inflammatory corneal angiogenesis

    PubMed Central

    Mukwaya, Anthony; Lindvall, Jessica M.; Xeroudaki, Maria; Peebo, Beatrice; Ali, Zaheer; Lennikov, Anton; Jensen, Lasse Dahl Ejby; Lagali, Neil

    2016-01-01

    In angiogenesis with concurrent inflammation, many pathways are activated, some linked to VEGF and others largely VEGF-independent. Pathways involving inflammatory mediators, chemokines, and micro-RNAs may play important roles in maintaining a pro-angiogenic environment or mediating angiogenic regression. Here, we describe a gene expression dataset to facilitate exploration of pro-angiogenic, pro-inflammatory, and remodelling/normalization-associated genes during both an active capillary sprouting phase, and in the restoration of an avascular phenotype. The dataset was generated by microarray analysis of the whole transcriptome in a rat model of suture-induced inflammatory corneal neovascularisation. Regions of active capillary sprout growth or regression in the cornea were harvested and total RNA extracted from four biological replicates per group. High quality RNA was obtained for gene expression analysis using microarrays. Fold change of selected genes was validated by qPCR, and protein expression was evaluated by immunohistochemistry. We provide a gene expression dataset that may be re-used to investigate corneal neovascularisation, and may also have implications in other contexts of inflammation-mediated angiogenesis. PMID:27874850

  12. Toward a universal microarray: prediction of gene expression through nearest-neighbor probe sequence identification

    PubMed Central

    Royce, Thomas E.; Rozowsky, Joel S.; Gerstein, Mark B.

    2007-01-01

    A generic DNA microarray design applicable to any species would greatly benefit comparative genomics. We have addressed the feasibility of such a design by leveraging the great feature densities and relatively unbiased nature of genomic tiling microarrays. Specifically, we first divided each Homo sapiens Refseq-derived gene's spliced nucleotide sequence into all of its possible contiguous 25 nt subsequences. For each of these 25 nt subsequences, we searched a recent human transcript mapping experiment's probe design for the 25 nt probe sequence having the fewest mismatches with the subsequence, but that did not match the subsequence exactly. Signal intensities measured with each gene's nearest-neighbor features were subsequently averaged to predict their gene expression levels in each of the experiment's thirty-three hybridizations. We examined the fidelity of this approach in terms of both sensitivity and specificity for detecting actively transcribed genes, for transcriptional consistency between exons of the same gene, and for reproducibility between tiling array designs. Taken together, our results provide proof-of-principle for probing nucleic acid targets with off-target, nearest-neighbor features. PMID:17686789

  13. Combining metabolomic analysis and microarray gene expression analysis in the characterization of the medicinal plant Chelidonium majus L.

    PubMed

    Orland, A; Knapp, K; König, G M; Ulrich-Merzenich, G; Knöß, W

    2014-10-15

    Even though herbal medicines have played an important role in disease management and health for many centuries, their present frequent use is challenged by the necessity to determine their complex composition and their multitarget mode of action. In the present study, modern methods were investigated towards their potential in the characterization of herbal substances. As a model the herbal substance Chelidonii herba was used, for which several reports on liver toxicities exist. Extracts of Chelidonii herba with different solvents were characterized phytochemically and functionally by experiments with HepG2 liver cells. Chelidonii herba was extracted with four solvents of different polarity (dichloromethane, water, ethanol, and ethanol 50% (V/V); four replicates each). The different extracts were characterized metabolomically by (1)H-NMR fingerprinting analysis and principal component analysis (PCA). The content of alkaloids was additionally determined by RP-HPLC. Functional characterization was achieved by the determination of cell proliferation and by transcriptomics techniques (Whole Genome Gene Expression Microarrays v2, Agilent Technologies) in HepG2 cells after exposure to the different extracts (four experimental replicates each). Based on data from (1)H-NMR fingerprints and RP-HPLC analyses the different extracts showed a divergent composition of constituents depending on the solvent used. HepG2 liver cells responded differentially to the four extracts. Microarray analysis revealed a significant regulation of genes and signal cascades related to biotransformation. Also liver-toxic signal cascades were activated. Neither the activated genes nor the proliferation response could be clearly related to the differing alkaloid content of the extracts. Different manufacturing processes lead to different herbal preparations. A systems biology approach combining a metabolomic plant analysis with a functional characterization by gene expression profiling in HepG2

  14. Evaluation of an Expanded Microarray for Detecting Antibiotic Resistance Genes in a Broad Range of Gram-Negative Bacterial Pathogens

    PubMed Central

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

    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. PMID:23129055

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

    PubMed

    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.

  16. Genome-wide prediction and analysis of human tissue-selective genes using microarray expression data.

    PubMed

    Teng, Shaolei; Yang, Jack Y; Wang, Liangjiang

    2013-01-01

    Understanding how genes are expressed specifically in particular tissues is a fundamental question in developmental biology. Many tissue-specific genes are involved in the pathogenesis of complex human diseases. However, experimental identification of tissue-specific genes is time consuming and difficult. The accurate predictions of tissue-specific gene targets could provide useful information for biomarker development and drug target identification. In this study, we have developed a machine learning approach for predicting the human tissue-specific genes using microarray expression data. The lists of known tissue-specific genes for different tissues were collected from UniProt database, and the expression data retrieved from the previously compiled dataset according to the lists were used for input vector encoding. Random Forests (RFs) and Support Vector Machines (SVMs) were used to construct accurate classifiers. The RF classifiers were found to outperform SVM models for tissue-specific gene prediction. The results suggest that the candidate genes for brain or liver specific expression can provide valuable information for further experimental studies. Our approach was also applied for identifying tissue-selective gene targets for different types of tissues. A machine learning approach has been developed for accurately identifying the candidate genes for tissue specific/selective expression. The approach provides an efficient way to select some interesting genes for developing new biomedical markers and improve our knowledge of tissue-specific expression.

  17. Maize Gene Atlas Developed by RNA Sequencing and Comparative Evaluation of Transcriptomes Based on RNA Sequencing and Microarrays

    PubMed Central

    Sekhon, Rajandeep S.; Briskine, Roman; Hirsch, Candice N.; Myers, Chad L.; Springer, Nathan M.; Buell, C. Robin; de Leon, Natalia; Kaeppler, Shawn M.

    2013-01-01

    Transcriptome analysis is a valuable tool for identification and characterization of genes and pathways underlying plant growth and development. We previously published a microarray-based maize gene atlas from the analysis of 60 unique spatially and temporally separated tissues from 11 maize organs [1]. To enhance the coverage and resolution of the maize gene atlas, we have analyzed 18 selected tissues representing five organs using RNA sequencing (RNA-Seq). For a direct comparison of the two methodologies, the same RNA samples originally used for our microarray-based atlas were evaluated using RNA-Seq. Both technologies produced similar transcriptome profiles as evident from high Pearson's correlation statistics ranging from 0.70 to 0.83, and from nearly identical clustering of the tissues. RNA-Seq provided enhanced coverage of the transcriptome, with 82.1% of the filtered maize genes detected as expressed in at least one tissue by RNA-Seq compared to only 56.5% detected by microarrays. Further, from the set of 465 maize genes that have been historically well characterized by mutant analysis, 427 show significant expression in at least one tissue by RNA-Seq compared to 390 by microarray analysis. RNA-Seq provided higher resolution for identifying tissue-specific expression as well as for distinguishing the expression profiles of closely related paralogs as compared to microarray-derived profiles. Co-expression analysis derived from the microarray and RNA-Seq data revealed that broadly similar networks result from both platforms, and that co-expression estimates are stable even when constructed from mixed data including both RNA-Seq and microarray expression data. The RNA-Seq information provides a useful complement to the microarray-based maize gene atlas and helps to further understand the dynamics of transcription during maize development. PMID:23637782

  18. cDNA microarray analysis of disk abalone genes in gills and hemocytes after viral hemorrhagic septicemia virus (VHSV) challenge.

    PubMed

    De Zoysa, Mahanama; Nikapitiya, Chamilani; Oh, Chulhong; Whang, Ilson; Shin, Hyun-Jin; Lee, Jehee

    2012-06-01

    A disk abalone Haliotis discus discus 4.2 K cDNA microarray was designed by selecting abalone expressed sequence tags (ESTs). Transcriptional profiles in gills and hemocytes were analyzed upon abalone challenged with viral hemorrhagic septicemia virus (VHSV) in order to select candidates for screening of immune response genes. Among the 4188 genes analyzed, 280 (6.6%) transcripts were changed their expression level in gills and hemocytes against VHSV challenge compared to control animals. Total of 88 and 65 genes were up-regulated in gills and hemocytes, respectively. These genes can be grouped under various immune-functional categories such as transcription factors (Krüppell-like factor; ETS-family transcription factor), inflammatory and apoptosis related genes (TNF superfamily members, Fas ligand), IFN regulatory proteins (IFN-44 like, interferon gamma-inducible lysosomal thiol reductase) and detoxification proteins (glutathione peroxidase). In contrast, 25 and 102 genes were shown down-regulation in gills and hemocytes, respectively. Among the differentially expressed transcripts, considerably higher numbers of ESTs were represented as either hypothetical (unknown) proteins or no GenBank match suggesting those may be novel genes associated with internal defense of abalone.

  19. Comprehensive gene expression microarray analysis of Ets-1 blockade in PC3 prostate cancer cells and correlations with prostate cancer tissues: Insights into genes involved in the metastatic cascade.

    PubMed

    Shaikhibrahim, Zaki; Lindstrot, Andreas; Langer, Berit; Buettner, Reinhard; Wernert, Nicolas

    2011-06-01

    Ets-1 is the prototype of the ETS family of transcription factors and is suggested to play an important role in the malignant progression of prostatic carcinomas. Therefore, in this study we investigated the effect of blocking Ets-1 in PC3 prostate cancer cells on genes involved in the metastatic cascade, and correlated these findings with prostate cancer tissues. Two stable PC3 cell cultures were established by transfection with either an Ets-1 inverse antisense expression vector or a mock control vector. The effect of blocking Ets-1 on genes involved in the metastatic cascade was assessed by a comprehensive gene expression microarray analysis of Ets-1 inverse and mock control cells. Correlating the sets of genes found in the PC3 microarray data with prostate cancer tissues was performed by verifying the genes in a comprehensive gene expression microarray analysis of RNA extracted from laser microdissected normal prostate glands and from carcinoma glands taken from prostate cancer patients. Western blot analysis confirmed the presence of Ets-1 in mock cells and its absence in Ets-1 inverse cells. In the Ets-1 blockade microarray, many differentially expressed genes were found; however, only genes with a greater than 10-fold up- or down-regulation between the Ets-1 blockade and mock control were considered significant. The genes were placed into four groups that play a role in the so-called metastatic cascade based on their known functions in proliferation, apoptosis, migration and angiogenesis. The genes found in the Ets-1 blockade microarray analysis were verified for their presence in the microarray analysis of prostate cancer tissues. Genes found in the microarray analysis of prostate cancer tissues with an >2-fold change and a p-value <0.01 were considered significant. We identified sets of genes that are involved in the metastatic cascade and are known to be implicated in prostate cancer to show changes in the expression patterns due to the Ets-1 blockade in

  20. GEPAS: a web-based resource for microarray gene expression data analysis

    PubMed Central

    Herrero, Javier; Al-Shahrour, Fátima; Díaz-Uriarte, Ramón; Mateos, Álvaro; Vaquerizas, Juan M.; Santoyo, Javier; Dopazo, Joaquín

    2003-01-01

    We present a web-based pipeline for microarray gene expression profile analysis, GEPAS, which stands for Gene Expression Profile Analysis Suite (http://gepas.bioinfo.cnio.es). GEPAS is composed of different interconnected modules which include tools for data pre-processing, two-conditions comparison, unsupervised and supervised clustering (which include some of the most popular methods as well as home made algorithms) and several tests for differential gene expression among different classes, continuous variables or survival analysis. A multiple purpose tool for data mining, based on Gene Ontology, is also linked to the tools, which constitutes a very convenient way of analysing clustering results. On-line tutorials are available from our main web server (http://bioinfo.cnio.es). PMID:12824345

  1. Microarray profiling of gene expression in aging and its alteration by caloric restriction in mice.

    PubMed

    Weindruch, R; Kayo, T; Lee, C K; Prolla, T A

    2001-03-01

    An active research area in biological gerontology concerns the mechanisms by which caloric restriction (CR) retards the aging process in laboratory rodents. We used high density oligonucleotide arrays representing 6347 genes to determine the gene expression profile of the aging process in gastrocnemius muscle of male C57BL/6 mice. Aging resulted in a differential gene expression pattern indicative of a marked stress response and lower expression of metabolic and biosynthetic genes. Most alterations were completely or partially prevented by CR. Transcriptional patterns of muscle from calorie-restricted animals suggest that CR retards the aging process by causing a metabolic shift toward increased protein turnover and decreased macromolecular damage. The use of high density oligonucleotide microarrays provides a new tool to measure biological age on a tissue-specific basis and to evaluate at the molecular level the efficacy of nutritional interventions designed to retard the aging process.

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

    PubMed Central

    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

  3. Combining SSH and cDNA microarrays for rapid identification of differentially expressed genes.

    PubMed

    Yang, G P; Ross, D T; Kuang, W W; Brown, P O; Weigel, R J

    1999-03-15

    Comparing patterns of gene expression in cell lines and tissues has important applications in a variety of biological systems. In this study we have examined whether the emerging technology of cDNA microarrays will allow a high throughput analysis of expression of cDNA clones generated by suppression subtractive hybridization (SSH). A set of cDNA clones including 332 SSH inserts amplified by PCR was arrayed using robotic printing. The cDNA arrays were hybridized with fluorescent labeled probes prepared from RNA from ER-positive (MCF7 and T47D) and ER-negative (MDA-MB-231 and HBL-100) breast cancer cell lines. Ten clones were identified that were over-expressed by at least a factor of five in the ER-positive cell lines. Northern blot analysis confirmed over-expression of these 10 cDNAs. Sequence analysis identified four of these clones as cytokeratin 19, GATA-3, CD24 and glutathione-S-transferase mu-3. Of the remaining six cDNA clones, four clones matched EST sequences from two different genes and two clones were novel sequences. Flow cytometry and immunofluorescence confirmed that CD24 protein was over-expressed in the ER-positive cell lines. We conclude that SSH and microarray technology can be successfully applied to identify differentially expressed genes. This approach allowed the identification of differentially expressed genes without the need to obtain previously cloned cDNAs.

  4. Development of a microarray for two rice subspecies: characterization and validation of gene expression in rice tissues.

    PubMed

    Chen, Jia-Shing; Lin, Shang-Chi; Chen, Chia-Ying; Hsieh, Yen-Ting; Pai, Ping-Hui; Chen, Long-Kung; Lee, Shengwan

    2014-01-08

    Rice is one of the major crop species in the world helping to sustain approximately half of the global population's diet especially in Asia. However, due to the impact of extreme climate change and global warming, rice crop production and yields may be adversely affected resulting in a world food crisis. Researchers have been keen to understand the effects of drought, temperature and other environmental stress factors on rice plant growth and development. Gene expression microarray technology represents a key strategy for the identification of genes and their associated expression patterns in response to stress. Here, we report on the development of the rice OneArray® microarray platform which is suitable for two major rice subspecies, japonica and indica. The rice OneArray® 60-mer, oligonucleotide microarray consists of a total of 21,179 probes covering 20,806 genes of japonica and 13,683 genes of indica. Through a validation study, total RNA isolated from rice shoots and roots were used for comparison of gene expression profiles via microarray examination. The results were submitted to NCBI's Gene Expression Omnibus (GEO). Data can be found under the GEO accession number GSE50844 (http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE50844). A list of significantly differentially expressed genes was generated; 438 shoot-specific genes were identified among 3,138 up-regulated genes, and 463 root-specific genes were found among 3,845 down-regulated genes. GO enrichment analysis demonstrates these results are in agreement with the known physiological processes of the different organs/tissues. Furthermore, qRT-PCR validation was performed on 66 genes, and found to significantly correlate with the microarray results (R = 0.95, p < 0.001***). The rice OneArray® 22 K microarray, the first rice microarray, covering both japonica and indica subspecies was designed and validated in a comprehensive study of gene expression in rice tissues. The rice OneArray® microarray

  5. Development of a microarray for two rice subspecies: characterization and validation of gene expression in rice tissues

    PubMed Central

    2014-01-01

    Background Rice is one of the major crop species in the world helping to sustain approximately half of the global population’s diet especially in Asia. However, due to the impact of extreme climate change and global warming, rice crop production and yields may be adversely affected resulting in a world food crisis. Researchers have been keen to understand the effects of drought, temperature and other environmental stress factors on rice plant growth and development. Gene expression microarray technology represents a key strategy for the identification of genes and their associated expression patterns in response to stress. Here, we report on the development of the rice OneArray® microarray platform which is suitable for two major rice subspecies, japonica and indica. Results The rice OneArray® 60-mer, oligonucleotide microarray consists of a total of 21,179 probes covering 20,806 genes of japonica and 13,683 genes of indica. Through a validation study, total RNA isolated from rice shoots and roots were used for comparison of gene expression profiles via microarray examination. The results were submitted to NCBI’s Gene Expression Omnibus (GEO). Data can be found under the GEO accession number GSE50844 (http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE50844). A list of significantly differentially expressed genes was generated; 438 shoot-specific genes were identified among 3,138 up-regulated genes, and 463 root-specific genes were found among 3,845 down-regulated genes. GO enrichment analysis demonstrates these results are in agreement with the known physiological processes of the different organs/tissues. Furthermore, qRT-PCR validation was performed on 66 genes, and found to significantly correlate with the microarray results (R = 0.95, p < 0.001***). Conclusion The rice OneArray® 22 K microarray, the first rice microarray, covering both japonica and indica subspecies was designed and validated in a comprehensive study of gene expression in

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

    PubMed Central

    Ramdas, Latha; Cogdell, David E; Jia, Jack Y; Taylor, Ellen E; Dunmire, Valerie R; Hu, Limei; Hamilton, Stanley R; Zhang, Wei

    2004-01-01

    Background DNA microarrays using long oligonucleotide probes are widely used to evaluate gene expression in biological samples. These oligonucleotides are pre-synthesized and sequence-optimized to represent specific genes with minimal cross-hybridization to homologous genes. Probe length and concentration are critical factors for signal sensitivity, particularly when genes with various expression levels are being tested. We evaluated the effects of oligonucleotide probe length and concentration on signal intensity measurements of the expression levels of genes in a target sample. Results Selected genes of various expression levels in a single cell line were hybridized to oligonucleotide arrays of four lengths and four concentrations of probes to determine how these critical parameters affected the intensity of the signal representing their expression. We found that oligonucleotides of longer length significantly increased the signals of genes with low-expression in the target. High-expressing gene signals were also boosted but to a lesser degree. Increasing the probe concentration, however, did not linearly increase the signal intensity for either low- or high-expressing genes. Conclusions We conclude that the longer the oligonuclotide probe the better the signal intensities of low expressing genes on oligonucleotide arrays. PMID:15196312

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

    PubMed Central

    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

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

    PubMed

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

    2012-01-01

    Genome scale experiments routinely produce large data sets that require computational analysis, yet there are few student-based labs that illustrate the design and execution of these experiments. In order for students to understand and participate in the genomic world, teaching labs must be available where students generate and analyze large data sets. We present a microarray-based gene expression analysis experiment that is tailored for undergraduate students. The methods in this article describe an expression analysis experiment that can also be applied to CGH and SNP experiments. Factors such as technical difficulty, duration, cost, and availability of materials and equipments are considered in the lab design. The microarray teaching lab is performed in two sessions. The first is an introductory wet bench exercise that allows students to master the basic technical skills. The second builds on the concepts and skills with students acquiring and analyzing the microarray data. This lab exercise familiarizes students with large-scale data experiments and introduces them to the initial analysis steps. Copyright © 2011 Wiley Periodicals, Inc.

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

    PubMed Central

    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. mRNA-Seq and microarray development for the Grooved carpet shell clam, Ruditapes decussatus: a functional approach to unravel host -parasite interaction

    PubMed Central

    2013-01-01

    Background The Grooved Carpet shell clam Ruditapes decussatus is the autochthonous European clam and the most appreciated from a gastronomic and economic point of view. The production is in decline due to several factors such as Perkinsiosis and habitat invasion and competition by the introduced exotic species, the manila clam Ruditapes philippinarum. After we sequenced R. decussatus transcriptome we have designed an oligo microarray capable of contributing to provide some clues on molecular response of the clam to Perkinsiosis. Results A database consisting of 41,119 unique transcripts was constructed, of which 12,479 (30.3%) were annotated by similarity. An oligo-DNA microarray platform was then designed and applied to profile gene expression in R. decussatus heavily infected by Perkinsus olseni. Functional annotation of differentially expressed genes between those two conditionswas performed by gene set enrichment analysis. As expected, microarrays unveil genes related with stress/infectious agents such as hydrolases, proteases and others. The extensive role of innate immune system was also analyzed and effect of parasitosis upon expression of important molecules such as lectins reviewed. Conclusions This study represents a first attempt to characterize Ruditapes decussatus transcriptome, an important marine resource for the European aquaculture. The trancriptome sequencing and consequent annotation will increase the available tools and resources for this specie, introducing the possibility of high throughput experiments such as microarrays analysis. In this specific case microarray approach was used to unveil some important aspects of host-parasite interaction between the Carpet shell clam and Perkinsus, two non-model species, highlighting some genes associated with this interaction. Ample information was obtained to identify biological processes significantly enriched among differentially expressed genes in Perkinsus infected versus non-infected gills. An

  11. mRNA-Seq and microarray development for the Grooved Carpet shell clam, Ruditapes decussatus: a functional approach to unravel host-parasite interaction.

    PubMed

    Leite, Ricardo B; Milan, Massimo; Coppe, Alessandro; Bortoluzzi, Stefania; dos Anjos, António; Reinhardt, Richard; Saavedra, Carlos; Patarnello, Tomaso; Cancela, M Leonor; Bargelloni, Luca

    2013-10-29

    The Grooved Carpet shell clam Ruditapes decussatus is the autochthonous European clam and the most appreciated from a gastronomic and economic point of view. The production is in decline due to several factors such as Perkinsiosis and habitat invasion and competition by the introduced exotic species, the manila clam Ruditapes philippinarum. After we sequenced R. decussatus transcriptome we have designed an oligo microarray capable of contributing to provide some clues on molecular response of the clam to Perkinsiosis. A database consisting of 41,119 unique transcripts was constructed, of which 12,479 (30.3%) were annotated by similarity. An oligo-DNA microarray platform was then designed and applied to profile gene expression in R. decussatus heavily infected by Perkinsus olseni. Functional annotation of differentially expressed genes between those two conditionswas performed by gene set enrichment analysis. As expected, microarrays unveil genes related with stress/infectious agents such as hydrolases, proteases and others. The extensive role of innate immune system was also analyzed and effect of parasitosis upon expression of important molecules such as lectins reviewed. This study represents a first attempt to characterize Ruditapes decussatus transcriptome, an important marine resource for the European aquaculture. The trancriptome sequencing and consequent annotation will increase the available tools and resources for this specie, introducing the possibility of high throughput experiments such as microarrays analysis. In this specific case microarray approach was used to unveil some important aspects of host-parasite interaction between the Carpet shell clam and Perkinsus, two non-model species, highlighting some genes associated with this interaction. Ample information was obtained to identify biological processes significantly enriched among differentially expressed genes in Perkinsus infected versus non-infected gills. An overview on the genes related with

  12. Fully integrated miniature device for automated gene expression DNA microarray processing.

    PubMed

    Liu, Robin Hui; Nguyen, Tai; Schwarzkopf, Kevin; Fuji, H Sho; Petrova, Alla; Siuda, Tony; Peyvan, Kia; Bizak, Michael; Danley, David; McShea, Andy

    2006-03-15

    A DNA microarray with 12,000 features was integrated with a microfluidic cartridge to automate the fluidic handling steps required to carry out a gene expression study of the human leukemia cell line (K562). The fully integrated microfluidic device consists of microfluidic pumps/mixers, fluid channels, reagent chambers, and a DNA microarray silicon chip. Microarray hybridization and subsequent fluidic handling and reactions (including a number of washing and labeling steps) were performed in this fully automated and miniature device before fluorescent image scanning of the microarray chip. Electrochemical micropumps were integrated into the cartridge to provide pumping of liquid solutions. The device was completely self-contained: no external pressure sources, fluid storage, mechanical pumps, mixers, or valves were necessary for fluid manipulation, thus eliminating possible sample contamination and simplifying device operation. Fluidic experiments were performed to study the on-chip washing efficiency and uniformity. A single-color transcriptional analysis of K562 cells with a series of calibration controls (spiked-in controls) to characterize this new platform with regard to sensitivity, specificity, and dynamic range was performed. The device detected sample RNAs with a concentration as low as 0.375 pM. Experiment also showed that the performance of the integrated microfluidic device is comparable with the conventional hybridization chambers with manual operations, indicating that the on-chip fluidic handling (washing and reaction) is highly efficient and can be automated with no loss of performance. The device provides a cost-effective solution to eliminate labor-intensive and time-consuming fluidic handling steps in genomic analysis.

  13. Microarray analysis of gene expression patterns in the leaf during potato tuberization in the potato somatic hybrid Solanum tuberosum and Solanum etuberosum.

    PubMed

    Tiwari, Jagesh Kumar; Devi, Sapna; Sundaresha, S; Chandel, Poonam; Ali, Nilofer; Singh, Brajesh; Bhardwaj, Vinay; Singh, Bir Pal

    2015-06-01

    Genes involved in photoassimilate partitioning and changes in hormonal balance are important for potato tuberization. In the present study, we investigated gene expression patterns in the tuber-bearing potato somatic hybrid (E1-3) and control non-tuberous wild species Solanum etuberosum (Etb) by microarray. Plants were grown under controlled conditions and leaves were collected at eight tuber developmental stages for microarray analysis. A t-test analysis identified a total of 468 genes (94 up-regulated and 374 down-regulated) that were statistically significant (p ≤ 0.05) and differentially expressed in E1-3 and Etb. Gene Ontology (GO) characterization of the 468 genes revealed that 145 were annotated and 323 were of unknown function. Further, these 145 genes were grouped based on GO biological processes followed by molecular function and (or) PGSC description into 15 gene sets, namely (1) transport, (2) metabolic process, (3) biological process, (4) photosynthesis, (5) oxidation-reduction, (6) transcription, (7) translation, (8) binding, (9) protein phosphorylation, (10) protein folding, (11) ubiquitin-dependent protein catabolic process, (12) RNA processing, (13) negative regulation of protein, (14) methylation, and (15) mitosis. RT-PCR analysis of 10 selected highly significant genes (p ≤ 0.01) confirmed the microarray results. Overall, we show that candidate genes induced in leaves of E1-3 were implicated in tuberization processes such as transport, carbohydrate metabolism, phytohormones, and transcription/translation/binding functions. Hence, our results provide an insight into the candidate genes induced in leaf tissues during tuberization in E1-3.

  14. Microarray analysis of changes in cellular gene expression induced by productive infection of primary human astrocytes: implications for HAD.

    PubMed

    Kim, Seon-Young; Li, Jinliang; Bentsman, Galina; Brooks, Andrew I; Volsky, David J

    2004-12-01

    The role of astrocytes in HIV-1 associated dementia (HAD) is not well understood. HIV-1 binds efficiently to astrocytes but infects only a small fraction of the cells in vitro and in vivo. To gain insight into the biology of HIV-1-expressing astrocytes, we productively infected human fetal astrocytes with pseudotyped HIV-1 and employed Affymetrix oligonucleotide microarrays to determine global changes in cellular gene expression at the peak of virus production. With a twofold change as a cutoff, HIV-1 increased transcription of 266 genes in astrocytes and suppressed expression of 468. The functions of highly expressed genes included interferon-mediated antiviral responses (OAS1, IFIT1), intercellular contacts (SH3, glia-derived nexin), cell homing/adhesion (matrix metalloproteinases), and cell-cell signaling (neuropilin 1 and 2). Surprisingly, genes involved in innate immune responses of astrocytes were largely unaffected. The single most significant effect of HIV-1, however, was down-modulation of at least 55 genes involved in control of cell cycle, DNA replication, and cell proliferation, which were overrepresented in these categories with probability scores of 10(-10)-10(-26). Our data suggest that HIV-1 expression in astrocytes profoundly alters host cell biology, with potential consequences for the physiological function of astrocytes during HIV-1 infection in the brain.

  15. Genomic DNA Microarray Analysis: Identification of New Genes Regulated by Light Color in the Cyanobacterium Fremyella diplosiphon

    PubMed Central

    Stowe-Evans, Emily L.; Ford, James; Kehoe, David M.

    2004-01-01

    Many cyanobacteria use complementary chromatic adaptation to efficiently utilize energy from both green and red regions of the light spectrum during photosynthesis. Although previous studies have shown that acclimation to changing light wavelengths involves many physiological responses, research to date has focused primarily on the expression and regulation of genes that encode proteins of the major photosynthetic light-harvesting antennae, the phycobilisomes. We have used two-dimensional gel electrophoresis and genomic DNA microarrays to expand our understanding of the physiology of acclimation to light color in the cyanobacterium Fremyella diplosiphon. We found that the levels of nearly 80 proteins are altered in cells growing in green versus red light and have cloned and positively identified 17 genes not previously known to be regulated by light color in any species. Among these are homologs of genes present in many bacteria that encode well-studied proteins lacking clearly defined functions, such as tspO, which encodes a tryptophan-rich sensory protein, and homologs of genes encoding proteins of clearly defined function in many species, such as nblA and chlL, encoding phycobilisome degradation and chlorophyll biosynthesis proteins, respectively. Our results suggest novel roles for several of these gene products and highly specialized, unique uses for others. PMID:15205436

  16. Gene expression profiling of osteoclast differentiation by combined suppression subtractive hybridization (SSH) and cDNA microarray analysis.

    PubMed

    Rho, Jaerang; Altmann, Curtis R; Socci, Nicholas D; Merkov, Lubomir; Kim, Nacksung; So, Hongseob; Lee, Okbok; Takami, Masamichi; Brivanlou, Ali H; Choi, Yongwon

    2002-08-01

    Bone homeostasis is maintained by the balanced action of bone-forming osteoblasts and bone-resorbing osteoclasts. Multinucleated, mature osteoclasts develop from hematopoietic stem cells via the monocyte-macrophage lineage, which also give rise to macrophages and dendritic cells. Despite their distinct physiologic roles in bone and the immune system, these cell types share many molecular and biochemical features. To provide insights into how osteoclasts differentiate and function to control bone metabolism, we employed a systematic approach to profile patterns of osteoclast-specific gene expression by combining suppression subtractive hybridization (SSH) and cDNA microarray analysis. Here we examined how gene expression profiles of mature osteoclast differ from macrophage or dendritic cells, how gene expression profiles change during osteoclast differentiation, and how Mitf, a transcription factor critical for osteoclast maturation, affects the gene expression profile. This approach revealed a set of genes coordinately regulated for osteoclast function, some of which have previously been implicated in several bone diseases in humans.

  17. Genomic DNA microarray analysis: identification of new genes regulated by light color in the cyanobacterium Fremyella diplosiphon.

    PubMed

    Stowe-Evans, Emily L; Ford, James; Kehoe, David M

    2004-07-01

    Many cyanobacteria use complementary chromatic adaptation to efficiently utilize energy from both green and red regions of the light spectrum during photosynthesis. Although previous studies have shown that acclimation to changing light wavelengths involves many physiological responses, research to date has focused primarily on the expression and regulation of genes that encode proteins of the major photosynthetic light-harvesting antennae, the phycobilisomes. We have used two-dimensional gel electrophoresis and genomic DNA microarrays to expand our understanding of the physiology of acclimation to light color in the cyanobacterium Fremyella diplosiphon. We found that the levels of nearly 80 proteins are altered in cells growing in green versus red light and have cloned and positively identified 17 genes not previously known to be regulated by light color in any species. Among these are homologs of genes present in many bacteria that encode well-studied proteins lacking clearly defined functions, such as tspO, which encodes a tryptophan-rich sensory protein, and homologs of genes encoding proteins of clearly defined function in many species, such as nblA and chlL, encoding phycobilisome degradation and chlorophyll biosynthesis proteins, respectively. Our results suggest novel roles for several of these gene products and highly specialized, unique uses for others.

  18. Phylogenetic Modeling of Heterogeneous Gene-Expression Microarray Data from Cancerous Specimens

    PubMed Central

    Abu-Asab, Mones S.; Chaouchi, Mohamed

    2008-01-01

    Abstract The qualitative dimension of gene expression data and its heterogeneous nature in cancerous specimens can be accounted for by phylogenetic modeling that incorporates the directionality of altered gene expressions, complex patterns of expressions among a group of specimens, and data-based rather than specimen-based gene linkage. Our phylogenetic modeling approach is a double algorithmic technique that includes polarity assessment that brings out the qualitative value of the data, followed by maximum parsimony analysis that is most suitable for the data heterogeneity of cancer gene expression. We demonstrate that polarity assessment of expression values into derived and ancestral states, via outgroup comparison, reduces experimental noise; reveals dichotomously expressed asynchronous genes; and allows data pooling as well as comparability of intra- and interplatforms. Parsimony phylogenetic analysis of the polarized values produces a multidimensional classification of specimens into clades that reveal shared derived gene expressions (the synapomorphies); provides better assessment of ontogenic pathways and phyletic relatedness of specimens; efficiently utilizes dichotomously expressed genes; produces highly predictive class recognition; illustrates gene linkage and multiple developmental pathways; provides higher concordance between gene lists; and projects the direction of change among specimens. Further implication of this phylogenetic approach is that it may transform microarray into diagnostic, prognostic, and predictive tool. PMID:18699725

  19. Phylogenetic modeling of heterogeneous gene-expression microarray data from cancerous specimens.

    PubMed

    Abu-Asab, Mones S; Chaouchi, Mohamed; Amri, Hakima

    2008-09-01

    The qualitative dimension of gene expression data and its heterogeneous nature in cancerous specimens can be accounted for by phylogenetic modeling that incorporates the directionality of altered gene expressions, complex patterns of expressions among a group of specimens, and data-based rather than specimen-based gene linkage. Our phylogenetic modeling approach is a double algorithmic technique that includes polarity assessment that brings out the qualitative value of the data, followed by maximum parsimony analysis that is most suitable for the data heterogeneity of cancer gene expression. We demonstrate that polarity assessment of expression values into derived and ancestral states, via outgroup comparison, reduces experimental noise; reveals dichotomously expressed asynchronous genes; and allows data pooling as well as comparability of intra- and interplatforms. Parsimony phylogenetic analysis of the polarized values produces a multidimensional classification of specimens into clades that reveal shared derived gene expressions (the synapomorphies); provides better assessment of ontogenic pathways and phyletic relatedness of specimens; efficiently utilizes dichotomously expressed genes; produces highly predictive class recognition; illustrates gene linkage and multiple developmental pathways; provides higher concordance between gene lists; and projects the direction of change among specimens. Further implication of this phylogenetic approach is that it may transform microarray into diagnostic, prognostic, and predictive tool.

  20. Identification and optimization of classifier genes from multi-class earthworm microarray dataset.

    PubMed

    Li, Ying; Wang, Nan; Perkins, Edward J; Zhang, Chaoyang; Gong, Ping

    2010-10-28

    Monitoring, assessment and prediction of environmental risks that chemicals pose demand rapid and accurate diagnostic assays. A variety of toxicological effects have been associated with explosive compounds TNT and RDX. One important goal of microarray experiments is to discover novel biomarkers for toxicity evaluation. We have developed an earthworm microarray containing 15,208 unique oligo probes and have used it to profile gene expression in 248 earthworms exposed to TNT, RDX or neither. We assembled a new machine learning pipeline consisting of several well-established feature filtering/selection and classification techniques to analyze the 248-array dataset in order to construct classifier models that can separate earthworm samples into three groups: control, TNT-treated, and RDX-treated. First, a total of 869 genes differentially expressed in response to TNT or RDX exposure were identified using a univariate statistical algorithm of class comparison. Then, decision tree-based algorithms were applied to select a subset of 354 classifier genes, which were ranked by their overall weight of significance. A multiclass support vector machine (MC-SVM) method and an unsupervised K-mean clustering method were applied to independently refine the classifier, producing a smaller subset of 39 and 30 classifier genes, separately, with 11 common genes being potential biomarkers. The combined 58 genes were considered the refined subset and used to build MC-SVM and clustering models with classification accuracy of 83.5% and 56.9%, respectively. This study demonstrates that the machine learning approach can be used to identify and optimize a small subset of classifier/biomarker genes from high dimensional datasets and generate classification models of acceptable precision for multiple classes.

  1. Mapping autosomal recessive intellectual disability: combined microarray and exome sequencing identifies 26 novel candidate genes in 192 consanguineous families.

    PubMed

    Harripaul, R; Vasli, N; Mikhailov, A; Rafiq, M A; Mittal, K; Windpassinger, C; Sheikh, T I; Noor, A; Mahmood, H; Downey, S; Johnson, M; Vleuten, K; Bell, L; Ilyas, M; Khan, F S; Khan, V; Moradi, M; Ayaz, M; Naeem, F; Heidari, A; Ahmed, I; Ghadami, S; Agha, Z; Zeinali, S; Qamar, R; Mozhdehipanah, H; John, P; Mir, A; Ansar, M; French, L; Ayub, M; Vincent, J B

    2017-04-11

    Approximately 1% of the global population is affected by intellectual disability (ID), and the majority receive no molecular diagnosis. Previous studies have indicated high levels of genetic heterogeneity, with estimates of more than 2500 autosomal ID genes, the majority of which are autosomal recessive (AR). Here, we combined microarray genotyping, homozygosity-by-descent (HBD) mapping, copy number variation (CNV) analysis, and whole exome sequencing (WES) to identify disease genes/mutations in 192 multiplex Pakistani and Iranian consanguineous families with non-syndromic ID. We identified definite or candidate mutations (or CNVs) in 51% of families in 72 different genes, including 26 not previously reported for ARID. The new ARID genes include nine with loss-of-function mutations (ABI2, MAPK8, MPDZ, PIDD1, SLAIN1, TBC1D23, TRAPPC6B, UBA7 and USP44), and missense mutations include the first reports of variants in BDNF or TET1 associated with ID. The genes identified also showed overlap with de novo gene sets for other neuropsychiatric disorders. Transcriptional studies showed prominent expression in the prenatal brain. The high yield of AR mutations for ID indicated that this approach has excellent clinical potential and should inform clinical diagnostics, including clinical whole exome and genome sequencing, for populations in which consanguinity is common. As with other AR disorders, the relevance will also apply to outbred populations.Molecular Psychiatry advance online publication, 11 April 2017; doi:10.1038/mp.2017.60.

  2. Identification and Functional Analysis of Light-Responsive Unique Genes and Gene Family Members in Rice

    PubMed Central

    Jung, Ki-Hong; Lee, Jinwon; Dardick, Chris; Seo, Young-Su; Cao, Peijian; Canlas, Patrick; Phetsom, Jirapa; Xu, Xia; Ouyang, Shu; An, Kyungsook; Cho, Yun-Ja; Lee, Geun-Cheol; Lee, Yoosook; An, Gynheung; Ronald, Pamela C.

    2008-01-01

    Functional redundancy limits detailed analysis of genes in many organisms. Here, we report a method to efficiently overcome this obstacle by combining gene expression data with analysis of gene-indexed mutants. Using a rice NSF45K oligo-microarray to compare 2-week-old light- and dark-grown rice leaf tissue, we identified 365 genes that showed significant 8-fold or greater induction in the light relative to dark conditions. We then screened collections of rice T-DNA insertional mutants to identify rice lines with mutations in the strongly light-induced genes. From this analysis, we identified 74 different lines comprising two independent mutant lines for each of 37 light-induced genes. This list was further refined by mining gene expression data to exclude genes that had potential functional redundancy due to co-expressed family members (12 genes) and genes that had inconsistent light responses across other publicly available microarray datasets (five genes). We next characterized the phenotypes of rice lines carrying mutations in ten of the remaining candidate genes and then carried out co-expression analysis associated with these genes. This analysis effectively provided candidate functions for two genes of previously unknown function and for one gene not directly linked to the tested biochemical pathways. These data demonstrate the efficiency of combining gene family-based expression profiles with analyses of insertional mutants to identify novel genes and their functions, even among members of multi-gene families. PMID:18725934