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Sample records for functional gene microarray

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

    PubMed

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

    2007-06-01

    Soil-borne microbial communities were examined via a functional gene microarray approach across a southern polar latitudinal gradient to gain insight into the environmental factors steering soil N- and C-cycling in terrestrial Antarctic ecosystems. The abundance and diversity of functional gene families were studied for soil-borne microbial communities inhabiting a range of environments from 51 degrees S (cool temperate-Falkland Islands) to 72 degrees S (cold rock desert-Coal Nunatak). The recently designed functional gene array used contains 24,243 oligonucleotide probes and covers >10,000 genes in >150 functional groups involved in nitrogen, carbon, sulfur and phosphorus cycling, metal reduction and resistance and organic contaminant degradation (He et al. 2007). The detected N- and C-cycle genes were significantly different across different sampling locations and vegetation types. A number of significant trends were observed regarding the distribution of key gene families across the environments examined. For example, the relative detection of cellulose degradation genes was correlated with temperature, and microbial C-fixation genes were more present in plots principally lacking vegetation. With respect to the N-cycle, denitrification genes were linked to higher soil temperatures, and N2-fixation genes were linked to plots mainly vegetated by lichens. These microarray-based results were confirmed for a number of gene families using specific real-time PCR, enzymatic assays and process rate measurements. The results presented demonstrate the utility of an integrated functional gene microarray approach in detecting shifts in functional community properties in environmental samples and provide insight into the forces driving important processes of terrestrial Antarctic nutrient cycling. PMID:18043626

  2. 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.

  3. Microarrays of lentiviruses for gene function screens in immortalized and primary cells.

    PubMed

    Bailey, Steve N; Ali, Siraj M; Carpenter, Anne E; Higgins, Caitlin O; Sabatini, David M

    2006-02-01

    Here we describe lentivirus-infected cell microarrays for the high-throughput screening of gene function in mammalian cells. To create these arrays, we cultured mammalian cells on glass slides 'printed' with lentiviruses pseudotyped as vesicular stomatitis virus glycoprotein, which encode short hairpin RNA or cDNA. Cells that land on the printed 'features' become infected with lentivirus, creating a living array of stably transduced cell clusters within a monolayer of uninfected cells. The small size of the features of the microarrays (300 microm in diameter) allows high-density spotting of lentivirus, permitting thousands of distinct parallel infections on a single glass slide. Because lentiviruses have a wide cellular tropism, including primary cells, lentivirus-infected cell microarrays can be used as a platform for high-throughput screening in a variety of cell types. PMID:16432521

  4. 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. PMID:25762300

  5. Functional Protein Microarray Technology

    PubMed Central

    Hu, Shaohui; Xie, Zhi; Qian, Jiang; Blackshaw, Seth; Zhu, Heng

    2010-01-01

    Functional protein microarrays are emerging as a promising new tool for large-scale and high-throughput studies. In this article, we will review their applications in basic proteomics research, where various types of assays have been developed to probe binding activities to other biomolecules, such as proteins, DNA, RNA, small molecules, and glycans. We will also report recent progress of using functional protein microarrays in profiling protein posttranslational modifications, including phosphorylation, ubiquitylation, acetylation, and nitrosylation. Finally, we will discuss potential of functional protein microarrays in biomarker identification and clinical diagnostics. We strongly believe that functional protein microarrays will soon become an indispensible and invaluable tool in proteomics research and systems biology. PMID:20872749

  6. Gene function analysis in osteosarcoma based on microarray gene expression profiling

    PubMed Central

    Zhao, Liang; Zhang, Jinghua; Tan, Hongyu; Wang, Weidong; Liu, Yilin; Song, Ruipeng; Wang, Limin

    2015-01-01

    Osteosa rcoma is an aggressive malignant neoplasm that exhibits osteoblastic differentiation and produces malignant osteoid. The aim of this study was to find feature genes associated with osteosarcoma and correlative gene functions which can distinguish cancer tissues from non-tumor tissues. Gene expression profile GSE14359 was downloaded from Gene Expression Omnibus (GEO) database, including 10 osteosarcoma samples and 2 normal samples. The differentially expressed genes (DEGs) between osteosarcoma and normal specimens were identified using limma package of R. DAVID was applied to mine osteosarcoma associated genes and analyze the GO enrichment on gene functions and KEGG pathways. Then, corresponding protein-protein interaction (PPI) network of DEGs was constructed based on the data collected from STRING datasets. Principal component of top10 DEGs and PPI network of top 20 DEGs were further analyzed. Finally, transcription factors were predicted by uploading the two groups of DEGs to TfactS database. A total of 437 genes, including 114 up-regulated genes and 323 down-regulated genes, were filtered as DEGs, of which 46 were associated with osteosarcoma by Disease Module. GO and KEGG pathway enrichment analysis showed that genes mainly affected the process of immune response and the development of skeletal and vascular system. The PPI network analysis elucidated that hemoglobin and histocompatibility proteins and enzymes, which were associated with immune response, were closely associated with osteosarcoma. Transcription factors MYC and SP1 were predicted to be significantly related to osteosarcoma. The discovery of gene functions and transcription factors has the potential to use in clinic for diagnosis of osteosarcoma in future. In addition, it will pave the way to studying mechanism and effective therapies for osteosarcoma. PMID:26379830

  7. 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.

  8. Harnessing the power of gene microarrays for the study of brain aging and Alzheimer's disease: statistical reliability and functional correlation.

    PubMed

    Blalock, E M; Chen, K-C; Stromberg, A J; Norris, C M; Kadish, I; Kraner, S D; Porter, N M; Landfield, P W

    2005-11-01

    During normal brain aging, numerous alterations develop in the physiology, biochemistry and structure of neurons and glia. Aging changes occur in most brain regions and, in the hippocampus, have been linked to declining cognitive performance in both humans and animals. Age-related changes in hippocampal regions also may be harbingers of more severe decrements to come from neurodegenerative disorders such as Alzheimer's disease (AD). However, unraveling the mechanisms underlying brain aging, AD and impaired function has been difficult because of the complexity of the networks that drive these aging-related changes. Gene microarray technology allows massively parallel analysis of most genes expressed in a tissue, and therefore is an important new research tool that potentially can provide the investigative power needed to address the complexity of brain aging/neurodegenerative processes. However, along with this new analytic power, microarrays bring several major bioinformatics and resource problems that frequently hinder the optimal application of this technology. In particular, microarray analyses generate extremely large and unwieldy data sets and are subject to high false positive and false negative rates. Concerns also have been raised regarding their accuracy and uniformity. Furthermore, microarray analyses can result in long lists of altered genes, most of which may be difficult to evaluate for functional relevance. These and other problems have led to some skepticism regarding the reliability and functional usefulness of microarray data and to a general view that microarray data should be validated by an independent method. Given recent progress, however, we suggest that the major problem for current microarray research is no longer validity of expression measurements, but rather, the reliability of inferences from the data, an issue more appropriately redressed by statistical approaches than by validation with a separate method. If tested using statistically

  9. Phenotype MicroArrays for High-Throughput Phenotypic Testing and Assay of Gene Function

    PubMed Central

    Bochner, Barry R.; Gadzinski, Peter; Panomitros, Eugenia

    2001-01-01

    The bacterium Escherichia coli is used as a model cellular system to test and validate a new technology called Phenotype MicroArrays (PMs). PM technology is a high-throughput technology for simultaneous testing of a large number of cellular phenotypes. It consists of preconfigured well arrays in which each well tests a different cellular phenotype and an automated instrument that continuously monitors and records the response of the cells in all wells of the arrays. For example, nearly 700 phenotypes of E. coli can be assayed by merely pipetting a cell suspension into seven microplate arrays. PMs can be used to directly assay the effects of genetic changes on cells, especially gene knock-outs. Here, we provide data on phenotypic analysis of six strains and show that we can detect expected phenotypes as well as, in some cases, unexpected phenotypes. PMID:11435407

  10. Pineal Function: Impact of Microarray Analysis

    PubMed Central

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

    2009-01-01

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

  11. Facilitating functional annotation of chicken microarray data

    PubMed Central

    2009-01-01

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

  12. 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.

  13. Functional microarray analysis of differentially expressed genes in granulosa cells from women with polycystic ovary syndrome related to MAPK/ERK signaling

    PubMed Central

    Lan, Chen-Wei; Chen, Mei-Jou; Tai, Kang-Yu; Yu, Danny CW; Yang, Yu-Chieh; Jan, Pey-Shynan; Yang, Yu-Shih; Chen, Hsin-Fu; Ho, Hong-Nerng

    2015-01-01

    Polycystic ovary syndrome (PCOS) is the most common endocrine disorder in women of reproductive age. Although its aetiology and pathogenesis remain unclear, recent studies suggest that the dysfunction of granulosa cells may partly be responsible. This study aimed to use cDNA microarray technology to compare granulosa cell gene expression profiles in women with and without PCOS to identify genes that may be aetiologically implicated in the pathogenesis of PCOS. The study cohort included 12 women undergoing in vitro fertilization, six with PCOS and six without PCOS. Differential gene expression profiles were classified by post-analyses of microarray data, followed by western blot analyses to confirm the microarray data of selected genes. In total, 243 genes were differentially expressed (125 upregulated and 118 downregulated) between the PCOS and non-PCOS granulosa cells. These genes are involved in reproductive system development, amino acid metabolism and cellular development and proliferation. Comparative analysis revealed genes involved in the mitogen-activated protein kinase/extracellular regulated kinase (MAPK/ERK) signaling pathways. Western blot analyses confirmed that mitogen-activated protein kinase kinase kinase 4 and phospho-ERK1/2 were decreased in PCOS granulosa cells. This study identified candidate genes involved in MAPK/ERK signaling pathways that may influence the function of granulosa cells in PCOS. PMID:26459919

  14. 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.

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

    PubMed

    Ward, Bess B; Eveillard, Damien; Kirshtein, Julie D; Nelson, Joshua D; Voytek, Mary A; Jackson, George A

    2007-10-01

    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. PMID:17803777

  16. 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.

  17. 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

  18. Functional analysis of 1440 Escherichia coli genes using the combination of knock-out library and phenotype microarrays.

    PubMed

    Ito, Mikito; Baba, Tomoya; Mori, Hirotada; Mori, Hideo

    2005-07-01

    Escherichia coli is one of the best elucidated organisms. However, about 40% of E. coli genes have not been assigned to their function yet. We analyzed 1440 single gene knock-out mutants using the GN2-MicroPlate, which permits assay of 95 carbon-source utilizations simultaneously. In the knock-out library there are 1044 of so called y-genes with no apparent function. The raw dataset was analyzed and genes were interrelated by the clustering method of the GeneSpring software. In the resulted dendrogram of genes, a group of genes with known and related function tended to be assembled into a cluster. Our clustering method would be useful for functional assignment of so called y-genes with no apparent function, since the resulted dendrogram could connect y-genes to phenotype and function of well-studied genes.

  19. 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…

  20. Identification of a Novel Uromodulin-Like Gene Related to Predator-Induced Bulgy Morph in Anuran Tadpoles by Functional Microarray Analysis

    PubMed Central

    Mori, Tsukasa; Kawachi, Hiroko; Imai, Chiharu; Sugiyama, Manabu; Kurata, Youichi; Kishida, Osamu; Nishimura, Kinya

    2009-01-01

    Tadpoles of the anuran species Rana pirica can undergo predator-specific morphological responses. Exposure to a predation threat by larvae of the salamander Hynobius retardatus results in formation of a bulgy body (bulgy morph) with a higher tail. The tadpoles revert to a normal phenotype upon removal of the larval salamander threat. Although predator-induced phenotypic plasticity is of major interest to evolutionary ecologists, the molecular and physiological mechanisms that control this response have yet to be elucidated. In a previous study, we identified various genes that are expressed in the skin of the bulgy morph. However, it proved difficult to determine which of these were key genes in the control of gene expression associated with the bulgy phenotype. Here, we show that a novel gene plays an important role in the phenotypic plasticity producing the bulgy morph. A functional microarray analysis using facial tissue samples of control and bulgy morph tadpoles identified candidate functional genes for predator-specific morphological responses. A larger functional microarray was prepared than in the previous study and used to analyze mRNAs extracted from facial and brain tissues of tadpoles from induction-reversion experiments. We found that a novel uromodulin-like gene, which we name here pirica, was up-regulated and that keratin genes were down-regulated as the period of exposure to larval salamanders increased. Pirica consists of a 1296 bp open reading frame, which is putatively translated into a protein of 432 amino acids. The protein contains a zona pellucida domain similar to that of proteins that function to control water permeability. We found that the gene was expressed in the superficial epidermis of the tadpole skin. PMID:19529781

  1. Development of a whole community genome amplification-assisted DNA microarray method to detect functional genes involved in the nitrogen cycle.

    PubMed

    Inoue, Daisuke; Pang, Junqin; Matsuda, Masami; Sei, Kazunari; Nishida, Kei; Ike, Michihiko

    2014-11-01

    A novel DNA microarray analysis targeting key functional genes involved in most nitrogen cycling reactions was developed to comprehensively analyze microbial populations associated with the nitrogen cycle. The developed microarray contained 876 oligonucleotide probes based on the nucleotide sequences of the nif, amo, hao/hzo, nap, nar, nirK, nirS, nrf, cnor, qnor and nos genes. An analytical method combining detection by the designed microarray with whole community genome amplification was then applied to monitor the nitrogen cycling microorganisms in river water and wastewater treatment sludge samples. The developed method revealed that nitrogen cycling microorganisms in river water appeared to become less diverse in response to input of effluent from municipal wastewater treatment plants. Additionally, the nitrogen cycling community associated with anaerobic ammonium oxidation and partial nitrification reactors could be reasonably analyzed by the developed method. However, the results obtained for two activated sludge samples from municipal wastewater treatment plants with almost equivalent wastewater treatment performance differed greatly from each other. These results suggested that the developed method is useful for comprehensive analysis of nitrogen cycling microorganisms, although its applicability to complex samples with abundant untargeted populations should be further examined.

  2. Relevant and significant supervised gene clusters for microarray cancer classification.

    PubMed

    Maji, Pradipta; Das, Chandra

    2012-06-01

    An important application of microarray data in functional genomics is to classify samples according to their gene expression profiles such as to classify cancer versus normal samples or to classify different types or subtypes of cancer. One of the major tasks with gene expression data is to find co-regulated gene groups whose collective expression is strongly associated with sample categories. In this regard, a gene clustering algorithm is proposed to group genes from microarray data. It directly incorporates the information of sample categories in the grouping process for finding groups of co-regulated genes with strong association to the sample categories, yielding a supervised gene clustering algorithm. The average expression of the genes from each cluster acts as its representative. Some significant representatives are taken to form the reduced feature set to build the classifiers for cancer classification. The mutual information is used to compute both gene-gene redundancy and gene-class relevance. The performance of the proposed method, along with a comparison with existing methods, is studied on six cancer microarray data sets using the predictive accuracy of naive Bayes classifier, K-nearest neighbor rule, and support vector machine. An important finding is that the proposed algorithm is shown to be effective for identifying biologically significant gene clusters with excellent predictive capability. PMID:22552589

  3. Microarray-based functional gene analysis of soil microbial communities during ozonation and biodegradation of crude oil.

    PubMed

    Liang, Yuting; Nostrand, Joy D Van; Wang, Jian; Zhang, Xu; Zhou, Jizhong; Li, Guanghe

    2009-04-01

    Ozonation with a subsequent biodegradation treatment was performed to remove recalcitrant organic compounds from long-term weathered crude oil contaminated soil. Samples were analyzed by GC/MS and column chromatography to monitor changes in crude oil composition. A functional gene array was used to examine microbial community dynamics. After a 6h ozonation treatment with a constant concentration of 10mgO(3)L(-1) at a flow rate of 2.0Lmin(-1), an average removal of crude oil was 22%. The concentration of long-chain n-alkanes (C(19)-C(28)) decreased while more biodegradable short-chain alkanes (C(14)-C(16)), n-aldehydes (C(13)-C(20)), and n-monocarboxylic acids (C(9)-C(20)) appeared. In the subsequent direct biodegradation and bioaugmentation, an additional 12-20% of residuals were removed. The total microbial functional gene numbers and overall genetic diversity decreased after ozonation. Also, most of the key functional genes pertaining to carbon, nitrogen, and sulfur cycling and organic contaminant degradation decreased, ranging from 20% to below the detection limit. However, in the subsequent biodegradation treatments, with and without bioaugmentation, the abundance of key genes in most functional groups recovered. This study provided insight into changes in crude oil composition and microbial functional genes responses during ozonation and bioremediation treatments. These changes demonstrate the feasibility of an integrated ozonation and biodegradation treatment to remove recalcitrant soil contaminants.

  4. 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

  5. Repeatability of published microarray gene expression analyses.

    PubMed

    Ioannidis, John P A; Allison, David B; Ball, Catherine A; Coulibaly, Issa; Cui, Xiangqin; Culhane, Aedín C; Falchi, Mario; Furlanello, Cesare; Game, Laurence; Jurman, Giuseppe; Mangion, Jon; Mehta, Tapan; Nitzberg, Michael; Page, Grier P; Petretto, Enrico; van Noort, Vera

    2009-02-01

    Given the complexity of microarray-based gene expression studies, guidelines encourage transparent design and public data availability. Several journals require public data deposition and several public databases exist. However, not all data are publicly available, and even when available, it is unknown whether the published results are reproducible by independent scientists. Here we evaluated the replication of data analyses in 18 articles on microarray-based gene expression profiling published in Nature Genetics in 2005-2006. One table or figure from each article was independently evaluated by two teams of analysts. We reproduced two analyses in principle and six partially or with some discrepancies; ten could not be reproduced. The main reason for failure to reproduce was data unavailability, and discrepancies were mostly due to incomplete data annotation or specification of data processing and analysis. Repeatability of published microarray studies is apparently limited. More strict publication rules enforcing public data availability and explicit description of data processing and analysis should be considered.

  6. 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

  7. Profiling protein function with small molecule microarrays

    PubMed Central

    Winssinger, Nicolas; Ficarro, Scott; Schultz, Peter G.; Harris, Jennifer L.

    2002-01-01

    The regulation of protein function through posttranslational modification, local environment, and protein–protein interaction is critical to cellular function. The ability to analyze on a genome-wide scale protein functional activity rather than changes in protein abundance or structure would provide important new insights into complex biological processes. Herein, we report the application of a spatially addressable small molecule microarray to an activity-based profile of proteases in crude cell lysates. The potential of this small molecule-based profiling technology is demonstrated by the detection of caspase activation upon induction of apoptosis, characterization of the activated caspase, and inhibition of the caspase-executed apoptotic phenotype using the small molecule inhibitor identified in the microarray-based profile. PMID:12167675

  8. 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

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

    PubMed Central

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

    2016-01-01

    Here, we developed a cell defined siRNA microarray (CDSM) for human bone marrow stromal cells (hBMSCs) designed to control the culture of cells inside the spot area without reducing the efficiency of siRNA silencing, “Development of a cell-defined siRNA microarray for analysis of gene functionin human bone marrow stromal cells” (Kim et al., 2016 [1]). First, we confirmed that p65 protein inhibition efficiency was maintained when hBMSCs were culture for 7 days on the siRNA spot, and siRNA spot activity remained in spite of long term storage (10 days and 2 months). Additionally, we confirmed p65 protein inhibition in U2OS cells after 48 h reverse transfection. PMID:27054175

  10. Estimating Gene Signals From Noisy Microarray Images

    PubMed Central

    Sarder, Pinaki; Davis, Paul H.; Stanley, Samuel L.

    2016-01-01

    In oligonucleotide microarray experiments, noise is a challenging problem, as biologists now are studying their organisms not in isolation but in the context of a natural environment. In low photomultiplier tube (PMT) voltage images, weak gene signals and their interactions with the background fluorescence noise are most problematic. In addition, nonspecific sequences bind to array spots intermittently causing inaccurate measurements. Conventional techniques cannot precisely separate the foreground and the background signals. In this paper, we propose analytically based estimation technique. We assume a priori spot-shape information using a circular outer periphery with an elliptical center hole. We assume Gaussian statistics for modeling both the foreground and background signals. The mean of the foreground signal quantifies the weak gene signal corresponding to the spot, and the variance gives the measure of the undesired binding that causes fluctuation in the measurement. We propose a foreground-signal and shape-estimation algorithm using the Gibbs sampling method. We compare our developed algorithm with the existing Mann–Whitney (MW)- and expectation maximization (EM)/iterated conditional modes (ICM)-based methods. Our method outperforms the existing methods with considerably smaller mean-square error (MSE) for all signal-to-noise ratios (SNRs) in computer-generated images and gives better qualitative results in low-SNR real-data images. Our method is computationally relatively slow because of its inherent sampling operation and hence only applicable to very noisy-spot images. In a realistic example using our method, we show that the gene-signal fluctuations on the estimated foreground are better observed for the input noisy images with relatively higher undesired bindings. PMID:18556262

  11. DNA Microarray Analysis of Estrogen-Responsive Genes.

    PubMed

    Eyster, Kathleen M

    2016-01-01

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

  12. Printing Proteins as Microarrays for High-Throughput Function Determination

    NASA Astrophysics Data System (ADS)

    MacBeath, Gavin; Schreiber, Stuart L.

    2000-09-01

    Systematic efforts are currently under way to construct defined sets of cloned genes for high-throughput expression and purification of recombinant proteins. To facilitate subsequent studies of protein function, we have developed miniaturized assays that accommodate extremely low sample volumes and enable the rapid, simultaneous processing of thousands of proteins. A high-precision robot designed to manufacture complementary DNA microarrays was used to spot proteins onto chemically derivatized glass slides at extremely high spatial densities. The proteins attached covalently to the slide surface yet retained their ability to interact specifically with other proteins, or with small molecules, in solution. Three applications for protein microarrays were demonstrated: screening for protein-protein interactions, identifying the substrates of protein kinases, and identifying the protein targets of small molecules.

  13. Emerging Use of Gene Expression Microarrays in Plant Physiology

    DOE PAGESBeta

    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

  14. Emerging Use of Gene Expression Microarrays in Plant Physiology

    PubMed Central

    Difazio, Stephen P.

    2003-01-01

    Microarrays have become an important technology for the global analysis of gene expression in humans, animals, plants, and microbes. Implemented in the context of a well-designed experiment, cDNA and oligonucleotide arrays can provide highthroughput, simultaneous analysis of transcript abundance for hundreds, if not thousands, of genes. However, despite widespread acceptance, the use of microarrays as a tool to better understand processes of interest to the plant physiologist is still being explored. To help illustrate current uses of microarrays in the plant sciences, several case studies that we believe demonstrate the emerging application of gene expression arrays in plant physiology were selected from among the many posters and presentations at the 2003 Plant and Animal Genome XI Conference. Based on this survey, microarrays are being used to assess gene expression in plants exposed to the experimental manipulation of air temperature, soil water content and aluminium concentration in the root zone. Analysis often includes characterizing transcript profiles for multiple post-treatment sampling periods and categorizing genes with common patterns of response using hierarchical clustering techniques. In addition, microarrays are also providing insights into developmental changes in gene expression associated with fibre and root elongation in cotton and maize, respectively. Technical and analytical limitations of microarrays are discussed and projects attempting to advance areas of microarray design and data analysis are highlighted. Finally, although much work remains, we conclude that microarrays are a valuable tool for the plant physiologist interested in the characterization and identification of individual genes and gene families with potential application in the fields of agriculture, horticulture and forestry. PMID:18629133

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

    PubMed Central

    Yang, Jianji; Cohen, Aaron; Hersh, William

    2009-01-01

    Background Summarization of gene information in the literature has the potential to help genomics researchers translate basic research into clinical benefits. Gene expression microarrays have been used to study biomarkers for disease and discover novel types of therapeutics and the task of finding information in journal articles on sets of genes is common for translational researchers working with microarray data. However, manually searching and scanning the literature references returned from PubMed is a time-consuming task for scientists. We built and evaluated an automatic summarizer of information on genes studied in microarray experiments. The Gene Information Clustering and Summarization System (GICSS) is a system that integrates two related steps of the microarray data analysis process: functional gene clustering and gene information gathering. The system evaluation was conducted during the process of genomic researchers analyzing their own experimental microarray datasets. Results The clusters generated by GICSS were validated by scientists during their microarray analysis process. In addition, presenting sentences in the abstract provided significantly more important information to the users than just showing the title in the default PubMed format. Conclusion The evaluation results suggest that GICSS can be useful for researchers in genomic area. In addition, the hybrid evaluation method, partway between intrinsic and extrinsic system evaluation, may enable researchers to gauge the true usefulness of the tool for the scientists in their natural analysis workflow and also elicit suggestions for future enhancements. Availability GICSS can be accessed online at: PMID:19208193

  16. A methodical microarray design enables surveying of expression of a broader range of genes in Ciona intestinalis.

    PubMed

    Matsumae, Hiromi; Hamada, Mayuko; Fujie, Manabu; Niimura, Yoshihito; Tanaka, Hiroshi; Kawashima, Takeshi

    2013-04-25

    We provide a new oligo-microarray for Ciona intestinalis, based on the NimbleGen 12-plex×135k format. The array represents 106,285 probes, which is more than double the probe number of the currently available 44k microarray. These probes cover 99.2% of the transcripts in the KyotoHoya (KH) models, published in 2008, and they contain 81.1% of the entries in the UniGene database that are not included in the KH models. In this paper, we show that gene expression levels measured by this new 135k microarray are highly correlated with those obtained by the existing 44k microarray for genes common to both arrays. We also investigated gene expression using samples obtained from the ovary and the neural complex of adult C. intestinalis, showing that the expression of tissue-specific genes is consistent with previous reports. Approximately half of the highly expressed genes identified in the 135k microarray are not included in the previous microarray. The high coverage of gene models by this microarray made it possible to identify splicing variants for a given transcript. The 135k microarray is useful in investigating the functions of genes that are not yet well characterized. Detailed information about this 135k microarray is accessible at no charge from supplemental materials, NCBI Gene Expression Omnibus (GEO), and http://marinegenomics.oist.jp.

  17. Functional study of Capsicum annuum fatty acid desaturase 1 cDNA clone induced by Tobacco mosaic virus via microarray and virus-induced gene silencing.

    PubMed

    Kim, Ki-Jeong; Lim, Jee Hyuck; Lee, Sanghyeob; Kim, Young Jin; Choi, Soo Bok; Lee, Min Kyung; Choi, Doil; Paek, Kyung-Hee

    2007-10-26

    A series of microarray analyses employing the expressed sequence tags (ESTs) of hot pepper was conducted in an effort to elucidate the molecular mechanisms inherent to hypersensitive response (HR) by viral or bacterial pathogens. There were 2535 ESTs exhibiting differential expression (over 2-fold changes) among about 5000 ESTs during viral or bacterial response. Further, via virus-induced gene silencing (VIGS) and TMV-infection studies, we were able to isolate several ESTs, which may be relevant to defense response against TMV. Of these ESTs, Capsicum annuum fatty acid desaturase 1 (CaFAD1) showed the distinct phenotype against TMV infection and thus was subjected to further study. CaFAD1-silenced plants showed weaker resistance against TMV-P0 infection compared to TRV2 control plants. Also the suppression of FAD1 expression caused blocking of cell death induced by Bcl2-associated X (Bax) protein in tobacco plants. Therefore, this report presents that both microarray and VIGS approaches are feasible in hot pepper plants and the TMV-induced CaFAD1 plays a role in HR response.

  18. Applications of Functional Protein Microarrays in Basic and Clinical Research

    PubMed Central

    Zhu, Heng; Qian, Jiang

    2013-01-01

    The protein microarray technology provides a versatile platform for characterization of hundreds of thousands of proteins in a highly parallel and high-throughput manner. It is viewed as a new tool that overcomes the limitation of DNA microarrays. On the basis of its application, protein microarrays fall into two major classes: analytical and functional protein microarrays. In addition, tissue or cell lysates can also be directly spotted on a slide to form the so-called “reverse-phase” protein microarray. In the last decade, applications of functional protein microarrays in particular have flourished in studying protein function and construction of networks and pathways. In this chapter, we will review the recent advancements in the protein microarray technology, followed by presenting a series of examples to illustrate the power and versatility of protein microarrays in both basic and clinical research. As a powerful technology platform, it would not be surprising if protein microarrays will become one of the leading technologies in proteomic and diagnostic fields in the next decade. PMID:22989767

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

    PubMed Central

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

    2002-01-01

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

  20. Affymetrix GeneChip microarray preprocessing for multivariate analyses.

    PubMed

    McCall, Matthew N; Almudevar, Anthony

    2012-09-01

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

  1. Applications in high-content functional protein microarrays.

    PubMed

    Moore, Cedric D; Ajala, Olutobi Z; Zhu, Heng

    2016-02-01

    Protein microarray technology provides a versatile platform for characterization of hundreds to thousands of proteins in a parallel and high-throughput manner. Over the last decade, applications of functional protein microarrays in particular have flourished in studying protein function at a systems level and have led to the construction of networks and pathways describing these functions. Relevant areas of research include the detection of various binding properties of proteins, the study of enzyme-substrate relationships, the analysis of host-microbe interactions, and profiling antibody specificity. In addition, discovery of novel biomarkers in autoimmune diseases and cancers is emerging as a major clinical application of functional protein microarrays. In this review, we will summarize the recent advances of functional protein microarrays in both basic and clinical applications. PMID:26599287

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

    PubMed

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

    2015-10-01

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

  3. Gene expression profiling in peanut using oligonucleotide microarrays

    Technology Transfer Automated Retrieval System (TEKTRAN)

    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...

  4. 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

  5. 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. PMID:23110046

  6. Detect Key Gene Information in Classification of Microarray Data

    NASA Astrophysics Data System (ADS)

    Liu, Yihui

    2008-12-01

    We detect key information of high-dimensional microarray profiles based on wavelet analysis and genetic algorithm. Firstly, wavelet transform is employed to extract approximation coefficients at 2nd level, which remove noise and reduce dimensionality. Genetic algorithm (GA) is performed to select the optimized features. Experiments are performed on four datasets, and experimental results prove that approximation coefficients are efficient way to characterize the microarray data. Furthermore, in order to detect the key genes in the classification of cancer tissue, we reconstruct the approximation part of gene profiles based on orthogonal approximation coefficients. The significant genes are selected based on reconstructed approximation information using genetic algorithm. Experiments prove that good performance of classification is achieved based on the selected key genes.

  7. Analysis of microarray experiments of gene expression profiling

    PubMed Central

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

    2008-01-01

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

  8. Classifying temporal microarray data by selecting informative genes.

    PubMed

    Lou, Qiang; Obradovic, Zoran

    2013-06-01

    In order to more accurately predict an individual's health status, in clinical applications it is often important to perform analysis of high-dimensional gene expression data that varies with time. A major challenge in predicting from such temporal microarray data is that the number of biomarkers used as features is typically much larger than the number of labeled subjects. One way to address this challenge is to perform feature selection as a preprocessing step and then apply a classification method on selected features. However, traditional feature selection methods cannot handle multivariate temporal data without applying techniques that flatten temporal data into a single matrix in advance. In this study, a feature selection filter that can directly select informative features from temporal gene expression data is proposed. In our approach, we measure the distance between multivariate temporal data from two subjects. Based on this distance, we define the objective function of temporal margin based feature selection to maximize each subject's temporal margin in its own relevant subspace. The experimental results on synthetic and two real flu data sets provide evidence that our method outperforms the alternatives, which flatten the temporal data in advance.

  9. Gene Expression Network Reconstruction by LEP Method Using Microarray Data

    PubMed Central

    You, Na; Mou, Peng; Qiu, Ting; Kou, Qiang; Zhu, Huaijin; Chen, Yuexi; Wang, Xueqin

    2012-01-01

    Gene expression network reconstruction using microarray data is widely studied aiming to investigate the behavior of a gene cluster simultaneously. Under the Gaussian assumption, the conditional dependence between genes in the network is fully described by the partial correlation coefficient matrix. Due to the high dimensionality and sparsity, we utilize the LEP method to estimate it in this paper. Compared to the existing methods, the LEP reaches the highest PPV with the sensitivity controlled at the satisfactory level. A set of gene expression data from the HapMap project is analyzed for illustration. PMID:23365528

  10. 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

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

    NASA Astrophysics Data System (ADS)

    Getz, Gad; Levine, Erel; Domany, Eytan

    2000-10-01

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

  12. Microarray technology to investigate genes associated with papillary thyroid carcinoma.

    PubMed

    Zhu, Xinyong; Yao, Jing; Tian, Wen

    2015-05-01

    DNA microarray data on thyroid tissue from patients with papillary thyroid carcinoma (PTC) and from healthy controls were compared in order to investigate the regulatory genes and uncover the underlying regulatory network in PTC. The DNA microarray data set, GSE3678, was downloaded from Gene Expression Omnibus database. This included seven thyroid tissue samples from patients with PTC and seven samples from healthy controls. Raw data were processed and differentially expressed genes (DEGs) were identified using corresponding R packages. Gene regulation analysis was conducted using TRANSFAC® and TRED. A total of 171 DEGs were obtained. A regulatory network was then established, using 104 of the DEGs. Subsequently, pathway enrichment analyses of the genes were conducted using Database for Annotation, Visualization and Integrated Discovery (DAVID) online tool. Three differentially expressed transcription factors were identified: Trefoil factor 3, cut‑like homeobox 2 and forkhead box protein A2. The most significant pathways involving the 104 DEGs were pathways involved in cancer. Biological process analysis using DAVID, suggested that these genes were associated with the positive regulation of gene expression, gene transcription and metabolic processes. The present study identified a range of genes associated with the development of PTC. The results of the present study were beneficial for understanding the regulatory mechanisms involved in PTC, and for developing clinical diagnostic and therapeutic approaches for this disease.

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

    PubMed Central

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

    2015-01-01

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

  14. 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.

  15. 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.

  16. Identification of common prognostic gene expression signatures with biological meanings from microarray gene expression datasets.

    PubMed

    Yao, Jun; Zhao, Qi; Yuan, Ying; Zhang, Li; Liu, Xiaoming; Yung, W K Alfred; Weinstein, John N

    2012-01-01

    Numerous prognostic gene expression signatures for breast cancer were generated previously with few overlap and limited insight into the biology of the disease. Here we introduce a novel algorithm named SCoR (Survival analysis using Cox proportional hazard regression and Random resampling) to apply random resampling and clustering methods in identifying gene features correlated with time to event data. This is shown to reduce overfitting noises involved in microarray data analysis and discover functional gene sets linked to patient survival. SCoR independently identified a common poor prognostic signature composed of cell proliferation genes from six out of eight breast cancer datasets. Furthermore, a sequential SCoR analysis on highly proliferative breast cancers repeatedly identified T/B cell markers as favorable prognosis factors. In glioblastoma, SCoR identified a common good prognostic signature of chromosome 10 genes from two gene expression datasets (TCGA and REMBRANDT), recapitulating the fact that loss of one copy of chromosome 10 (which harbors the tumor suppressor PTEN) is linked to poor survival in glioblastoma patients. SCoR also identified prognostic genes on sex chromosomes in lung adenocarcinomas, suggesting patient gender might be used to predict outcome in this disease. These results demonstrate the power of SCoR to identify common and biologically meaningful prognostic gene expression signatures.

  17. Identification of Common Prognostic Gene Expression Signatures with Biological Meanings from Microarray Gene Expression Datasets

    PubMed Central

    Yao, Jun; Zhao, Qi; Yuan, Ying; Zhang, Li; Liu, Xiaoming; Yung, W. K. Alfred; Weinstein, John N.

    2012-01-01

    Numerous prognostic gene expression signatures for breast cancer were generated previously with few overlap and limited insight into the biology of the disease. Here we introduce a novel algorithm named SCoR (Survival analysis using Cox proportional hazard regression and Random resampling) to apply random resampling and clustering methods in identifying gene features correlated with time to event data. This is shown to reduce overfitting noises involved in microarray data analysis and discover functional gene sets linked to patient survival. SCoR independently identified a common poor prognostic signature composed of cell proliferation genes from six out of eight breast cancer datasets. Furthermore, a sequential SCoR analysis on highly proliferative breast cancers repeatedly identified T/B cell markers as favorable prognosis factors. In glioblastoma, SCoR identified a common good prognostic signature of chromosome 10 genes from two gene expression datasets (TCGA and REMBRANDT), recapitulating the fact that loss of one copy of chromosome 10 (which harbors the tumor suppressor PTEN) is linked to poor survival in glioblastoma patients. SCoR also identified prognostic genes on sex chromosomes in lung adenocarcinomas, suggesting patient gender might be used to predict outcome in this disease. These results demonstrate the power of SCoR to identify common and biologically meaningful prognostic gene expression signatures. PMID:23029298

  18. 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.

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

    PubMed Central

    Sîrbu, Alina; Crane, Martin; Ruskin, Heather J.

    2015-01-01

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

  20. 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

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

    PubMed Central

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

    2015-01-01

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

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

    PubMed Central

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

    2015-01-01

    The biological function of human ovaries declines with age. To identify the potential molecular changes in ovarian aging, we performed genome-wide gene expression analysis by microarray of ovaries from young, middle-aged, and old rhesus monkeys. Microarray data was validated by quantitative real-time PCR. Results showed that a total of 503 (60 upregulated, 443 downregulated) and 84 (downregulated) genes were differentially expressed in old ovaries compared to young and middle-aged groups, respectively. No difference in gene expression was found between middle-aged and young groups. Differentially expressed genes were mainly enriched in cell and organelle, cellular and physiological process, binding, and catalytic activity. These genes were primarily associated with KEGG pathways of cell cycle, DNA replication and repair, oocyte meiosis and maturation, MAPK, TGF-beta, and p53 signaling pathway. Genes upregulated were involved in aging, defense response, oxidation reduction, and negative regulation of cellular process; genes downregulated have functions in reproduction, cell cycle, DNA and RNA process, macromolecular complex assembly, and positive regulation of macromolecule metabolic process. These findings show that monkey ovary undergoes substantial change in global transcription with age. Gene expression profiles are useful in understanding the mechanisms underlying ovarian aging and age-associated infertility in primates. PMID:26421297

  3. 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.

  4. A custom microarray platform for analysis of microRNA gene expression.

    PubMed

    Thomson, J Michael; Parker, Joel; Perou, Charles M; Hammond, Scott M

    2004-10-01

    MicroRNAs are short, noncoding RNA transcripts that post-transcriptionally regulate gene expression. Several hundred microRNA genes have been identified in Caenorhabditis elegans, Drosophila, plants and mammals. MicroRNAs have been linked to developmental processes in C. elegans, plants and humans and to cell growth and apoptosis in Drosophila. A major impediment in the study of microRNA function is the lack of quantitative expression profiling methods. To close this technological gap, we have designed dual-channel microarrays that monitor expression levels of 124 mammalian microRNAs. Using these tools, we observed distinct patterns of expression among adult mouse tissues and embryonic stem cells. Expression profiles of staged embryos demonstrate temporal regulation of a large class of microRNAs, including members of the let-7 family. This microarray technology enables comprehensive investigation of microRNA expression, and furthers our understanding of this class of recently discovered noncoding RNAs.

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

    PubMed

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

    2015-10-01

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

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

    PubMed

    Aharoni, Asaph; O'Connell, Ann P

    2002-10-01

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

  7. 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...

  8. Identification of FHL2-regulated genes in liver by microarray and bioinformatics analysis.

    PubMed

    Ng, Chor-Fung; Xu, Jia-Ying; Li, Man-Shan; Tsui, Stephen Kwok-Wing

    2014-04-01

    FHL2 is a LIM domain protein that is able to form various protein complexes and regulate gene transcription. Recent findings showed that FHL2 is a potential tumor suppressor gene that was down-regulated in hepatocellular carcinoma. In the present study, microarray profiling of gene expression was performed to identify the genes regulated by FHL2 in mouse livers. The differentially expressed genes were further analyzed by bioinformatics tools including DAVID, KEGG, and STRING. Our data illustrate that FHL2 affects genes involved in various functions including signal transduction, responses to external stimulus, cancer-related pathways, cardiovascular function and regulation of actin cytoskeleton. Moreover, a network of differentially expressed genes identified in this study and known FHL2-interacting proteins was constructed. Then, genes identified by bioinformatics tools and most functional relevant to FHL2 were selected for further validation. Finally, the differential expression of Ar, Id3, Inhbe, Alas1, Bcl6, Pparδ, Angptl4, and Erbb4 were confirmed by quantitative real-time PCR. In summary, we have established a database of genes that are potentially regulated by FHL2 and these genes should be future targets for the elucidation of functional roles of FHL2.

  9. 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.

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

    PubMed

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

    2013-01-01

    To identify rapidly a number of genes probably involved in sex determination and differentiation of the dioecious plant Asparagus officinalis, gene expression profiles in early flower development for male and female plants were investigated by microarray assay with 8,665 probes. In total, 638 male-biased and 543 female-biased genes were identified. These genes with biased-expression for male and female were involved in a variety of processes associated with molecular functions, cellular components, and biological processes, suggesting that a complex mechanism underlies the sex development of asparagus. Among the differentially expressed genes involved in the reproductive process, a number of genes associated with floral development were identified. Reverse transcription-PCR was performed for validation, and the results were largely consistent with those obtained by microarray analysis. The findings of this study might contribute to understanding of the molecular mechanisms of sex determination and differentiation in dioecious asparagus and provide a foundation for further studies of this plant. PMID:23748756

  11. A lesson for cancer research: placental microarray gene analysis in preeclampsia

    PubMed Central

    Louwen, Frank; Muschol-Steinmetz, Cornelia; Reinhard, Joscha; Reitter, Anke; Yuan, Juping

    2012-01-01

    Tumor progression and pregnancy share many common features, such as immune tolerance and invasion. The invasion of trophoblasts in the placenta into the uterine wall is essential for fetal development, and is thus precisely regulated. Its deregulation has been implicated in preeclampsia, a leading cause for maternal and perinatal mortality and morbidity. Pathogenesis of preeclampsia remains to be defined. Microarray-based gene profiling has been widely used for identifying genes responsible for preeclampsia. In this review, we have summarized the recent data from the microarray studies with preeclamptic placentas. Despite the complex of gene signatures, suggestive of the heterogeneity of preeclampsia, these studies identified a number of differentially expressed genes associated with preeclampsia. Interestingly, most of them have been reported to be tightly involved in tumor progression. We have discussed these interesting genes and analyzed their potential molecular functions in preeclampsia, compared with their roles in malignancy development. Further investigations are warranted to explore the involvement in molecular network of each identified gene, which may provide not only novel strategies for prevention and therapy for preeclampsia but also a better understanding of cancer cells. The trophoblastic cells, with their capacity for proliferation and differentiation, apoptosis and survival, migration, angiogenesis and immune modulation by exploiting similar molecular pathways, make them a compelling model for cancer research. PMID:22929622

  12. Identification of Hub Genes Related to the Recovery Phase of Irradiation Injury by Microarray and Integrated Gene Network Analysis

    PubMed Central

    Zhang, Jing; Yang, Yue; Wang, Yin; Zhang, Jinyuan; Wang, Zejian; Yin, Ming; Shen, Xudong

    2011-01-01

    Background Irradiation commonly causes long-term bone marrow injury charactertized by defective HSC self-renewal and a decrease in HSC reserve. However, the effect of high-dose IR on global gene expression during bone marrow recovery remains unknown. Methodology Microarray analysis was used to identify differentially expressed genes that are likely to be critical for bone marrow recovery. Multiple bioinformatics analyses were conducted to identify key hub genes, pathways and biological processes. Principal Findings 1) We identified 1302 differentially expressed genes in murine bone marrow at 3, 7, 11 and 21 days after irradiation. Eleven of these genes are known to be HSC self-renewal associated genes, including Adipoq, Ccl3, Ccnd1, Ccnd2, Cdkn1a, Cxcl12, Junb, Pten, Tal1, Thy1 and Tnf; 2) These 1302 differentially expressed genes function in multiple biological processes of immunity, including hematopoiesis and response to stimuli, and cellular processes including cell proliferation, differentiation, adhesion and signaling; 3) Dynamic Gene Network analysis identified a subgroup of 25 core genes that participate in immune response, regulation of transcription and nucleosome assembly; 4) A comparison of our data with known irradiation-related genes extracted from literature showed 42 genes that matched the results of our microarray analysis, thus demonstrated consistency between studies; 5) Protein-protein interaction network and pathway analyses indicated several essential protein-protein interactions and signaling pathways, including focal adhesion and several immune-related signaling pathways. Conclusions Comparisons to other gene array datasets indicate that global gene expression profiles of irradiation damaged bone marrow show significant differences between injury and recovery phases. Our data suggest that immune response (including hematopoiesis) can be considered as a critical biological process in bone marrow recovery. Several critical hub genes that are

  13. Microarray Analyses of Gene Expression during the Tetrahymena thermophila Life Cycle

    PubMed Central

    Miao, Wei; Xiong, Jie; Bowen, Josephine; Wang, Wei; Liu, Yifan; Braguinets, Olga; Grigull, Jorg; Pearlman, Ronald E.; Orias, Eduardo; Gorovsky, Martin A.

    2009-01-01

    Background The model eukaryote, Tetrahymena thermophila, is the first ciliated protozoan whose genome has been sequenced, enabling genome-wide analysis of gene expression. Methodology/Principal Findings A genome-wide microarray platform containing the predicted coding sequences (putative genes) for T. thermophila is described, validated and used to study gene expression during the three major stages of the organism's life cycle: growth, starvation and conjugation. Conclusions/Significance Of the ∼27,000 predicted open reading frames, transcripts homologous to only ∼5900 are not detectable in any of these life cycle stages, indicating that this single-celled organism does indeed contain a large number of functional genes. Transcripts from over 5000 predicted genes are expressed at levels >5× corrected background and 95 genes are expressed at >250× corrected background in all stages. Transcripts homologous to 91 predicted genes are specifically expressed and 155 more are highly up-regulated in growing cells, while 90 are specifically expressed and 616 are up-regulated during starvation. Strikingly, transcripts homologous to 1068 predicted genes are specifically expressed and 1753 are significantly up-regulated during conjugation. The patterns of gene expression during conjugation correlate well with the developmental stages of meiosis, nuclear differentiation and DNA elimination. The relationship between gene expression and chromosome fragmentation is analyzed. Genes encoding proteins known to interact or to function in complexes show similar expression patterns, indicating that co-ordinate expression with putative genes of known function can identify genes with related functions. New candidate genes associated with the RNAi-like process of DNA elimination and with meiosis are identified and the late stages of conjugation are shown to be characterized by specific expression of an unexpectedly large and diverse number of genes not involved in nuclear functions

  14. Identifying Subspace Gene Clusters from Microarray Data Using Low-Rank Representation

    PubMed Central

    Cui, Yan; Zheng, Chun-Hou; Yang, Jian

    2013-01-01

    Identifying subspace gene clusters from the gene expression data is useful for discovering novel functional gene interactions. In this paper, we propose to use low-rank representation (LRR) to identify the subspace gene clusters from microarray data. LRR seeks the lowest-rank representation among all the candidates that can represent the genes as linear combinations of the bases in the dataset. The clusters can be extracted based on the block diagonal representation matrix obtained using LRR, and they can well capture the intrinsic patterns of genes with similar functions. Meanwhile, the parameter of LRR can balance the effect of noise so that the method is capable of extracting useful information from the data with high level of background noise. Compared with traditional methods, our approach can identify genes with similar functions yet without similar expression profiles. Also, it could assign one gene into different clusters. Moreover, our method is robust to the noise and can identify more biologically relevant gene clusters. When applied to three public datasets, the results show that the LRR based method is superior to existing methods for identifying subspace gene clusters. PMID:23527177

  15. 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...

  16. 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.

  17. Functional protein microarray as molecular decathlete: a versatile player in clinical proteomics.

    PubMed

    Zhu, Heng; Cox, Eric; Qian, Jiang

    2012-12-01

    Functional protein microarrays were developed as a high-throughput tool to overcome the limitations of DNA microarrays and to provide a versatile platform for protein functional analyses. Recent years have witnessed tremendous growth in the use of protein microarrays, particularly functional protein microarrays, to address important questions in the field of clinical proteomics. In this review, we will summarize some of the most innovative and exciting recent applications of protein microarrays in clinical proteomics, including biomarker identification, pathogen-host interactions, and cancer biology. PMID:23027439

  18. Weighted Change-Point Method for Detecting Differential Gene Expression in Breast Cancer Microarray Data

    PubMed Central

    Wang, Yao; Sun, Guang; Ji, Zhaohua; Xing, Chong; Liang, Yanchun

    2012-01-01

    In previous work, we proposed a method for detecting differential gene expression based on change-point of expression profile. This non-parametric change-point method gave promising result in both simulation study and public dataset experiment. However, the performance is still limited by the less sensitiveness to the right bound and the statistical significance of the statistics has not been fully explored. To overcome the insensitiveness to the right bound we modified the original method by adding a weight function to the Dn statistic. Simulation study showed that the weighted change-point statistics method is significantly better than the original NPCPS in terms of ROC, false positive rate, as well as change-point estimate. The mean absolute error of the estimated change-point by weighted change-point method was 0.03, reduced by more than 50% comparing with the original 0.06, and the mean FPR was reduced by more than 55%. Experiment on microarray Dataset I resulted in 3974 differentially expressed genes out of total 5293 genes; experiment on microarray Dataset II resulted in 9983 differentially expressed genes among total 12576 genes. In summary, the method proposed here is an effective modification to the previous method especially when only a small subset of cancer samples has DGE. PMID:22276133

  19. Microarrays in hematology.

    PubMed

    Walker, Josef; Flower, Darren; Rigley, Kevin

    2002-01-01

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

  20. 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.

  1. Gene expression microarray analysis of heat stress in the soil invertebrate Folsomia candida.

    PubMed

    Nota, B; van Straalen, N M; Ylstra, B; Roelofs, D

    2010-06-01

    Sudden temperature changes in soil can induce stress in soil-dwelling invertebrates. Hyperthermic conditions have an impact on gene expression as one of the first steps. We use a transcriptomics approach using microarrays to identify expression changes in response to heat in the springtail Folsomia candida. An elevation of temperature (Delta 10 degrees C) altered the expression of 142 genes (116 up-, 26 down-regulated). Many up-regulated genes encoded heat shock proteins, enzymes involved in ATP synthesis, oxidative stress responsive enzymes and anion-transporting ATPases. Down-regulated were glycoside hydrolases, involved in catalysis of disaccharides. The small number of altered transcripts suggest a mild response to heat in this soil invertebrate, but further research is needed to confirm this. This study presents candidate genes for future functional studies concerning thermal stress in soil-dwelling invertebrates. PMID:20074298

  2. Analyzing Illumina Gene Expression Microarray Data Obtained From Human Whole Blood Cell and Blood Monocyte Samples.

    PubMed

    Teumer, Alexander; Schurmann, Claudia; Schillert, Arne; Schramm, Katharina; Ziegler, Andreas; Prokisch, Holger

    2016-01-01

    Microarray profiling of gene expression is widely applied to studies in molecular biology and functional genomics. Experimental and technical variations make not only the statistical analysis of single studies but also meta-analyses of different studies very challenging. Here, we describe the analytical steps required to substantially reduce the variations of gene expression data without affecting true effect sizes. A software pipeline has been established using gene expression data from a total of 3358 whole blood cell and blood monocyte samples, all from three German population-based cohorts, measured on the Illumina HumanHT-12 v3 BeadChip array. In summary, adjustment for a few selected technical factors greatly improved reliability of gene expression analyses. Such adjustments are particularly required for meta-analyses of different studies. PMID:26614070

  3. 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.

  4. 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.

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

    PubMed Central

    Jahandeh, Nadia; Ranjbar, Reza; Behzadi, Elham

    2015-01-01

    Introduction 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. Material and methods 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. Results 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. Conclusions 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. PMID:26855801

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

    PubMed Central

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

    2015-01-01

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

  7. 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.

  8. An advanced application of protein microarrays: cell-based assays for functional genomics.

    PubMed

    Carbone, Roberta

    2009-01-01

    Microarrays have become common tools for approaching different experimental questions: DNA, protein and peptide arrays offer the power of multiplexing the assay and by means of miniaturization technology, the possibility to reduce cost and amount of samples and reagents. Recently, a novel technology for functional assays has been proposed. Sabatini and co-workers have shown a cell-based microarrays method (1) that relies on the deposition and immobilization of an array of cDNA plasmids on a slide where cells are subsequently plated; the cDNA is then internalized by "reverse transfection" and cells overexpress or downregulate in each single spot the genes of interest. This approach allows the screening of different phenotypes in living cells of many genes in parallel on a single slide. To overcome some relevant limitations of this approach, we have implemented the technology by means of viral immobilization (2) on a novel surface of cluster-assembled nanostructured TiO2 (3) previously functionalized with an array of a docking protein. In this work, we present the detailed development of the "reverse infection cell-microarray based technology" in U2OS cells on a novel coated slide that represents an advanced application of protein arrays.

  9. 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.

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

    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...

  11. Development and Validation of a 2,000 Gene Microarray in the Fathead Minnow, Pimephales promelas

    EPA Science Inventory

    The development of the gene microarray has given the field of ecotoxicology a new tool to understand the mechanisms of action (MOA) of various anthropogenic compounds. . .Overall, data from this analysis suggest that the microarrays can be broadly useful in ecotoxicology studies ...

  12. Gene order computation using Alzheimer's DNA microarray gene expression data and the Ant Colony Optimisation algorithm.

    PubMed

    Pang, Chaoyang; Jiang, Gang; Wang, Shipeng; Hu, Benqiong; Liu, Qingzhong; Deng, Youping; Huang, Xudong

    2012-01-01

    As Alzheimer's Disease (AD) is the most common form of dementia, the study of AD-related genes via biocomputation is an important research topic. One method of studying AD-related gene is to cluster similar genes together into a gene order. Gene order is a good clustering method as the results can be optimal globally while other clustering methods are only optimal locally. Herein we use the Ant Colony Optimisation (ACO)-based algorithm to calculate the gene order from an Alzheimer's DNA microarray dataset. We test it with four distance measurements: Pearson distance, Spearmen distance, Euclidean distance, and squared Euclidean distance. Our computing results indicate: a different distance formula generated a different quality of gene order, the squared Euclidean distance approach produced the optimal AD-related gene order.

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

    PubMed

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

    2014-01-01

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

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

    PubMed Central

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

    2014-01-01

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

  15. 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

  16. Microarray analysis of gene expression in soybean roots susceptible to the soybean cyst nematode two days post invasion.

    PubMed

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

    2004-09-01

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

  17. 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

  18. DNA microarray detection of antimicrobial resistance genes in Detection and Characterization of Antibiotic Resistance

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Detection of antimicrobial resistance genes is essential for research and an important tool for clinical diagnostics. Most techniques used to identify resistance genes can only detect one or a few genes per assay, whereas DNA microarray technology can detect thousands of genes in a single assay. Sev...

  19. 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.

  20. 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

  1. High-quality gene assembly directly from unpurified mixtures of microarray-synthesized oligonucleotides

    PubMed Central

    Borovkov, Alex Y.; Loskutov, Andrey V.; Robida, Mark D.; Day, Kristen M.; Cano, Jose A.; Le Olson, Tien; Patel, Hetal; Brown, Kevin; Hunter, Preston D.; Sykes, Kathryn F.

    2010-01-01

    To meet the growing demand for synthetic genes more robust, scalable and inexpensive gene assembly technologies must be developed. Here, we present a protocol for high-quality gene assembly directly from low-cost marginal-quality microarray-synthesized oligonucleotides. Significantly, we eliminated the time- and money-consuming oligonucleotide purification steps through the use of hybridization-based selection embedded in the assembly process. The protocol was tested on mixtures of up to 2000 oligonucleotides eluted directly from microarrays obtained from three different chip manufacturers. These mixtures containing <5% perfect oligos, and were used directly for assembly of 27 test genes of different sizes. Gene quality was assessed by sequencing, and their activity was tested in coupled in vitro transcription/translation reactions. Genes assembled from the microarray-eluted material using the new protocol matched the quality of the genes assembled from >95% pure column-synthesized oligonucleotides by the standard protocol. Both averaged only 2.7 errors/kb, and genes assembled from microarray-eluted material without clonal selection produced only 30% less protein than sequence-confirmed clones. This report represents the first demonstration of cost-efficient gene assembly from microarray-synthesized oligonucleotides. The overall cost of assembly by this method approaches 5¢ per base, making gene synthesis more affordable than traditional cloning. PMID:20693531

  2. 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...

  3. 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, ...

  4. 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.

  5. Identification of differentially expressed genes in microarray data in a principal component space.

    PubMed

    Ospina, Luis; López-Kleine, Liliana

    2013-12-01

    Microarray experiments are often conducted in order to compare gene expression between two conditions. Tests to detected mean differential expression of genes between conditions are conducted applying correction for multiple testing. Seldom, relationships between gene expression and microarray conditions are investigated in a multivariate approach. Here we propose determining the relationship between genes and conditions using a Principal Component Analysis (PCA) space and classifying genes to one of two biological conditions based on their position relative to a direction on the PC space representing each condition.

  6. Assembly of a gene sequence tag microarray by reversible biotin-streptavidin capture for transcript analysis of Arabidopsis thaliana

    PubMed Central

    Wirta, Valtteri; Holmberg, Anders; Lukacs, Morten; Nilsson, Peter; Hilson, Pierre; Uhlén, Mathias; Bhalerao, Rishikesh P; Lundeberg, Joakim

    2005-01-01

    Background Transcriptional profiling using microarrays has developed into a key molecular tool for the elucidation of gene function and gene regulation. Microarray platforms based on either oligonucleotides or purified amplification products have been utilised in parallel to produce large amounts of data. Irrespective of platform examined, the availability of genome sequence or a large number of representative expressed sequence tags (ESTs) is, however, a pre-requisite for the design and selection of specific and high-quality microarray probes. This is of great importance for organisms, such as Arabidopsis thaliana, with a high number of duplicated genes, as cross-hybridisation signals between evolutionary related genes cannot be distinguished from true signals unless the probes are carefully designed to be specific. Results We present an alternative solid-phase purification strategy suitable for efficient preparation of short, biotinylated and highly specific probes suitable for large-scale expression profiling. Twenty-one thousand Arabidopsis thaliana gene sequence tags were amplified and subsequently purified using the described technology. The use of the arrays is exemplified by analysis of gene expression changes caused by a four-hour indole-3-acetic (auxin) treatment. A total of 270 genes were identified as differentially expressed (120 up-regulated and 150 down-regulated), including several previously known auxin-affected genes, but also several previously uncharacterised genes. Conclusions The described solid-phase procedure can be used to prepare gene sequence tag microarrays based on short and specific amplified probes, facilitating the analysis of more than 21 000 Arabidopsis transcripts. PMID:15689241

  7. 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

  8. 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

  9. Identifying genes relevant to specific biological conditions in time course microarray experiments.

    PubMed

    Singh, Nitesh Kumar; Repsilber, Dirk; Liebscher, Volkmar; Taher, Leila; Fuellen, Georg

    2013-01-01

    Microarrays have been useful in understanding various biological processes by allowing the simultaneous study of the expression of thousands of genes. However, the analysis of microarray data is a challenging task. One of the key problems in microarray analysis is the classification of unknown expression profiles. Specifically, the often large number of non-informative genes on the microarray adversely affects the performance and efficiency of classification algorithms. Furthermore, the skewed ratio of sample to variable poses a risk of overfitting. Thus, in this context, feature selection methods become crucial to select relevant genes and, hence, improve classification accuracy. In this study, we investigated feature selection methods based on gene expression profiles and protein interactions. We found that in our setup, the addition of protein interaction information did not contribute to any significant improvement of the classification results. Furthermore, we developed a novel feature selection method that relies exclusively on observed gene expression changes in microarray experiments, which we call "relative Signal-to-Noise ratio" (rSNR). More precisely, the rSNR ranks genes based on their specificity to an experimental condition, by comparing intrinsic variation, i.e. variation in gene expression within an experimental condition, with extrinsic variation, i.e. variation in gene expression across experimental conditions. Genes with low variation within an experimental condition of interest and high variation across experimental conditions are ranked higher, and help in improving classification accuracy. We compared different feature selection methods on two time-series microarray datasets and one static microarray dataset. We found that the rSNR performed generally better than the other methods.

  10. Identification of Differential Gene Expression Profiles in Placentas from Preeclamptic Pregnancies Versus Normal Pregnancies by DNA Microarrays

    PubMed Central

    Chen, Haiying; Sun, Manni; Wang, He; Zhao, Ge; Wang, Xiaoshuang

    2012-01-01

    Abstract The purpose of this study was to perform a comprehensive analysis of gene expression profiles in placentas from preeclamptic pregnancies versus normal placentas. Placental tissues were obtained immediately after delivery from women with normal pregnancies (n=6) and patients with preeclampsia (n=6). The gene expression profile was assessed by oligonucleotide-based DNA microarrays and validated by quantitative real-time RT-PCR. Functional relationships and canonical pathways/networks of differentially-expressed genes were evaluated by GeneSpring™ GX 11.0 software, and ingenuity pathways analysis (IPA). A total of 939 genes were identified that differed significantly in expression: 483 genes were upregulated and 456 genes were downregulated in preeclamptic placentas compared with normal placentas (fold change ≥2 and p<0.05 by unpaired t-test corrected with Bonferroni multiple testing). The IPA revealed that the primary molecular functions of these genes are involved in cellular function and maintenance, cellular development, cell signaling, and lipid metabolism. Pathway analysis provided evidence that a number of biological pathways, including Notch, Wnt, NF-κB, and transforming growth factor-β (TGF-β) signaling pathways, were aberrantly regulated in preeclampsia. In conclusion, our microarray analysis represents a comprehensive list of placental gene expression profiles and various dysregulated signaling pathways that are altered in preeclampsia. These observations may provide the basis for developing novel predictive, diagnostic, and prognostic biomarkers of preeclampsia to improve reproductive outcomes and reduce the risk for subsequent cardiovascular disease. PMID:22702245

  11. 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.

  12. 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.

  13. Gene regulation induced in the C57BL/6J mouse retina by hyperoxia: a temporal microarray study

    PubMed Central

    Provis, Jan; Valter, Krisztina; Stone, Jonathan

    2008-01-01

    Purpose Hyperoxia is specifically toxic to photoreceptors, and this toxicity may be important in the progress of retinal dystrophies. This study examines gene expression induced in the C57BL/6J mouse retina by hyperoxia over the 14-day period during which photoreceptors first resist, then succumb to, hyperoxia. Methods Young adult C57BL/6J mice were exposed to hyperoxia (75% oxygen) for up to 14 days. On day 0 (control), day 3, day 7, and day 14, retinal RNA was extracted and processed on Affymetrix GeneChip® Mouse Genome 430 2.0 arrays. Microarray data were analyzed using GCOS Version 1.4 and GeneSpring Version 7.3.1. For 15 genes, microarray data were confirmed using relative quantitative real-time reverse transcription polymerase chain reaction techniques. Results The overall numbers of hyperoxia-regulated genes increased monotonically with exposure. Within that increase, however, a distinctive temporal pattern was apparent. At 3 days exposure, there was prominent upregulation of genes associated with neuroprotection. By day 14, these early-responsive genes were downregulated, and genes related to cell death were strongly expressed. At day 7, the regulation of these genes was mixed, indicating a possible “transition period” from stability at day 3 to degeneration at day 14. When functional groupings of genes were analyzed separately, there was significant regulation in genes responsive to stress, genes known to cause human photoreceptor dystrophies and genes associated with apoptosis. Conclusions Microarray analysis of the response of the retina to prolonged hyperoxia demonstrated a temporal pattern involving early neuroprotection and later cell death, and provided insight into the mechanisms involved in the two phases of response. As hyperoxia is a consistent feature of the late stages of photoreceptor degenerations, understanding the mechanisms of oxygen toxicity may be important therapeutically. PMID:18989387

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

    PubMed

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

    2010-12-01

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

  16. 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

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

    PubMed

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

    2003-07-15

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

  20. 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

  1. 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

  2. Evaluation of gene expression in MG63 human osteoblastlike cells exposed to tantalum powder by microarray technology.

    PubMed

    Sollazzo, Vincenzo; Pezzetti, Furio; Massari, Leo; Palmieri, Annalisa; Brunelli, Giorgio; Zollino, Ilaria; Lucchese, Alessandra; Caruso, Gaetano; Carinci, Francesco

    2011-01-01

    Conventional orthopedic implants are composed from titanium. To improve some characteristics (ie, volumetric porosity, modulus of elasticity, frictional modulus), a new porous tantalum biomaterial has been developed and its biocompatibility reported. By using DNA microarrays containing 20,000 genes, several genes whose expression were significantly up- or down-regulated were identified in an osteoblastlike cell line (MG63) cultured with tantalum powder (TP). The differentially expressed genes cover a broad range of functional activities: signaling transduction; transcription; cell cycle regulation, proliferation, and apoptosis; and cytoskeleton formation. To the authors' knowledge, the data reported represent the first genetic portrait of TP.

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

    PubMed Central

    Leong, Hui Sun; Kipling, David

    2009-01-01

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

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

    PubMed Central

    SUN, XIAOLI; JIA, YU; WEI, YUANYU; LIU, SHUAI; YUE, BAOHONG

    2016-01-01

    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. PMID:27374947

  5. 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.

  6. 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. PMID:18629153

  7. The LeFE algorithm: embracing the complexity of gene expression in the interpretation of microarray data

    PubMed Central

    Eichler, Gabriel S; Reimers, Mark; Kane, David; Weinstein, John N

    2007-01-01

    Interpretation of microarray data remains a challenge, and most methods fail to consider the complex, nonlinear regulation of gene expression. To address that limitation, we introduce Learner of Functional Enrichment (LeFE), a statistical/machine learning algorithm based on Random Forest, and demonstrate it on several diverse datasets: smoker/never smoker, breast cancer classification, and cancer drug sensitivity. We also compare it with previously published algorithms, including Gene Set Enrichment Analysis. LeFE regularly identifies statistically significant functional themes consistent with known biology. PMID:17845722

  8. Reconstruction of gene co-expression network from microarray data using local expression patterns

    PubMed Central

    2014-01-01

    Background Biological networks connect genes, gene products to one another. A network of co-regulated genes may form gene clusters that can encode proteins and take part in common biological processes. A gene co-expression network describes inter-relationships among genes. Existing techniques generally depend on proximity measures based on global similarity to draw the relationship between genes. It has been observed that expression profiles are sharing local similarity rather than global similarity. We propose an expression pattern based method called GeCON to extract Gene CO-expression Network from microarray data. Pair-wise supports are computed for each pair of genes based on changing tendencies and regulation patterns of the gene expression. Gene pairs showing negative or positive co-regulation under a given number of conditions are used to construct such gene co-expression network. We construct co-expression network with signed edges to reflect up- and down-regulation between pairs of genes. Most existing techniques do not emphasize computational efficiency. We exploit a fast correlogram matrix based technique for capturing the support of each gene pair to construct the network. Results We apply GeCON to both real and synthetic gene expression data. We compare our results using the DREAM (Dialogue for Reverse Engineering Assessments and Methods) Challenge data with three well known algorithms, viz., ARACNE, CLR and MRNET. Our method outperforms other algorithms based on in silico regulatory network reconstruction. Experimental results show that GeCON can extract functionally enriched network modules from real expression data. Conclusions In view of the results over several in-silico and real expression datasets, the proposed GeCON shows satisfactory performance in predicting co-expression network in a computationally inexpensive way. We further establish that a simple expression pattern matching is helpful in finding biologically relevant gene network. In

  9. DNA Microarray Analysis in Screening Features of Genes Involved in Spinal Cord Injury

    PubMed Central

    Liu, Yugang; Wang, Ying; Teng, Zhaowei; Zhang, Xiufeng; Ding, Min; Zhang, Zhaojun; Chen, Junli; Xu, Yanli

    2016-01-01

    Background Spinal cord injury (SCI) is the most critical complication of spinal injury. We aimed to identify differentially expressed genes (DEGs) and to find associated pathways that may function as targets for SCI prognosis and therapy. Material/Methods Seven gene microarray expression profiles, downloaded from the GEO database (ID: GSE33886), were used to screen the DEGs of leg tissue and to compare these between SCI patients and corresponding normal specimens. Then, GO enrichment analysis was performed on these selected DEGs. Afterwards, interactions among these DEGs were analyzed by String database and then a PPI network was constructed to obtain topology character and modules in the PPI network. Finally, roles of the critical proteins in the pathway were explained by comparing the enrichment results of the genes in sub-modules and all the DEGs. Results A total of 113 DEGs were determined. We found that 21 up-regulated genes were enriched in 7 biological processes, while 9 down-regulated genes were significantly enriched in 4 KEGG pathways. The PPI network was constructed, including 40 interacting genes and 73 interactions. Three obvious function modules were identified by exploring the PPI network, and ACTC1 was identified as the critical protein in the 3 enriched signal pathways. However, no obvious difference was found in the signal pathway in which both the 11 genes in module 1 and all 113 DEGs participated. Conclusions Core proteins in the signal pathway associated with spinal cord injury may serve as potential prognostic and predictive markers for the diagnosis and treatment of spinal cord injury in clinical applications. PMID:27160807

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

    PubMed

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

    2005-07-01

    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 http://genome.ucsd.edu/microarray.

  11. Identification of plant defence genes in canola using Arabidopsis cDNA microarrays.

    PubMed

    Schenk, P M; Thomas-Hall, S R; Nguyen, A V; Manners, J M; Kazan, K; Spangenberg, G

    2008-09-01

    We report the identification of novel defence genes in canola by using a cDNA microarray from Arabidopsis. We examined changes that occur in the abundance of transcripts corresponding to 2375 Arabidopsis expressed sequence tags (selected for defence gene identification) following inoculation of canola plants with the fungal necrotrophic leaf pathogen, Alternaria brassicicola. Microarray data obtained from this cross-hybridisation experiment were compared to expression profiles previously obtained from the equivalent Arabidopsis experiment. Homology searches using a canola expressed sequence tag database with approximately 6000 unique clones led to identification of canola defence genes. Pathogen-responsive transcripts included those associated to known defence genes, reactive oxygen species metabolism, disease resistance and regulatory genes, and cell maintenance/metabolism genes. Using specific primers for quantitative real-time reverse transcriptase PCR, gene expression profiles in canola were obtained that demonstrated coordinated defence responses, including systemic responses in distal tissue and salicylic acid- and methyl jasmonate-mediated signalling against A. brassicicola.

  12. 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.

  13. Effect of orally administered collagen hydrolysate on gene expression profiles in mouse skin: a DNA microarray analysis.

    PubMed

    Oba, Chisato; Ito, Kyoko; Ichikawa, Satomi; Morifuji, Masashi; Nakai, Yuji; Ishijima, Tomoko; Abe, Keiko; Kawahata, Keiko

    2015-08-01

    Dietary collagen hydrolysate has been hypothesized to improve skin barrier function. To investigate the effect of long-term collagen hydrolysate administration on the skin, we evaluated stratum corneum water content and skin elasticity in intrinsically aged mice. Female hairless mice were fed a control diet or a collagen hydrolysate-containing diet for 12 wk. Stratum corneum water content and skin elasticity were gradually decreased in chronologically aged control mice. Intake of collagen hydrolysate significantly suppressed such changes. Moreover, we used DNA microarrays to analyze gene expression in the skin of mice that had been administered collagen hydrolysate. Twelve weeks after the start of collagen intake, no significant differences appeared in the gene expression profile compared with the control group. However, 1 wk after administration, 135 genes were upregulated and 448 genes were downregulated in the collagen group. This suggests that gene changes preceded changes of barrier function and elasticity. We focused on several genes correlated with functional changes in the skin. Gene Ontology terms related to epidermal cell development were significantly enriched in upregulated genes. These skin function-related genes had properties that facilitate epidermal production and differentiation while suppressing dermal degradation. In conclusion, our results suggest that altered gene expression at the early stages after collagen administration affects skin barrier function and mechanical properties. Long-term oral intake of collagen hydrolysate improves skin dysfunction by regulating genes related to production and maintenance of skin tissue.

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

    PubMed

    Wu, Gang; Zhang, Ying; Wei, Yimin

    2010-04-01

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

  15. 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.

  16. 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

  17. A robust measure of correlation between two genes on a microarray

    PubMed Central

    Hardin, Johanna; Mitani, Aya; Hicks, Leanne; VanKoten, Brian

    2007-01-01

    Background The underlying goal of microarray experiments is to identify gene expression patterns across different experimental conditions. Genes that are contained in a particular pathway or that respond similarly to experimental conditions could be co-expressed and show similar patterns of expression on a microarray. Using any of a variety of clustering methods or gene network analyses we can partition genes of interest into groups, clusters, or modules based on measures of similarity. Typically, Pearson correlation is used to measure distance (or similarity) before implementing a clustering algorithm. Pearson correlation is quite susceptible to outliers, however, an unfortunate characteristic when dealing with microarray data (well known to be typically quite noisy.) Results We propose a resistant similarity metric based on Tukey's biweight estimate of multivariate scale and location. The resistant metric is simply the correlation obtained from a resistant covariance matrix of scale. We give results which demonstrate that our correlation metric is much more resistant than the Pearson correlation while being more efficient than other nonparametric measures of correlation (e.g., Spearman correlation.) Additionally, our method gives a systematic gene flagging procedure which is useful when dealing with large amounts of noisy data. Conclusion When dealing with microarray data, which are known to be quite noisy, robust methods should be used. Specifically, robust distances, including the biweight correlation, should be used in clustering and gene network analysis. PMID:17592643

  18. 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

  19. Identification and expression analysis of salt-responsive genes using a comparative microarray approach in Salix matsudana.

    PubMed

    Liu, Mingying; Qiao, Guirong; Jiang, Jing; Han, Xiaojiao; Sang, Jian; Zhuo, Renying

    2014-10-01

    Salt stress exerts negative effects on plant growth, development and yields, with roots being the primary site of both perception and damage. Salix matsudana (Chinese willow) is tolerant of high salinity. However, genes associated with this trait were rarely characterized. Therefore, we first performed salt-stress treatment on S. matsudana plants, then identified differentially expressed genes by comparison of salt-treated roots and untreated controls using microarray analysis. A total of 403 salt-responsive genes were identified, of which 239 were repressed and 164 were up-regulated. Functional classification analysis revealed that these genes belonged to families encoding proteins involved in metabolism, regulation of transcription, signal transduction, hormone responses, abiotic stress responses, and other processes related to growth and development. This suggested that when S. matsudana was confronted with salt stress, coordinated adjustments are made to physiological and biochemical processes, which would then allow more resources to be allocated to protective mechanisms to avoid salt injury. The expression patterns of representative genes were further validated and the diversity of the temporal profiles indicated that a combination of several genes and the initiation of diverse pathways performed functions in S. matsudana salt tolerance. This work represents the first study employing microarrays to investigate salt tolerance in S. matsudana. The data presented herein enhance our understanding of the molecular mechanisms of S. matsudana responses to salinity stress and lay the groundwork for genetic engineering strategies to improve stress tolerance of agronomically important species.

  20. Renal medullary genes in salt-sensitive hypertension: a chromosomal substitution and cDNA microarray study.

    PubMed

    Liang, Mingyu; Yuan, Baozhi; Rute, Elizabeth; Greene, Andrew S; Zou, Ai-Ping; Soares, Paulo; MCQuestion, Gregory D; Slocum, Glenn R; Jacob, Howard J; Cowley, Allen W

    2002-02-28

    Substitution of chromosome 13 from Brown Norway BN/SsNHsd/Mcw (BN/Mcw) rats into the Dahl salt-sensitive SS/JrHsd/Mcw (SS/Mcw) rats resulted in substantial reduction of blood pressure salt sensitivity in this consomic rat strain designated SSBN13. In the present study, we attempted to identify genes associated with salt-sensitive hypertension by utilizing a custom, known-gene cDNA microarray to compare the mRNA expression profiles in the renal medulla (a tissue playing a pivotal role in long-term blood pressure regulation) of SS/Mcw and SSBN13 rats on either low-salt (0.4% NaCl) or high-salt (4% NaCl, 2 wk) diets. To increase the reliability of microarray data, we designed a four-way comparison experiment incorporating several levels of replication and developed a conservative yet robust data analysis method. Using this approach, from the 1,751 genes examined (representing more than 80% of all currently known rat genes), we identified 80 as being differentially expressed in at least 1 of the 4 comparisons. Substantial agreements were found between the microarray results and the results predicted on the basis of the four-way comparison as well as the results of Northern blots of 20 randomly selected genes. Analysis of the four-way comparison further indicated that approximately 75% of the 80 differentially expressed genes were likely related to salt-sensitive hypertension. Many of these genes had not previously been recognized to be important in hypertension, whereas several genes/pathways known to be involved in hypertension were confirmed. These results should provide an informative source for designing future functional studies in salt-sensitive hypertension.

  1. 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

    2015-01-01

    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.

  2. 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.

  3. 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.

  4. 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…

  5. Development and Validation of an Oligonucleotide Microarray for Detection of Multiple Virulence and Antimicrobial Resistance Genes in Escherichia coli†

    PubMed Central

    Bruant, Guillaume; Maynard, Christine; Bekal, Sadjia; Gaucher, Isabelle; Masson, Luke; Brousseau, Roland; Harel, Josée

    2006-01-01

    An oligonucleotide microarray detecting 189 Escherichia coli virulence genes or markers and 30 antimicrobial resistance genes was designed and validated using DNA from known reference strains. This microarray was confirmed to be a powerful diagnostic tool for monitoring emerging E. coli pathotypes and antimicrobial resistance, as well as for environmental, epidemiological, and phylogenetic studies including the evaluation of genome plasticity. PMID:16672535

  6. 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

  7. Gene Expression Analyses of Subchondral Bone in Early Experimental Osteoarthritis by Microarray

    PubMed Central

    Chen, YuXian; Shen, Jun; Lu, HuaDing; Zeng, Chun; Ren, JianHua; Zeng, Hua; Li, ZhiFu; Chen, ShaoMing; Cai, DaoZhang; Zhao, Qing

    2012-01-01

    Osteoarthritis (OA) is a degenerative joint disease that affects both cartilage and bone. A better understanding of the early molecular changes in subchondral bone may help elucidate the pathogenesis of OA. We used microarray technology to investigate the time course of molecular changes in the subchondral bone in the early stages of experimental osteoarthritis in a rat model. We identified 2,234 differentially expressed (DE) genes at 1 week, 1,944 at 2 weeks and 1,517 at 4 weeks post-surgery. Further analyses of the dysregulated genes indicated that the events underlying subchondral bone remodeling occurred sequentially and in a time-dependent manner at the gene expression level. Some of the identified dysregulated genes that were identified have suspected roles in bone development or remodeling; these genes include Alp, Igf1, Tgf β1, Postn, Mmp3, Tnfsf11, Acp5, Bmp5, Aspn and Ihh. The differences in the expression of these genes were confirmed by real-time PCR, and the results indicated that our microarray data accurately reflected gene expression patterns characteristic of early OA. To validate the results of our microarray analysis at the protein level, immunohistochemistry staining was used to investigate the expression of Mmp3 and Aspn protein in tissue sections. These analyses indicate that Mmp3 protein expression completely matched the results of both the microarray and real-time PCR analyses; however, Aspn protein expression was not observed to differ at any time. In summary, our study demonstrated a simple method of separation of subchondral bone sample from the knee joint of rat, which can effectively avoid bone RNA degradation. These findings also revealed the gene expression profiles of subchondral bone in the rat OA model at multiple time points post-surgery and identified important DE genes with known or suspected roles in bone development or remodeling. These genes may be novel diagnostic markers or therapeutic targets for OA. PMID:22384228

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

    PubMed

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

    2016-03-01

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

  9. 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.

  10. 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

  11. 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.

  12. 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...

  13. 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...

  14. 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...

  15. Optical transfer function for an f-theta lens based confocal fluorescent microarray analyzer

    NASA Astrophysics Data System (ADS)

    Shi, Yan; Ni, Xuxiang; Xu, Guoxiong; Li, Chen; Zhang, Xi; Lu, Zukang

    2005-01-01

    Optical transfer function is widely used to evaluate the imaging performance of an optical system. Combined with confocal scanning technology, f-theta lens can increase the reading speed for microarrays greatly in guarantee of sufficient resolution and fluorescence collection efficiency, compared with micro-array analyzers that adopting mechanical scanning. In this paper, the characteristics of a confocal scanning f-theta objective lens, which was used in micro-array analyzing instrument, were analyzed by means of optical transfer function. In the whole system, laser passed through the f-theta lens, and arrived at the microarray slide where fluorophores were excited. Fluorescence emitting from the micro-array slide was collected by the same f-theta lens, and was captured by a detector. As a laser illumination system, the objective lens had a smaller stop aperture. As a fluorescence collection system, it had a bigger stop aperture. In conclusion, optical transfer function for the whole system, from source to detector, is the combination of that of the laser illumination, a coherent system, and that of the fluorescence collection system, an incoherent system. Uniformity of laser illumination at the micro-array slide was analyzed using optical transfer function during the course of scanning. The influence of aberrations on optical transfer function is given. The simulating results for above characteristics are also presented.

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

    PubMed

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

    2000-01-01

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

  17. 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

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

    PubMed

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

    2007-11-01

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

  20. Influence of microarrays experiments missing values on the stability of gene groups by hierarchical clustering

    PubMed Central

    de Brevern, Alexandre G; Hazout, Serge; Malpertuy, Alain

    2004-01-01

    Background Microarray technologies produced large amount of data. The hierarchical clustering is commonly used to identify clusters of co-expressed genes. However, microarray datasets often contain missing values (MVs) representing a major drawback for the use of the clustering methods. Usually the MVs are not treated, or replaced by zero or estimated by the k-Nearest Neighbor (kNN) approach. The topic of the paper is to study the stability of gene clusters, defined by various hierarchical clustering algorithms, of microarrays experiments including or not MVs. Results In this study, we show that the MVs have important effects on the stability of the gene clusters. Moreover, the magnitude of the gene misallocations is depending on the aggregation algorithm. The most appropriate aggregation methods (e.g. complete-linkage and Ward) are highly sensitive to MVs, and surprisingly, for a very tiny proportion of MVs (e.g. 1%). In most of the case, the MVs must be replaced by expected values. The MVs replacement by the kNN approach clearly improves the identification of co-expressed gene clusters. Nevertheless, we observe that kNN approach is less suitable for the extreme values of gene expression. Conclusion The presence of MVs (even at a low rate) is a major factor of gene cluster instability. In addition, the impact depends on the hierarchical clustering algorithm used. Some methods should be used carefully. Nevertheless, the kNN approach constitutes one efficient method for restoring the missing expression gene values, with a low error level. Our study highlights the need of statistical treatments in microarray data to avoid misinterpretation. PMID:15324460

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

    PubMed Central

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

    2012-01-01

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

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

    PubMed Central

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

    2014-01-01

    Summary Complex human diseases can show significant heterogeneity between patients with the same phenotypic disorder. An outlier detection strategy was developed to identify variants at the level of gene transcription that are of potential biological and phenotypic importance. Here we describe a graphical software package (z-score outlier detection (ZODET)) that enables identification and visualisation of gross abnormalities in gene expression (outliers) in individuals, using whole genome microarray data. Mean and standard deviation of expression in a healthy control cohort is used to detect both over and under-expressed probes in individual test subjects. We compared the potential of ZODET to detect outlier genes in gene expression datasets with a previously described statistical method, gene tissue index (GTI), using a simulated expression dataset and a publicly available monocyte-derived macrophage microarray dataset. Taken together, these results support ZODET as a novel approach to identify outlier genes of potential pathogenic relevance in complex human diseases. The algorithm is implemented using R packages and Java. Availability The software is freely available from http://www.ucl.ac.uk/medicine/molecular-medicine/publications/microarray-outlier-analysis. PMID:24416128

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

    PubMed

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

    2012-10-01

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

  4. 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

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

    PubMed

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

    2006-01-01

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

  6. Replicate high-density rat genome oligonucleotide microarrays reveal hundreds of regulated genes in the dorsal root ganglion after peripheral nerve injury.

    PubMed Central

    Costigan, Michael; Befort, Katia; Karchewski, Laurie; Griffin, Robert S; D'Urso, Donatella; Allchorne, Andrew; Sitarski, Joanne; Mannion, James W; Pratt, Richard E; Woolf, Clifford J

    2002-01-01

    Background Rat oligonucleotide microarrays were used to detect changes in gene expression in the dorsal root ganglion (DRG) 3 days following sciatic nerve transection (axotomy). Two comparisons were made using two sets of triplicate microarrays, naïve versus naïve and naïve versus axotomy. Results Microarray variability was assessed using the naïve versus naïve comparison. These results support use of a P < 0.05 significance threshold for detecting regulated genes, despite the large number of hypothesis tests required. For the naïve versus axotomy comparison, a 2-fold cut off alone led to an estimated error rate of 16%; combining a >1.5-fold expression change and P < 0.05 significance reduced the estimated error to 5%. The 2-fold cut off identified 178 genes while the combined >1.5-fold and P < 0.05 criteria generated 240 putatively regulated genes, which we have listed. Many of these have not been described as regulated in the DRG by axotomy. Northern blot, quantitative slot blots and in situ hybridization verified the expression of 24 transcripts. These data showed an 83% concordance rate with the arrays; most mismatches represent genes with low expression levels reflecting limits of array sensitivity. A significant correlation was found between actual mRNA differences and relative changes between microarrays (r2 = 0.8567). Temporal patterns of individual genes regulation varied. Conclusions We identify parameters for microarray analysis which reduce error while identifying many putatively regulated genes. Functional classification of these genes suggest reorganization of cell structural components, activation of genes expressed by immune and inflammatory cells and down-regulation of genes involved in neurotransmission. PMID:12401135

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

    PubMed Central

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

    2010-01-01

    Purpose To determine global mRNA expression levels in corneal and conjunctival epithelia and identify transcripts that exhibit preferential tissue expression. Methods cDNA samples derived from human conjunctival and corneal epithelia were hybridized in three independent experiments to a commercial oligonucleotide array representing more than 22,000 transcripts. The resultant signal intensities and microarray software transcript present/absent calls were used in conjunction with the local pooled error (LPE) statistical method to identify transcripts that are preferentially or exclusively expressed in one of the two tissues at significant levels (expression >1% of the β-actin level). EASE (Expression Analysis Systematic Explorer software) was used to identify biological systems comparatively overrepresented in either epithelium. Immuno-, and cytohistochemistry was performed to validate or expand on selected results of interest. Results The analysis identified 332 preferential and 93 exclusive significant corneal epithelial transcripts. The corresponding numbers of conjunctival epithelium transcripts were 592 and 211, respectively. The overrepresented biological processes in the cornea were related to cell adhesion and oxiredox equilibria and cytoprotection activities. In the conjunctiva, the biological processes that were most prominent were related to innate immunity and melanogenesis. Immunohistochemistry for antigen-presenting cells and melanocytes was consistent with these gene signatures. The transcript comparison identified a substantial number of genes that have either not been identified previously or are not known to be highly expressed in these two epithelia, including testican-1, ECM1, formin, CRTAC1, and NQO1 in the cornea and, in the conjunctiva, sPLA2-IIA, lipocalin 2, IGFBP3, multiple MCH class II proteins, and the Na-Pi cotransporter type IIb. Conclusions Comparative gene expression profiling leads to the identification of many biological processes

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

    PubMed

    De Zoysa, Mahanama; Nikapitiya, Chamilani; Oh, Chulhong; Lee, Youngdeuk; Whang, Ilson; Lee, Jae-Seong; Choi, Cheol Young; Lee, Jehee

    2011-02-01

    In this study, we investigated the gene expression profiling of disk abalone, Haliotis discus discus challenged by a mixture of three pathogenic bacteria Vibrio alginolyticus, Vibrio parahemolyticus, and Listeria monocytogenes using a cDNA microarray. Upon bacteria challenge, 68 (1.6%) and 112 (2.7%) gene transcripts changed their expression levels ≥2 or ≤2 -fold in gills and digestive tract, respectively. There were 46 tissue-specific transcripts that up-regulated specifically in the digestive tract. In contrast, only 13 transcripts showed gill-specific up-regulation. Quantitative real-time PCR was performed to verify microarray data and results revealed that candidate genes namely Krüppell-like factor (KLF), lachesin, muscle lim protein, thioredoxin-2 (TRx-2), nuclear factor interleukin 3 (NFIL-3) and abalone protein 38 were up-regulated. Also, our results further indicated that bacteria challenge may activate the transcription factors or their activators (Krüppell-like factor, inhibitor of NF-κB or Ik-B), inflammatory cytokines (IL-3 regulated protein, allograft inflammatory factor), other cytokines (IFN-44-like protein, SOCS-2), antioxidant enzymes (glutathione-S-transferase, thioredoxin-2 and thioredoxin peroxidase), and apoptosis-related proteins (TNF-α, archeron) in abalone. The identification of immune and stress response genes and their expression profiles in this microarray will permit detailed investigation of the stress and immune responses of abalone genes.

  9. DNA Microarrays

    NASA Astrophysics Data System (ADS)

    Nguyen, C.; Gidrol, X.

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

  10. DNA microarrays in neuropsychopharmacology.

    PubMed

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

    2001-08-01

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

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

    PubMed Central

    2010-01-01

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

  12. 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

  13. CDNA microarray analysis of nerve growth factor-regulated gene expression profile in rat PC12 cells.

    PubMed

    Lee, Kyung-Hee; Ryu, Chun Jeih; Hong, Hyo Jeong; Kim, Jiyoung; Lee, Eunjoo H

    2005-04-01

    Nerve growth factor (NGF)-driven differentiation of PC12 cells into neuronal-like cells provides a representative model system for studying neuronal differentiation processes. Despite of extensive research, gene regulation associated with the differentiation program in PC12 cells still needs to be elucidated. We used cDNA microarray analysis to characterize the response of PC12 cells to NGF at mRNA expression. Forty-six genes were reproducibly influenced by 2-fold or more after NGF treatment for 5 days. Twenty-five of the regulated transcripts were matched to genes which have known functions. Among the microarray results confirmed with real-time reverse transcriptase assay, several genes have not previously known to be modulated by NGF. The results mostly reflected changes in molecules regulating neural plasticity, cytoskeletal organization, and lipid metabolism, which include neuritin, PDZ protein Mrt1, lipoprotein lipase, tropomodulin 1 and rhoB. These observed genetic changes may provide new information about molecular mechanisms underlying NGF-promoted differentiation of PC12 cells. PMID:16076023

  14. 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

  15. 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. PMID:20387151

  16. 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

  17. Gene expression profiling and identification of resistance genes to Aspergillus flavus infection in peanut through EST and microarray strategies.

    PubMed

    Guo, Baozhu; Fedorova, Natalie D; Chen, Xiaoping; Wan, Chun-Hua; Wang, Wei; Nierman, William C; Bhatnagar, Deepak; Yu, Jiujiang

    2011-07-01

    Aspergillus flavus and A. parasiticus infect peanut seeds and produce aflatoxins, which are associated with various diseases in domestic animals and humans throughout the world. The most cost-effective strategy to minimize aflatoxin contamination involves the development of peanut cultivars that are resistant to fungal infection and/or aflatoxin production. To identify peanut Aspergillus-interactive and peanut Aspergillus-resistance genes, we carried out a large scale peanut Expressed Sequence Tag (EST) project which we used to construct a peanut glass slide oligonucleotide microarray. The fabricated microarray represents over 40% of the protein coding genes in the peanut genome. For expression profiling, resistant and susceptible peanut cultivars were infected with a mixture of Aspergillusflavus and parasiticus spores. The subsequent microarray analysis identified 62 genes in resistant cultivars that were up-expressed in response to Aspergillus infection. In addition, we identified 22 putative Aspergillus-resistance genes that were constitutively up-expressed in the resistant cultivar in comparison to the susceptible cultivar. Some of these genes were homologous to peanut, corn, and soybean genes that were previously shown to confer resistance to fungal infection. This study is a first step towards a comprehensive genome-scale platform for developing Aspergillus-resistant peanut cultivars through targeted marker-assisted breeding and genetic engineering. PMID:22069737

  18. Steady state approach to model gene regulatory networks--simulation of microarray experiments.

    PubMed

    Rawool, Subodh B; Venkatesh, K V

    2007-01-01

    Genetic regulatory networks (GRN) represent complex interactions between genes brought about through proteins that they code for. Quantification of expression levels in GRN either through experiments or theoretical modeling is a challenging task. Recently, microarray experiments have gained importance in evaluating GRN at the genome level. Microarray experiments yield log fold change in mRNA abundance which is helpful in deciphering connectivity in GRN. Current approaches such as data mining, Boolean or Bayesian modeling and combined use of expression and location data are useful in analyzing microarray data. However, these methodologies lack underlying mechanistic details present in GRN. We present here a steady state gene expression simulator (SSGES) which sets up steady state equations and simulates the response for a given network structure of a GRN. SSGES includes mechanistic details such as stoichiometry, protein-DNA and protein-protein interactions, translocation of regulatory proteins and autoregulation. SSGES can be used to simulate the response of a GRN in terms of fractional transcription and protein expression. SSGES can also be used to generate log fold change in mRNA abundance and protein expression implying that it is useful to simulate microarray type experiments. We have demonstrated these capabilities of SSGES by modeling the steady state response of GAL regulatory system in Saccharomyces cerevisiae. We have demonstrated that the predicted data qualitatively matched the microarray data obtained experimentally by Ideker et al. [Ideker, T., Thorsson, V., Ranish, J.A., Christmas, R., Buhler, J., Eng, J.K., Bumgarner, R., Goodlett, D.R., Aebersold, R., Hood, L., 2001. Integrated genomic and proteomic analyses of a systematically perturbed metabolic network. Science 292, 929-934]. SSGES is available from authors upon request.

  19. 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.

  20. SNOMAD (Standardization and NOrmalization of MicroArray Data): web-accessible gene expression data analysis.

    PubMed

    Colantuoni, Carlo; Henry, George; Zeger, Scott; Pevsner, Jonathan

    2002-11-01

    SNOMAD is a collection of algorithms for the normalization and standardization of gene expression datasets derived from diverse biological and technological sources. In addition to conventional transformations and visualization tools, SNOMAD includes two non-linear transformations which correct for bias and variance which are non-uniformly distributed across the range of microarray element signal intensities: (1). Local mean normalization; and (2). Local variance correction (Z-score generation using a locally calculated standard deviation).

  1. 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. PMID:19578720

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

    PubMed

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

    2016-03-01

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

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

    PubMed

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

    2016-03-01

    Naturally occurring astaxantin (ASX) is one of the noticeable carotenoid and dietary supplement, which has strong antioxidant and anti-inflammatory properties, and neuroprotective effects in the brain through crossing the blood-brain barrier. Specially, we are interested in the role of ASX as a brain food. Although ASX has been suggested to have potential benefit to the brain function, the underlying molecular mechanisms and events mediating such effect remain unknown. Here we examined molecular factors in the hippocampus of adult mouse fed ASX diets (0.1% and 0.5% doses) using DNA microarray (Agilent 4 × 44 K whole mouse genome chip) analysis. In this study, we described in detail our experimental workflow and protocol, and validated quality controls with the housekeeping gene expression (Gapdh and Beta-actin) on the dye-swap based approach to advocate our microarray data, which have been uploaded to Gene Expression Omnibus (accession number GSE62197) as a gene resource for the scientific community. This data will also form an important basis for further detailed experiments and bioinformatics analysis with an aim to unravel the potential molecular pathways or mechanisms underlying the positive effects of ASX supplementation on the brain, in particular the hippocampus. PMID:26981356

  4. 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

  5. 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

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

    PubMed Central

    Liu, Wanting

    2013-01-01

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

  7. Gene expression profiling of gastric cancer by microarray combined with laser capture microdissection

    PubMed Central

    Wu, Ming-Shiang; Lin, Yi-Shing; Chang, Yu-Ting; Shun, Chia-Tung; Lin, Ming-Tsan; Lin, Jaw-Town

    2005-01-01

    AIM: To examine the gene expression profile of gastric cancer (GC) by combination of laser capture microdissection (LCM) and microarray and to correlate the profiling with histological subtypes. METHODS: Using LCM, pure cancer cells were procured from 45 cancerous tissues. After procurement of about 5 000 cells, total RNA was extracted and the quality of RNA was determined before further amplification and hybridization. One microgram of amplified RNA was converted to cDNA and hybridized to cDNA microarray. RESULTS: Among 45 cases, only 21 were qualified for their RNAs. A total of 62 arrays were performed. These included 42 arrays for cancer (21 cases with dye-swab duplication) and 20 arrays for non-tumorous cells (10 cases with dye-swab duplication) with universal reference. Analyzed data showed 504 genes were differentially expressed and could distinguish cancerous and non-cancerous groups with more than 99% accuracy. Of the 504 genes, trefoil factors 1, 2, and 3 were in the list and their expression patterns were consistent with previous reports. Immunohistochemical staining of trefoil factor 1 was also consistent with the array data. Analyses of the tumor group with these 504 genes showed that there were 3 subgroups of GC that did not correspond to any current classification system, including Lauren’s classification. CONCLUSION: By using LCM, linear amplification of RNA, and cDNA microarray, we have identified a panel of genes that have the power to discriminate between GC and non-cancer groups. The new molecular classification and the identified novel genes in gastric carcinogenesis deserve further investigations to elucidate their clinicopathological significance. PMID:16437709

  8. 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

  9. 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

  10. Microarray analysis of E-box binding-related gene expression in young and replicatively senescent human fibroblasts.

    PubMed

    Semov, Alexandre; Marcotte, Richard; Semova, Natalie; Ye, Xiangyun; Wang, Eugenia

    2002-03-01

    An E-box (CACGTG) designer microarray was developed to monitor a group of genes whose expressions share a particular regulatory mode. Sensitivity and specificity of microarray hybridization, as well as variability of microarray data, were evaluated. This designer microarray was used to generate expression profiles of E-box binding-related genes in WI-38 fibroblast cultures at three different growth states: low-passage replicating, low-passage contact-inhibited quiescent, and replicatively senescent. Microarray gene screening reveals that quiescent and senescent cells, in comparison with replicating ones, are characterized by downregulation of Pam, a protein associated with c-Myc, and upregulation of Mad family genes, Max dimerization proteins. Moreover, quiescence and senescence can be distinguished by increased expression of Irlb, c-Myc transcription factor, and Miz-1, c-Myc-interacting Zn finger protein 1, only in the former state. Senescence is characterized by downregulation of Id4, inhibitor of DNA binding 4, and Mitf, microphthalmia-associated transcription factor, in comparison with young replicating and quiescent states. Differential expression of genes detected by microarray hybridization was independently confirmed by reverse transcription polymerase chain reaction technique. Alterations in the expression of E-box-binding transcription factors and c-Myc-binding proteins demonstrate the importance of these genes in establishing the contact-inhibited quiescent or senescent phenotypes.

  11. 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.

  12. 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.

  13. 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

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

    PubMed

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

    2008-04-01

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

  15. 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.

  16. 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

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

    PubMed Central

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

    2011-01-01

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

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

    PubMed

    Tiwari, Krishnaraj; Paliyath, Gopinadhan

    2011-03-01

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

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

    PubMed Central

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

    2015-01-01

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

  20. Genome-wide prediction and analysis of human tissue-selective genes using microarray expression data

    PubMed Central

    2013-01-01

    Background Understanding how genes are expressed specifically in particular tissues is a fundamental question in developmental biology. Many tissue-specific genes are involved in the pathogenesis of complex human diseases. However, experimental identification of tissue-specific genes is time consuming and difficult. The accurate predictions of tissue-specific gene targets could provide useful information for biomarker development and drug target identification. Results In this study, we have developed a machine learning approach for predicting the human tissue-specific genes using microarray expression data. The lists of known tissue-specific genes for different tissues were collected from UniProt database, and the expression data retrieved from the previously compiled dataset according to the lists were used for input vector encoding. Random Forests (RFs) and Support Vector Machines (SVMs) were used to construct accurate classifiers. The RF classifiers were found to outperform SVM models for tissue-specific gene prediction. The results suggest that the candidate genes for brain or liver specific expression can provide valuable information for further experimental studies. Our approach was also applied for identifying tissue-selective gene targets for different types of tissues. Conclusions A machine learning approach has been developed for accurately identifying the candidate genes for tissue specific/selective expression. The approach provides an efficient way to select some interesting genes for developing new biomedical markers and improve our knowledge of tissue-specific expression. PMID:23369200

  1. Immunohistochemical Validation of Overexpressed Genes Identified by Global Expression Microarrays in Adrenocortical Carcinoma Reveals Potential Predictive and Prognostic Biomarkers

    PubMed Central

    Ip, Julian C.Y.; Pang, Tony C.Y.; Glover, Anthony R.; Soon, Patsy; Zhao, Jing Ting; Clarke, Stephen; Robinson, Bruce G.; Gill, Anthony J.

    2015-01-01

    Background. Adrenocortical carcinoma (ACC) is a rare malignancy with a poor prognosis. The aim of this study was to identify novel protein signatures that would predict clinical outcomes in a large cohort of patients with ACC based on data from previous gene expression microarray studies. Materials and Methods. A tissue microarray was generated from the paraffin tissue blocks of 61 patients with clinical outcomes data. Selected protein biomarkers based on previous gene expression microarray profiling studies were selected, and immunohistochemistry staining was performed. Staining patterns were correlated with clinical outcomes, and a multivariate analysis was undertaken to identify potential biomarkers of prognosis. Results. Median overall survival was 45 months, with a 5-year overall survival rate of 44%. Median disease-free survival was 58 months, with a 5-year disease-free survival rate of 44%. The proliferation marker Ki-67 and DNA topoisomerase TOP2A were associated with significantly poorer overall and disease-free survival. The results also showed strong correlation between the transcriptional repressor EZH2 and TOP2A expression, suggesting a novel role for EZH2 as an additional marker of prognosis. In contrast, increased expression of the BARD1 protein, with its ubiquitin ligase function, was associated with significantly improved overall and disease-free survival, which has yet to be documented for ACC. Conclusion. We present novel biomarkers that assist in determining prognosis for patients with ACC. Ki-67, TOP2A, and EZH2 were all significantly associated with poorer outcomes, whereas BARD1 was associated with improved overall survival. It is hoped that these biomarkers may help tailor additional therapy and be potential targets for directed therapy. PMID:25657202

  2. Genome-wide microarray analysis of gene expression profiling in major depression and antidepressant therapy.

    PubMed

    Lin, Eugene; Tsai, Shih-Jen

    2016-01-01

    Major depressive disorder (MDD) is a serious health concern worldwide. Currently there are no predictive tests for the effectiveness of any particular antidepressant in an individual patient. Thus, doctors must prescribe antidepressants based on educated guesses. With the recent advent of scientific research, genome-wide gene expression microarray studies are widely utilized to analyze hundreds of thousands of biomarkers by high-throughput technologies. In addition to the candidate-gene approach, the genome-wide approach has recently been employed to investigate the determinants of MDD as well as antidepressant response to therapy. In this review, we mainly focused on gene expression studies with genome-wide approaches using RNA derived from peripheral blood cells. Furthermore, we reviewed their limitations and future directions with respect to the genome-wide gene expression profiling in MDD pathogenesis as well as in antidepressant therapy.

  3. Function analysis of proteins encoded by ORFs 1 to 8 of porcine circovirus-like virus P1 by microarray assay.

    PubMed

    Wen, Libin; Wang, Fengzhi; Zhang, Dan; He, Kongwang

    2015-12-01

    Porcine circovirus-like agent P1 is a newly discovered virus containing a single-strand circular genome. The genome of P1 is a DNA molecule of 648 nucleotides which contains eight open reading frames (ORFs) that probably encode potential proteins or polypeptides. Thus it is very important to clarify these proteins' function. Here we provide the methods and analysis of microarray data in detail to characterize the transcriptome profile of P1 with and without the ORF. The relevant microarray data sets have been deposited in Gene Expression Omnibus (GEO) database under accession number GSE71945. PMID:26697373

  4. 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

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

    PubMed

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

    2009-03-01

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

  6. 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

  7. 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.

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

    SciTech Connect

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

    2007-05-01

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

  9. 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.

  10. 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.

  11. 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

  12. Identification and Optimization of Classifier Genes from Multi-Class Earthworm Microarray Dataset

    PubMed Central

    Li, Ying; Wang, Nan; Perkins, Edward J.; Zhang, Chaoyang; Gong, Ping

    2010-01-01

    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. PMID:21060837

  13. Evolution of insect metamorphosis: a microarray-based study of larval and adult gene expression in the ant Camponotus festinatus.

    PubMed

    Goodisman, Michael A D; Isoe, Jun; Wheeler, Diana E; Wells, Michael A

    2005-04-01

    Holometabolous insects inhabit almost every terrestrial ecosystem. The evolutionary success of holometabolous insects stems partly from their developmental program, which includes discrete larval and adult stages. To gain an understanding of how development differs among holometabolous insect taxa, we used cDNA microarray technology to examine differences in gene expression between larval and adult Camponotus festinatus ants. We then compared expression patterns obtained from our study to those observed in the fruitfly Drosophila melanogaster. We found that many genes showed distinct patterns of expression between the larval and adult ant life stages, a result that was confirmed through quantitative reverse-transcriptase polymerase chain reaction. Genes involved in protein metabolism and possessing structural activity tended to be more highly expressed in larval than adult ants. In contrast, genes relatively upregulated in adults possessed a greater diversity of functions and activities. We also discovered that patterns of expression observed for homologous genes in D. melanogaster differed substantially from those observed in C. festinatus. Our results suggest that the specific molecular mechanisms involved in metamorphosis will differ substantially between insect taxa. Systematic investigation of gene expression during development of other taxa will provide additional information on how developmental pathways evolve.

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

    PubMed Central

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

    2013-01-01

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

  15. Biological data warehousing system for identifying transcriptional regulatory sites from gene expressions of microarray data.

    PubMed

    Tsou, Ann-Ping; Sun, Yi-Ming; Liu, Chia-Lin; Huang, Hsien-Da; Horng, Jorng-Tzong; Tsai, Meng-Feng; Liu, Baw-Juine

    2006-07-01

    Identification of transcriptional regulatory sites plays an important role in the investigation of gene regulation. For this propose, we designed and implemented a data warehouse to integrate multiple heterogeneous biological data sources with data types such as text-file, XML, image, MySQL database model, and Oracle database model. The utility of the biological data warehouse in predicting transcriptional regulatory sites of coregulated genes was explored using a synexpression group derived from a microarray study. Both of the binding sites of known transcription factors and predicted over-represented (OR) oligonucleotides were demonstrated for the gene group. The potential biological roles of both known nucleotides and one OR nucleotide were demonstrated using bioassays. Therefore, the results from the wet-lab experiments reinforce the power and utility of the data warehouse as an approach to the genome-wide search for important transcription regulatory elements that are the key to many complex biological systems.

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

    PubMed

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

    2016-01-01

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

  17. Microarray-Based Detection of Salmonella enterica Serovar Enteritidis Genes Involved in Chicken Reproductive Tract Colonization

    PubMed Central

    Raspoet, R.; Appia-Ayme, C.; Shearer, N.; Martel, A.; Pasmans, F.; Haesebrouck, F.; Ducatelle, R.; Thompson, A.

    2014-01-01

    Salmonella enterica serovar Enteritidis has developed the potential to contaminate table eggs internally, by colonization of the chicken reproductive tract and internalization in the forming egg. The serotype Enteritidis has developed mechanisms to colonize the chicken oviduct more successfully than other serotypes. Until now, the strategies exploited by Salmonella Enteritidis to do so have remained largely unknown. For that reason, a microarray-based transposon library screen was used to identify genes that are essential for the persistence of Salmonella Enteritidis inside primary chicken oviduct gland cells in vitro and inside the reproductive tract in vivo. A total of 81 genes with a potential role in persistence in both the oviduct cells and the oviduct tissue were identified. Major groups of importance include the Salmonella pathogenicity islands 1 and 2, genes involved in stress responses, cell wall, and lipopolysaccharide structure, and the region-of-difference genomic islands 9, 21, and 40. PMID:25281378

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

    PubMed Central

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

    2016-01-01

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

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

    PubMed

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

    2012-01-01

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

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

    PubMed Central

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

    2008-01-01

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

  1. Comprehensive network analysis of anther-expressed genes in rice by the combination of 33 laser microdissection and 143 spatiotemporal microarrays.

    PubMed

    Aya, Koichiro; Suzuki, Go; Suwabe, Keita; Hobo, Tokunori; Takahashi, Hirokazu; Shiono, Katsuhiro; Yano, Kentaro; Tsutsumi, Nobuhiro; Nakazono, Mikio; Nagamura, Yoshiaki; Matsuoka, Makoto; Watanabe, Masao

    2011-01-01

    Co-expression networks systematically constructed from large-scale transcriptome data reflect the interactions and functions of genes with similar expression patterns and are a powerful tool for the comprehensive understanding of biological events and mining of novel genes. In Arabidopsis (a model dicot plant), high-resolution co-expression networks have been constructed from very large microarray datasets and these are publicly available as online information resources. However, the available transcriptome data of rice (a model monocot plant) have been limited so far, making it difficult for rice researchers to achieve reliable co-expression analysis. In this study, we performed co-expression network analysis by using combined 44 K agilent microarray datasets of rice, which consisted of 33 laser microdissection (LM)-microarray datasets of anthers, and 143 spatiotemporal transcriptome datasets deposited in RicexPro. The entire data of the rice co-expression network, which was generated from the 176 microarray datasets by the Pearson correlation coefficient (PCC) method with the mutual rank (MR)-based cut-off, contained 24,258 genes and 60,441 genes pairs. Using these datasets, we constructed high-resolution co-expression subnetworks of two specific biological events in the anther, "meiosis" and "pollen wall synthesis". The meiosis network contained many known or putative meiotic genes, including genes related to meiosis initiation and recombination. In the pollen wall synthesis network, several candidate genes involved in the sporopollenin biosynthesis pathway were efficiently identified. Hence, these two subnetworks are important demonstrations of the efficiency of co-expression network analysis in rice. Our co-expression analysis included the separated transcriptomes of pollen and tapetum cells in the anther, which are able to provide precise information on transcriptional regulation during male gametophyte development in rice. The co-expression network data

  2. The Importance of Normalization on Large and Heterogeneous Microarray Datasets

    EPA Science Inventory

    DNA microarray technology is a powerful functional genomics tool increasingly used for investigating global gene expression in environmental studies. Microarrays can also be used in identifying biological networks, as they give insight on the complex gene-to-gene interactions, ne...

  3. Microarray data analysis and mining approaches.

    PubMed

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

    2007-12-01

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

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

    PubMed

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

    2013-01-01

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

  5. Probing High-density Functional Protein Microarrays to Detect Protein-protein Interactions.

    PubMed

    Fasolo, Joseph; Im, Hogune; Snyder, Michael P

    2015-01-01

    High-density functional protein microarrays containing ~4,200 recombinant yeast proteins are examined for kinase protein-protein interactions using an affinity purified yeast kinase fusion protein containing a V5-epitope tag for read-out. Purified kinase is obtained through culture of a yeast strain optimized for high copy protein production harboring a plasmid containing a Kinase-V5 fusion construct under a GAL inducible promoter. The yeast is grown in restrictive media with a neutral carbon source for 6 hr followed by induction with 2% galactose. Next, the culture is harvested and kinase is purified using standard affinity chromatographic techniques to obtain a highly purified protein kinase for use in the assay. The purified kinase is diluted with kinase buffer to an appropriate range for the assay and the protein microarrays are blocked prior to hybridization with the protein microarray. After the hybridization, the arrays are probed with monoclonal V5 antibody to identify proteins bound by the kinase-V5 protein. Finally, the arrays are scanned using a standard microarray scanner, and data is extracted for downstream informatics analysis to determine a high confidence set of protein interactions for downstream validation in vivo. PMID:26274875

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

    PubMed Central

    2013-01-01

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

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

    PubMed

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

    2016-06-01

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

  8. Profiling candidate genes involved in wax biosynthesis in Arabidopsis thaliana by microarray analysis.

    PubMed

    Costaglioli, Patricia; Joubès, Jérôme; Garcia, Christel; Stef, Marianne; Arveiler, Benoît; Lessire, René; Garbay, Bertrand

    2005-06-01

    Plant epidermal wax forms a hydrophobic layer covering aerial plant organs which constitutes a barrier against uncontrolled water loss and biotic stresses. Wax biosynthesis requires the coordinated activity of a large number of enzymes for the formation of saturated very-long-chain fatty acids and their further transformation in several aliphatic compounds. We found in the available database 282 candidate genes that may play a role in wax synthesis, regulation and transport. To identify the most interesting candidates, we measured the level of expression of 204 genes in the aerial parts of 15-day-old Arabidopsis seedlings by performing microarray experiments. We showed that only 25% of the putative candidates were expressed to significant levels in our samples, thus significantly reducing the number of genes which will be worth studying using reverse genetics to demonstrate their involvement in wax accumulation. We identified a beta-keto acyl-CoA synthase gene, At5g43760, which is co-regulated with the wax gene CER6 in a number of conditions and organs. By contrast, we showed that neither the fatty acyl-CoA reductase genes nor the wax synthase genes were expressed in 15-day-old leaves and stems, raising questions about the identity of the enzymes involved in the acyl-reduction pathway that accounts for 20% of the total wax amount. PMID:15914083

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

    PubMed

    Bertagnolli, Nicolas M; Drake, Justin A; Tennessen, Jason M; Alter, Orly

    2013-01-01

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

  10. Microarray Analysis of Gene Expression in Saccharomyces cerevisiae kap108Δ Mutants upon Addition of Oxidative Stress.

    PubMed

    Belanger, Kenneth D; Larson, Nathaniel; Kahn, Jonathan; Tkachev, Dmitry; Ay, Ahmet

    2016-01-01

    Protein transport between the nucleus and cytoplasm of eukaryotic cells is tightly regulated, providing a mechanism for controlling intracellular localization of proteins, and regulating gene expression. In this study, we have investigated the importance of nucleocytoplasmic transport mediated by the karyopherin Kap108 in regulating cellular responses to oxidative stress in Saccharomyces cerevisiae We carried out microarray analyses on wild-type and kap108 mutant cells grown under normal conditions, shortly after introduction of oxidative stress, after 1 hr of oxidative stress, and 1 hr after oxidative stress was removed. We observe more than 500 genes that undergo a 40% or greater change in differential expression between wild-type and kap108Δ cells under at least one of these conditions. Genes undergoing changes in expression can be categorized in two general groups: 1) those that are differentially expressed between wild-type and kap108Δ cells, no matter the oxidative stress conditions; and 2) those that have patterns of response dependent upon both the absence of Kap108, and introduction or removal of oxidative stress. Gene ontology analysis reveals that, among the genes whose expression is reduced in the absence of Kap108 are those involved in stress response and intracellular transport, while those overexpressed are largely involved in mating and pheromone response. We also identified 25 clusters of genes that undergo similar patterns of change in gene expression when oxidative stresses are added and subsequently removed, including genes involved in stress response, oxidation-reduction processing, iron homeostasis, ascospore wall assembly, transmembrane transport, and cell fusion during mating. These data suggest that Kap108 is important for regulating expression of genes involved in a variety of specific cell functions.

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

    PubMed Central

    Zhou, Xichun; Turchi, Craig; Wang, Denong

    2009-01-01

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

  12. Rapid and Facile Microwave-Assisted Surface Chemistry for Functionalized Microarray Slides

    PubMed Central

    Lee, Jeong Heon; Hyun, Hoon; Cross, Conor J.; Henary, Maged; Nasr, Khaled A.; Oketokoun, Rafiou; Choi, Hak Soo; Frangioni, John V.

    2011-01-01

    We describe a rapid and facile method for surface functionalization and ligand patterning of glass slides based on microwave-assisted synthesis and a microarraying robot. Our optimized reaction enables surface modification 42-times faster than conventional techniques and includes a carboxylated self-assembled monolayer, polyethylene glycol linkers of varying length, and stable amide bonds to small molecule, peptide, or protein ligands to be screened for binding to living cells. We also describe customized slide racks that permit functionalization of 100 slides at a time to produce a cost-efficient, highly reproducible batch process. Ligand spots can be positioned on the glass slides precisely using a microarraying robot, and spot size adjusted for any desired application. Using this system, we demonstrate live cell binding to a variety of ligands and optimize PEG linker length. Taken together, the technology we describe should enable high-throughput screening of disease-specific ligands that bind to living cells. PMID:23467787

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

    PubMed Central

    2011-01-01

    Background Gene regulatory networks have an essential role in every process of life. In this regard, the amount of genome-wide time series data is becoming increasingly available, providing the opportunity to discover the time-delayed gene regulatory networks that govern the majority of these molecular processes. Results This paper aims at reconstructing gene regulatory networks from multiple genome-wide microarray time series datasets. In this sense, a new model-free algorithm called GRNCOP2 (Gene Regulatory Network inference by Combinatorial OPtimization 2), which is a significant evolution of the GRNCOP algorithm, was developed using combinatorial optimization of gene profile classifiers. The method is capable of inferring potential time-delay relationships with any span of time between genes from various time series datasets given as input. The proposed algorithm was applied to time series data composed of twenty yeast genes that are highly relevant for the cell-cycle study, and the results were compared against several related approaches. The outcomes have shown that GRNCOP2 outperforms the contrasted methods in terms of the proposed metrics, and that the results are consistent with previous biological knowledge. Additionally, a genome-wide study on multiple publicly available time series data was performed. In this case, the experimentation has exhibited the soundness and scalability of the new method which inferred highly-related statistically-significant gene associations. Conclusions A novel method for inferring time-delayed gene regulatory networks from genome-wide time series datasets is proposed in this paper. The method was carefully validated with several publicly available data sets. The results have demonstrated that the algorithm constitutes a usable model-free approach capable of predicting meaningful relationships between genes, revealing the time-trends of gene regulation. PMID:21524308

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

    PubMed

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

    2016-01-04

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

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

    PubMed

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

    2016-03-01

    Pathogen identification and microbial source tracking (MST) to identify sources of fecal pollution improve evaluation of water quality. They contribute to improved assessment of human health risks and remediation of pollution sources. An MST microarray was used to simultaneously detect genes for multiple pathogens and indicators of fecal pollution in freshwater, marine water, sewage-contaminated freshwater and marine water, and treated wastewater. Dead-end ultrafiltration (DEUF) was used to concentrate organisms from water samples, yielding a recovery efficiency of >95% for Escherichia coli and human polyomavirus. Whole-genome amplification (WGA) increased gene copies from ultrafiltered samples and increased the sensitivity of the microarray. Viruses (adenovirus, bocavirus, hepatitis A virus, and human polyomaviruses) were detected in sewage-contaminated samples. Pathogens such as Legionella pneumophila, Shigella flexneri, and Campylobacter fetus were detected along with genes conferring resistance to aminoglycosides, beta-lactams, and tetracycline. Nonmetric dimensional analysis of MST marker genes grouped sewage-spiked freshwater and marine samples with sewage and apart from other fecal sources. The sensitivity (percent true positives) of the microarray probes for gene targets anticipated in sewage was 51 to 57% and was lower than the specificity (percent true negatives; 79 to 81%). A linear relationship between gene copies determined by quantitative PCR and microarray fluorescence was found, indicating the semiquantitative nature of the MST microarray. These results indicate that ultrafiltration coupled with WGA provides sufficient nucleic acids for detection of viruses, bacteria, protozoa, and antibiotic resistance genes by the microarray in applications ranging from beach monitoring to risk assessment. PMID:26729716

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

    PubMed Central

    Li, Xiang; Harwood, Valerie J.; Nayak, Bina

    2016-01-01

    Pathogen identification and microbial source tracking (MST) to identify sources of fecal pollution improve evaluation of water quality. They contribute to improved assessment of human health risks and remediation of pollution sources. An MST microarray was used to simultaneously detect genes for multiple pathogens and indicators of fecal pollution in freshwater, marine water, sewage-contaminated freshwater and marine water, and treated wastewater. Dead-end ultrafiltration (DEUF) was used to concentrate organisms from water samples, yielding a recovery efficiency of >95% for Escherichia coli and human polyomavirus. Whole-genome amplification (WGA) increased gene copies from ultrafiltered samples and increased the sensitivity of the microarray. Viruses (adenovirus, bocavirus, hepatitis A virus, and human polyomaviruses) were detected in sewage-contaminated samples. Pathogens such as Legionella pneumophila, Shigella flexneri, and Campylobacter fetus were detected along with genes conferring resistance to aminoglycosides, beta-lactams, and tetracycline. Nonmetric dimensional analysis of MST marker genes grouped sewage-spiked freshwater and marine samples with sewage and apart from other fecal sources. The sensitivity (percent true positives) of the microarray probes for gene targets anticipated in sewage was 51 to 57% and was lower than the specificity (percent true negatives; 79 to 81%). A linear relationship between gene copies determined by quantitative PCR and microarray fluorescence was found, indicating the semiquantitative nature of the MST microarray. These results indicate that ultrafiltration coupled with WGA provides sufficient nucleic acids for detection of viruses, bacteria, protozoa, and antibiotic resistance genes by the microarray in applications ranging from beach monitoring to risk assessment. PMID:26729716

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

    PubMed Central

    2010-01-01

    -BLAST function within SSHdb grouped redundant clones together and illustrated that the SSHscreen plots are a useful tool for choosing anonymous clones for sequencing, since redundant clones cluster together on the enrichment ratio plots. Conclusions We developed the SSHscreen-SSHdb software pipeline, which greatly facilitates gene discovery using suppression subtractive hybridization by improving the selection of clones for sequencing after screening the library on a small number of microarrays. Annotation of the sequence information and collaboration was further enhanced through a web-based SSHdb database, and we illustrated this through identification of drought responsive genes from cowpea, which can now be investigated in gene function studies. SSH is a popular and powerful gene discovery tool, and therefore this pipeline will have application for gene discovery in any biological system, particularly non-model organisms. SSHscreen 2.0.1 and a link to SSHdb are available from http://microarray.up.ac.za/SSHscreen. PMID:20359330

  18. Bayesian Hierarchical Model for Estimating Gene Expression Intensity Using Multiple Scanned Microarrays

    PubMed Central

    2008-01-01

    We propose a method for improving the quality of signal from DNA microarrays by using several scans at varying scanner sen-sitivities. A Bayesian latent intensity model is introduced for the analysis of such data. The method improves the accuracy at which expressions can be measured in all ranges and extends the dynamic range of measured gene expression at the high end. Our method is generic and can be applied to data from any organism, for imaging with any scanner that allows varying the laser power, and for extraction with any image analysis software. Results from a self-self hybridization data set illustrate an improved precision in the estimation of the expression of genes compared to what can be achieved by applying standard methods and using only a single scan. PMID:18464926

  19. Robust gene signatures from microarray data using genetic algorithms enriched with biological pathway keywords.

    PubMed

    Luque-Baena, R M; Urda, D; Gonzalo Claros, M; Franco, L; Jerez, J M

    2014-06-01

    Genetic algorithms are widely used in the estimation of expression profiles from microarrays data. However, these techniques are unable to produce stable and robust solutions suitable to use in clinical and biomedical studies. This paper presents a novel two-stage evolutionary strategy for gene feature selection combining the genetic algorithm with biological information extracted from the KEGG database. A comparative study is carried out over public data from three different types of cancer (leukemia, lung cancer and prostate cancer). Even though the analyses only use features having KEGG information, the results demonstrate that this two-stage evolutionary strategy increased the consistency, robustness and accuracy of a blind discrimination among relapsed and healthy individuals. Therefore, this approach could facilitate the definition of gene signatures for the clinical prognosis and diagnostic of cancer diseases in a near future. Additionally, it could also be used for biological knowledge discovery about the studied disease.

  20. Identification of Novel Cholesteatoma-Related Gene Expression Signatures Using Full-Genome Microarrays

    PubMed Central

    Klenke, Christin; Janowski, Sebastian; Borck, Daniela; Widera, Darius; Ebmeyer, Jörg; Kalinowski, Jörn; Leichtle, Anke; Hofestädt, Ralf; Upile, Tahwinder; Kaltschmidt, Christian; Kaltschmidt, Barbara; Sudhoff, Holger

    2012-01-01

    Background Cholesteatoma is a gradually expanding destructive epithelial lesion within the middle ear. It can cause extensive local tissue destruction in the temporal bone and can initially lead to the development of conductive hearing loss via ossicular erosion. As the disease progresses, sensorineural hearing loss, vertigo or facial palsy may occur. Cholesteatoma may promote the spread of infection through the tegmen of the middle ear and cause meningitis or intracranial infections with abscess formation. It must, therefore, be considered as a potentially life-threatening middle ear disease. Methods and Findings In this study, we investigated differentially expressed genes in human cholesteatomas in comparison to regular auditory canal skin using Whole Human Genome Microarrays containing 19,596 human genes. In addition to already described up-regulated mRNAs in cholesteatoma, such as MMP9, DEFB2 and KRT19, we identified 3558 new cholesteatoma-related transcripts. 811 genes appear to be significantly differentially up-regulated in cholesteatoma. 334 genes were down-regulated more than 2-fold. Significantly regulated genes with protein metabolism activity include matrix metalloproteinases as well as PI3, SERPINB3 and SERPINB4. Genes like SPP1, KRT6B, PRPH, SPRR1B and LAMC2 are known as genes with cell growth and/or maintenance activity. Transport activity genes and signal transduction genes are LCN2, GJB2 and CEACAM6. Three cell communication genes were identified; one CDH19 and two from the S100 family. Conclusions This study demonstrates that the expression profile of cholesteatoma is similar to a metastatic tumour and chronically inflamed tissue. Based on the investigated profiles we present novel protein-protein interaction and signal transduction networks, which include cholesteatoma-regulated transcripts and may be of great value for drug targeting and therapy development. PMID:23285167

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

    PubMed Central

    Zhao, Xin; Cheung, Leo Wang-Kit

    2007-01-01

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

  2. Gene expression microarray analysis of the sciatic nerve of mice with diabetic neuropathy.

    PubMed

    Zhang, Lei; Qu, Shen; Liang, Aibin; Jiang, Hong; Wang, Hao

    2015-02-01

    The present study aimed to explore novel target genes that regulate the development of diabetic neuropathy (DN) by analyzing gene expression profiles in the sciatic nerve of infected mice. The GSE11343 microarray dataset, which was downloaded from Gene Expression Omnibus, included data on 4 control samples and 5 samples from mice with diabetes induced by streptozotocin (STZ), 5 samples from normal mice treated with rosiglitazone (Rosi) and 5 samples from mice with diabetes induced by STZ and treated with Rosi. Differentially expressed genes (DEGs) between the different groups were identified using the substitution augmentation modification redefinition (SAMR) model. The Gene Ontology (GO) term and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed using the Database for Annotation, Visualization and Integrated Discovery (DAVID). Regulatory and protein‑protein interaction networks were searched using BioCarta and STRING, respectively. The protein structures of potential regulatory genes were predicted using the SYBYL program. Compared with the controls, 1,384 DEGs were identified in the mice with STZ-induced diabetes and 7 DEGs were identified in the mice treated with Rosi. There were 518 DEGs identified between the mice in the STZ + Rosi and STZ groups. We identified 45 GO items, and the calmodulin nerve phosphatase and chemokine signaling pathways were identified as the main pathways. Three genes [myristoylated alanine-rich protein kinase C substrate (Marcks), GLI pathogenesis-related 2 (Glipr2) and centrosomal protein 170 kDa (Cep170)] were found to be co-regulated by both STZ and Rosi, the protein structure of which was predicted and certain binding activity to Rosi was docked. Our study demonstrates that the Marcks, Glipr2 and Cep170 genes may be underlying drug targets in the treatment of DN. PMID:25435094

  3. Gene expression microarray analysis of the sciatic nerve of mice with diabetic neuropathy

    PubMed Central

    ZHANG, LEI; QU, SHEN; LIANG, AIBIN; JIANG, HONG; WANG, HAO

    2015-01-01

    The present study aimed to explore novel target genes that regulate the development of diabetic neuropathy (DN) by analyzing gene expression profiles in the sciatic nerve of infected mice. The GSE11343 microarray dataset, which was downloaded from Gene Expression Omnibus, included data on 4 control samples and 5 samples from mice with diabetes induced by streptozotocin (STZ), 5 samples from normal mice treated with rosiglitazone (Rosi) and 5 samples from mice with diabetes induced by STZ and treated with Rosi. Differentially expressed genes (DEGs) between the different groups were identified using the substitution augmentation modification redefinition (SAMR) model. The Gene Ontology (GO) term and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed using the Database for Annotation, Visualization and Integrated Discovery (DAVID). Regulatory and protein-protein interaction networks were searched using BioCarta and STRING, respectively. The protein structures of potential regulatory genes were predicted using the SYBYL program. Compared with the controls, 1,384 DEGs were identified in the mice with STZ-induced diabetes and 7 DEGs were identified in the mice treated with Rosi. There were 518 DEGs identified between the mice in the STZ + Rosi and STZ groups. We identified 45 GO items, and the calmodulin nerve phosphatase and chemokine signaling pathways were identified as the main pathways. Three genes [myristoylated alanine-rich protein kinase C substrate (Marcks), GLI pathogenesis-related 2 (Glipr2) and centrosomal protein 170 kDa (Cep170)] were found to be co-regulated by both STZ and Rosi, the protein structure of which was predicted and certain binding activity to Rosi was docked. Our study demonstrates that the Marcks, Glipr2 and Cep170 genes may be underlying drug targets in the treatment of DN. PMID:25435094

  4. Responses of Cultured Human Keratocytes and Myofibroblasts to Ethyl Pyruvate: A Microarray Analysis of Gene Expression

    PubMed Central

    Guerriero, Emily; Charukamnoetkanok, Nahthai; Piluek, Jordan; Schuman, Joel S.; SundarRaj, Nirmala

    2010-01-01

    Purpose. Ethyl pyruvate (EP) has pharmacologic effects that remediate cellular stress. In the organ-cultured murine lens, EP ameliorates oxidative stress, and in a rat cataract model, it attenuates cataract formation. However, corneal responses to EP have not been elucidated. In this study, the potential of EP as a therapeutic agent in corneal wound healing was determined by examining its effects on the transition of quiescent corneal stromal keratocytes into contractile myofibroblasts. Methods. Three independent preparations of cultured human keratocytes were treated with TGF-β1, to elicit a phenotypic transition to myofibroblasts in the presence or absence of 10 or 15 mM EP. Gene expression profiles of the 12 samples (keratocytes ± EP ± TGF-β1 for three preparations) were produced by using gene microarrays. Results. TGF-β1–driven twofold changes in at least two of three experiments defined a group of 1961 genes. Genes showing twofold modulation by EP in at least two experiments appeared exclusively in myofibroblasts (857 genes), exclusively in keratocytes (409 genes), or in both phenotypes (252 genes). Analysis of these three EP-modulated groups showed that EP (1) inhibited myofibroblast proliferation with concomitant modulation of some cell cycle genes, (2) augmented the NRF2-mediated antioxidant response in both keratocytes and myofibroblasts, and (3) modified the TGF-β1–driven transition of keratocytes to myofibroblasts by inhibiting the upregulation of a subset of profibrotic genes. Conclusions. These EP-induced phenotypic changes in myofibroblasts indicate the potential of EP as a therapeutic agent in corneal wound healing. PMID:20053976

  5. Identification of genes associated with tumorigenesis and metastatic potential of hypopharyngeal cancer by microarray analysis.

    PubMed

    Cromer, Anne; Carles, Annaïck; Millon, Régine; Ganguli, Gitali; Chalmel, Frédéric; Lemaire, Frédéric; Young, Julia; Dembélé, Doulaye; Thibault, Christelle; Muller, Danièle; Poch, Olivier; Abecassis, Joseph; Wasylyk, Bohdan

    2004-04-01

    Head and neck squamous cell carcinoma (HNSCC) is the sixth most common cancer among men in the developed world. There is a need, for both clinical and scientific reasons, to find markers to identify patients with aggressive disease as early as possible, and to understand the events leading to malignant transformation and susceptibility to metastasis. We report the first large-scale gene expression analysis of a unique HNSCC location, the hypopharynx. Four normal and 34 tumour samples were analysed with 12 600 gene microarrays. Clusters of differentially expressed genes were identified in the chromosomal regions 3q27.3, 17q21.2-q21.31, 7q11.22-q22.1 and 11q13.1-q13.3, which, interestingly, have already been identified by comparative genomic hybridization (CGH) as major regions of gene amplification. We showed that six overexpressed genes (EIF4G1, DVL3, EPHB4, MCM7, BRMS1 and SART1) located in these regions are indeed amplified. We report 119 genes that are highly differentially expressed between 'early' tumours and normal samples. Of these, we validated by quantitative PCR six novel poorly characterized genes. These genes are potential new markers of HNSCC. Comparing patients with relatively nonaggressive and aggressive tumours (without or with clinical evidence of metastasis 3 years after surgery), we identified 164 differentially expressed genes potentially involved in the acquisition of metastatic potential. This study contributes to the understanding of HNSCC, staging patients into prognostic groups and identifying high-risk patients who may benefit from more aggressive treatment.

  6. Vaccine-induced modulation of gene expression in turbot peritoneal cells. A microarray approach.

    PubMed

    Fontenla, Francisco; Blanco-Abad, Verónica; Pardo, Belén G; Folgueira, Iria; Noia, Manuel; Gómez-Tato, Antonio; Martínez, Paulino; Leiro, José M; Lamas, Jesús

    2016-07-01

    We used a microarray approach to examine changes in gene expression in turbot peritoneal cells after injection of the fish with vaccines containing the ciliate parasite Philasterides dicentrarchi as antigen and one of the following adjuvants: chitosan-PVMMA microspheres, Freund́s complete adjuvant, aluminium hydroxide gel or Matrix-Q (Isconova, Sweden). We identified 374 genes that were differentially expressed in all groups of fish. Forty-two genes related to tight junctions and focal adhesions and/or actin cytoskeleton were differentially expressed in free peritoneal cells. The profound changes in gene expression related to cell adherence and cytoskeleton may be associated with cell migration and also with the formation of cell-vaccine masses and their attachment to the peritoneal wall. Thirty-five genes related to apoptosis were differentially expressed. Although most of the proteins coded by these genes have a proapoptotic effect, others are antiapoptotic, indicating that both types of signals occur in peritoneal leukocytes of vaccinated fish. Interestingly, many of the genes related to lymphocytes and lymphocyte activity were downregulated in the groups injected with vaccine. We also observed decreased expression of genes related to antigen presentation, suggesting that macrophages (which were abundant in the peritoneal cavity after vaccination) did not express these during the early inflammatory response in the peritoneal cavity. Finally, several genes that participate in the inflammatory response were differentially expressed, and most participated in resolution of inflammation, indicating that an M2 macrophage response is generated in the peritoneal cavity of fish one day post vaccination. PMID:27318565

  7. Vaccine-induced modulation of gene expression in turbot peritoneal cells. A microarray approach.

    PubMed

    Fontenla, Francisco; Blanco-Abad, Verónica; Pardo, Belén G; Folgueira, Iria; Noia, Manuel; Gómez-Tato, Antonio; Martínez, Paulino; Leiro, José M; Lamas, Jesús

    2016-07-01

    We used a microarray approach to examine changes in gene expression in turbot peritoneal cells after injection of the fish with vaccines containing the ciliate parasite Philasterides dicentrarchi as antigen and one of the following adjuvants: chitosan-PVMMA microspheres, Freund́s complete adjuvant, aluminium hydroxide gel or Matrix-Q (Isconova, Sweden). We identified 374 genes that were differentially expressed in all groups of fish. Forty-two genes related to tight junctions and focal adhesions and/or actin cytoskeleton were differentially expressed in free peritoneal cells. The profound changes in gene expression related to cell adherence and cytoskeleton may be associated with cell migration and also with the formation of cell-vaccine masses and their attachment to the peritoneal wall. Thirty-five genes related to apoptosis were differentially expressed. Although most of the proteins coded by these genes have a proapoptotic effect, others are antiapoptotic, indicating that both types of signals occur in peritoneal leukocytes of vaccinated fish. Interestingly, many of the genes related to lymphocytes and lymphocyte activity were downregulated in the groups injected with vaccine. We also observed decreased expression of genes related to antigen presentation, suggesting that macrophages (which were abundant in the peritoneal cavity after vaccination) did not express these during the early inflammatory response in the peritoneal cavity. Finally, several genes that participate in the inflammatory response were differentially expressed, and most participated in resolution of inflammation, indicating that an M2 macrophage response is generated in the peritoneal cavity of fish one day post vaccination.

  8. Gene Selection in Arthritis Classification With Large-Scale Microarray Expression Profiles

    PubMed Central

    Sha, Naijun; Brown, Philip J.; Trower, Michael K.; Amphlett, Gillian; Falciani, Francesco

    2003-01-01

    The use of large-scale microarray expression profiling to identify predictors of disease class has become of major interest. Beyond their impact in the clinical setting (i.e. improving diagnosis and treatment), these markers are also likely to provide clues on the molecular mechanisms underlining the diseases. In this paper we describe a new method for the identification of multiple gene predictors of disease class. The method is applied to the classification of two forms of arthritis that have a similar clinical endpoint but different underlying molecular mechanisms: rheumatoid arthritis (RA) and osteoarthritis (OA). We aim at both the classification of samples and the location of genes characterizing the different classes. We achieve both goals simultaneously by combining a binary probit model for classification with Bayesian variable selection methods to identify important genes.We find very small sets of genes that lead to good classification results. Some of the selected genes are clearly correlated with known aspects of the biology of arthritis and, in some cases, reflect already known differences between RA and OA. PMID:18629129

  9. DNA microarray analysis of functionally discrete human brain regions reveals divergent transcriptional profiles

    PubMed Central

    Evans, S.J.; Choudary, P.V.; Vawter, M.P.; Li, J.; Meador-Woodruff, J.H.; Lopez, J.F.; Burke, S.M.; Thompson, R.C.; Myers, R.M.; Jones, E.G.; Bunney, W.E.; Watson, S.J.; Akil, H.

    2010-01-01

    Transcriptional profiles within discrete human brain regions are likely to reflect structural and functional specialization. Using DNA microarray technology, this study investigates differences in transcriptional profiles of highly divergent brain regions (the cerebellar cortex and the cerebral cortex) as well as differences between two closely related brain structures (the anterior cingulate cortex and the dorsolateral prefrontal cortex). Replication of this study across three independent laboratories, to address false-positive and false-negative results using microarray technology, is also discussed. We find greater than a thousand transcripts to be differentially expressed between cerebellum and cerebral cortex and very few transcripts to be differentially expressed between the two neocortical regions. We further characterized transcripts that were found to be specifically expressed within brain regions being compared and found that ontological classes representing signal transduction machinery, neurogenesis, synaptic transmission, and transcription factors were most highly represented. PMID:14572446

  10. Microarray immunoassay for phenoxybenzoic acid using polymer-functionalized lanthanide oxide nanoparticles as fluorescent labels

    NASA Astrophysics Data System (ADS)

    Nichkova, Mikaela; Dosev, Dosi; Gee, Shirley J.; Hammock, Bruce D.; Kennedy, Ian M.

    2005-11-01

    Fluorescent properties and low production cost makes lanthanide oxide nanoparticles attractive labels in biochemistry. Nanoparticles with different fluorescent spectra were produced by doping of oxides such as Y IIO 3 and Gd IIO 3 with different lanthanide ions (Eu, Tb, Sm) giving the possibility for multicolor labeling. Protein microarrays have the potential to play a fundamental role in the miniaturization of biosensors, clinical immunological assays, and protein-protein interaction studies. Here we present the application of fluorescent lanthanide oxide nanoparticles as labels in microarray-based immunoassay for phenoxybenzoic acid (PBA), a generic biomarker of human exposure to the highly potent insecticides pyrethroids. A novel polymer-based protocol was developed for biochemical functionalization of the nanoparticles. Microarrays of antibodies were fabricated by microcontact printing in line patterns onto glass substrates and immunoassays were successfully performed using the corresponding functionalized nanoparticles. The applicability of the fluorophore nanoparticles as reporters for detection of antibody-antigen interactions has been demonstrated for phenoxybenzoic acid (PBA)/anti-PBA IgG. The sensitivity of the competitive fluorescent immunoassay for PBA was similar to that of the corresponding ELISA.

  11. Functionalization of poly(methyl methacrylate) (PMMA) as a substrate for DNA microarrays

    PubMed Central

    Fixe, F.; Dufva, M.; Telleman, P.; Christensen, C. B. V.

    2004-01-01

    A chemical procedure was developed to functionalize poly(methyl methacrylate) (PMMA) substrates. PMMA is reacted with hexamethylene diamine to yield an aminated surface for immobilizing DNA in microarrays. The density of primary NH2 groups was 0.29 nmol/cm2. The availability of these primary amines was confirmed by the immobilization of DNA probes and hybridization with a complementary DNA strand. The hybridization signal and the hybridization efficiency of the chemically aminated PMMA slides were comparable to the hybridization signal and the hybridization efficiency obtained from differently chemically modified PMMA slides, silanized glass, commercial silylated glass and commercial plastic Euray™ slides. Immobilized and hybridized densities of 10 and 0.75 pmol/cm2, respectively, were observed for microarrays on chemically aminated PMMA. The immobilized probes were heat stable since the hybridization performance of microarrays subjected to 20 PCR heat cycles was only reduced by 4%. In conclusion, this new strategy to modify PMMA provides a robust procedure to immobilize DNA, which is a very useful substrate for fabricating single use diagnostics devices with integrated functions, like sample preparation, treatment and detection using microfabrication and microelectronic techniques. PMID:14718554

  12. Functionalization of poly(methyl methacrylate) (PMMA) as a substrate for DNA microarrays.

    PubMed

    Fixe, F; Dufva, M; Telleman, P; Christensen, C B V

    2004-01-01

    A chemical procedure was developed to functionalize poly(methyl methacrylate) (PMMA) substrates. PMMA is reacted with hexamethylene diamine to yield an aminated surface for immobilizing DNA in microarrays. The density of primary NH2 groups was 0.29 nmol/cm2. The availability of these primary amines was confirmed by the immobilization of DNA probes and hybridization with a complementary DNA strand. The hybridization signal and the hybridization efficiency of the chemically aminated PMMA slides were comparable to the hybridization signal and the hybridization efficiency obtained from differently chemically modified PMMA slides, silanized glass, commercial silylated glass and commercial plastic Euray trade mark slides. Immobilized and hybridized densities of 10 and 0.75 pmol/cm2, respectively, were observed for microarrays on chemically aminated PMMA. The immobilized probes were heat stable since the hybridization performance of microarrays subjected to 20 PCR heat cycles was only reduced by 4%. In conclusion, this new strategy to modify PMMA provides a robust procedure to immobilize DNA, which is a very useful substrate for fabricating single use diagnostics devices with integrated functions, like sample preparation, treatment and detection using microfabrication and microelectronic techniques. PMID:14718554

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

    PubMed Central

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

    2008-01-01

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

  14. Microarray-Based Identification of Differentially Expressed Genes in Intracellular Brucella abortus within RAW264.7 Cells

    PubMed Central

    Tian, Mingxing; Qu, Jing; Han, Xiangan; Zhang, Min; Ding, Chan; Ding, Jiabo; Chen, Guanghua; Yu, Shengqing

    2013-01-01

    Brucella spp. is a species of facultative intracellular Gram-negative bacteria that induces abortion and causes sterility in domesticated mammals and chronic undulant fever in humans. Important determinants of Brucella’s virulence and potential for chronic infection include the ability to circumvent the host cell’s internal surveillance system and the capability to proliferate within dedicated and non-dedicated phagocytes. Hence, identifying genes necessary for intracellular survival may hold the key to understanding Brucella infection. In the present study, microarray analysis reveals that 7.82% (244/3334) of all Brucella abortus genes were up-regulated and 5.4% (180/3334) were down-regulated in RAW264.7 cells, compared to free-living cells in TSB. qRT-PCR verification further confirmed a >5-fold up-regulation for fourteen genes. Functional analysis classified araC, ddp, and eryD as to partake in information storage and processing, alp, flgF and virB9 to be involved in cellular processes, hpcd and aldh to play a role in metabolism, mfs and nikC to be involved in both cellular processes and metabolism, and four hypothetical genes (bruAb1_1814, bruAb1_0475, bruAb1_1926, and bruAb1_0292) had unknown functions. Furthermore, we constructed a B. abortus 2308 mutant Δddp where the ddp gene is deleted in order to evaluate the role of ddp in intracellular survival. Infection assay indicated significantly higher adherence and invasion abilities of the Δddp mutant, however it does not survive well in RAW264.7 cells. Brucella may survive in hostile intracellular environment by modulating gene expression. PMID:23950864

  15. Microarray Expression Data Identify DCC as a Candidate Gene for Early Meningioma Progression

    PubMed Central

    Schulten, Hans-Juergen; Hussein, Deema; Al-Adwani, Fatima; Karim, Sajjad; Al-Maghrabi, Jaudah; Al-Sharif, Mona; Jamal, Awatif; Al-Ghamdi, Fahad; Baeesa, Saleh S.; Bangash, Mohammed; Chaudhary, Adeel; Al-Qahtani, Mohammed

    2016-01-01

    Meningiomas are the most common primary brain tumors bearing in a minority of cases an aggressive phenotype. Although meningiomas are stratified according to their histology and clinical behavior, the underlying molecular genetics predicting aggressiveness are not thoroughly understood. We performed whole transcript expression profiling in 10 grade I and four grade II meningiomas, three of which invaded the brain. Microarray expression analysis identified deleted in colorectal cancer (DCC) as a differentially expressed gene (DEG) enabling us to cluster meningiomas into DCC low expression (3 grade I and 3 grade II tumors), DCC medium expression (2 grade I and 1 grade II tumors), and DCC high expression (5 grade I tumors) groups. Comparison between the DCC low expression and DCC high expression groups resulted in 416 DEGs (p-value < 0.05; fold change > 2). The most significantly downregulated genes in the DCC low expression group comprised DCC, phosphodiesterase 1C (PDE1C), calmodulin-dependent 70kDa olfactomedin 2 (OLFM2), glutathione S-transferase mu 5 (GSTM5), phosphotyrosine interaction domain containing 1 (PID1), sema domain, transmembrane domain (TM) and cytoplasmic domain, (semaphorin) 6D (SEMA6D), and indolethylamine N-methyltransferase (INMT). The most significantly upregulated genes comprised chromosome 5 open reading frame 63 (C5orf63), homeodomain interacting protein kinase 2 (HIPK2), and basic helix-loop-helix family, member e40 (BHLHE40). Biofunctional analysis identified as predicted top upstream regulators beta-estradiol, TGFB1, Tgf beta complex, LY294002, and dexamethasone and as predicted top regulator effectors NFkB, PIK3R1, and CREBBP. The microarray expression data served also for a comparison between meningiomas from female and male patients and for a comparison between brain invasive and non-invasive meningiomas resulting in a number of significant DEGs and related biofunctions. In conclusion, based on its expression levels, DCC may constitute

  16. Identification of novel pancreatic adenocarcinoma cell-surface targets by gene expression profiling and tissue microarray.

    PubMed

    Morse, David L; Balagurunathan, Yoga; Hostetter, Galen; Trissal, Maria; Tafreshi, Narges K; Burke, Nancy; Lloyd, Mark; Enkemann, Steven; Coppola, Domenico; Hruby, Victor J; Gillies, Robert J; Han, Haiyong

    2010-09-01

    Pancreatic cancer has a high mortality rate, which is generally related to the initial diagnosis coming at late stage disease combined with a lack of effective treatment options. Novel agents that selectively detect pancreatic cancer have potential for use in the molecular imaging of cancer, allowing for non-invasive determination of tumor therapeutic response and molecular characterization of the disease. Such agents may also be used for the targeted delivery of therapy to tumor cells while decreasing systemic effects. Using complementary assays of mRNA expression profiling to determine elevated expression in pancreatic cancer tissues relative to normal pancreas tissues, and validation of protein expression by immunohistochemistry on tissue microarray, we have identified cell-surface targets with potential for imaging and therapeutic agent development. Expression profiles of 2177 cell-surface genes for 28 pancreatic tumor specimens and 4 normal pancreas tissue samples were evaluated. Expression in normal tissues was evaluated using array data from 103 samples representing 28 organ sites as well as mining published data. One-hundred seventy unique targets were highly expressed in 2 or more of the pancreatic tumor specimens and were not expressed in the normal pancreas samples. Two targets (TLR2 and ABCC3) were further validated for protein expression by tissue microarray (TMA) based immunohistochemistry. These validated targets have potential for the development of diagnostic imaging and therapeutic agents for pancreatic cancer.

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

    NASA Astrophysics Data System (ADS)

    Wu, Xiongwu; Chen, Yidong; Brooks, Bernard R.; Su, Yan A.

    2004-12-01

    An unsupervised data clustering method, called the local maximum clustering (LMC) method, is proposed for identifying clusters in experiment data sets based on research interest. A magnitude property is defined according to research purposes, and data sets are clustered around each local maximum of the magnitude property. By properly defining a magnitude property, this method can overcome many difficulties in microarray data clustering such as reduced projection in similarities, noises, and arbitrary gene distribution. To critically evaluate the performance of this clustering method in comparison with other methods, we designed three model data sets with known cluster distributions and applied the LMC method as well as the hierarchic clustering method, the[InlineEquation not available: see fulltext.]-mean clustering method, and the self-organized map method to these model data sets. The results show that the LMC method produces the most accurate clustering results. As an example of application, we applied the method to cluster the leukemia samples reported in the microarray study of Golub et al. (1999).

  18. Microarray analysis of gene regulations and potential association with acephate-resistance and fitness cost in Lygus lineolaris.

    PubMed

    Zhu, Yu Cheng; Guo, Zibiao; He, Yueping; Luttrell, Randall

    2012-01-01

    The tarnished plant bug has become increasingly resistant to organophosphates in recent years. To better understand acephate resistance mechanisms, biological, biochemical, and molecular experiments were systematically conducted with susceptible (LLS) and acephate-selected (LLR) strains. Selection of a field population with acephate significantly increased resistance ratio to 5.9-fold, coupled with a significant increase of esterase activities by 2-fold. Microarray analysis of 6,688 genes revealed 329 up- and 333 down-regulated (≥2-fold) genes in LLR. Six esterase, three P450, and one glutathione S-transferase genes were significantly up-regulated, and no such genes were down-regulated in LLR. All vitellogenin and eggshell protein genes were significantly down-regulated in LLR. Thirteen protease genes were significantly down-regulated and only 3 were up-regulated in LLR. More than twice the number of catalysis genes and more than 3.6-fold of metabolic genes were up-regulated, respectively, as compared to those down-regulated with the same molecular and biological functions. The large portion of metabolic or catalysis genes with significant up-regulations indicated a substantial increase of metabolic detoxification in LLR. Significant increase of acephate resistance, increases of esterase activities and gene expressions, and variable esterase sequences between LLS and LLR consistently demonstrated a major esterase-mediated resistance in LLR, which was functionally provable by abolishing the resistance with esterase inhibitors. In addition, significant elevation of P450 gene expression and reduced susceptibility to imidacloprid in LLR indicated a concurrent resistance risk that may impact other classes of insecticides. This study demonstrated the first association of down-regulation of reproductive- and digestive-related genes with resistance to conventional insecticides, suggesting potential fitness costs associated with resistance development. This study shed new

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

    PubMed Central

    2011-01-01

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

  20. Microarrays, Integrated Analytical Systems

    NASA Astrophysics Data System (ADS)

    Combinatorial chemistry is used to find materials that form sensor microarrays. This book discusses the fundamentals, and then proceeds to the many applications of microarrays, from measuring gene expression (DNA microarrays) to protein-protein interactions, peptide chemistry, carbodhydrate chemistry, electrochemical detection, and microfluidics.

  1. A system-based approach to interpret dose- and time-dependent microarray data: quantitative integration of gene ontology analysis for risk assessment.

    PubMed

    Yu, Xiaozhong; Griffith, William C; Hanspers, Kristina; Dillman, James F; Ong, Hansel; Vredevoogd, Melinda A; Faustman, Elaine M

    2006-08-01

    Although microarray technology has emerged as a powerful tool to explore expression levels of thousands of genes or even complete genomes after exposure to toxicants, the functional interpretation of microarray data sets still represents a time-consuming and challenging task. Gene ontology (GO) and pathway mapping have both been shown to be powerful approaches to generate a global view of biological processes and cellular components impacted by toxicants. However, current methods only allow for comparisons across two experimental settings at one particular time point. In addition, the resulting annotations are presented in extensive gene lists with minimal or limited quantitative information, data that are crucial in the application of toxicogenomic data for risk assessment. To facilitate quantitative interpretation of dose- or time-dependent genomic data, we propose to use combined average raw gene expression values (e.g., intensity or ratio) of genes associated with specific functional categories derived from the GO database. We developed an extended program (GO-Quant) to extract quantitative gene expression values and to calculate the average intensity or ratio for those significantly altered by functional gene category based on MAPPFinder results. To demonstrate its application, we applied this approach to a previously published dose- and time-dependent toxicogenomic data set (J. F. Dillman et al., 2005, Chem. Res. Toxicol. 18, 28-34). Our results indicate that the above systems approach can describe quantitatively the degree to which functional gene systems change across dose or time. Additionally, this approach provides a robust measurement to illustrate results compared to single-gene assessments and enables the user to calculate the corresponding ED(50) for each specific functional GO term, important for risk assessment.

  2. Microarray Analysis of Gene Expression at the Tumor Front of Colon Cancer.

    PubMed

    Kobayashi, Takaaki; Masaki, Tadahiko; Nozaki, Eriko; Sugiyama, Masanori; Nagashima, Fumio; Furuse, Junji; Onishi, Hiroaki; Watanabe, Takashi; Ohkura, Yasuo

    2015-12-01

    Budding or the presence poorly differentiated clusters at the boundary of cancer tissue is a pathologically important finding and serves as a prognostic factor in colorectal cancer. However, few studies have examined the cancer tissue boundary in clinical samples. The purpose of the present study was to examine gene expression at the tumor front of colon cancer in surgically resected samples. Cancer tissues were obtained by laser microdissection of 20 surgically resected specimens. Genes with significantly different microarray signals between the tumor front and the tumor center were identified. Among genes showing significant up-regulation at the tumor front were six chemokines [chemokine c-c motif ligand (CCL)2 and -18, chemokine (C-X-C motif) ligand (CXCL)9-11, and interleukin 8 (IL8)], and two apoptosis-related molecules [ubiquitin D (UBD) and baculoviral iap repeat-containing 3 (BIRC3)]. Expression of laminin gamma 2 (LAMC2), matrix metallopeptidase 7 (MMP7) and epithelial-mesenchymal transition (EMT)-related molecules were elevated in the tumor front, but their fold changes were smaller than those of the aforementioned genes. These results suggest that chemokines, in addition to EMT-related molecules, may play important roles in invasion of colon cancer. PMID:26637872

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

    PubMed Central

    2013-01-01

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

  4. Analytical approach for selecting normalizing genes from a cDNA microarray platform to be used in q-RT-PCR assays: a cnidarian case study.

    PubMed

    Rodriguez-Lanetty, Mauricio; Phillips, Wendy S; Dove, Sophie; Hoegh-Guldberg, Ove; Weis, Virginia M

    2008-04-24

    Research in gene function using Quantitative Reverse Transcription PCR (q-RT-PCR) and microarray approaches are emerging and just about to explode in the field of coral and cnidarian biology. These approaches are showing the great potential to significantly advance our understanding of how corals respond to abiotic and biotic stresses, and how host cnidarians/dinoflagellates symbioses are maintained and regulated. With these genomic advances, however, new analytical challenges are also emerging, such as the normalization of gene expression data derived from q-RT-PCR. In this study, an effective analytical method is introduced to identify candidate housekeeping genes (HKG) from a sea anemone (Anthopleura elegantissima) cDNA microarray platform that can be used as internal control genes to normalize q-RT-PCR gene expression data. It is shown that the identified HKGs were stable among the experimental conditions tested in this study. The three most stables genes identified, in term of gene expression, were beta-actin, ribosomal protein L12, and a Poly(a) binding protein. The applications of these HKGs in other cnidarian systems are further discussed. PMID:17913235

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

    PubMed

    Gao, Jian-Jie; Peng, Ri-He; Zhu, Bo; Wang, Bo; Wang, Li-Juan; Xu, Jing; Sun, Miao; Yao, Quan-Hong

    2015-10-01

    Acrylamide (ACR) is a widely used industrial chemical. However, it is a dangerous compound because it showed neurotoxic effects in humans and act as reproductive toxicant and carcinogen in many animal species. In the environment, acrylamide has high soil mobility and may travel via groundwater. Phytoremediation is an effective method to remove the environmental pollutants, but the mechanism of plant response to acrylamide remains unknown. With the purpose of assessing remediation potentials of plants for acrylamide, we have examined acrylamide uptake by the model plant Arabidopsis grown on contaminated substrates with high performance liquid chromatography (HPLC) analysis. The result revealed that acrylamide could be absorbed and degraded by Arabidopsis. Further microarray analysis showed that 527 transcripts were up-regulated within 2-days under acrylamide exposure condition. We have found many potential acrylamide-induced genes playing a major role in plant metabolism and phytoremediation.

  6. Detecting Staphylococcus aureus Virulence and Resistance Genes: a Comparison of Whole-Genome Sequencing and DNA Microarray Technology.

    PubMed

    Strauß, Lena; Ruffing, Ulla; Abdulla, Salim; Alabi, Abraham; Akulenko, Ruslan; Garrine, Marcelino; Germann, Anja; Grobusch, Martin Peter; Helms, Volkhard; Herrmann, Mathias; Kazimoto, Theckla; Kern, Winfried; Mandomando, Inácio; Peters, Georg; Schaumburg, Frieder; von Müller, Lutz; Mellmann, Alexander

    2016-04-01

    Staphylococcus aureusis a major bacterial pathogen causing a variety of diseases ranging from wound infections to severe bacteremia or intoxications. Besides host factors, the course and severity of disease is also widely dependent on the genotype of the bacterium. Whole-genome sequencing (WGS), followed by bioinformatic sequence analysis, is currently the most extensive genotyping method available. To identify clinically relevant staphylococcal virulence and resistance genes in WGS data, we developed anin silicotyping scheme for the software SeqSphere(+)(Ridom GmbH, Münster, Germany). The implemented target genes (n= 182) correspond to those queried by the IdentibacS. aureusGenotyping DNA microarray (Alere Technologies, Jena, Germany). Thein silicoscheme was evaluated by comparing the typing results of microarray and of WGS for 154 humanS. aureusisolates. A total of 96.8% (n= 27,119) of all typing results were equally identified with microarray and WGS (40.6% present and 56.2% absent). Discrepancies (3.2% in total) were caused by WGS errors (1.7%), microarray hybridization failures (1.3%), wrong prediction of ambiguous microarray results (0.1%), or unknown causes (0.1%). Superior to the microarray, WGS enabled the distinction of allelic variants, which may be essential for the prediction of bacterial virulence and resistance phenotypes. Multilocus sequence typing clonal complexes and staphylococcal cassette chromosomemecelement types inferred from microarray hybridization patterns were equally determined by WGS. In conclusion, WGS may substitute array-based methods due to its universal methodology, open and expandable nature, and rapid parallel analysis capacity for different characteristics in once-generated sequences.

  7. Detecting Staphylococcus aureus Virulence and Resistance Genes: a Comparison of Whole-Genome Sequencing and DNA Microarray Technology

    PubMed Central

    Strauß, Lena; Ruffing, Ulla; Abdulla, Salim; Alabi, Abraham; Akulenko, Ruslan; Garrine, Marcelino; Germann, Anja; Grobusch, Martin Peter; Helms, Volkhard; Herrmann, Mathias; Kazimoto, Theckla; Kern, Winfried; Mandomando, Inácio; Peters, Georg; Schaumburg, Frieder; von Müller, Lutz

    2016-01-01

    Staphylococcus aureus is a major bacterial pathogen causing a variety of diseases ranging from wound infections to severe bacteremia or intoxications. Besides host factors, the course and severity of disease is also widely dependent on the genotype of the bacterium. Whole-genome sequencing (WGS), followed by bioinformatic sequence analysis, is currently the most extensive genotyping method available. To identify clinically relevant staphylococcal virulence and resistance genes in WGS data, we developed an in silico typing scheme for the software SeqSphere+ (Ridom GmbH, Münster, Germany). The implemented target genes (n = 182) correspond to those queried by the Identibac S. aureus Genotyping DNA microarray (Alere Technologies, Jena, Germany). The in silico scheme was evaluated by comparing the typing results of microarray and of WGS for 154 human S. aureus isolates. A total of 96.8% (n = 27,119) of all typing results were equally identified with microarray and WGS (40.6% present and 56.2% absent). Discrepancies (3.2% in total) were caused by WGS errors (1.7%), microarray hybridization failures (1.3%), wrong prediction of ambiguous microarray results (0.1%), or unknown causes (0.1%). Superior to the microarray, WGS enabled the distinction of allelic variants, which may be essential for the prediction of bacterial virulence and resistance phenotypes. Multilocus sequence typing clonal complexes and staphylococcal cassette chromosome mec element types inferred from microarray hybridization patterns were equally determined by WGS. In conclusion, WGS may substitute array-based methods due to its universal methodology, open and expandable nature, and rapid parallel analysis capacity for different characteristics in once-generated sequences. PMID:26818676

  8. The prostate cancer immunome: In silico functional analysis of antigenic proteins from microarray profiling with IgG.

    PubMed

    Luna-Coronell, Johana A; Vierlinger, Klemens; Gamperl, Magdalena; Hofbauer, Johann; Berger, Ingrid; Weinhäusel, Andreas

    2016-04-01

    The study of the immunome of prostate cancer (PCa) and characterization of autoantibody signature from differentially reactive antigens can uncover disease stage proteins, reveal enriched networks and even expose aberrant cellular mechanisms during the disease process. By conducting plasma IgG profiling on protein microarrays presenting 5449 unique human proteins expressed in 15 417 E. coli human cDNA expression clones, we elucidated 471 (21 higher reactive in PCa) differentially reactive antigens in 50 PCa versus 49 patients with benign prostate hyperplasia (BPH) at initial diagnosis. Functional analyzes show that the immune-profile of PCa compared to BPH control samples is significantly enriched in features targeting Cellular assembly, Cell death and pathways involved in Cell cycle, translation, and assembly of proteins as EIF2 signaling, PCa related genes as AXIN1 and TP53, and ribosomal proteins (e.g. RPS10). An overlap of 61 (out of 471) DIRAGs with the published 1545 antigens from the SEREX database has been found, however those were higher reactive in BPH. Clinical relevance is shown when antibody-reactivities against eight proteins were significantly (p < 0.001) correlated with Gleason-score. Herewith we provide a biological and pathophysiological characterization of the immunological layer of cancerous (PCa) versus benign (BPH) disease, derived from antibody profiling on protein microarrays. PMID:27089054

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

    PubMed

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

    2016-08-01

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

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

    PubMed

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

    2016-08-01

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

  11. Development of a Genotyping Microarray for Studying the Role of Gene-Environment Interactions in Risk for Lung Cancer

    PubMed Central

    Baldwin, Don A.; Sarnowski, Christopher P.; Reddy, Sabrina A.; Blair, Ian A.; Clapper, Margie; Lazarus, Philip; Li, Mingyao; Muscat, Joshua E.; Penning, Trevor M.; Vachani, Anil; Whitehead, Alexander S.

    2013-01-01

    A microarray (LungCaGxE), based on Illumina BeadChip technology, was developed for high-resolution genotyping of genes that are candidates for involvement in environmentally driven aspects of lung cancer oncogenesis and/or tumor growth. The iterative array design process illustrates techniques for managing large panels of candidate genes and optimizing marker selection, aided by a new bioinformatics pipeline component, Tagger Batch Assistant. The LungCaGxE platform targets 298 genes and the proximal genetic regions in which they are located, using ∼13,000 DNA single nucleotide polymorphisms (SNPs), which include haplotype linkage markers with a minimum allele frequency of 1% and additional specifically targeted SNPs, for which published reports have indicated functional consequences or associations with lung cancer or other smoking-related diseases. The overall assay conversion rate was 98.9%; 99.0% of markers with a minimum Illumina design score of 0.6 successfully generated allele calls using genomic DNA from a study population of 1873 lung-cancer patients and controls. PMID:24294113

  12. Discovering Hidden Connections among Diseases, Genes and Drugs Based on Microarray Expression Profiles with Negative-Term Filtering

    PubMed Central

    2014-01-01

    Microarrays based on gene expression profiles (GEPs) can be tailored specifically for a variety of topics to provide a precise and efficient means with which to discover hidden information. This study proposes a novel means of employing existing GEPs to reveal hidden relationships among diseases, genes, and drugs within a rich biomedical database, PubMed. Unlike the co-occurrence method, which considers only the appearance of keywords, the proposed method also takes into account negative relationships and non-relationships among keywords, the importance of which has been demonstrated in previous studies. Three scenarios were conducted to verify the efficacy of the proposed method. In Scenario 1, disease and drug GEPs (disease: lymphoma cancer, lymph node cancer, and drug: cyclophosphamide) were used to obtain lists of disease- and drug-related genes. Fifteen hidden connections were identified between the diseases and the drug. In Scenario 2, we adopted different diseases and drug GEPs (disease: AML-ALL dataset and drug: Gefitinib) to obtain lists of important diseases and drug-related genes. In this case, ten hidden connections were identified. In Scenario 3, we obtained a list of disease-related genes from the disease-related GEP (liver cancer) and the drug (Capecitabine) on the PharmGKB website, resulting in twenty-two hidden connections. Experimental results demonstrate the efficacy of the proposed method in uncovering hidden connections among diseases, genes, and drugs. Following implementation of the weight function in the proposed method, a large number of the documents obtained in each of the scenarios were judged to be related: 834 of 4028 documents, 789 of 1216 documents, and 1928 of 3791 documents in Scenarios 1, 2, and 3, respectively. The negative-term filtering scheme also uncovered a large number of negative relationships as well as non-relationships among these connections: 97 of 834, 38 of 789, and 202 of 1928 in Scenarios 1, 2, and 3, respectively

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

    PubMed

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

    2005-01-01

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

  14. Tissue Microarrays.

    PubMed

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

    2016-01-01

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

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

    PubMed Central

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

    2015-01-01

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

  16. Identification of Arabidopsis Candidate Genes in Response to Biotic and Abiotic Stresses Using Comparative Microarrays

    PubMed Central

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

    2015-01-01

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

  17. Cross-species hybridisation of human and bovine orthologous genes on high density cDNA microarrays

    PubMed Central

    Adjaye, James; Herwig, Ralf; Herrmann, Doris; Wruck, Wasco; BenKahla, Alia; Brink, Thore C; Nowak, Monika; Carnwath, Joseph W; Hultschig, Claus; Niemann, Heiner; Lehrach, Hans

    2004-01-01

    Background Cross-species gene-expression comparison is a powerful tool for the discovery of evolutionarily conserved mechanisms and pathways of expression control. The usefulness of cDNA microarrays in this context is that broad areas of homology are compared and hybridization probes are sufficiently large that small inter-species differences in nucleotide sequence would not affect the analytical results. This comparative genomics approach would allow a common set of genes within a specific developmental, metabolic, or disease-related gene pathway to be evaluated in experimental models of human diseases. The objective of this study was to investigate the feasibility and reproducibility of cross-species analysis employing a human cDNA microarray as probe. Results As a proof of principle, total RNA derived from human and bovine fetal brains was used as a source of labelled targets for hybridisation onto a human cDNA microarray composed of 349 characterised genes. Each gene was spotted 20 times representing 6,980 data points thus enabling highly reproducible spot quantification. Employing high stringency hybridisation and washing conditions, followed by data analysis, revealed slight differences in the expression levels and reproducibility of the signals between the two species. We also assigned each of the genes into three expression level categories- i.e. high, medium and low. The correlation co-efficient of cross hybridisation between the orthologous genes was 0.94. Verification of the array data by semi-quantitative RT-PCR using common primer sequences enabled co-amplification of both human and bovine transcripts. Finally, we were able to assign gene names to previously uncharacterised bovine ESTs. Conclusions Results of our study demonstrate the harnessing and utilisation power of comparative genomics and prove the feasibility of using human microarrays to facilitate the identification of co-expressed orthologous genes in common tissues derived from different

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

    PubMed Central

    Turkheimer, Federico E; Roncaroli, Federico; Hennuy, Benoit; Herens, Christian; Nguyen, Minh; Martin, Didier; Evrard, Annick; Bours, Vincent; Boniver, Jacques; Deprez, Manuel

    2006-01-01

    Background Expression microarrays represent a powerful technique for the simultaneous investigation of thousands of genes. The evidence that genes are not randomly distributed in the genome and that their coordinated expression depends on their position on chromosomes has highlighted the need for mathematical approaches to exploit this dependency for the analysis of expression data-sets. Results We have devised a novel mathematical technique (CHROMOWAVE) based on the Haar wavelet transform and applied it to a dataset obtained with the Affymetrix® HG-U133_Plus_2 array in 27 gliomas. CHROMOWAVE generated multi-chromosomal pattern featuring low expression in chromosomes 1p, 4, 9q, 13, 18, and 19q. This pattern was not only statistically robust but also clinically relevant as it was predictive of favourable outcome. This finding was replicated on a data-set independently acquired by another laboratory. FISH analysis indicated that monosomy 1p and 19q was a frequent feature of tumours displaying the CHROMOWAVE pattern but that allelic loss on chromosomes 4, 9q, 13 and 18 was much less common. Conclusion The ability to detect expression changes of spatially related genes and to map their position on chromosomes makes CHROMOWAVE a valuable screening method for the identification and display of regional gene expression changes of clinical relevance. In this study, FISH data showed that monosomy was frequently associated with diffuse low gene expression on chromosome 1p and 19q but not on chromosomes 4, 9q, 13 and 18. Comparative genomic hybridisation, allelic polymorphism analysis and methylation studies are in progress in order to identify the various mechanisms involved in this multi-chromosomal expression pattern. PMID:17140431

  19. Combinatory Microarray and SuperSAGE Analyses Identify Pairing-Dependently Transcribed Genes in Schistosoma mansoni Males, Including Follistatin

    PubMed Central

    Leutner, Silke; Oliveira, Katia C.; Rotter, Björn; Beckmann, Svenja; Buro, Christin; Hahnel, Steffen; Kitajima, Joao P.; Verjovski-Almeida, Sergio; Winter, Peter; Grevelding, Christoph G.

    2013-01-01

    Background Schistosomiasis is a disease of world-wide importance and is caused by parasitic flatworms of the genus Schistosoma. These parasites exhibit a unique reproduction biology as the female's sexual maturation depends on a constant pairing-contact to the male. Pairing leads to gonad differentiation in the female, and even gene expression of some gonad-associated genes is controlled by pairing. In contrast, no morphological changes have been observed in males, although first data indicated an effect of pairing also on gene transcription in males. Methodology/Principal Findings To investigate the influence of pairing on males, we performed a combinatory approach applying SuperSAGE and microarray hybridization, generating the most comprehensive data-set on differential transcription available to date. Of 6,326 sense transcripts detected by both analyses, 29 were significantly differentially transcribed. Besides mutual confirmation, the two methods complemented each other as shown by data comparison and real-time PCR, which revealed a number of genes with consistent regulation across all methods. One of the candidate genes, follistatin of S. mansoni (SmFst) was characterized in more detail by in situ hybridization and yeast two-hybrid (Y2H) interaction analyses with potential binding partners. Conclusions/Significance Beyond confirming previously hypothesized differences in metabolic processes between pairing-experienced (EM) and pairing-unexperienced males (UM), our data indicate that neuronal processes are involved in male-female interaction but also TGFβ-signaling. One candidate revealing significant down-regulation in EM was the TGFβ-pathway controlling molecule follistatin (SmFst). First functional analyses demonstrated SmFst interaction with the S. mansoni TGFβ-receptor agonists inhibin/activin (SmInAct) and bone morphogenic protein (SmBMP), and all molecules colocalized in the testes. This indicates a yet unknown role of the TGFβ-pathway for

  20. Development of a DNA Microarray for Enterococcal Species, Virulence, and Antibiotic Resistance Gene Determinations among Isolates from Poultry▿

    PubMed Central

    Champagne, J.; Diarra, M. S.; Rempel, H.; Topp, E.; Greer, C. W.; Harel, J.; Masson, L.

    2011-01-01

    A DNA microarray (Enteroarray) was designed with probes targeting four species-specific taxonomic identifiers to discriminate among 18 different enterococcal species, while other probes were designed to identify 18 virulence factors and 174 antibiotic resistance genes. In total, 262 genes were utilized for rapid species identification of enterococcal isolates, while characterizing their virulence potential through the simultaneous identification of endogenous antibiotic resistance and virulence genes. Enterococcal isolates from broiler chicken farms were initially identified by using the API 20 Strep system, and the results were compared to those obtained with the taxonomic genes atpA, recA, pheS, and ddl represented on our microarray. Among the 171 isolates studied, five different enterococcal species were identified by using the API 20 Strep system: Enterococcus faecium, E. faecalis, E. durans, E. gallinarum, and E. avium. The Enteroarray detected the same species as API 20 Strep, as well as two more: E. casseliflavus and E. hirae. Species comparisons resulted in 15% (27 isolates) disagreement between the two methods among the five API 20 Strep identifiable species and 24% (42 isolates) disagreement when considering the seven Enteroarray identified species. The species specificity of key antibiotic and virulence genes identified by the Enteroarray were consistent with the literature adding further robustness to the redundant taxonomic probe data. Sequencing of the cpn60 gene further confirmed the complete accuracy of the microarray results. The new Enteroarray should prove to be a useful tool to accurately genotype strains of enterococci and assess their virulence potential. PMID:21335389

  1. Protein Microarrays

    NASA Astrophysics Data System (ADS)

    Ricard-Blum, S.

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

  2. Translating golden retriever muscular dystrophy microarray findings to novel biomarkers for cardiac/skeletal muscle function in Duchenne Muscular Dystrophy

    PubMed Central

    Galindo, Cristi L.; Soslow, Jonathan H.; Brinkmeyer-Langford, Candice L.; Gupte, Manisha; Smith, Holly M.; Sengsayadeth, Seng; Sawyer, Douglas B.; Benson, D. Woodrow; Kornegay, Joe N.; Markham, Larry W.

    2016-01-01

    Background In Duchenne muscular dystrophy (DMD), abnormal cardiac function is typically preceded by a decade of skeletal muscle disease. Molecular reasons for differences in onset and progression of these muscle groups are unknown. Human biomarkers are lacking. Methods We analyzed cardiac and skeletal muscle microarrays from normal and golden retriever muscular dystrophy (GRMD) dogs (ages 6, 12, or 47+ months) to gain insight into muscle dysfunction and to identify putative DMD biomarkers. These biomarkers were then measured using human DMD blood samples. Results We identified GRMD candidate genes that might contribute to the disparity between cardiac and skeletal muscle disease, focusing on brain-derived neurotropic factor (BDNF) and osteopontin (OPN/SPP1). BDNF was elevated in cardiac muscle of younger GRMD but was unaltered in skeletal muscle, while SPP1 was increased only in GRMD skeletal muscle. In human DMD, circulating levels of BDNF were inversely correlated with ventricular function and fibrosis, while SPP1 levels correlated with skeletal muscle function. Conclusion These results highlight gene expression patterns that could account for differences in cardiac and skeletal disease in GRMD. Most notably, animal model-derived data were translated to DMD and support use of BDNF and SPP1 as biomarkers for cardiac and skeletal muscle involvement, respectively. PMID:26672735

  3. Trait Specific Expression Profiling of Salt Stress Responsive Genes in Diverse Rice Genotypes as Determined by Modified Significance Analysis of Microarrays

    PubMed Central

    Hossain, Mohammad R.; Bassel, George W.; Pritchard, Jeremy; Sharma, Garima P.; Ford-Lloyd, Brian V.

    2016-01-01

    Stress responsive gene expression is commonly profiled in a comparative manner involving different stress conditions or genotypes with contrasting reputation of tolerance/resistance. In contrast, this research exploited a wide natural variation in terms of taxonomy, origin and salt sensitivity in eight genotypes of rice to identify the trait specific patterns of gene expression under salt stress. Genome wide transcptomic responses were interrogated by the weighted continuous morpho-physiological trait responses using modified Significance Analysis of Microarrays. More number of genes was found to be differentially expressed under salt stressed compared to that of under unstressed conditions. Higher numbers of genes were observed to be differentially expressed for the traits shoot Na+/K+, shoot Na+, root K+, biomass and shoot Cl−, respectively. The results identified around 60 genes to be involved in Na+, K+, and anion homeostasis, transport, and transmembrane activity under stressed conditions. Gene Ontology (GO) enrichment analysis identified 1.36% (578 genes) of the entire transcriptome to be involved in the major molecular functions such as signal transduction (>150 genes), transcription factor (81 genes), and translation factor activity (62 genes) etc., under salt stress. Chromosomal mapping of the genes suggests that majority of the genes are located on chromosomes 1, 2, 3, 6, and 7. The gene network analysis showed that the transcription factors and translation initiation factors formed the major gene networks and are mostly active in nucleus, cytoplasm and mitochondria whereas the membrane and vesicle bound proteins formed a secondary network active in plasma membrane and vacuoles. The novel genes and the genes with unknown functions thus identified provide picture of a synergistic salinity response representing the potentially fundamental mechanisms that are active in the wide natural genetic background of rice and will be of greater use once their roles

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

    PubMed Central

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

    2016-01-01

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

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

    PubMed

    Moorhouse, Michael J; Sharma, Hari S

    2011-08-01

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

  6. Gene expression profile analysis of Manila clam (Ruditapes philippinarum) hemocytes after a Vibrio alginolyticus challenge using an immune-enriched oligo-microarray

    PubMed Central

    2014-01-01

    Background The Manila clam (Ruditapes philippinarum) is a cultured bivalve with worldwide commercial importance, and diseases cause high economic losses. For this reason, interest in the immune genes in this species has recently increased. The present work describes the construction of the first R. philippinarum microarray containing immune-related hemocyte sequences and its application to study the gene transcription profiles of hemocytes from clams infected with V. alginolyticus through a time course. Results The complete set of sequences from R. philippinarum available in the public databases and the hemocyte sequences enriched in immune transcripts were assembled successfully. A total of 12,156 annotated sequences were used to construct the 8 ×15 k oligo-microarray. The microarray experiments yielded a total of 579 differentially expressed transcripts. Using the gene expression results, the associated Gene Ontology terms and the enrichment analysis, we found different response mechanisms throughout the experiment. Genes related to signaling, transcription and apoptosis, such as IL-17D, NF-κB or calmodulin, were typically expressed as early as 3 hours post-challenge (hpc), while characteristic immune genes, such as PGRPs, FREPs and defense proteins appeared later at 8 hpc. This immune-triggering response could have affected a high number of processes that seemed to be activated 24 hpc to overcome the Vibrio challenge, including the expression of many cytoskeleton molecules, which is indicative of the active movement of hemocytes. In fact functional studies showed an increment in apoptosis, necrosis or cell migration after the infection. Finally, 72 hpc, activity returned to normal levels, and more than 50% of the genes were downregulated in a negative feedback of all of the previously active processes. Conclusions Using a new version of the R. philippinarum oligo-microarray, a putative timing for the response against a Vibrio infection was established. The key

  7. [Protein microarrays and personalized medicine].

    PubMed

    Yu, Xiabo; Schneiderhan-Marra, Nicole; Joos, Thomas O

    2011-01-01

    Over the last 10 years, DNA microarrays have achieved a robust analytical performance, enabling their use for analyzing the whole transcriptome or for screening thousands of single-nucleotide polymorphisms in a single experiment. DNA microarrays allow scientists to correlate gene expression signatures with disease progression, to screen for disease-specific mutations, and to treat patients according to their individual genetic profiles; however, the real key is proteins and their manifold functions. It is necessary to achieve a greater understanding of not only protein function and abundance but also their role in the development of diseases. Protein concentrations have been shown to reflect the physiological and pathologic state of an organ, tissue, or cells far more directly than DNA, and proteins can be profiled effectively with protein microarrays, which require only a small amount of sample material. Protein microarrays have become wellestablished tools in basic and applied research, and the first products have already entered the in vitro diagnostics market. This review focuses on protein microarray applications for biomarker discovery and validation, disease diagnosis, and use within the area of personalized medicine. Protein microarrays have proved to be reliable research tools in screening for a multitude of parameters with only a minimal quantity of sample and have enormous potential in applications for diagnostic and personalized medicine.

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

    SciTech Connect

    Kimura, Shinzo; Ishidou, Emi; Kurita, Sakiko; Suzuki, Yoshiteru; Shibato, Junko; Rakwal, Randeep . E-mail: rakwal-68@aist.go.jp; Iwahashi, Hitoshi

    2006-07-21

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

  9. Analyzing illumina gene expression microarray data from different tissues: methodological aspects of data analysis in the metaxpress consortium.

    PubMed

    Schurmann, Claudia; Heim, Katharina; Schillert, Arne; Blankenberg, Stefan; Carstensen, Maren; Dörr, Marcus; Endlich, Karlhans; Felix, Stephan B; Gieger, Christian; Grallert, Harald; Herder, Christian; Hoffmann, Wolfgang; Homuth, Georg; Illig, Thomas; Kruppa, Jochen; Meitinger, Thomas; Müller, Christian; Nauck, Matthias; Peters, Annette; Rettig, Rainer; Roden, Michael; Strauch, Konstantin; Völker, Uwe; Völzke, Henry; Wahl, Simone; Wallaschofski, Henri; Wild, Philipp S; Zeller, Tanja; Teumer, Alexander; Prokisch, Holger; Ziegler, Andreas

    2012-01-01

    Microarray profiling of gene expression is widely applied in molecular biology and functional genomics. Experimental and technical variations make meta-analysis of different studies challenging. In a total of 3358 samples, all from German population-based cohorts, we investigated the effect of data preprocessing and the variability due to sample processing in whole blood cell and blood monocyte gene expression data, measured on the Illumina HumanHT-12 v3 BeadChip array.Gene expression signal intensities were similar after applying the log(2) or the variance-stabilizing transformation. In all cohorts, the first principal component (PC) explained more than 95% of the total variation. Technical factors substantially influenced signal intensity values, especially the Illumina chip assignment (33-48% of the variance), the RNA amplification batch (12-24%), the RNA isolation batch (16%), and the sample storage time, in particular the time between blood donation and RNA isolation for the whole blood cell samples (2-3%), and the time between RNA isolation and amplification for the monocyte samples (2%). White blood cell composition parameters were the strongest biological factors influencing the expression signal intensities in the whole blood cell samples (3%), followed by sex (1-2%) in both sample types. Known single nucleotide polymorphisms (SNPs) were located in 38% of the analyzed probe sequences and 4% of them included common SNPs (minor allele frequency >5%). Out of the tested SNPs, 1.4% significantly modified the probe-specific expression signals (Bonferroni corrected p-value<0.05), but in almost half of these events the signal intensities were even increased despite the occurrence of the mismatch. Thus, the vast majority of SNPs within probes had no significant effect on hybridization efficiency.In summary, adjustment for a few selected technical factors greatly improved reliability of gene expression analyses. Such adjustments are particularly required for meta

  10. t-Test at the Probe Level: An Alternative Method to Identify Statistically Significant Genes for Microarray Data

    PubMed Central

    Boareto, Marcelo; Caticha, Nestor

    2014-01-01

    Microarray data analysis typically consists in identifying a list of differentially expressed genes (DEG), i.e., the genes that are differentially expressed between two experimental conditions. Variance shrinkage methods have been considered a better choice than the standard t-test for selecting the DEG because they correct the dependence of the error with the expression level. This dependence is mainly caused by errors in background correction, which more severely affects genes with low expression values. Here, we propose a new method for identifying the DEG that overcomes this issue and does not require background correction or variance shrinkage. Unlike current methods, our methodology is easy to understand and implement. It consists of applying the standard t-test directly on the normalized intensity data, which is possible because the probe intensity is proportional to the gene expression level and because the t-test is scale- and location-invariant. This methodology considerably improves the sensitivity and robustness of the list of DEG when compared with the t-test applied to preprocessed data and to the most widely used shrinkage methods, Significance Analysis of Microarrays (SAM) and Linear Models for Microarray Data (LIMMA). Our approach is useful especially when the genes of interest have small differences in expression and therefore get ignored by standard variance shrinkage methods.

  11. The functional potential of high Arctic permafrost revealed by metagenomic sequencing, qPCR and microarray analyses.

    PubMed

    Yergeau, Etienne; Hogues, Hervé; Whyte, Lyle G; Greer, Charles W

    2010-09-01

    The fate of the carbon stocked in permafrost following global warming and permafrost thaw is of major concern in view of the potential for increased CH(4) and CO(2) emissions from these soils. Complex carbon compound degradation and greenhouse gas emissions are due to soil microbial communities, but no comprehensive study has yet addressed their composition and functional potential in permafrost. Here, a 2-m deep permafrost sample and its overlying active layer soil were subjected to metagenomic sequencing, quantitative PCR (qPCR) and microarray analyses. The active layer soil and the 2-m permafrost microbial community structures were very similar, with Actinobacteria being the dominant phylum. The two samples also possessed a highly similar spectrum of functional genes, especially when compared with other already published metagenomes. Key genes related to methane generation, methane oxidation and organic matter degradation were highly diverse for both samples in the metagenomic libraries and some (for example, pmoA) showed relatively high abundance in qPCR assays. Genes related to nitrogen fixation and ammonia oxidation, which could have important roles following climatic change in these nitrogen-limited environments, showed low diversity but high abundance. The 2-m permafrost showed lower abundance and diversity for all the assessed genes and taxa. Experimental biases were also evaluated using qPCR and showed that the whole-community genome amplification technique used caused representational biases in the metagenomic libraries by increasing the abundance of Bacteroidetes and decreasing the abundance of Actinobacteria. This study describes for the first time the detailed functional potential of permafrost-affected soils.

  12. Simple and Flexible Classification of Gene Expression Microarrays Via Swirls and Ripples | Division of Cancer Prevention

    Cancer.gov

    By Stuart G. Baker The program requires Mathematica 7.01.0 The key function is Classify [datalist,options] where datalist={data, genename, dataname} data ={matrix for class 0, matrix for class 1}, matrix is gene expression by specimen genename a list of names of genes, dataname ={name of data set, name of class0, name of class1} |

  13. An undergraduate laboratory exercise to study the effect of darkness on plant gene expression using DNA microarray.

    PubMed

    Chang, Ming-Mei; Briggs, George M

    2007-11-01

    DNA microarrays are microscopic arrays on a solid surface, typically a glass slide, on which DNA oligonucleotides are deposited or synthesized in a high-density matrix with a predetermined spatial order. Several types of DNA microarrays have been developed and used for various biological studies. Here, we developed an undergraduate laboratory exercise using an Arabidopsis DNA microarray to study the gene expression of Brassica rapa, Wisconsin Fast Plant. Genes involved in senescence, cell wall loosening/degradation, and sugar transport were the most upregulated, while those involved in photosynthesis, the elimination of reactive oxygen intermediates associated with photooxidative stress and auxin synthesis, were the most downregulated. Students were able to complete the experiment successfully. Throughout the exercise, they learned various important molecular techniques including RNA isolation, quantification, reverse transcription, cRNA synthesis, labeling and purification, and microarray hybridization, washing, scanning, and feature extraction. The exercise can be integrated into a college-level molecular biology laboratory. The procedure used can be adapted to examine other effects on other organisms.

  14. An undergraduate laboratory exercise to study the effect of darkness on plant gene expression using DNA microarray.

    PubMed

    Chang, Ming-Mei; Briggs, George M

    2007-11-01

    DNA microarrays are microscopic arrays on a solid surface, typically a glass slide, on which DNA oligonucleotides are deposited or synthesized in a high-density matrix with a predetermined spatial order. Several types of DNA microarrays have been developed and used for various biological studies. Here, we developed an undergraduate laboratory exercise using an Arabidopsis DNA microarray to study the gene expression of Brassica rapa, Wisconsin Fast Plant. Genes involved in senescence, cell wall loosening/degradation, and sugar transport were the most upregulated, while those involved in photosynthesis, the elimination of reactive oxygen intermediates associated with photooxidative stress and auxin synthesis, were the most downregulated. Students were able to complete the experiment successfully. Throughout the exercise, they learned various important molecular techniques including RNA isolation, quantification, reverse transcription, cRNA synthesis, labeling and purification, and microarray hybridization, washing, scanning, and feature extraction. The exercise can be integrated into a college-level molecular biology laboratory. The procedure used can be adapted to examine other effects on other organisms. PMID:21591140

  15. Global Gene Expression Patterns in Clostridium thermocellum as Determined by Microarray Analysis of Chemostat Cultures on Cellulose or Cellobiose▿ †

    PubMed Central

    Riederer, Allison; Takasuka, Taichi E.; Makino, Shin-ichi; Stevenson, David M.; Bukhman, Yury V.; Elsen, Nathaniel L.; Fox, Brian G.

    2011-01-01

    A microarray study of chemostat growth on insoluble cellulose or soluble cellobiose has provided substantial new information on Clostridium thermocellum gene expression. This is the first comprehensive examination of gene expression in C. thermocellum under defined growth conditions. Expression was detected from 2,846 of 3,189 genes, and regression analysis revealed 348 genes whose changes in expression patterns were growth rate and/or substrate dependent. Successfully modeled genes included those for scaffoldin and cellulosomal enzymes, intracellular metabolic enzymes, transcriptional regulators, sigma factors, signal transducers, transporters, and hypothetical proteins. Unique genes encoding glycolytic pathway and ethanol fermentation enzymes expressed at high levels simultaneously with previously established maximal ethanol production were also identified. Ranking of normalized expression intensities revealed significant changes in transcriptional levels of these genes. The pattern of expression of transcriptional regulators, sigma factors, and signal transducers indicates that response to growth rate is the dominant global mechanism used for control of gene expression in C. thermocellum. PMID:21169455

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

    PubMed Central

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

    2011-01-01

    Purpose To evaluate the accuracy of the sub-classification of renal cortical neoplasms using molecular signatures. Experimental Design A search of publicly available databases was performed to identify microarray datasets with multiple histologic sub-types of renal cortical neoplasms. Meta-analytic techniques were utilized to identify differentially expressed genes for each histologic subtype. The lists of genes obtained from the meta-analysis were used to create predictive signatures through the use of a pair-based method. These signatures were organized into an algorithm to sub-classify renal neoplasms. The use of these signatures according to our algorithm was validated on several independent datasets. Results We identified three Gene Expression Omnibus datasets that fit our criteria to develop a training set. All of the datasets in our study utilized the Affymetrix platform. The final training dataset included 149 samples represented by the four most common histologic subtypes of renal cortical neoplasms: 69 clear cell, 41 papillary, 16 chromophobe, and 23 oncocytomas. When validation of our signatures was performed on external datasets, we were able to correctly classify 68 of the 72 samples (94%). The correct classification by subtype was 19/20 (95%) for clear cell, 14/14 (100%) for papillary, 17/19 (89%) for chromophobe, 18/19 (95%) for oncocytomas. Conclusions Through the use of meta-analytic techniques, we were able to create an algorithm that sub-classified renal neoplasms on a molecular level with 94% accuracy across multiple independent datasets. This algorithm may aid in selecting molecular therapies and may improve the accuracy of subtyping of renal cortical tumors. PMID:21818257

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

    PubMed Central

    Timlin, Jerilyn A; Haaland, David M; Sinclair, Michael B; Aragon, Anthony D; Martinez, M Juanita; Werner-Washburne, Margaret

    2005-01-01

    Background Commercial microarray scanners and software cannot distinguish between spectrally overlapping emission sources, and hence cannot accurately identify or correct for emissions not originating from the labeled cDNA. We employed our hyperspectral microarray scanner coupled with multivariate data analysis algorithms that independently identify and quantitate emissions from all sources to investigate three artifacts that reduce the accuracy and reliability of microarray data: skew toward the green channel, dye separation, and variable background emissions. Results Here we demonstrate that several common microarray artifacts resulted from the presence of emission sources other than the labeled cDNA that can dramatically alter the accuracy and reliability of the array data. The microarrays utilized in this study were representative of a wide cross-section of the microarrays currently employed in genomic research. These findings reinforce the need for careful attention to detail to recognize and subsequently eliminate or quantify the presence of extraneous emissions in microarray images. Conclusion Hyperspectral scanning together with multivariate analysis offers a unique and detailed understanding of the sources of microarray emissions after hybridization. This opportunity to simultaneously identify and quantitate contaminant and background emissions in microarrays markedly improves the reliability and accuracy of the data and permits a level of quality control of microarray emissions previously unachievable. Using these tools, we can not only quantify the extent and contribution of extraneous emission sources to the signal, but also determine the consequences of failing to account for them and gain the insight necessary to adjust preparation protocols to prevent such problems from occurring. PMID:15888208

  18. Safety evaluation of the aqueous extract Kothala himbutu (Salacia reticulata) stem in the hepatic gene expression profile of normal mice using DNA microarrays.

    PubMed

    Im, Ryanghyok; Mano, Hiroshi; Nakatani, Sachie; Shimizu, Jun; Wada, Masahiro

    2008-12-01

    Kothala himbutu is a traditional Ayurvedic medicinal plant used to treat diabetes. We aimed to evaluate the safety of an aqueous extract of Kothala himbutu stem (KTE) in normal mice. The mice were divided into two groups: one was administered KTE and the other distilled water for 3 weeks. During the test period, the groups showed no significant differences in body weight gain or plasma parameters, such as fasting blood glucose level, oral glucose tolerance test, or aspartate transaminase (AST) or alanine transaminase (ALT) activity. DNA microarray analysis revealed that expression of genes of known function, such as those for the stress response, ribosomal proteins, transcription, cell function, the inflammatory/immune response, and metabolism (xenobiotic, glutathione, etc.) remained largely unaffected by KTE. However some genes such as catechol-o-methyltransferase and succinyl-CoA synthetase were regulated by KTE, indicating that KTE is not toxic to normal mice and might be effective as a functional food. PMID:19060410

  19. CSIOVDB: a microarray gene expression database of epithelial ovarian cancer subtype.

    PubMed

    Tan, Tuan Zea; Yang, He; Ye, Jieru; Low, Jeffrey; Choolani, Mahesh; Tan, David Shao Peng; Thiery, Jean-Paul; Huang, Ruby Yun-Ju

    2015-12-22

    Databases pertaining to various diseases provide valuable resources on particular genes of interest but lack the molecular subtype and epithelial-mesenchymal transition status. CSIOVDB is a transcriptomic microarray database of 3,431 human ovarian cancers, including carcinoma of the ovary, fallopian tube, and peritoneum, and metastasis to the ovary. The database also comprises stroma and ovarian surface epithelium from normal ovary tissue, as well as over 400 early-stage ovarian cancers. This unique database presents the molecular subtype and epithelial-mesenchymal transition status for each ovarian cancer sample, with major ovarian cancer histologies (clear cell, endometrioid, mucinous, low-grade serous, serous) represented. Clinico-pathological parameters available include tumor grade, surgical debulking status, clinical response and age. The database has 1,868 and 1,516 samples with information pertaining to overall and disease-free survival rates, respectively. The database also provides integration with the copy number, DNA methylation and mutation data from TCGA. CSIOVDB seeks to provide a resource for biomarker and therapeutic target exploration for ovarian cancer research. PMID:26549805

  20. CSIOVDB: a microarray gene expression database of epithelial ovarian cancer subtype.

    PubMed

    Tan, Tuan Zea; Yang, He; Ye, Jieru; Low, Jeffrey; Choolani, Mahesh; Tan, David Shao Peng; Thiery, Jean-Paul; Huang, Ruby Yun-Ju

    2015-12-22

    Databases pertaining to various diseases provide valuable resources on particular genes of interest but lack the molecular subtype and epithelial-mesenchymal transition status. CSIOVDB is a transcriptomic microarray database of 3,431 human ovarian cancers, including carcinoma of the ovary, fallopian tube, and peritoneum, and metastasis to the ovary. The database also comprises stroma and ovarian surface epithelium from normal ovary tissue, as well as over 400 early-stage ovarian cancers. This unique database presents the molecular subtype and epithelial-mesenchymal transition status for each ovarian cancer sample, with major ovarian cancer histologies (clear cell, endometrioid, mucinous, low-grade serous, serous) represented. Clinico-pathological parameters available include tumor grade, surgical debulking status, clinical response and age. The database has 1,868 and 1,516 samples with information pertaining to overall and disease-free survival rates, respectively. The database also provides integration with the copy number, DNA methylation and mutation data from TCGA. CSIOVDB seeks to provide a resource for biomarker and therapeutic target exploration for ovarian cancer research.

  1. Microarray analysis and functional tests suggest the involvement of expansins in the early stages of symbiosis of the arbuscular mycorrhizal fungus Glomus intraradices on tomato (Solanum lycopersicum).

    PubMed

    Dermatsev, Vladimir; Weingarten-Baror, Carmiya; Resnick, Nathalie; Gadkar, Vijay; Wininger, Smadar; Kolotilin, Igor; Mayzlish-Gati, Einav; Zilberstein, Avia; Koltai, Hinanit; Kapulnik, Yoram

    2010-01-01

    Arbuscular mycorrhizal (AM) symbiosis occurs between fungi of the phylum Glomeromycota and most terrestrial plants. However, little is known about the molecular symbiotic signalling between AM fungi (AMFs) and non-leguminous plant species. We sought to further elucidate the molecular events occurring in tomato, a non-leguminous host plant, during the early, pre-symbiotic stage of AM symbiosis, i.e. immediately before and after contact between the AMF (Glomus intraradices) and the host. We adopted a semi-synchronized AMF root infection protocol, followed by genomic-scale, microarray-based, gene expression profiling at several defined time points during pre-symbiotic AM stages. The microarray results suggested differences in the number of differentially expressed genes and in the differential regulation of several functional groups of genes at the different time points examined. The microarray results were validated and one of the genes induced during contact between AMF and tomato, the expansin-like EXLB1, was functionally analysed. Expansins, encoded by a large multigene family, facilitate plant cell expansion. However, no biological or biochemical function has yet been established for plant-originated expansin-like proteins. EXLB1 transcripts were localized early during the association to cells that may perceive the fungal signal, and later during the association in close proximity to sites of AMF hypha-root colonization. Moreover, in transgenic roots, we demonstrated that a reduction in the steady-state level of EXLB1 transcript was correlated with a reduced rate of infection, reduced arbuscule expansion and reduced AMF spore formation.

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

    PubMed Central

    2012-01-01

    Background Seedlessness is an important agronomic trait for citrus, and male sterility (MS) is one main cause of seedless citrus fruit. However, the molecular mechanism of citrus seedlessness remained not well explored. Results An integrative strategy combining suppression subtractive hybridization (SSH) library with cDNA microarray was employed to study the underlying mechanism of seedlessness of a Ponkan mandarin seedless mutant (Citrus reticulata Blanco). Screening with custom microarray, a total of 279 differentially expressed clones were identified, and 133 unigenes (43 contigs and 90 singletons) were obtained after sequencing. Gene Ontology (GO) distribution based on biological process suggested that the majority of differential genes are involved in metabolic process and respond to stimulus and regulation of biology process; based on molecular function they function as DNA/RNA binding or have catalytic activity and oxidoreductase activity. A gene encoding male sterility-like protein was highly up-regulated in the seedless mutant compared with the wild type, while several transcription factors (TFs) such as AP2/EREBP, MYB, WRKY, NAC and C2C2-GATA zinc-finger domain TFs were down-regulated. Conclusion Our research highlighted some candidate pathways that participated in the citrus male gametophyte development and could be beneficial for seedless citrus breeding in the future. PMID:22897898

  3. Microarray amplification bias: loss of 30% differentially expressed genes due to long probe – poly(A)-tail distances

    PubMed Central

    Boelens, Mirjam C; te Meerman, Gerard J; Gibcus, Johan H; Blokzijl, Tjasso; Boezen, H Marike; Timens, Wim; Postma, Dirkje S; Groen, Harry JM; van den Berg, Anke

    2007-01-01

    Background Laser microdissection microscopy has become a rising tool to assess gene expression profiles of pure cell populations. Given the low yield of RNA, a second round of amplification is usually mandatory to yield sufficient amplified-RNA for microarray approaches. Since amplification induces truncation of RNA molecules, we studied the impact of a second round of amplification on identification of differentially expressed genes in relation to the probe – poly(A)-tail distances. Results Disagreement was observed between gene expression profiles acquired after a second round of amplification compared to a single round. Thirty percent of the differentially expressed genes identified after one round of amplification were not detected after two rounds. These inconsistent genes have a significant longer probe – poly(A)-tail distance. qRT-PCR on unamplified RNA confirmed differential expression of genes with a probe – poly(A)-tail distance >500 nucleotides appearing only after one round of amplification. Conclusion Our data demonstrate a marked loss of 30% of truly differentially expressed genes after a second round of amplification. Therefore, we strongly recommend improvement of amplification procedures and importance of microarray probe design to allow detection of all differentially expressed genes in case of limited amounts of RNA. PMID:17697374

  4. Gene Organization in Rice Revealed by Full-Length cDNA Mapping and Gene Expression Analysis through Microarray

    PubMed Central

    Satoh, Kouji; Doi, Koji; Nagata, Toshifumi; Kishimoto, Naoki; Suzuki, Kohji; Otomo, Yasuhiro; Kawai, Jun; Nakamura, Mari; Hirozane-Kishikawa, Tomoko; Kanagawa, Saeko; Arakawa, Takahiro; Takahashi-Iida, Juri; Murata, Mitsuyoshi; Ninomiya, Noriko; Sasaki, Daisuke; Fukuda, Shiro; Tagami, Michihira; Yamagata, Harumi; Kurita, Kanako; Kamiya, Kozue; Yamamoto, Mayu; Kikuta, Ari; Bito, Takahito; Fujitsuka, Nahoko; Ito, Kazue; Kanamori, Hiroyuki; Choi, Il-Ryong; Nagamura, Yoshiaki; Matsumoto, Takashi; Murakami, Kazuo; Matsubara, Ken-ichi; Carninci, Piero; Hayashizaki, Yoshihide; Kikuchi, Shoshi

    2007-01-01

    Rice (Oryza sativa L.) is a model organism for the functional genomics of monocotyledonous plants since the genome size is considerably smaller than those of other monocotyledonous plants. Although highly accurate genome sequences of indica and japonica rice are available, additional resources such as full-length complementary DNA (FL-cDNA) sequences are also indispensable for comprehensive analyses of gene structure and function. We cross-referenced 28.5K individual loci in the rice genome defined by mapping of 578K FL-cDNA clones with the 56K loci predicted in the TIGR genome assembly. Based on the annotation status and the presence of corresponding cDNA clones, genes were classified into 23K annotated expressed (AE) genes, 33K annotated non-expressed (ANE) genes, and 5.5K non-annotated expressed (NAE) genes. We developed a 60mer oligo-array for analysis of gene expression from each locus. Analysis of gene structures and expression levels revealed that the general features of gene structure and expression of NAE and ANE genes were considerably different from those of AE genes. The results also suggested that the cloning efficiency of rice FL-cDNA is associated with the transcription activity of the corresponding genetic locus, although other factors may also have an effect. Comparison of the coverage of FL-cDNA among gene families suggested that FL-cDNA from genes encoding rice- or eukaryote-specific domains, and those involved in regulatory functions were difficult to produce in bacterial cells. Collectively, these results indicate that rice genes can be divided into distinct groups based on transcription activity and gene structure, and that the coverage bias of FL-cDNA clones exists due to the incompatibility of certain eukaryotic genes in bacteria. PMID:18043742

  5. Database for mRNA half-life of 19 977 genes obtained by DNA microarray analysis of pluripotent and differentiating mouse embryonic stem cells.

    PubMed

    Sharova, Lioudmila V; Sharov, Alexei A; Nedorezov, Timur; Piao, Yulan; Shaik, Nabeebi; Ko, Minoru S H

    2009-02-01

    Degradation of mRNA is one of the key processes that control the steady-state level of gene expression. However, the rate of mRNA decay for the majority of genes is not known. We successfully obtained the rate of mRNA decay for 19 977 non-redundant genes by microarray analysis of RNA samples obtained from mouse embryonic stem (ES) cells. Median estimated half-life was 7.1 h and only <100 genes, including Prdm1, Myc, Gadd45 g, Foxa2, Hes5 and Trib1, showed half-life less than 1 h. In general, mRNA species with short half-life were enriched among genes with regulatory functions (transcription factors), whereas mRNA species with long half-life were enriched among genes related to metabolism and structure (extracellular matrix, cytoskeleton). The stability of mRNAs correlated more significantly with the structural features of genes than the function of genes: mRNA stability showed the most significant positive correlation with the number of exon junctions per open reading frame length, and negative correlation with the presence of PUF-binding motifs and AU-rich elements in 3'-untranslated region (UTR) and CpG di-nucleotides in the 5'-UTR. The mRNA decay rates presented in this report are the largest data set for mammals and the first for ES cells.

  6. Identification of rat lung – prominent genes by a parallel DNA microarray hybridization

    PubMed Central

    Chen, Zhongming; Chen, Jiwang; Weng, Tingting; Jin, Nili; Liu, Lin

    2006-01-01

    Background The comparison of organ transcriptomes is an important strategy for understanding gene functions. In the present study, we attempted to identify lung-prominent genes by comparing the normal transcriptomes of rat lung, heart, kidney, liver, spleen, and brain. To increase the efficiency and reproducibility, we first developed a novel parallel hybridization system, in which 6 samples could be hybridized onto a single slide at the same time. Results We identified the genes prominently expressed in the lung (147) or co-expressed in lung-heart (23), lung-liver (37), lung-spleen (203), and lung-kidney (98). The known functions of the lung-prominent genes mainly fell into 5 categories: ligand binding, signal transducer, cell communication, development, and metabolism. Real-time PCR confirmed 13 lung-prominent genes, including 5 genes that have not been investigated in the lung, vitamin D-dependent calcium binding protein (Calb3), mitogen activated protein kinase 13 (Mapk13), solute carrier family 29 transporters, member 1 (Slc29a1), corticotropin releasing hormone receptor (Crhr1), and lipocalin 2 (Lcn2). Conclusion The lung-prominent genes identified in this study may provide an important clue for further investigation of pulmonary functions. PMID:16533406

  7. Development of high-density DNA microarray membrane for profiling smoke- and hydrogen peroxide-induced genes in a human bronchial epithelial cell line.

    PubMed

    Yoneda, K; Peck, K; Chang, M M; Chmiel, K; Sher, Y P; Chen, J; Yang, P C; Chen, Y; Wu, R

    2001-11-15

    Development of the high-density DNA microarray technique permits the analysis of thousands of genes simultaneously for their differential expression patterns in various biological processes. Through clustering analysis and pattern recognition, the significance of differentially expressed genes can be recognized and correlated with biological events that may take place inside the cell and tissue. With this notion in mind, high-density DNA microarray nylon membrane with colorimetry detection was used to profile the expression of smoke- and hydrogen peroxide-inducible genes in a human bronchial epithelial cell line, HBE1. On the basis of the time course of expression, at least three phases of change in gene expression could be recognized. The first phase is an immediate event in response to oxidant injury. This phase includes induction of the bcl-2 and mdm-2 genes, which are involved in the regulation of apoptosis, and the mitogen-activated protein (MAP) kinase phosphatase 1 (MKP-1) gene, that functions as a regulator of various mitogen-activated protein kinase activities. The second phase, usually 5 h later, includes the induction of various stress proteins and ubiquitin, which are important in providing the chaperone mechanism and the turnover of damaged macromolecules. The third phase, which is 5-10 h later, includes the induction of genes that are apparently involved in reducing oxidative stress by metabolizing reactive oxygen species. In this phase, enzymes associated with tissue and cell remodeling are also elevated. These results demonstrate a complex gene expression array by bronchial epithelial cells in response to the insult of oxidants that are relevant to environmental pollutants.

  8. Microarray gene expression profiling of osteoarthritic bone suggests altered bone remodelling, WNT and transforming growth factor-β/bone morphogenic protein signalling

    PubMed Central

    Hopwood, Blair; Tsykin, Anna; Findlay, David M; Fazzalari, Nicola L

    2007-01-01

    Osteoarthritis (OA) is characterized by alterations to subchondral bone as well as articular cartilage. Changes to bone in OA have also been identified at sites distal to the affected joint, which include increased bone volume fraction and reduced bone mineralization. Altered bone remodelling has been proposed to underlie these bone changes in OA. To investigate the molecular basis for these changes, we performed microarray gene expression profiling of bone obtained at autopsy from individuals with no evidence of joint disease (control) and from individuals undergoing joint replacement surgery for either degenerative hip OA, or fractured neck of femur (osteoporosis [OP]). The OP sample set was included because an inverse association, with respect to bone density, has been observed between OA and the low bone density disease OP. Compugen human 19K-oligo microarray slides were used to compare the gene expression profiles of OA, control and OP bone samples. Four sets of samples were analyzed, comprising 10 OA-control female, 10 OA-control male, 10 OA-OP female and 9 OP-control female sample pairs. Print tip Lowess normalization and Bayesian statistical analyses were carried out using linear models for microarray analysis, which identified 150 differentially expressed genes in OA bone with t scores above 4. Twenty-five of these genes were then confirmed to be differentially expressed (P < 0.01) by real-time PCR analysis. A substantial number of the top-ranking differentially expressed genes identified in OA bone are known to play roles in osteoblasts, osteocytes and osteoclasts. Many of these genes are targets of either the WNT (wingless MMTV integration) signalling pathway (TWIST1, IBSP, S100A4, MMP25, RUNX2 and CD14) or the transforming growth factor (TGF)-β/bone morphogenic protein (BMP) signalling pathway (ADAMTS4, ADM, MEPE, GADD45B, COL4A1 and FST). Other differentially expressed genes included WNT (WNT5B, NHERF1, CTNNB1 and PTEN) and TGF-β/BMP (TGFB1, SMAD3

  9. Identification of Differentially Expressed Gene after Femoral Fracture via Microarray Profiling

    PubMed Central

    Zhong, Donggen

    2014-01-01

    We aimed to investigate differentially expressed genes (DEGs) in different stages after femoral fracture based on rat models, providing the basis for the treatment of sport-related fractures. Gene expression data GSE3298 was downloaded from Gene Expression Omnibus (GEO), including 16 chips. All femoral fracture samples were classified into earlier fracture stage and later fracture stage. Total 87 DEGs simultaneously occurred in two stages, of which 4 genes showed opposite expression tendency. Out of the 4 genes, Rest and Cst8 were hub nodes in protein-protein interaction (PPI) network. The GO (Gene Ontology) function enrichment analysis verified that nutrition supply related genes were enriched in the earlier stage and neuron growth related genes were enriched in the later stage. Calcium signaling pathway was the most significant pathway in earlier stage; in later stage, DEGs were enriched into 2 neurodevelopment-related pathways. Analysis of Pearson's correlation coefficient showed that a total of 3,300 genes were significantly associated with fracture time, none of which was overlapped with identified DEGs. This study suggested that Rest and Cst8 might act as potential indicators for fracture healing. Calcium signaling pathway and neurodevelopment-related pathways might be deeply involved in bone healing after femoral fracture. PMID:25110652

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

    PubMed

    Yasrebi, Haleh

    2016-09-01

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

  11. Two-Way Gene Interaction From Microarray Data Based on Correlation Methods

    PubMed Central

    Alavi Majd, Hamid; Talebi, Atefeh; Gilany, Kambiz; Khayyer, Nasibeh

    2016-01-01

    Background Gene networks have generated a massive explosion in the development of high-throughput techniques for monitoring various aspects of gene activity. Networks offer a natural way to model interactions between genes, and extracting gene network information from high-throughput genomic data is an important and difficult task. Objectives The purpose of this study is to construct a two-way gene network based on parametric and nonparametric correlation coefficients. The first step in constructing a Gene Co-expression Network is to score all pairs of gene vectors. The second step is to select a score threshold and connect all gene pairs whose scores exceed this value. Materials and Methods In the foundation-application study, we constructed two-way gene networks using nonparametric methods, such as Spearman’s rank correlation coefficient and Blomqvist’s measure, and compared them with Pearson’s correlation coefficient. We surveyed six genes of venous thrombosis disease, made a matrix entry representing the score for the corresponding gene pair, and obtained two-way interactions using Pearson’s correlation, Spearman’s rank correlation, and Blomqvist’s coefficient. Finally, these methods were compared with Cytoscape, based on BIND, and Gene Ontology, based on molecular function visual methods; R software version 3.2 and Bioconductor were used to perform these methods. Results Based on the Pearson and Spearman correlations, the results were the same and were confirmed by Cytoscape and GO visual methods; however, Blomqvist’s coefficient was not confirmed by visual methods. Conclusions Some results of the correlation coefficients are not the same with visualization. The reason may be due to the small number of data.

  12. Two-Way Gene Interaction From Microarray Data Based on Correlation Methods

    PubMed Central

    Alavi Majd, Hamid; Talebi, Atefeh; Gilany, Kambiz; Khayyer, Nasibeh

    2016-01-01

    Background Gene networks have generated a massive explosion in the development of high-throughput techniques for monitoring various aspects of gene activity. Networks offer a natural way to model interactions between genes, and extracting gene network information from high-throughput genomic data is an important and difficult task. Objectives The purpose of this study is to construct a two-way gene network based on parametric and nonparametric correlation coefficients. The first step in constructing a Gene Co-expression Network is to score all pairs of gene vectors. The second step is to select a score threshold and connect all gene pairs whose scores exceed this value. Materials and Methods In the foundation-application study, we constructed two-way gene networks using nonparametric methods, such as Spearman’s rank correlation coefficient and Blomqvist’s measure, and compared them with Pearson’s correlation coefficient. We surveyed six genes of venous thrombosis disease, made a matrix entry representing the score for the corresponding gene pair, and obtained two-way interactions using Pearson’s correlation, Spearman’s rank correlation, and Blomqvist’s coefficient. Finally, these methods were compared with Cytoscape, based on BIND, and Gene Ontology, based on molecular function visual methods; R software version 3.2 and Bioconductor were used to perform these methods. Results Based on the Pearson and Spearman correlations, the results were the same and were confirmed by Cytoscape and GO visual methods; however, Blomqvist’s coefficient was not confirmed by visual methods. Conclusions Some results of the correlation coefficients are not the same with visualization. The reason may be due to the small number of data. PMID:27621916

  13. Detection of mRNAs in soils using targeted microarrays for genes associated with lignin degradation

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Microarrays have become established tools for describing microbial systems, however the direct assessment of expression profiles for uncharacterized environmental microbial communities still presents unique challenges. Notably, the concentration of particular transcripts are likely very dilute relat...

  14. DNA microarray analysis reveals a role for lysophosphatidic acid in the regulation of anti-inflammatory genes in MC3T3-E1 cells

    SciTech Connect

    Waters, Katrina M.; Tan, Ruimin; Genetos, Damian C.; Verma, Seema; Yellowley, Clare E.; Karin, Norm J.

    2007-11-01

    DNA microarray analysis revealed that treatment of bone cells with a lipid growth factor led to extensive changes in gene expression. Particular relevance to fracture healing and inflammation was revealed.

  15. Screening feature genes of astrocytoma using a combined method of microarray gene expression profiling and bioinformatics analysis

    PubMed Central

    Cai, Yong; Zhong, Xingming; Wang, Yiqi; Yang, Jianguo

    2015-01-01

    The aim of our study was to find feature genes associated with astrocytoma and correlative gene functions which can distinguish cancer tissue from adjacent non-tumor astrocyte tissues. Gene expression profile GSE15824 was downloaded from Gene Expression Omnibus database which included 8 astrocytoma tissues and 3 adjacent non-tumor astrocyte samples. The raw data were first transformed into probe-level data and the differentially expressed genes (DEGs) between tissues of patients with astrocytoma and normal specimen were identified using T-test in samr package of R. The Database for Annotation, Visualization and Integrated Discovery (DAVID) was applied to analyze the gene ontology (GO) enrichment on gene functions and the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. Finally, corresponding protein-protein interaction (PPI) networks of DEGs was constructed using the Cytoscape based on the data collected from STRING online datasets. A total of 3072 genes, including 1799 up-regulated genes and 1273 down-regulated genes, were filtered as DEGs, and we learnt that the DEGs including AQP4, PMP2, SRARCL1 and SLC1A2CAMs etc and that AQP4 was most significantly related to cell osmotic pressure. Three feature genes in KEGG pathway are highly enriched in cancer specimen while two genes are in the normal tissues. The discovery of featured genes significantly related to the regulation of cell osmotic pressure, has the potential to use in clinic for diagnosis of astrocytoma in future. In addition, it has a great significance on studying mechanism, distinguishing normal and cancer tissues, and exploring new treatments for astrocytoma. However, further experiments were needed to confirm our result. PMID:26770395

  16. Screening feature genes of astrocytoma using a combined method of microarray gene expression profiling and bioinformatics analysis.

    PubMed

    Cai, Yong; Zhong, Xingming; Wang, Yiqi; Yang, Jianguo

    2015-01-01

    The aim of our study was to find feature genes associated with astrocytoma and correlative gene functions which can distinguish cancer tissue from adjacent non-tumor astrocyte tissues. Gene expression profile GSE15824 was downloaded from Gene Expression Omnibus database which included 8 astrocytoma tissues and 3 adjacent non-tumor astrocyte samples. The raw data were first transformed into probe-level data and the differentially expressed genes (DEGs) between tissues of patients with astrocytoma and normal specimen were identified using T-test in samr package of R. The Database for Annotation, Visualization and Integrated Discovery (DAVID) was applied to analyze the gene ontology (GO) enrichment on gene functions and the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. Finally, corresponding protein-protein interaction (PPI) networks of DEGs was constructed using the Cytoscape based on the data collected from STRING online datasets. A total of 3072 genes, including 1799 up-regulated genes and 1273 down-regulated genes, were filtered as DEGs, and we learnt that the DEGs including AQP4, PMP2, SRARCL1 and SLC1A2CAMs etc and that AQP4 was most significantly related to cell osmotic pressure. Three feature genes in KEGG pathway are highly enriched in cancer specimen while two genes are in the normal tissues. The discovery of featured genes significantly related to the regulation of cell osmotic pressure, has the potential to use in clinic for diagnosis of astrocytoma in future. In addition, it has a great significance on studying mechanism, distinguishing normal and cancer tissues, and exploring new treatments for astrocytoma. However, further experiments were needed to confirm our result. PMID:26770395

  17. Analyzing gene expression data from microarray and next-generation dna sequencing transcriptome profiling assays using GeneSifter analysis edition.

    PubMed

    Porter, Sandra; Olson, N Eric; Smith, Todd

    2009-09-01

    Transcription profiling with microarrays has become a standard procedure for comparing the levels of gene expression between pairs of samples, or multiple samples following different experimental treatments. New technologies, collectively known as next-generation DNA sequencing methods, are also starting to be used for transcriptome analysis. These technologies, with their low background, large capacity for data collection, and dynamic range, provide a powerful and complementary tool to the assays that formerly relied on microarrays. In this chapter, we describe two protocols for working with microarray data from pairs of samples and samples treated with multiple conditions, and discuss alternative protocols for carrying out similar analyses with next-generation DNA sequencing data from two different instrument platforms (Illumina GA and Applied Biosystems SOLiD).

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

    PubMed

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

    2016-01-01

    Ethylene is commonly used as a latex stimulant of Hevea brasiliensis by application of ethephon (chloro-2-ethylphosphonic acid); however, the molecular mechanism by which ethylene increases latex production is not clear. To better understand the effects of ethylene stimulation on the laticiferous cells of rubber trees, a latex expressed sequence tag (EST)-based complementary DNA microarray containing 2,973 unique genes (probes) was first developed and used to analyze the gene expression changes in the latex of the mature virgin rubber trees after ethephon treatment at three different time-points: 8, 24 and 48 h. Transcript levels of 163 genes were significantly altered with fold-change values ≥ 2 or ≤ -2 (q-value < 0.05) in ethephon-treated rubber trees compared with control trees. Of the 163 genes, 92 were up-regulated and 71 down-regulated. The microarray results were further confirmed using real-time quantitative reverse transcript-PCR for 20 selected genes. The 163 ethylene-responsive genes were involved in several biological processes including organic substance metabolism, cellular metabolism, primary metabolism, biosynthetic process, cellular response to stimulus and stress. The presented data suggest that the laticifer water circulation, production and scavenging of reactive oxygen species, sugar metabolism, and assembly and depolymerization of the latex actin cytoskeleton might play important roles in ethylene-induced increase of latex production. The results may provide useful insights into understanding the molecular mechanism underlying the effect of ethylene on latex metabolism of H. brasiliensis.

  19. Identification of differentially expressed genes and signalling pathways in bark of Hevea brasiliensis seedlings associated with secondary laticifer differentiation using gene expression microarray.

    PubMed

    Loh, Swee Cheng; Thottathil, Gincy P; Othman, Ahmad Sofiman

    2016-10-01

    The natural rubber of Para rubber tree, Hevea brasiliensis, is the main crop involved in industrial rubber production due to its superior quality. The Hevea bark is commercially exploited to obtain latex, which is produced from the articulated secondary laticifer. The laticifer is well defined in the aspect of morphology; however, only some genes associated with its development have been reported. We successfully induced secondary laticifer in the jasmonic acid (JA)-treated and linolenic acid (LA)-treated Hevea bark but secondary laticifer is not observed in the ethephon (ET)-treated and untreated Hevea bark. In this study, we analysed 27,195 gene models using NimbleGen microarrays based on the Hevea draft genome. 491 filtered differentially expressed (FDE) transcripts that are common to both JA- and LA-treated bark samples but not ET-treated bark samples were identified. In the Eukaryotic Orthologous Group (KOG) analysis, 491 FDE transcripts belong to different functional categories that reflect the diverse processes and pathways involved in laticifer differentiation. In the Kyoto Encyclopedia of Genes and Genomes (KEGG) and KOG analysis, the profile of the FDE transcripts suggest that JA- and LA-treated bark samples have a sufficient molecular basis for secondary laticifer differentiation, especially regarding secondary metabolites metabolism. FDE genes in this category are from the cytochrome (CYP) P450 family, ATP-binding cassette (ABC) transporter family, short-chain dehydrogenase/reductase (SDR) family, or cinnamyl alcohol dehydrogenase (CAD) family. The data includes many genes involved in cell division, cell wall synthesis, and cell differentiation. The most abundant transcript in FDE list was SDR65C, reflecting its importance in laticifer differentiation. Using the Basic Local Alignment Search Tool (BLAST) as part of annotation and functional prediction, several characterised as well as uncharacterized transcription factors and genes were found in the

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

    SciTech Connect

    Tholouli, Eleni; MacDermott, Sarah; Hoyland, Judith; Yin, John Liu; Byers, Richard

    2012-08-24

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

  1. The 'PUCE CAFE' Project: the First 15K Coffee Microarray, a New Tool for Discovering Candidate Genes correlated to Agronomic and Quality Traits

    PubMed Central

    2011-01-01

    Background Understanding the genetic elements that contribute to key aspects of coffee biology will have an impact on future agronomical improvements for this economically important tree. During the past years, EST collections were generated in Coffee, opening the possibility to create new tools for functional genomics. Results The "PUCE CAFE" Project, organized by the scientific consortium NESTLE/IRD/CIRAD, has developed an oligo-based microarray using 15,721 unigenes derived from published coffee EST sequences mostly obtained from different stages of fruit development and leaves in Coffea Canephora (Robusta). Hybridizations for two independent experiments served to compare global gene expression profiles in three types of tissue matter (mature beans, leaves and flowers) in C. canephora as well as in the leaves of three different coffee species (C. canephora, C. eugenoides and C. arabica). Microarray construction, statistical analyses and validation by Q-PCR analysis are presented in this study. Conclusion We have generated the first 15 K coffee array during this PUCE CAFE project, granted by Génoplante (the French consortium for plant genomics). This new tool will help study functional genomics in a wide range of experiments on various plant tissues, such as analyzing bean maturation or resistance to pathogens or drought. Furthermore, the use of this array has proven to be valid in different coffee species (diploid or tetraploid), drastically enlarging its impact for high-throughput gene expression in the community of coffee research. PMID:21208403

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

    PubMed

    Kwiatkowski, Przemysław; Wierzbicki, Piotr; Kmieć, Andrzej; Godlewski, Janusz

    2012-06-11

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

  3. Altered gene expression in the brain and ovaries of zebrafish (Danio rerio) exposed to the aromatase inhibitor fadrozole: microarray analysis and hypothesis generation.

    PubMed

    Villeneuve, L; Wang, Rong-Lin; Bencic, David C; Biales, Adam D; Martinović, Dalma; Lazorchak, James M; Toth, Gregory; Ankley, Gerald T

    2009-08-01

    As part of a research effort examining system-wide responses of the hypothalamic-pituitary-gonadal (HPG) axis in fish to endocrine-active chemicals (EACs) with different modes of action, zebrafish (Danio rerio) were exposed to 25 or 100 microg/L of the aromatase inhibitor fadrozole for 24, 48, or 96 h. Global transcriptional response in brain and ovarian tissue of fish exposed to 25 microg/L of fadrozole was compared to that in control fish using a commercially available, 22,000-gene oligonucleotide microarray. Transcripts altered in brain were functionally linked to differentiation, development, DNA replication, and cell cycle. Additionally, multiple genes associated with the one-carbon pool by folate pathway (KEGG 00670) were significantly up-regulated. Transcripts altered in ovary were functionally linked to cell-cell adhesion, extracellular matrix, vasculogenesis, and development. Promoter motif analysis identified GATA-binding factor 2, Ikaros 2, alcohol dehydrogenase gene regulator 1, myoblast-determining factor, and several heat shock factors as being associated with coexpressed gene clusters that were differentially expressed following exposure to fadrozole. Based on the transcriptional changes observed, it was hypothesized that fadrozole elicits neurodegenerative stress in brain tissue and that fish cope with this stress through proliferation of radial glial cells. Additionally, it was hypothesized that changes of gene expression in the ovary of fadrozole-exposed zebrafish reflect disruption of oocyte maturation and ovulation because of impaired vitellogenesis. These hypotheses and others derived from the microarray results provide a foundation for future studies aimed at understanding responses of the HPG axis to EACs and other chemical stressors.

  4. Finding differentially expressed genes in two-channel DNA microarray datasets: how to increase reliability of data preprocessing.

    PubMed

    Rotter, Ana; Hren, Matjaz; Baebler, Spela; Blejec, Andrej; Gruden, Kristina

    2008-09-01

    Due to the great variety of preprocessing tools in two-channel expression microarray data analysis it is difficult to choose the most appropriate one for a given experimental setup. In our study, two independent two-channel inhouse microarray experiments as well as a publicly available dataset were used to investigate the influence of the selection of preprocessing methods (background correction, normalization, and duplicate spots correlation calculation) on the discovery of differentially expressed genes. Here we are showing that both the list of differentially expressed genes and the expression values of selected genes depend significantly on the preprocessing approach applied. The choice of normalization method to be used had the highest impact on the results. We propose a simple but efficient approach to increase the reliability of obtained results, where two normalization methods which are theoretically distinct from one another are used on the same dataset. Then the intersection of results, that is, the lists of differentially expressed genes, is used in order to get a more accurate estimation of the genes that were de facto differentially expressed.

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

    PubMed Central

    Singh, Sushmita; Kaur, Kuljeet; Kapur, Vivek

    2004-01-01

    High throughput detection of differential expression of genes is an efficient means of identifying genes and pathways that may play a role in biological systems under certain experimental conditions. There exist a variety of approaches that could be used to identify groups of genes that change in expression in response to a particular stimulus or environment. We here describe the application of suppression subtractive hybridization (SSH) coupled with cDNA microarray analysis for isolation and identification of chicken transcripts that change in expression on infection of host cells with a paramyxovirus. SSH was used for initial isolation of differentially expressed transcripts, a large-scale validation of which was accomplished by microarray analysis. The data reveals a large group of regulated genes constituting many biochemical pathways that could serve as targets for future investigations to explore their role in paramyxovirus pathogenesis. The detailed methods described herein could be useful and adaptable to any biological system for studying changes in gene expression. PMID:15181476

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

    PubMed

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

    2014-01-01

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

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

    PubMed

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

    2014-01-01

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

  8. Emerging tools for real-time label-free detection of interactions on functional protein microarrays.

    PubMed

    Ramachandran, Niroshan; Larson, Dale N; Stark, Peter R H; Hainsworth, Eugenie; LaBaer, Joshua

    2005-11-01

    The availability of extensive genomic information and content has spawned an era of high-throughput screening that is generating large sets of functional genomic data. In particular, the need to understand the biochemical wiring within a cell has introduced novel approaches to map the intricate networks of biological interactions arising from the interactions of proteins. The current technologies for assaying protein interactions--yeast two-hybrid and immunoprecipitation with mass spectrometric detection--have met with considerable success. However, the parallel use of these approaches has identified only a small fraction of physiologically relevant interactions among proteins, neglecting all nonprotein interactions, such as with metabolites, lipids, DNA and small molecules. This highlights the need for further development of proteome scale technologies that enable the study of protein function. Here we discuss recent advances in high-throughput technologies for displaying proteins on functional protein microarrays and the real-time label-free detection of interactions using probes of the local index of refraction, carbon nanotubes and nanowires, or microelectromechanical systems cantilevers. The combination of these technologies will facilitate the large-scale study of protein interactions with proteins as well as with other biomolecules.

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

    PubMed

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

    2015-06-01

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

  10. Microarray analysis and scale-free gene networks identify candidate regulators in drought-stressed roots of loblolly pine (P. taeda L.)

    PubMed Central

    2011-01-01

    Background Global transcriptional analysis of loblolly pine (Pinus taeda L.) is challenging due to limited molecular tools. PtGen2, a 26,496 feature cDNA microarray, was fabricated and used to assess drought-induced gene expression in loblolly pine propagule roots. Statistical analysis of differential expression and weighted gene correlation network analysis were used to identify drought-responsive genes and further characterize the molecular basis of drought tolerance in loblolly pine. Results Microarrays were used to interrogate root cDNA populations obtained from 12 genotype × treatment combinations (four genotypes, three watering regimes). Comparison of drought-stressed roots with roots from the control treatment identified 2445 genes displaying at least a 1.5-fold expression difference (false discovery rate = 0.01). Genes commonly associated with drought response in pine and other plant species, as well as a number of abiotic and biotic stress-related genes, were up-regulated in drought-stressed roots. Only 76 genes were identified as differentially expressed in drought-recovered roots, indicating that the transcript population can return to the pre-drought state within 48 hours. Gene correlation analysis predicts a scale-free network topology and identifies eleven co-expression modules that ranged in size from 34 to 938 members. Network topological parameters identified a number of central nodes (hubs) including those with significant homology (E-values ≤ 2 × 10-30) to 9-cis-epoxycarotenoid dioxygenase, zeatin O-glucosyltransferase, and ABA-responsive protein. Identified hubs also include genes that have been associated previously with osmotic stress, phytohormones, enzymes that detoxify reactive oxygen species, and several genes of unknown function. Conclusion PtGen2 was used to evaluate transcriptome responses in loblolly pine and was leveraged to identify 2445 differentially expressed genes responding to severe drought stress in roots. Many of the

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

    PubMed

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

    2014-01-01

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

  12. Discovery of Possible Gene Relationships through the Application of Self-Organizing Maps to DNA Microarray Databases

    PubMed Central

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

    2014-01-01

    DNA microarrays and cell cycle synchronization experiments have made possible the study of the mechanisms of cell cycle regulation of Saccharomyces cerevisiae by simultaneously monitoring the expression levels of thousands of genes at specific time points. On the other hand, pattern recognition techniques can contribute to the analysis of such massive measurements, providing a model of gene expression level evolution through the cell cycle process. In this paper, we propose the use of one of such techniques –an unsupervised artificial neural network called a Self-Organizing Map (SOM)–which has been successfully applied to processes involving very noisy signals, classifying and organizing them, and assisting in the discovery of behavior patterns without requiring prior knowledge about the process under analysis. As a test bed for the use of SOMs in finding possible relationships among genes and their possible contribution in some biological processes, we selected 282 S. cerevisiae genes that have been shown through biological experiments to have an activity during the cell cycle. The expression level of these genes was analyzed in five of the most cited time series DNA microarray databases used in the study of the cell cycle of this organism. With the use of SOM, it was possible to find clusters of genes with similar behavior in the five databases along two cell cycles. This result suggested that some of these genes might be biologically related or might have a regulatory relationship, as was corroborated by comparing some of the clusters obtained with SOMs against a previously reported regulatory network that was generated using biological knowledge, such as protein-protein interactions, gene expression levels, metabolism dynamics, promoter binding, and modification, regulation and transport of proteins. The methodology described in this paper could be applied to the study of gene relationships of other biological processes in different organisms. PMID:24699245

  13. Microarray analyses for identifying genes conferring resistance to pepper leaf curl virus in chilli pepper (Capsicum spp.).

    PubMed

    Rai, Ved Prakash; Rai, Ashutosh; Kumar, Rajesh; Kumar, Sanjay; Kumar, Sanjeet; Singh, Major; Singh, Sheo Pratap

    2016-09-01

    Pepper leaf curl virus (PepLCV) is a serious threat to pepper (Capsicum spp.) production worldwide. Molecular mechanism underlying pepper plants response to PepLCV infection is key to develop PepLCV resistant varieties. In this study, we generated transcriptome profiles of PepLCV resistant genotype (BS-35) and susceptible genotype (IVPBC-535) after artificial viral inoculation using microarray technology and detail experimental procedures and analyses are described. A total of 319 genes differentially expressed between resistant and susceptible genotypes were identified, out of that 234 unique genes were found to be up-regulated > 2-fold in resistant line BS-35 when compared to susceptible, IVPBC-535. The data set we generated has been analyzed to identify genes that are involved in the regulation of resistance against PepLCV. The raw data have been deposited in the Gene Expression Omnibus (GEO) database under accession number GSE41131.

  14. Microarray analyses for identifying genes conferring resistance to pepper leaf curl virus in chilli pepper (Capsicum spp.).

    PubMed

    Rai, Ved Prakash; Rai, Ashutosh; Kumar, Rajesh; Kumar, Sanjay; Kumar, Sanjeet; Singh, Major; Singh, Sheo Pratap

    2016-09-01

    Pepper leaf curl virus (PepLCV) is a serious threat to pepper (Capsicum spp.) production worldwide. Molecular mechanism underlying pepper plants response to PepLCV infection is key to develop PepLCV resistant varieties. In this study, we generated transcriptome profiles of PepLCV resistant genotype (BS-35) and susceptible genotype (IVPBC-535) after artificial viral inoculation using microarray technology and detail experimental procedures and analyses are described. A total of 319 genes differentially expressed between resistant and susceptible genotypes were identified, out of that 234 unique genes were found to be up-regulated > 2-fold in resistant line BS-35 when compared to susceptible, IVPBC-535. The data set we generated has been analyzed to identify genes that are involved in the regulation of resistance against PepLCV. The raw data have been deposited in the Gene Expression Omnibus (GEO) database under accession number GSE41131. PMID:27556012

  15. Analysis of differentially expressed genes in placental tissues of preeclampsia patients using microarray combined with the Connectivity Map database.

    PubMed

    Song, Y; Liu, J; Huang, S; Zhang, L

    2013-12-01

    Preeclampsia (PE), which affects 2-7% of human pregnancies, causes significant maternal and neonatal morbidity and mortality. To better understand the pathophysiology of PE, the gene expression profiles of placental tissue from 5 controls and 5 PE patients were assessed using microarray. A total of 224 transcripts were significantly differentially expressed (>2-fold change and q value <0.05, SAM software). Gene Ontology (GO) enrichment analysis indicated that genes involved in hypoxia and oxidative and reductive processes were significantly changed. Three differentially expressed genes (DEGs) involved in these biological processes were further verified by quantitative real-time PCR. Finally, the potential therapeutic agents for PE were explored via the Connectivity Map database. In conclusion, the data obtained in this study might provide clues to better understand the pathophysiology of PE and to identify potential therapeutic agents for PE patients.

  16. PathoPlant: a platform for microarray expression data to analyze co-regulated genes involved in plant defense responses.

    PubMed

    Bülow, Lorenz; Schindler, Martin; Hehl, Reinhard

    2007-01-01

    Plants react to pathogen attack by expressing specific proteins directed toward the infecting pathogens. This involves the transcriptional activation of specific gene sets. PathoPlant, a database on plant-pathogen interactions and signal transduction reactions, has now been complemented by microarray gene expression data from Arabidopsis thaliana subjected to pathogen infection and elicitor treatment. New web tools enable identification of plant genes regulated by specific stimuli. Sets of genes co-regulated by multiple stimuli can be displayed as well. A user-friendly web interface was created for the submission of gene sets to be analyzed. This results in a table, listing the stimuli that act either inducing or repressing on the respective genes. The search can be restricted to certain induction factors to identify, e.g. strongly up- or down-regulated genes. Up to three stimuli can be combined with the option of induction factor restriction to determine similarly regulated genes. To identify common cis-regulatory elements in co-regulated genes, a resulting gene list can directly be exported to the AthaMap database for analysis. PathoPlant is freely accessible at http://www.pathoplant.de. PMID:17099232

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

    PubMed

    Lin, Chih-Ming; Feng, Wayne

    2012-08-01

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

  18. Microarray and real-time RT-PCR analyses of differential human gene expression patterns induced by severe acute respiratory syndrome (SARS) coronavirus infection of Vero cells.

    PubMed

    Leong, W F; Tan, H C; Ooi, E E; Koh, D R; Chow, Vincent T K

    2005-02-01

    Vero E6 African green monkey kidney cells are highly susceptible to infection with the newly emerging severe acute respiratory syndrome coronavirus (SARS-CoV), and they are permissive for rapid viral replication, with resultant cytopathic effects. We employed cDNA microarray analysis to characterize the cellular transcriptional responses of homologous human genes at 12 h post-infection. Seventy mRNA transcripts belonging to various functional classes exhibited significant alterations in gene expression. There was considerable induction of heat shock proteins that are crucial to the immune response mechanism. Modified levels of several transcripts involved in pro-inflammatory and anti-inflammatory processes exemplified the balance between opposing forces during SARS pathogenesis. Other genes displaying altered transcription included those associated with host translation, cellular metabolism, cell cycle, signal transduction, transcriptional regulation, protein trafficking, protein modulators, and cytoskeletal proteins. Alterations in the levels of several novel transcripts encoding hypothetical proteins and expressed sequence tags were also identified. In addition, transcription of apoptosis-related genes DENN and hIAP1 was upregulated in contrast to FAIM. Elevated Mx1 expression signified a strong host response to mediate antiviral resistance. Also expressed in infected cells was the C-terminal alternative splice variant of the p53 tumor suppressor gene encoding a modified truncated protein that can influence the activity of wild-type p53. We observed the interplay between various mechanisms to favor virus multiplication before full-blown apoptosis and the triggering of several pathways in host cells in an attempt to eliminate the pathogen. Microarray analysis identifies the critical host-pathogen interactions during SARS-CoV infection and provides new insights into the pathophysiology of SARS.

  19. Microarray Analysis in Glioblastomas

    PubMed Central

    Bhawe, Kaumudi M.; Aghi, Manish K.

    2016-01-01

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

  20. Microarray Analysis in Glioblastomas.

    PubMed

    Bhawe, Kaumudi M; Aghi, Manish K

    2016-01-01

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

  1. QA/QC issues to aid regulatory acceptance of microarray gene expression data.

    PubMed

    Fuscoe, James C; Tong, Weida; Shi, Leming

    2007-06-01

    The U.S. Food and Drug Administration is responsible for (1) promoting and protecting public health by assuring the safety and effectiveness of medicines and medical devices and (2) advancing public health by helping to speed innovations that make medicines and foods safer, more effective, and more affordable. The genomics revolution has dramatically increased our knowledge of basic biology but this has not resulted in the expected acceleration of new medical product development. The Agency's Critical Path to New Medical Products stresses that new tools are needed to address this pipeline problem. Microarray technology is one of these promising tools although questions have risen about the reproducibility of measurements. The Microarray Quality Control (MAQC) Project was initiated by FDA scientists to address this issue. This large project, which evaluated reference RNA samples on seven microarray platforms, found good intralaboratory repeatability and interlaboratory reproducibility. In addition, there was high cross-platform consistency. All data are available free of cost and the reference RNA samples are available for proficiency testing. Thus, current microarray technology appears to provide both reliability and consistency for regulatory submissions. PMID:17567852

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

    PubMed

    Li, Lu; Wang, Xianwei; Zhang, Xiaoli; Wang, Jinxing; Jin, Wenrui

    2015-01-01

    We report a novel ultra-sensitive and high-selective single-molecule-detection microarray assay (SMA) for multiple DNA determination. In the SMA, a capture DNA (DNAc) microarray consisting of 10 subarrays with 9 spots for each subarray is fabricated on a silanized glass coverslip as the substrate. On the subarrays, the spot-to-spot spacing is 500 μm and each spot has a diameter of ∼300 μm. The sequence of the DNAcs on the 9 spots of a subarray is different, to determine 8 types of target DNAs (DNAts). Thus, 8 types of DNAts are captured to their complementary DNAcs at 8 spots of a subarray, respectively, and then labeled with quantum dots (QDs) attached to 8 types of detection DNAs (DNAds) with different sequences. The ninth spot is used to detect the blank value. In order to determine the same 8 types of DNAts in 10 samples, the 10 DNAc-modified subarrays on the microarray are identical. Fluorescence single-molecule images of the QD-labeled DNAts on each spot of the subarray are acquired using a home-made single-molecule microarray reader. The amounts of the DNAts are quantified by counting the bright dots from the QDs. For a microarray, 8 types of DNAts in 10 samples can be quantified in parallel. The limit of detection of the SMA for DNA determination is as low as 1.3×10(-16) mol L(-1). The SMA for multi-DNA determination can also be applied in single-cell multiple gene expression analysis through quantification of complementary DNAs (cDNAs) corresponding to multiple messenger RNAs (mRNAs) in single cells. To do so, total RNA in single cells is extracted and reversely transcribed into their cDNAs. Three types of cDNAs corresponding to beta-2-microglobulin, glyceraldehyde-3-phosphate dehydrogenase and ribosomal protein, large, P2 mRNAs in single human breast cancer cells and 5 random synthetic DNAts are simultaneously quantified to examine the SMA and SMA-based single-cell multiple gene expression analysis. PMID:25479875

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

    PubMed

    Li, Lu; Wang, Xianwei; Zhang, Xiaoli; Wang, Jinxing; Jin, Wenrui

    2015-01-01

    We report a novel ultra-sensitive and high-selective single-molecule-detection microarray assay (SMA) for multiple DNA determination. In the SMA, a capture DNA (DNAc) microarray consisting of 10 subarrays with 9 spots for each subarray is fabricated on a silanized glass coverslip as the substrate. On the subarrays, the spot-to-spot spacing is 500 μm and each spot has a diameter of ∼300 μm. The sequence of the DNAcs on the 9 spots of a subarray is different, to determine 8 types of target DNAs (DNAts). Thus, 8 types of DNAts are captured to their complementary DNAcs at 8 spots of a subarray, respectively, and then labeled with quantum dots (QDs) attached to 8 types of detection DNAs (DNAds) with different sequences. The ninth spot is used to detect the blank value. In order to determine the same 8 types of DNAts in 10 samples, the 10 DNAc-modified subarrays on the microarray are identical. Fluorescence single-molecule images of the QD-labeled DNAts on each spot of the subarray are acquired using a home-made single-molecule microarray reader. The amounts of the DNAts are quantified by counting the bright dots from the QDs. For a microarray, 8 types of DNAts in 10 samples can be quantified in parallel. The limit of detection of the SMA for DNA determination is as low as 1.3×10(-16) mol L(-1). The SMA for multi-DNA determination can also be applied in single-cell multiple gene expression analysis through quantification of complementary DNAs (cDNAs) corresponding to multiple messenger RNAs (mRNAs) in single cells. To do so, total RNA in single cells is extracted and reversely transcribed into their cDNAs. Three types of cDNAs corresponding to beta-2-microglobulin, glyceraldehyde-3-phosphate dehydrogenase and ribosomal protein, large, P2 mRNAs in single human breast cancer cells and 5 random synthetic DNAts are simultaneously quantified to examine the SMA and SMA-based single-cell multiple gene expression analysis.

  4. Reconstruction of a Functional Human Gene Network, with an Application for Prioritizing Positional Candidate Genes

    PubMed Central

    Franke, Lude; Bakel, Harm van; Fokkens, Like; de Jong, Edwin D.; Egmont-Petersen, Michael; Wijmenga, Cisca

    2006-01-01

    Most common genetic disorders have a complex inheritance and may result from variants in many genes, each contributing only weak effects to the disease. Pinpointing these disease genes within the myriad of susceptibility loci identified in linkage studies is difficult because these loci may contain hundreds of genes. However, in any disorder, most of the disease genes will be involved in only a few different molecular pathways. If we know something about the relationships between the genes, we can assess whether some genes (which may reside in different loci) functionally interact with each other, indicating a joint basis for the disease etiology. There are various repositories of information on pathway relationships. To consolidate this information, we developed a functional human gene network that integrates information on genes and the functional relationships between genes, based on data from the Kyoto Encyclopedia of Genes and Genomes, the Biomolecular Interaction Network Database, Reactome, the Human Protein Reference Database, the Gene Ontology database, predicted protein-protein interactions, human yeast two-hybrid interactions, and microarray coexpressions. We applied this network to interrelate positional candidate genes from different disease loci and then tested 96 heritable disorders for which the Online Mendelian Inheritance in Man database reported at least three disease genes. Artificial susceptibility loci, each containing 100 genes, were constructed around each disease gene, and we used the network to rank these genes on the basis of their functional interactions. By following up the top five genes per artificial locus, we were able to detect at least one known disease gene in 54% of the loci studied, representing a 2.8-fold increase over random selection. This suggests that our method can significantly reduce the cost and effort of pinpointing true disease genes in analyses of disorders for which numerous loci have been reported but for which

  5. Identification of hypoxia-responsive genes in a dopaminergic cell line by subtractive cDNA libraries and microarray analysis.

    PubMed

    Beitner-Johnson, D; Seta, K; Yuan, Y; Kim, H -W.; Rust, R T.; Conrad, P W.; Kobayashi, S; Millhorn, D E.

    2001-07-01

    Transplantation of dopamine-secreting cells harvested from fetal mesencephalon directly into the striatum has had limited success as a therapy for Parkinson's disease. A major problem is that the majority of the cells die during the first 3 weeks following transplantation. Hypoxia in the tissue surrounding the graft is a potential cause of the cell death. We have used subtractive cDNA libraries and microarray analysis to identify the gene expression profile that regulates tolerance to hypoxia. An improved understanding of the molecular basis of hypoxia-tolerance may allow investigators to engineer cells that can survive in the hypoxic environment of the brain parenchyma following transplantation. PMID:11331199

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

    PubMed Central

    Barat, Ana; Ruskin, Heather J.; Byrne, Annette T.; Prehn, Jochen H. M.

    2015-01-01

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

  7. Saliva Microbiota Carry Caries-Specific Functional Gene Signatures

    PubMed Central

    Chang, Xingzhi; Yuan, Xiao; Tu, Qichao; Yuan, Tong; Deng, Ye; Hemme, Christopher L.; Van Nostrand, Joy; Cui, Xinping; He, Zhili; Chen, Zhenggang; Guo, Dawei; Yu, Jiangbo; Zhang, Yue; Zhou, Jizhong; Xu, Jian

    2014-01-01

    Human saliva microbiota is phylogenetically divergent among host individuals yet their roles in health and disease are poorly appreciated. We employed a microbial functional gene microarray, HuMiChip 1.0, to reconstruct the global functional profiles of human saliva microbiota from ten healthy and ten caries-active adults. Saliva microbiota in the pilot population featured a vast diversity of functional genes. No significant distinction in gene number or diversity indices was observed between healthy and caries-active microbiota. However, co-presence network analysis of functional genes revealed that caries-active microbiota was more divergent in non-core genes than healthy microbiota, despite both groups exhibited a similar degree of conservation at their respective core genes. Furthermore, functional gene structure of saliva microbiota could potentially distinguish caries-active patients from healthy hosts. Microbial functions such as Diaminopimelate epimerase, Prephenate dehydrogenase, Pyruvate-formate lyase and N-acetylmuramoyl-L-alanine amidase were significantly linked to caries. Therefore, saliva microbiota carried disease-associated functional signatures, which could be potentially exploited for caries diagnosis. PMID:24533043

  8. Classification of Non-Small Cell Lung Cancer Using Significance Analysis of Microarray-Gene Set Reduction Algorithm

    PubMed Central

    Zhang, Lei; Wang, Linlin; Du, Bochuan; Wang, Tianjiao; Tian, Pu

    2016-01-01

    Among non-small cell lung cancer (NSCLC), adenocarcinoma (AC), and squamous cell carcinoma (SCC) are two major histology subtypes, accounting for roughly 40% and 30% of all lung cancer cases, respectively. Since AC and SCC differ in their cell of origin, location within the lung, and growth pattern, they are considered as distinct diseases. Gene expression signatures have been demonstrated to be an effective tool for distinguishing AC and SCC. Gene set analysis is regarded as irrelevant to the identification of gene expression signatures. Nevertheless, we found that one specific gene set analysis method, significance analysis of microarray-gene set reduction (SAMGSR), can be adopted directly to select relevant features and to construct gene expression signatures. In this study, we applied SAMGSR to a NSCLC gene expression dataset. When compared with several novel feature selection algorithms, for example, LASSO, SAMGSR has equivalent or better performance in terms of predictive ability and model parsimony. Therefore, SAMGSR is a feature selection algorithm, indeed. Additionally, we applied SAMGSR to AC and SCC subtypes separately to discriminate their respective stages, that is, stage II versus stage I. Few overlaps between these two resulting gene signatures illustrate that AC and SCC are technically distinct diseases. Therefore, stratified analyses on subtypes are recommended when diagnostic or prognostic signatures of these two NSCLC subtypes are constructed. PMID:27446945

  9. Global gene expression of a murein (Braun) lipoprotein mutant of Salmonella enterica serovar Typhimurium by microarray analysis.

    PubMed

    Fadl, A A; Galindo, C L; Sha, J; Klimpel, G R; Popov, V L; Chopra, A K

    2006-06-01

    Braun/murein lipoprotein (Lpp) is one of the major outer membrane components of gram-negative enteric bacteria involved in inflammatory responses and septic shock. In previous studies, we reported that two copies of the lipoprotein (lpp) gene (designated as lppA and lppB) existed on the chromosome of Salmonella enterica serovar Typhimurium. Deletion of both lppA and lppB genes rendered Salmonella defective in invasion, motility, induction of cytotoxicity, and production of inflammatory cytokines/chemokines. The lppAB double-knockout (DKO) mutant was attenuated in mice, and animals immunized with this mutant were protected against subsequent challenge with lethal doses of wild-type (wt) S. Typhimurium. To better understand how deletion of the lpp gene might affect Salmonella virulence, we performed global transcriptional profiling of the genes in the wt and the lppAB DKO mutant of S. Typhimurium using microarrays. Our data revealed alterations in the expression of flagellar genes, invasion-associated type III secretion system genes, and transcriptional virulence gene regulators in the lppAB DKO mutant compared to wt S. Typhimurium. These data correlated with the lppAB DKO mutant phenotype and provided possible mechanism(s) of Lpp-associated attenuation in S. Typhimurium. Although these studies were performed in in vitro grown bacteria, our future research will be targeted at global transcriptional profiling of the genes in in vivo grown wt S. Typhimurium and its Lpp mutant.

  10. Classification of Non-Small Cell Lung Cancer Using Significance Analysis of Microarray-Gene Set Reduction Algorithm.

    PubMed

    Zhang, Lei; Wang, Linlin; Du, Bochuan; Wang, Tianjiao; Tian, Pu; Tian, Suyan

    2016-01-01

    Among non-small cell lung cancer (NSCLC), adenocarcinoma (AC), and squamous cell carcinoma (SCC) are two major histology subtypes, accounting for roughly 40% and 30% of all lung cancer cases, respectively. Since AC and SCC differ in their cell of origin, location within the lung, and growth pattern, they are considered as distinct diseases. Gene expression signatures have been demonstrated to be an effective tool for distinguishing AC and SCC. Gene set analysis is regarded as irrelevant to the identification of gene expression signatures. Nevertheless, we found that one specific gene set analysis method, significance analysis of microarray-gene set reduction (SAMGSR), can be adopted directly to select relevant features and to construct gene expression signatures. In this study, we applied SAMGSR to a NSCLC gene expression dataset. When compared with several novel feature selection algorithms, for example, LASSO, SAMGSR has equivalent or better performance in terms of predictive ability and model parsimony. Therefore, SAMGSR is a feature selection algorithm, indeed. Additionally, we applied SAMGSR to AC and SCC subtypes separately to discriminate their respective stages, that is, stage II versus stage I. Few overlaps between these two resulting gene signatures illustrate that AC and SCC are technically distinct diseases. Therefore, stratified analyses on subtypes are recommended when diagnostic or prognostic signatures of these two NSCLC subtypes are constructed. PMID:27446945

  11. Azide-Reactive Liposome for Chemoselective and Biocompatible Liposomal Surface Functionalization and Glyco-Liposomal Microarray Fabrication

    PubMed Central

    Ma, Yong; Zhang, Hailong; Gruzdys, Valentinas; Sun, Xue-Long

    2011-01-01

    A chemically selective liposomal surface functionalization and liposomal microarray fabrication using azide-reactive liposome are described. First, liposome carrying PEG-triphenylphosphine was prepared for Staudinger ligation with azide-containing biotin, which was conducted in PBS buffer (pH 7.4) at room temperature without catalyst. Then, immobilization and microarray fabrication of the biotinylated liposome onto streptavidin-modified glass slide via specific streptavidin/biotin interaction were investigated by comparing with direct-formed biotin-liposome, which was prepared by conventional liposome formulation of lipid-biotin with all other lipid components. Next, covalent microarray fabrication of liposome carrying triphenylphosphine onto an azide-modified glass slide and its further glyco-modification with azide-containing carbohydrate were demonstrated for glyco-liposomal microarray fabrication via Staudinger ligation. Fluorescence imaging confirmed the successful immobilization and protein binding of the intact immobilized liposomes and arrayed glyco-liposomes. The azide-reactive liposome provides a facile strategy for a membrane-mimetic glycoarray fabrication, which may find important biological and biomedical applications such as studying carbohydrate-protein interaction and toxin and antibody screening. PMID:21928859

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

    PubMed Central

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

    2016-01-01

    Ethylene is commonly used as a latex stimulant of Hevea brasiliensis by application of ethephon (chloro-2-ethylphosphonic acid); however, the molecular mechanism by which ethylene increases latex production is not clear. To better understand the effects of ethylene stimulation on the laticiferous cells of rubber trees, a latex expressed sequence tag (EST)-based complementary DNA microarray containing 2,973 unique genes (probes) was first developed and used to analyze the gene expression changes in the latex of the mature virgin rubber trees after ethephon treatment at three different time-points: 8, 24 and 48 h. Transcript levels of 163 genes were significantly altered with fold-change values ≥ 2 or ≤ –2 (q-value < 0.05) in ethephon-treated rubber trees compared with control trees. Of the 163 genes, 92 were up-regulated and 71 down-regulated. The microarray results were further confirmed using real-time quantitative reverse transcript-PCR for 20 selected genes. The 163 ethylene-responsive genes were involved in several biological processes including organic substance metabolism, cellular metabolism, primary metabolism, biosynthetic process, cellular response to stimulus and stress. The presented data suggest that the laticifer water circulation, production and scavenging of reactive oxygen species, sugar metabolism, and assembly and depolymerization of the latex actin cytoskeleton might play important roles in ethylene-induced increase of latex production. The results may provide useful insights into understanding the molecular mechanism underlying the effect of ethylene on latex metabolism of H. brasiliensis. PMID:26985821

  13. Folic Acid supplementary reduce the incidence of adenocarcinoma in a mouse model of colorectal cancer: microarray gene expression profile

    PubMed Central

    2011-01-01

    Background Whether Folic acid is a potential drug that may prevent the progression of colorectal carcinoma and when to use are important healthy issues we focus on. Our study is to examine the effect of folic acid on the development of the CRC and the optimal time folic acid should be provided in a mouse-ICR model induced by 1, 2-Dimethylhydrazine. Also, we investigated the gene expression profile of this model related to folic acid. Method Female ICR mouse (n = 130) were divided into 7 groups either with the treatment of 1, 2-Dimethylhydrazine (20 mg/kg bodyweight) weekly or folic acid (8 mg/kg bodyweight) twice a week for 12 or 24 weeks. Using a 4 × 44 K Agilent whole genome oligo microarray assay, different gene expression among groups (NS, DMH, FA2, FA3) were identified and selected genes were validated by real-time polymerase chain reaction. Results Animals with a supplementary of folic acid showed a significant decrease in the incidence, the maximum diameter and multiplicity of adenocarcinomas (P < 0.05). Furthermore, there were fewer adenomas or adenocarcinomas developed in the group of folic acid supplementation in pre-adenoma stage compared to group of post-adenoma stage. Meanwhile, about 1070 genes that were changed by 1, 2-Dimethylhydrazine can be reversed by folic acid and 172 differentially genes were identified between the groups of pre- and post- adenoma stage using microarray gene expression analysis. Conclusion Our study demonstrated that folic acid supplementary was significantly associated with the decrease risk of CRC. And the subgroup of providing folic acid without precancerous lesions was more effective than that with precancerous lesions. PMID:22206623

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

    PubMed Central

    Parodi, Stefano; Pistoia, Vito; Muselli, Marco

    2008-01-01

    Background Most microarray experiments are carried out with the purpose of identifying genes whose expression varies in relation with specific conditions or in response to environmental stimuli. In such studies, genes showing similar mean expression values between two or more groups are considered as not differentially expressed, even if hidden subclasses with different expression values may exist. In this paper we propose a new method for identifying differentially expressed genes, based on the area between the ROC curve and the rising diagonal (ABCR). ABCR represents a more general approach than the standard area under the ROC curve (AUC), because it can identify both proper (i.e., concave) and not proper ROC curves (NPRC). In particular, NPRC may correspond to those genes that tend to escape standard selection methods. Results We assessed the performance of our method using data from a publicly available database of 4026 genes, including 14 normal B cell samples (NBC) and 20 heterogeneous lymphomas (namely: 9 follicular lymphomas and 11 chronic lymphocytic leukemias). Moreover, NBC also included two sub-classes, i.e., 6 heavily stimulated and 8 slightly or not stimulated samples. We identified 1607 differentially expressed genes with an estimated False Discovery Rate of 15%. Among them, 16 corresponded to NPRC and all escaped standard selection procedures based on AUC and t statistics. Moreover, a simple inspection to the shape of such plots allowed to identify the two subclasses in either one class in 13 cases (81%). Conclusion NPRC represent a new useful tool for the analysis of microarray data. PMID:18834513

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

    PubMed

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

    2016-01-01

    Ethylene is commonly used as a latex stimulant of Hevea brasiliensis by application of ethephon (chloro-2-ethylphosphonic acid); however, the molecular mechanism by which ethylene increases latex production is not clear. To better understand the effects of ethylene stimulation on the laticiferous cells of rubber trees, a latex expressed sequence tag (EST)-based complementary DNA microarray containing 2,973 unique genes (probes) was first developed and used to analyze the gene expression changes in the latex of the mature virgin rubber trees after ethephon treatment at three different time-points: 8, 24 and 48 h. Transcript levels of 163 genes were significantly altered with fold-change values ≥ 2 or ≤ -2 (q-value < 0.05) in ethephon-treated rubber trees compared with control trees. Of the 163 genes, 92 were up-regulated and 71 down-regulated. The microarray results were further confirmed using real-time quantitative reverse transcript-PCR for 20 selected genes. The 163 ethylene-responsive genes were involved in several biological processes including organic substance metabolism, cellular metabolism, primary metabolism, biosynthetic process, cellular response to stimulus and stress. The presented data suggest that the laticifer water circulation, production and scavenging of reactive oxygen species, sugar metabolism, and assembly and depolymerization of the latex actin cytoskeleton might play important roles in ethylene-induced increase of latex production. The results may provide useful insights into understanding the molecular mechanism underlying the effect of ethylene on latex metabolism of H. brasiliensis. PMID:26985821

  16. The Microarray Gene Profiling Analysis of Glioblastoma Cancer Cells Reveals Genes Affected by FAK Inhibitor Y15 and Combination of Y15 and Temozolomide

    PubMed Central

    Huang, Grace; Ho, Baotran; Conroy, Jeffrey; Liu, Song; Qiang, Hu; Golubovskaya, Vita

    2013-01-01

    Focal adhesion is known to be highly expressed and activated in glioma cells. Recently, we demonstrated that FAK autophosphorylation inhibitor, Y15 significantly decreased tumor growth of DBTRG and U87 cells, especially in combination with temozolomide. In the present report, we performed gene expression analysis in these cells to reveal genes affected by Y15, temozolomide and combination of Y15 and temozolomide. We tested the effect of Y15 on gene expression by Illumina Human HT12v4 microarray assay and detected 8087 and 6555 genes, which were significantly either up- or down-regulated by Y15-treatment in DBTRG and U87 cells, respectively (p<0.05). Moreover, DBTRG and U87 cells treated with Y15 changed expression of 1332 and 462 genes more than 1.5 fold, p<0.05, respectively and had 237 common genes affected by Y15. The common genes up-regulated by Y15 included GADD45A, HSPA6 (heat-shock 70); DUSP1, DUSP 5 (dual-phosphatase 5); CDKN1A (p21) and common down-regulated genes included kinesins, such as KIF11, 14, 20A, 20B; topoisomerase II, TOP2A; cyclin F; cell cycle protein: BUB1; PARP1, POLA1. In addition, we detected genes affected by temozolomide and by combination of Y15 and temozolomide treatment in U87 cells. Among genes up-regulated by Y15 and temozolomide more significantly than by each agent alone were: COX7B; interferon, gamma-inducible transcript: IFI16; DDIT4; GADD45G and down-regulated: KIF3A, AKT1; ABL; JAK1, GLI3 and ALDH1A3. Thus, microarray gene expression analysis can be effective in establishing genes affected in response to FAK inhibitor alone and in response to combination of Y15 with temozolomide that is important for glioblastoma therapy. PMID:23387973

  17. A microarray-based comparative analysis of gene expression profiles during grain development in transgenic and wild type wheat.

    PubMed

    Gregersen, Per L; Brinch-Pedersen, Henrik; Holm, Preben B

    2005-12-01

    Global, comparative gene expression analysis is potentially a very powerful tool in the safety assessment of transgenic plants since it allows for the detection of differences in gene expression patterns between a transgenic line and the mother variety. In the present study, we compared the gene expression profile in developing seeds of wild type wheat and wheat transformed for endosperm-specific expression of an Aspergillus fumigatus phytase. High-level expression of the phytase gene was ensured by codon modification towards the prevalent codon usage of wheat genes and by using the wheat 1DX5HMW glutenin promoter for driving transgene expression. A 9K wheat unigene cDNA microarray was produced from cDNA libraries prepared mainly from developing wheat seed. The arrays were hybridised to flourescently labelled cDNA prepared from developing seeds of the transgenic wheat line and the mother variety, Bobwhite, at three developmental stages. Comparisons and statistical analyses of the gene expression profiles of the transgenic line vs. that of the mother line revealed only slight differences at the three developmental stages. In the few cases where differential expression was indicated by the statistical analysis it was primarily genes that were strongly expressed over a shorter interval of seed development such as genes encoding storage proteins. Accordingly, we interpret these differences in gene expression levels to result from minor asynchrony in seed development between the transgenic line and the mother line. In support of this, real time PCR validation of results from selected genes at the late developmental stage could not confirm differential expression of these genes. We conclude that the expression of the codon-modified A. fumigatus phytase gene in the wheat seed had no significant effects on the overall gene expression patterns in the developing seed.

  18. Using a customized DNA microarray for expression profiling of the estrogen-responsive genes to evaluate estrogen activity among natural estrogens and industrial chemicals.

    PubMed Central

    Terasaka, Shunichi; Aita, Yukie; Inoue, Akio; Hayashi, Shinichi; Nishigaki, Michiko; Aoyagi, Kazuhiko; Sasaki, Hiroki; Wada-Kiyama, Yuko; Sakuma, Yasuo; Akaba, Shuichi; Tanaka, Junko; Sone, Hideko; Yonemoto, Junzo; Tanji, Masao; Kiyama, Ryoiti

    2004-01-01

    We developed a DNA microarray to evaluate the estrogen activity of natural estrogens and industrial chemicals. Using MCF-7 cells, we conducted a comprehensive analysis of estrogen-responsive genes among approximately 20,000 human genes. On the basis of reproducible and reliable responses of the genes to estrogen, we selected 172 genes to be used for developing a customized DNA microarray. Using this DNA microarray, we examined estrogen activity among natural estrogens (17beta-estradiol, estriol, estrone, genistein), industrial chemicals (diethylstilbestrol, bisphenol A, nonylphenol, methoxychlor), and dioxin. We obtained results identical to those for other bioassays that are used for detecting estrogen activity. On the basis of statistical correlations analysis, these bioassays have shown more sensitivity for dioxin and methoxychlor. PMID:15159206

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

    PubMed Central

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

    2013-01-01

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

  20. Effects of curcumin on global gene expression profiles in the highly invasive human breast carcinoma cell line MDA-MB 231: A gene network-based microarray analysis.

    PubMed

    Cine, Naci; Limtrakul, Pornngarm; Sunnetci, Deniz; Nagy, Balint; Savli, Hakan

    2013-01-01

    Curcumin, or diferuloylmethane, is a major chemical component of turmeric (Curcuma longa Linn.) that has been consumed as a dietary spice through the ages. This yellow-colored polyphenol has a notably wide range of beneficial properties, including anti-inflammatory, antioxidant, antitumoral, anti-invasive and anti-metastatic activity. In the present study, microarray gene expression analysis was applied to identify the curcumin-regulated genes in a highly invasive human breast carcinoma cell line (MDA-MB 231). Cells were cultured with curcumin (20 μM) for 24 h; total RNA was isolated and hybridized to Whole Human Genome Microarray slides. Gene set enrichment analyses on our whole genome expression data revealed downregulation of the EGF pathway elements following curcumin treatment. Furthermore, gene network analysis identified a significantly relevant network among the differentially expressed genes, centered on the EGR1 and FOS genes. The members of these pathways and networks play an essential role in the regulation of cancer cell growth and development; the majority exhibited decreased expression levels following treatment with curcumin. These observations suggest that curcumin is an excellent candidate for the prevention and treatment of breast cancer. PMID:23251236

  1. The use of microarrays in microbial ecology

    SciTech Connect

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

    2009-09-15

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

  2. A novel universal DNA labeling and amplification system for rapid microarray-based detection of 117 antibiotic resistance genes in Gram-positive bacteria.

    PubMed

    Strauss, Christian; Endimiani, Andrea; Perreten, Vincent

    2015-01-01

    A rapid and simple DNA labeling system has been developed for disposable microarrays and has been validated for the detection of 117 antibiotic resistance genes abundant in Gram-positive bacteria. The DNA was fragmented and amplified using phi-29 polymerase and random primers with linkers. Labeling and further amplification were then performed by classic PCR amplification using biotinylated primers specific for the linkers. The microarray developed by Perreten et al. (Perreten, V., Vorlet-Fawer, L., Slickers, P., Ehricht, R., Kuhnert, P., Frey, J., 2005. Microarray-based detection of 90 antibiotic resistance genes of gram-positive bacteria. J.Clin.Microbiol. 43, 2291-2302.) was improved by additional oligonucleotides. A total of 244 oligonucleotides (26 to 37 nucleotide length and with similar melting temperatures) were spotted on the microarray, including genes conferring resistance to clinically important antibiotic classes like β-lactams, macrolides, aminoglycosides, glycopeptides and tetracyclines. Each antibiotic resistance gene is represented by at least 2 oligonucleotides designed from consensus sequences of gene families. The specificity of the oligonucleotides and the quality of the amplification and labeling were verified by analysis of a collection of 65 strains belonging to 24 species. Association between genotype and phenotype was verified for 6 antibiotics using 77 Staphylococcus strains belonging to different species and revealed 95% test specificity and a 93% predictive value of a positive test. The DNA labeling and amplification is independent of the species and of the target genes and could be used for different types of microarrays. This system has also the advantage to detect several genes within one bacterium at once, like in Staphylococcus aureus strain BM3318, in which up to 15 genes were detected. This new microarray-based detection system offers a large potential for applications in clinical diagnostic, basic research, food safety and

  3. Identification of Genes Associated With Progression and Metastasis of Advanced Cervical Cancers After Radiotherapy by cDNA Microarray Analysis

    SciTech Connect

    Harima, Yoko; Ikeda, Koshi; Utsunomiya, Keita; Shiga, Toshiko; Komemushi, Atsushi; Kojima, Hiroyuki; Nomura, Motoo; Kamata, Minoru; Sawada, Satoshi

    2009-11-15

    Purpose: To identify a set of genes related to the progression and metastasis of advanced cervical cancer after radiotherapy and to establish a predictive method. Methods and Materials: A total of 28 patients with cervical cancer (15 stage IIIB, 13 stage IVA patients) who underwent definitive radiotherapy between May 1995 and April 2001 were included in this study. All patients were positive for human papillomavirus infection and harbored the wild-type p53 gene. The expression profiles of 14 tumors with local failure and multiple distant metastasis and 14 tumors without metastasis (cancer free) obtained by punch biopsy were compared before treatment, using a cDNA microarray consisting of 23,040 human genes. Results: Sixty-three genes were selected on the basis of a clustering analysis, and the validity of these genes was confirmed using a cross-validation test. The most accurate prediction was achieved for 63 genes (sensitivity, 78.8%; specificity, 38.1%). Some of these genes were already known to be associated with metastasis via chromosomal instability (TTK, BUB1B), extracellular matrix components (matrix metalloproteinase 1 [MMP-1]), and carcinogenesis (protein phosphatase 1 regulatory subunit 7 [PPP1R7]). A 'predictive score' system was developed that could predict the probability for development of metastases using leave-one-out cross-validation methods. Conclusions: The present results may provide valuable information for identified predictive markers and novel therapeutic target molecules for progression and metastasis of advanced cervical cancer.

  4. Removing Batch Effects from Longitudinal Gene Expression - Quantile Normalization Plus ComBat as Best Approach for Microarray Transcriptome Data.

    PubMed

    Müller, Christian; Schillert, Arne; Röthemeier, Caroline; Trégouët, David-Alexandre; Proust, Carole; Binder, Harald; Pfeiffer, Norbert; Beutel, Manfred; Lackner, Karl J; Schnabel, Renate B; Tiret, Laurence; Wild, Philipp S; Blankenberg, Stefan; Zeller, Tanja; Ziegler, Andreas

    2016-01-01

    Technical variation plays an important role in microarray-based gene expression studies, and batch effects explain a large proportion of this noise. It is therefore mandatory to eliminate technical variation while maintaining biological variability. Several strategies have been proposed for the removal of batch effects, although they have not been evaluated in large-scale longitudinal gene expression data. In this study, we aimed at identifying a suitable method for batch effect removal in a large study of microarray-based longitudinal gene expression. Monocytic gene expression was measured in 1092 participants of the Gutenberg Health Study at baseline and 5-year follow up. Replicates of selected samples were measured at both time points to identify technical variability. Deming regression, Passing-Bablok regression, linear mixed models, non-linear models as well as ReplicateRUV and ComBat were applied to eliminate batch effects between replicates. In a second step, quantile normalization prior to batch effect correction was performed for each method. Technical variation between batches was evaluated by principal component analysis. Associations between body mass index and transcriptomes were calculated before and after batch removal. Results from association analyses were compared to evaluate maintenance of biological variability. Quantile normalization, separately performed in each batch, combined with ComBat successfully reduced batch effects and maintained biological variability. ReplicateRUV performed perfectly in the replicate data subset of the study, but failed when applied to all samples. All other methods did not substantially reduce batch effects in the replicate data subset. Quantile normalization plus ComBat appears to be a valuable approach for batch correction in longitudinal gene expression data.

  5. Removing Batch Effects from Longitudinal Gene Expression - Quantile Normalization Plus ComBat as Best Approach for Microarray Transcriptome Data.

    PubMed

    Müller, Christian; Schillert, Arne; Röthemeier, Caroline; Trégouët, David-Alexandre; Proust, Carole; Binder, Harald; Pfeiffer, Norbert; Beutel, Manfred; Lackner, Karl J; Schnabel, Renate B; Tiret, Laurence; Wild, Philipp S; Blankenberg, Stefan; Zeller, Tanja; Ziegler, Andreas

    2016-01-01

    Technical variation plays an important role in microarray-based gene expression studies, and batch effects explain a large proportion of this noise. It is therefore mandatory to eliminate technical variation while maintaining biological variability. Several strategies have been proposed for the removal of batch effects, although they have not been evaluated in large-scale longitudinal gene expression data. In this study, we aimed at identifying a suitable method for batch effect removal in a large study of microarray-based longitudinal gene expression. Monocytic gene expression was measured in 1092 participants of the Gutenberg Health Study at baseline and 5-year follow up. Replicates of selected samples were measured at both time points to identify technical variability. Deming regression, Passing-Bablok regression, linear mixed models, non-linear models as well as ReplicateRUV and ComBat were applied to eliminate batch effects between replicates. In a second step, quantile normalization prior to batch effect correction was performed for each method. Technical variation between batches was evaluated by principal component analysis. Associations between body mass index and transcriptomes were calculated before and after batch removal. Results from association analyses were compared to evaluate maintenance of biological variability. Quantile normalization, separately performed in each batch, combined with ComBat successfully reduced batch effects and maintained biological variability. ReplicateRUV performed perfectly in the replicate data subset of the study, but failed when applied to all samples. All other methods did not substantially reduce batch effects in the replicate data subset. Quantile normalization plus ComBat appears to be a valuable approach for batch correction in longitudinal gene expression data. PMID:27272489

  6. Removing Batch Effects from Longitudinal Gene Expression - Quantile Normalization Plus ComBat as Best Approach for Microarray Transcriptome Data

    PubMed Central

    Müller, Christian; Schillert, Arne; Röthemeier, Caroline; Trégouët, David-Alexandre; Proust, Carole; Binder, Harald; Pfeiffer, Norbert; Beutel, Manfred; Lackner, Karl J.; Schnabel, Renate B.; Tiret, Laurence; Wild, Philipp S.; Blankenberg, Stefan

    2016-01-01

    Technical variation plays an important role in microarray-based gene expression studies, and batch effects explain a large proportion of this noise. It is therefore mandatory to eliminate technical variation while maintaining biological variability. Several strategies have been proposed for the removal of batch effects, although they have not been evaluated in large-scale longitudinal gene expression data. In this study, we aimed at identifying a suitable method for batch effect removal in a large study of microarray-based longitudinal gene expression. Monocytic gene expression was measured in 1092 participants of the Gutenberg Health Study at baseline and 5-year follow up. Replicates of selected samples were measured at both time points to identify technical variability. Deming regression, Passing-Bablok regression, linear mixed models, non-linear models as well as ReplicateRUV and ComBat were applied to eliminate batch effects between replicates. In a second step, quantile normalization prior to batch effect correction was performed for each method. Technical variation between batches was evaluated by principal component analysis. Associations between body mass index and transcriptomes were calculated before and after batch removal. Results from association analyses were compared to evaluate maintenance of biological variability. Quantile normalization, separately performed in each batch, combined with ComBat successfully reduced batch effects and maintained biological variability. ReplicateRUV performed perfectly in the replicate data subset of the study, but failed when applied to all samples. All other methods did not substantially reduce batch effects in the replicate data subset. Quantile normalization plus ComBat appears to be a valuable approach for batch correction in longitudinal gene expression data. PMID:27272489

  7. Investigation of genetic diversity of the bla(SHV) gene and development of an oligonucleotide microarray to detect mutations in the bla(SHV) gene.

    PubMed

    Dong, Yuanyuan; Sheng, Haihui; Zeng, Xainting; Yan, Jufen; Li, Haiyan; Xiao, Huasheng; Li, Xiaokun; Yang, Shulin

    2012-12-01

    SHV β-lactamases, including SHV extended-spectrum β-lactamases, are widespread throughout the world, and confer a broad spectrum of resistance to antibiotic drugs. Mutations ranging from single base-pair substitutions to small deletions within bla(SHV) often result in diminished activity and an increased susceptibility to β-lactamase inhibitors. Here, we collected 1,320 clinical isolates from three hospitals in Shanghai. We developed a novel oligonucleotide microarray to detect mutations in the bla(SHV) gene, and validated the array data by direct sequencing. Sixty-two of the 1,320 isolates carried the bla(SHV) gene. The genotypes of these 62 isolates were successfully called by the microarray and were consistent with the genotypes identified by bidirectional sequencing. Sixteen different bla(SHV) alleles were identified. The SHV-1 variant was the most frequent (32.26%), followed by SHV-11 (27.42%) and SHV-12 (25.81%). Of the 62 isolates, 12 contained two different bla(SHV) alleles. Our microarray significantly facilitated the identification of bla(SHV) variants, which makes it an attractive option for the detection of SHV variants in clinical laboratories. PMID:22897109

  8. T Cell Dynamic Activation and Functional Analysis in Nanoliter Droplet Microarray

    PubMed Central

    Sarkar, Saheli; Motwani, Vinny; Sabhachandani, Pooja; Cohen, Noa; Konry, Tania

    2015-01-01

    Objective Characterization of the heterogeneity in immune reactions requires assessing dynamic single cell responses as well as interactions between the various immune cell subsets. Maturation and activation of effector cells is regulated by cell contact-dependent and soluble factor-mediated paracrine signalling. Currently there are few methods available that allow dynamic investigation of both processes simultaneously without physically constraining non-adherent cells and eliminating crosstalk from neighboring cell pairs. We describe here a microfluidic droplet microarray platform that permits rapid functional analysis of single cell responses and co-encapsulation of heterotypic cell pairs, thereby allowing us to evaluate the dynamic activation state of primary T cells. Methods The microfluidic droplet platform enables generation and docking of monodisperse nanoliter volume (0.523 nl) droplets, with the capacity of monitoring a thousand droplets per experiment. Single human T cells were encapsulated in droplets and stimulated on-chip with the calcium ionophore ionomycin. T cells were also co-encapsulated with dendritic cells activated by ovalbumin peptide, followed by dynamic calcium signal monitoring. Results Ionomycin-stimulated cells depicted fluctuation in calcium signalling compared to control. Both cell populations demonstrated marked heterogeneity in responses. Calcium signalling was observed in T cells immediately following contact with DCs, suggesting an early activation signal. T cells further showed non-contact mediated increase in calcium level, although this response was delayed compared to contact-mediated signals. Conclusions Our results suggest that this nanoliter droplet array-based microfluidic platform is a promising technique for assessment of heterogeneity in various types of cellular responses, detection of early/delayed signalling events and live cell phenotyping of immune cells. PMID:26613065

  9. Prenatal alcohol exposure alters gene expression in the rat brain: Experimental design and bioinformatic analysis of microarray data.

    PubMed

    Lussier, Alexandre A; Stepien, Katarzyna A; Weinberg, Joanne; Kobor, Michael S

    2015-09-01

    We previously identified gene expression changes in the prefrontal cortex and hippocampus of rats prenatally exposed to alcohol under both steady-state and challenge conditions (Lussier et al., 2015, Alcohol.: Clin. Exp. Res., 39, 251-261). In this study, adult female rats from three prenatal treatment groups (ad libitum-fed control, pair-fed, and ethanol-fed) were injected with physiological saline solution or complete Freund׳s adjuvant (CFA) to induce arthritis (adjuvant-induced arthritis, AA). The prefrontal cortex and hippocampus were collected 16 days (peak of arthritis) or 39 days (during recovery) following injection, and whole genome gene expression was assayed using Illumina׳s RatRef-12 expression microarray. Here, we provide additional metadata, detailed explanations of data pre-processing steps and quality control, as well as a basic framework for the bioinformatic analyses performed. The datasets from this study are publicly available on the GEO repository (accession number GSE63561). PMID:26217797

  10. Prenatal alcohol exposure alters gene expression in the rat brain: Experimental design and bioinformatic analysis of microarray data

    PubMed Central

    Lussier, Alexandre A.; Stepien, Katarzyna A.; Weinberg, Joanne; Kobor, Michael S.

    2015-01-01

    We previously identified gene expression changes in the prefrontal cortex and hippocampus of rats prenatally exposed to alcohol under both steady-state and challenge conditions (Lussier et al., 2015, Alcohol.: Clin. Exp. Res., 39, 251–261). In this study, adult female rats from three prenatal treatment groups (ad libitum-fed control, pair-fed, and ethanol-fed) were injected with physiological saline solution or complete Freund׳s adjuvant (CFA) to induce arthritis (adjuvant-induced arthritis, AA). The prefrontal cortex and hippocampus were collected 16 days (peak of arthritis) or 39 days (during recovery) following injection, and whole genome gene expression was assayed using Illumina׳s RatRef-12 expression microarray. Here, we provide additional metadata, detailed explanations of data pre-processing steps and quality control, as well as a basic framework for the bioinformatic analyses performed. The datasets from this study are publicly available on the GEO repository (accession number GSE63561). PMID:26217797

  11. Microarray analysis of lexA gene deletion mutant of deep-sea bacterium Shewanella piezotolerans WP3 at low-temperature and high-pressure

    PubMed Central

    Jian, Huahua; Wang, Fengping

    2015-01-01

    Addressing DNA lesion, the SOS response is conserved in bacterial domain and governed by DNA binding protein LexA, which have been well characterized in model microorganism such as Escherichia coli. However, our understanding of the roles of SOS pathway in deep-sea bacteria is limited. To indentify the composition of SOS regulon and function of LexA, we performed whole genome transcriptional profiling using a custom designed microarray which contains 95% open reading frames of Shewanella piezotolerans WP3. Here we describe the experimental procedures and methods in detail to reproduce the results (available at Gene Expression Omnibus database under GSE66790) and provide resource to be employed for comparative analyses of SOS response in microorganisms which inhabited in different environments, and thus broaden our understanding of life strategy of bacteria against various environment stresses. PMID:26484197

  12. Laser microdissection and microarray analysis of the hippocampus of Ras-GRF1 knockout mice reveals gene expression changes affecting signal transduction pathways related to memory and learning.

    PubMed

    Fernández-Medarde, A; Porteros, A; de las Rivas, J; Núñez, A; Fuster, J J; Santos, E

    2007-04-25

    We used manual macrodissection or laser capture microdissection (LCM) to isolate tissue sections of the hippocampus area of Ras-GRF1 wild type and knockout mice brains, and analyzed their transcriptional patterns using commercial oligonucleotide microarrays. Comparison between the transcriptomes of macrodissected and microdissected samples showed that the LCM samples allowed detection of significantly higher numbers of differentially expressed genes, with higher statistical rates of significance. These results validate LCM as a reliable technique for in vivo genomic studies in the brain hippocampus, where contamination by surrounding areas (not expressing Ras-GRF1) increases background noise and impairs identification of differentially expressed genes. Comparison between wild type and knockout LCM hippocampus samples revealed that Ras-GRF1 elimination caused significant gene expression changes, mostly affecting signal transduction and related neural processes. The list of 36 most differentially expressed genes included loci concerned mainly with Ras/G protein signaling and cytoskeletal organization (i.e. 14-3-3gamma/zeta, Kcnj6, Clasp2) or related, cross-talking pathways (i.e. jag2, decorin, strap). Consistent with the phenotypes shown by Ras-GRF1 knockout mice, many of these differentially expressed genes play functional roles in processes such as sensory development and function (i.e. Sptlc1, antiquitin, jag2) and/or neurological development/neurodegeneration processes affecting memory and learning. Indeed, potential links to neurodegenerative diseases such as Alzheimer disease (AD) or Creutzfeldt-Jacobs disease (CJD), have been reported for a number of differentially expressed genes identified in this study (Ptma, Aebp2, Clasp2, Hebp1, 14-3-3gamma/zeta, Csnk1delta, etc.). These data, together with the previously described role of IRS and insulin (known Ras-GRF1 activators) in AD, warrant further investigation of a potential functional link of Ras-GRF1 to

  13. Gene expression analysis in sections and tissue microarrays of archival tissues by mRNA in situ hybridization.

    PubMed

    Henke, R T; Maitra, A; Paik, S; Wellstein, A

    2005-01-01

    Altered expression of genes in diseased tissues can prognosticate a distinct natural progression of the disease as well as predict sensitivity or resistance to particular therapies. Archival tissues from patients with a known medical history and treatments are an invaluable resource to validate the utility of candidate genes for prognosis and prediction of therapy outcomes. However, stored tissues with associated long-term follow-up information typically are formalin-fixed, paraffin-embedded specimen and this can severely restrict the methods applicable for gene expression analysis. We report here on the utility of tissue microarrays (TMAs) that use valuable tissues sparingly and provide a platform for simultaneous analysis of gene expression in several hundred samples. In particular, we describe a stable method applicable to mRNA expression screening in such archival tissues. TMAs are constructed from sections of small drill cores, taken from tissue blocks of archival tissues and multiple samples can thus be arranged on a single microscope slide. We used mRNA in situ hybridization (ISH) on >500 full sections and >100 TMAs for >10 different cDNAs that yielded >10,000 data points. We provide detailed experimental protocols that can be implemented without major hurdles in a molecular pathology laboratory and discuss quantitative analysis and the advantages and limitations of ISH. We conclude that gene expression analysis in archival tissues by ISH is reliable and particularly useful when no protein detection methods are available for a candidate gene.

  14. Identification of genes expressed in response to acid stress in Synechocystis sp. PCC 6803 using DNA microarrays.

    PubMed

    Ohta, Hisataka; Shibata, Yousuke; Haseyama, Youhei; Yoshino, Yuka; Suzuki, Takehiro; Kagasawa, Tsuyoshi; Kamei, Ayako; Ikeuchi, Masahiko; Enami, Isao

    2005-06-01

    Plant cells are always exposed to various environmental stresses such as high light, low temperature and acid rain, and thus have to respond in order to survive these stresses. Although some mechanisms of responses to high light and low temperature etc., have been clarified, there is little information about the acclimation process to acid stress. In this study, the gene expression changes of Synechocystis sp. PCC 6803 in response to acid stress were examined using DNA microarrays (CyanoCHIP). We compared gene expression profiles of the cells treated at pH 8 (control) and pH 3 for 0.5, 1, 2 or 4 h. As a result, we found that 32 genes were upregulated by more than 3-fold, and 29 genes were downregulated by at least 3-fold after the acid treatment. Among these upregulated genes, expressions of slr0967 and sll0939 kept-increasing until 4 h under the acid stress and increased by 7 to 16-fold after the 4 h treatment. This suggests that the products of these two genes play important roles in the acid acclimation process.

  15. An integrated genomic analysis of gene-function correlation on schizophrenia susceptibility genes.

    PubMed

    Chu, Tearina T; Liu, Ying

    2010-05-01

    Schizophrenia is a highly complex inheritable disease characterized by numerous genetic susceptibility elements, each contributing a modest increase in risk for the disease. Although numerous linkage or association studies have identified a large set of schizophrenia-associated loci, many are controversial. In addition, only a small portion of these loci overlaps with the large cumulative pool of genes that have shown changes of expression in schizophrenia. Here, we applied a genomic gene-function approach to identify susceptibility loci that show direct effect on gene expression, leading to functional abnormalities in schizophrenia. We carried out an integrated analysis by cross-examination of the literature-based susceptibility loci with the schizophrenia-associated expression gene list obtained from our previous microarray study (Journal of Human Genetics (2009) 54: 665-75) using bioinformatic tools, followed by confirmation of gene expression changes using qPCR. We found nine genes (CHGB, SLC18A2, SLC25A27, ESD, C4A/C4B, TCP1, CHL1 and CTNNA2) demonstrate gene-function correlation involving: synapse and neurotransmission; energy metabolism and defense mechanisms; and molecular chaperone and cytoskeleton. Our findings further support the roles of these genes in genetic influence and functional consequences on the development of schizophrenia. It is interesting to note that four of the nine genes are located on chromosome 6, suggesting a special chromosomal vulnerability in schizophrenia.

  16. Fast DNA Serotyping and Antimicrobial Resistance Gene Determination of Salmonella enterica with an Oligonucleotide Microarray-Based Assay

    PubMed Central

    Braun, Sascha D.; Ziegler, Albrecht; Methner, Ulrich; Slickers, Peter; Keiling, Silke; Monecke, Stefan; Ehricht, Ralf

    2012-01-01

    Salmonellosis caused by Salmonella (S.) belongs to the most prevalent food-borne zoonotic diseases throughout the world. Therefore, serotype identification for all culture-confirmed cases of Salmonella infection is important for epidemiological purposes. As a standard, the traditional culture method (ISO 6579:2002) is used to identify Salmonella. Classical serotyping takes 4–5 days to be completed, it is labor-intensive, expensive and more than 250 non-standardized sera are necessary to characterize more than 2,500 Salmonella serovars currently known. These technical difficulties could be overcome with modern molecular methods. We developed a microarray based serogenotyping assay for the most prevalent Salmonella serovars in Europe and North America. The current assay version could theoretically discriminate 28 O-antigens and 86 H-antigens. Additionally, we included 77 targets analyzing antimicrobial resistance genes. The Salmonella assay was evaluated with a set of 168 reference strains representing 132 serovars previously serotyped by conventional agglutination through various reference centers. 117 of 132 (81%) tested serovars showed an unique microarray pattern. 15 of 132 serovars generated a pattern which was shared by multiple serovars (e.g., S. ser. Enteritidis and S. ser. Nitra). These shared patterns mainly resulted from the high similarity of the genotypes of serogroup A and D1. Using patterns of the known reference strains, a database was build which represents the basis of a new PatternMatch software that can serotype unknown Salmonella isolates automatically. After assay verification, the Salmonella serogenotyping assay was used to identify a field panel of 105 Salmonella isolates. All were identified as Salmonella and 93 of 105 isolates (88.6%) were typed in full concordance with conventional serotyping. This microarray based assay is a powerful tool for serogenotyping. PMID:23056321

  17. Fast DNA serotyping and antimicrobial resistance gene determination of salmonella enterica with an oligonucleotide microarray-based assay.

    PubMed

    Braun, Sascha D; Ziegler, Albrecht; Methner, Ulrich; Slickers, Peter; Keiling, Silke; Monecke, Stefan; Ehricht, Ralf

    2012-01-01

    Salmonellosis caused by Salmonella (S.) belongs to the most prevalent food-borne zoonotic diseases throughout the world. Therefore, serotype identification for all culture-confirmed cases of Salmonella infection is important for epidemiological purposes. As a standard, the traditional culture method (ISO 6579:2002) is used to identify Salmonella. Classical serotyping takes 4-5 days to be completed, it is labor-intensive, expensive and more than 250 non-standardized sera are necessary to characterize more than 2,500 Salmonella serovars currently known. These technical difficulties could be overcome with modern molecular methods. We developed a microarray based serogenotyping assay for the most prevalent Salmonella serovars in Europe and North America. The current assay version could theoretically discriminate 28 O-antigens and 86 H-antigens. Additionally, we included 77 targets analyzing antimicrobial resistance genes. The Salmonella assay was evaluated with a set of 168 reference strains representing 132 serovars previously serotyped by conventional agglutination through various reference centers. 117 of 132 (81%) tested serovars showed an unique microarray pattern. 15 of 132 serovars generated a pattern which was shared by multiple serovars (e.g., S. ser. Enteritidis and S. ser. Nitra). These shared patterns mainly resulted from the high similarity of the genotypes of serogroup A and D1. Using patterns of the known reference strains, a database was build which represents the basis of a new PatternMatch software that can serotype unknown Salmonella isolates automatically. After assay verification, the Salmonella serogenotyping assay was used to identify a field panel of 105 Salmonella isolates. All were identified as Salmonella and 93 of 105 isolates (88.6%) were typed in full concordance with conventional serotyping. This microarray based assay is a powerful tool for serogenotyping. PMID:23056321

  18. Deubiquitylase, deSUMOylase, and deISGylase activity microarrays for assay of substrate preference and functional modifiers.

    PubMed

    Loch, Christian M; Cuccherini, Charles L; Leach, Craig A; Strickler, James E

    2011-01-01

    Microarray-based proteomics expanded the information potential of DNA arrays to the level of protein translation and interaction, but so far, not much beyond. Although enzymatic activity from immobilized proteins has been reliably studied using surface plasmon resonance, a microarray of catalytically competent enzymes would facilitate high throughput, parallel study of their function. The ability to localize activity from soluble substrates has frustrated development of such an array. Here, we report the novel use of previously developed, highly specific suicide substrates for three families of enzymes: deubiquitylases, deSUMOylases, and deISGylases. We show specificity of each family to its cognate substrate, and demonstrate utility of the array in a secondary screen of small molecule inhibitors.

  19. Discovery of molecular mechanisms of traditional Chinese medicinal formula Si-Wu-Tang using gene expression microarray and connectivity map.

    PubMed

    Wen, Zhining; Wang, Zhijun; Wang, Steven; Ravula, Ranadheer; Yang, Lun; Xu, Jun; Wang, Charles; Zuo, Zhong; Chow, Moses S S; Shi, Leming; Huang, Ying

    2011-03-28

    To pursue a systematic approach to discovery of mechanisms of action of traditional Chinese medicine (TCM), we used microarrays, bioinformatics and the "Connectivity Map" (CMAP) to examine TCM-induced changes in gene expression. We demonstrated that this approach can be used to elucidate new molecular targets using a model TCM herbal formula Si-Wu-Tang (SWT) which is widely used for women's health. The human breast cancer MCF-7 cells treated with 0.1 µM estradiol or 2.56 mg/ml of SWT showed dramatic gene expression changes, while no significant change was detected for ferulic acid, a known bioactive compound of SWT. Pathway analysis using differentially expressed genes related to the treatment effect identified that expression of genes in the nuclear factor erythroid 2-related factor 2 (Nrf2) cytoprotective pathway was most significantly affected by SWT, but not by estradiol or ferulic acid. The Nrf2-regulated genes HMOX1, GCLC, GCLM, SLC7A11 and NQO1 were upregulated by SWT in a dose-dependent manner, which was validated by real-time RT-PCR. Consistently, treatment with SWT and its four herbal ingredients resulted in an increased antioxidant response element (ARE)-luciferase reporter activity in MCF-7 and HEK293 cells. Furthermore, the gene expression profile of differentially expressed genes related to SWT treatment was used to compare with those of 1,309 compounds in the CMAP database. The CMAP profiles of estradiol-treated MCF-7 cells showed an excellent match with SWT treatment, consistent with SWT's widely claimed use for women's diseases and indicating a phytoestrogenic effect. The CMAP profiles of chemopreventive agents withaferin A and resveratrol also showed high similarity to the profiles of SWT. This study identified SWT as an Nrf2 activator and phytoestrogen, suggesting its use as a nontoxic chemopreventive agent, and demonstrated the feasibility of combining microarray gene expression profiling with CMAP mining to discover mechanisms of actions and

  20. A novel method to quantify gene set functional association based on gene ontology.

    PubMed

    Lv, Sali; Li, Yan; Wang, Qianghu; Ning, Shangwei; Huang, Teng; Wang, Peng; Sun, Jie; Zheng, Yan; Liu, Weisha; Ai, Jing; Li, Xia

    2012-05-01

    Numerous gene sets have been used as molecular signatures for exploring the genetic basis of complex disorders. These gene sets are distinct but related to each other in many cases; therefore, efforts have been made to compare gene sets for studies such as those evaluating the reproducibility of different experiments. Comparison in terms of biological function has been demonstrated to be helpful to biologists. We improved the measurement of semantic similarity to quantify the functional association between gene sets in the context of gene ontology and developed a web toolkit named Gene Set Functional Similarity (GSFS; http://bioinfo.hrbmu.edu.cn/GSFS). Validation based on protein complexes for which the functional associations are known demonstrated that the GSFS scores tend to be correlated with sequence similarity scores and that complexes with high GSFS scores tend to be involved in the same functional catalogue. Compared with the pairwise method and the annotation method, the GSFS shows better discrimination and more accurately reflects the known functional catalogues shared between complexes. Case studies comparing differentially expressed genes of prostate tumour samples from different microarray platforms and identifying coronary heart disease susceptibility pathways revealed that the method could contribute to future studies exploring the molecular basis of complex disorders.

  1. Ranking, selecting, and prioritising genes with desirability functions.

    PubMed

    Lazic, Stanley E

    2015-01-01

    In functional genomics experiments, researchers often select genes to follow-up or validate from a long list of differentially expressed genes. Typically, sharp thresholds are used to bin genes into groups such as significant/non-significant or fold change above/below a cut-off value, and ad hoc criteria are also used such as favouring well-known genes. Binning, however, is inefficient and does not take the uncertainty of the measurements into account. Furthermore, p-values, fold-changes, and other outcomes are treated as equally important, and relevant genes may be overlooked with such an approach. Desirability functions are proposed as a way to integrate multiple selection criteria for ranking, selecting, and prioritising genes. These functions map any variable to a continuous 0-1 scale, where one is maximally desirable and zero is unacceptable. Multiple selection criteria are then combined to provide an overall desirability that is used to rank genes. In addition to p-values and fold-changes, further experimental results and information contained in databases can be easily included as criteria. The approach is demonstrated with a breast cancer microarray data set. The functions and an example data set can be found in the desiR package on CRAN (https://cran.r-project.org/web/packages/desiR/) and the development version is available on GitHub (https://github.com/stanlazic/desiR). PMID:26644980

  2. Ranking, selecting, and prioritising genes with desirability functions.

    PubMed

    Lazic, Stanley E

    2015-01-01

    In functional genomics experiments, researchers often select genes to follow-up or validate from a long list of differentially expressed genes. Typically, sharp thresholds are used to bin genes into groups such as significant/non-significant or fold change above/below a cut-off value, and ad hoc criteria are also used such as favouring well-known genes. Binning, however, is inefficient and does not take the uncertainty of the measurements into account. Furthermore, p-values, fold-changes, and other outcomes are treated as equally important, and relevant genes may be overlooked with such an approach. Desirability functions are proposed as a way to integrate multiple selection criteria for ranking, selecting, and prioritising genes. These functions map any variable to a continuous 0-1 scale, where one is maximally desirable and zero is unacceptable. Multiple selection criteria are then combined to provide an overall desirability that is used to rank genes. In addition to p-values and fold-changes, further experimental results and information contained in databases can be easily included as criteria. The approach is demonstrated with a breast cancer microarray data set. The functions and an example data set can be found in the desiR package on CRAN (https://cran.r-project.org/web/packages/desiR/) and the development version is available on GitHub (https://github.com/stanlazic/desiR).

  3. Identification of differentially expressed genes affecting hair and cashmere growth in the Laiwu black goat by microarray.

    PubMed

    Zhao, Jinshan; Li, Hegang; Liu, Kaidong; Zhang, Baoxun; Li, Peipei; He, Jianning; Cheng, Ming; De, Wei; Liu, Jifeng; Zhao, Yaofeng; Yang, Lihua; Liu, Nan

    2016-10-01

    Goats are an important source of fibers. In the present study microarray technology was used to investigate the potential genes primarily involved in hair and cashmere growth in the Laiwu black goat. A total of 655 genes differentially expressed in body (hair‑growing) and groin (hairless) skin were identified, and their potential association with hair and cashmere growth was analyzed. The majority of genes associated with hair growth regulation could be assigned to intracellular, intracellular organelle, membrane‑bound vesicle, cytoplasmic vesicle, pattern binding, heparin binding, polysaccharide binding, glycosaminoglycan binding and cytoplasmic membrane‑bound vesicle categories. Numerous genes upregulated in body compared with groin skin contained common motifs for nuclear factor 1A, Yi, E2 factor (E2F) and cyclic adenosine monophosphate response element binding (CREB)/CREBβ binding sites in their promoter region. The promoter region of certain genes downregulated in body compared with groin skin contained three common regions with LF‑A1, Yi, E2F, Collier/Olfactory‑1/early B‑cell factor 1, peroxisome proliferator‑activated receptor α or U sites. Thus, the present study identified molecules in the cashmere‑bearing skin area of the Laiwu black goat, which may contribute to hair and cashmere traits. PMID:27600677

  4. A Measure of the Signal-to-Noise Ratio of Microarray Samples and Studies Using Gene Correlations

    PubMed Central

    Venet, David; Detours, Vincent; Bersini, Hugues

    2012-01-01

    Background The quality of gene expression data can vary dramatically from platform to platform, study to study, and sample to sample. As reliable statistical analysis rests on reliable data, determining such quality is of the utmost importance. Quality measures to spot problematic samples exist, but they are platform-specific, and cannot be used to compare studies. Results As a proxy for quality, we propose a signal-to-noise ratio for microarray data, the “Signal-to-Noise Applied to Gene Expression Experiments”, or SNAGEE. SNAGEE is based on the consistency of gene-gene correlations. We applied SNAGEE to a compendium of 80 large datasets on 37 platforms, for a total of 24,380 samples, and assessed the signal-to-noise ratio of studies and samples. This allowed us to discover serious issues with three studies. We show that signal-to-noise ratios of both studies and samples are linked to the statistical significance of the biological results. Conclusions We showed that SNAGEE is an effective way to measure data quality for most types of gene expression studies, and that it often outperforms existing techniques. Furthermore, SNAGEE is platform-independent and does not require raw data files. The SNAGEE R package is available in BioConductor. PMID:23251415

  5. Allelic imbalances and microdeletions affecting the PTPRD gene in cutaneous squamous cell carcinomas detected using single nucleotide polymorphism microarray analysis.

    PubMed

    Purdie, Karin J; Lambert, Sally R; Teh, Muy-Teck; Chaplin, Tracy; Molloy, Gael; Raghavan, Manoj; Kelsell, David P; Leigh, Irene M; Harwood, Catherine A; Proby, Charlotte M; Young, Bryan D

    2007-07-01

    Cutaneous squamous cell carcinomas (SCC) are the second most commonly diagnosed cancers in fair-skinned people; yet the genetic mechanisms involved in SCC tumorigenesis remain poorly understood. We have used single nucleotide polymorphism (SNP) microarray analysis to examine genome-wide allelic imbalance in 16 primary and 2 lymph node metastatic SCC using paired non-tumour samples to counteract normal copy number variation. The most common genetic change was loss of heterozygosity (LOH) on 9p, observed in 13 of 16 primary SCC. Other recurrent events included LOH on 3p (9 tumors), 2q, 8p, and 13 (each in 8 SCC) and allelic gain on 3q and 8q (each in 6 tumors). Copy number-neutral LOH was observed in a proportion of samples, implying that somatic recombination had led to acquired uniparental disomy, an event not previously demonstrated in SCC. As well as recurrent patterns of gross chromosomal changes, SNP microarray analysis revealed, in 2 primary SCC, a homozygous microdeletion on 9p23 within the protein tyrosine phosphatase receptor type D (PTPRD) locus, an emerging frequent target of homozygous deletion in lung cancer and neuroblastoma. A third sample was heterozygously deleted within this locus and PTPRD expression was aberrant. Two of the 3 primary SCC with PTPRD deletion had demonstrated metastatic potential. Our data identify PTPRD as a candidate tumor suppressor gene in cutaneous SCC with a possible association with metastasis.

  6. Evaluation of two outlier-detection-based methods for detecting tissue-selective genes from microarray data.

    PubMed

    Kadota, Koji; Konishi, Tomokazu; Shimizu, Kentaro

    2007-01-01

    Large-scale expression profiling using DNA microarrays enables identification of tissue-selective genes for which expression is considerably higher and/or lower in some tissues than in others. Among numerous possible methods, only two outlier-detection-based methods (an AIC-based method and Sprent's non-parametric method) can treat equally various types of selective patterns, but they produce substantially different results. We investigated the performance of these two methods for different parameter settings and for a reduced number of samples. We focused on their ability to detect selective expression patterns robustly. We applied them to public microarray data collected from 36 normal human tissue samples and analyzed the effects of both changing the parameter settings and reducing the number of samples. The AIC-based method was more robust in both cases. The findings confirm that the use of the AIC-based method in the recently proposed ROKU method for detecting tissue-selective expression patterns is correct and that Sprent's method is not suitable for ROKU. PMID:19936074

  7. The Genopolis Microarray Database

    PubMed Central

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

    2007-01-01

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

  8. DNA Microarray Technology

    SciTech Connect

    WERNER-WASHBURNE, MARGARET; DAVIDSON, GEORGE S.

    2002-01-01

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

  9. Cross-Platform Microarray Meta-Analysis for the Mouse Jejunum Selects Novel Reference Genes with Highly Uniform Levels of Expression

    PubMed Central

    Meyer, Florian R. L.; Grausgruber, Heinrich; Binter, Claudia; Mair, Georg E.; Guelly, Christian; Vogl, Claus; Steinborn, Ralf

    2013-01-01

    Reference genes (RGs) with uniform expression are used for normalization of reverse transcription quantitative PCR (RT-qPCR) data. Their optimization for a specific biological context, e.g. a specific tissue, has been increasingly considered. In this article, we compare RGs identified by expression data meta-analysis restricted to the context tissue, the jejunum of Mus musculus domesticus, i) to traditional RGs, ii) to expressed interspersed repeated DNA elements, and iii) to RGs identified by meta-analysis of expression data from diverse tissues and conditions. To select the set of candidate RGs, we developed a novel protocol for the cross-platform meta-analysis of microarray data. The expression stability of twenty-four putative RGs was analysed by RT-qPCR in at least 14 jejunum samples of the mouse strains C57Bl/6N, CD1, and OF1. Across strains, the levels of expression of the novel RGs Plekha7, Zfx, and Ube2v1 as well as of Oaz1 varied less than two-fold irrespective of genotype, sex or their combination. The gene set consisting of Plekha7 and Oaz1 showed superior expression stability analysed with the tool RefFinder. The novel RGs are functionally diverse. This facilitates expression studies over a wide range of conditions. The highly uniform expression of the optimized RGs in the jejunum points towards their involvement in tightly regulated pathways in this tissue. We also applied our novel protocol of cross-microarray platform meta-analysis to the identification of RGs in the duodenum, the ileum and the entire small intestine. The selection of RGs with improved expression stability in a specific biological context can reduce the number of RGs for the normalization step of RT-qPCR expression analysis, thus reducing the number of samples and experimental costs. PMID:23671661

  10. Gene Chips and Functional Genomics

    NASA Astrophysics Data System (ADS)

    Hamadeh, Hisham; Afshari, Cynthia

    2000-11-01

    These past few years of scientific discovery will undoubtedly be remembered as the "genomics era," the period in which biologists succeeded in enumerating the sequence of nucleotides making up all, or at least most, of human DNA. And while this achievement has been heralded as a technological feat equal to the moon landing, it is only the first of many advances in DNA technology. Scientists are now faced with the task of understanding the meaning of the DNA sequence. Specifically, they want to learn how the DNA code relates to protein function. An important tool in the study of "functional genomics," is the cDNA microarray—also known as the gene chip. Inspired by computer microchips, gene chips allow scientists to monitor the expression of hundreds, even thousands, of genes in a fraction of the time it used to take to monitor the expression of a single one. By altering the conditions under which a particular tissue expresses genes—say, by exposing it to toxins or growth factors—scientists can determine the suite of genes expressed in different situations and hence start to get a handle on the function of these genes. The authors discuss this important new technology and some of its practical applications.

  11. Validation and implementation of a method for microarray gene expression profiling of minor B-cell subpopulations in man

    PubMed Central

    2014-01-01

    Background This report describes a method for the generation of global gene expression profiles from low frequent B-cell subsets by using fluorescence-activated cell sorting and RNA amplification. However, some of the differentiating compartments involve a low number of cells and therefore it is important to optimize and validate each step in the procedure. Methods Normal lymphoid tissues from blood, tonsils, thymus and bone marrow were immunophenotyped by the 8-colour Euroflow panel using multiparametric flow cytometry. Subsets of B-cells containing cell numbers ranging from 800 to 33,000 and with frequencies varying between 0.1 and 10 percent were sorted, subjected to mRNA purification, amplified by the NuGEN protocol and finally analysed by the Affymetrix platform. Results Following a step by step strategy, each step in the workflow was validated and the sorting/storage conditions optimized as described in this report. First, an analysis of four cancer cell lines on Affymetrix arrays, using either 100 ng RNA labelled with the Ambion standard protocol or 1 ng RNA amplified and labelled by the NuGEN protocol, revealed a significant correlation of gene expressions (r ≥ 0.9 for all). Comparison of qPCR data in samples with or without amplification for 8 genes showed that a relative difference between six cell lines was preserved (r ≥ 0.9). Second, a comparison of cells sorted into PrepProtect, RNAlater or directly into lysis/binding buffer showed a higher yield of purified mRNA following storage in lysis/binding buffer (p < 0.001). Third, the identity of the B-cell subsets validated by the cluster of differentiation (CD) membrane profile was highly concordant with the transcriptional gene expression (p-values <0.001). Finally, in normal bone marrow and tonsil samples, eight evaluated genes were expressed in accordance with the biology of lymphopoiesis (p-values < 0.001), which enabled the generation of a gene-specific B-cell atlas. Conclusion A

  12. Differential Gene Expression from Genome-Wide Microarray Analyses Distinguishes Lohmann Selected Leghorn and Lohmann Brown Layers

    PubMed Central

    Habig, Christin; Geffers, Robert; Distl, Ottmar

    2012-01-01

    The Lohmann Selected Leghorn (LSL) and Lohmann Brown (LB) layer lines have been selected for high egg production since more than 50 years and belong to the worldwide leading commercial layer lines. The objectives of the present study were to characterize the molecular processes that are different among these two layer lines using whole genome RNA expression profiles. The hens were kept in the newly developed small group housing system Eurovent German with two different group sizes. Differential expression was observed for 6,276 microarray probes (FDR adjusted P-value <0.05) among the two layer lines LSL and LB. A 2-fold or greater change in gene expression was identified on 151 probe sets. In LSL, 72 of the 151 probe sets were up- and 79 of them were down-regulated. Gene ontology (GO) enrichment analysis accounting for biological processes evinced 18 GO-terms for the 72 probe sets with higher expression in LSL, especially those taking part in immune system processes and membrane organization. A total of 32 enriched GO-terms were determined among the 79 down-regulated probe sets of LSL. Particularly, these terms included phosphorus metabolic processes and signaling pathways. In conclusion, the phenotypic differences among the two layer lines LSL and LB are clearly reflected in their gene expression profiles of the cerebrum. These novel findings provide clues for genes involved in economically important line characteristics of commercial laying hens. PMID:23056453

  13. Microarray and RT-PCR screening for white spot syndrome virus immediate-early genes in cycloheximide-treated shrimp

    SciTech Connect

    Liu Wangjing; Chang Yunshiang; Wang Chunghsiung; Kou, Guang-Hsiung; Lo Chufang . E-mail: gracelow@ntu.edu.tw

    2005-04-10

    Here, we report for the first time the successful use of cycloheximide (CHX) as an inhibitor to block de novo viral protein synthesis during WSSV (white spot syndrome virus) infection. Sixty candidate IE (immediate-early) genes were identified using a global analysis microarray technique. RT-PCR showed that the genes corresponding to ORF126, ORF242 and ORF418 in the Taiwan isolate were consistently CHX-insensitive, and these genes were designated ie1, ie2 and ie3, respectively. The sequences for these IE genes also appear in the two other WSSV isolates that have been sequenced. Three corresponding ORFs were identified in the China WSSV isolate, but only an ORF corresponding to ie1 was predicted in the Thailand isolate. In a promoter activity assay in Sf9 insect cells using EGFP (enhanced green fluorescence protein) as a reporter, ie1 showed very strong promoter activity, producing higher EGFP signals than the insect Orgyia pseudotsugata multicapsid nuclear polyhedrosis virus (OpMNPV) ie2 promoter.

  14. Effect of Cu-nanoparticles versus Cu-salt in Enchytraeus albidus (Oligochaeta): differential gene expression through microarray analysis.

    PubMed

    Gomes, Susana I L; Novais, Sara C; Scott-Fordsmand, Janeck J; De Coen, Wim; Soares, Amadeu M V M; Amorim, Mónica J B

    2012-03-01

    Despite increased utilization of copper (Cu) nanoparticles, their behaviour and effect in the environment is largely unknown. Enchytraeids are extensively used in studies of soil ecotoxicology. Ecotoxicogenomic tools have shown to be valuable in nanotoxicity interpretation. A cDNA microarray for Enchytraeus albidus has recently been developed, which was used in this study. We compared the gene expression profiles of E. albidus when exposed to Cu-salt (CuCl(2)) and Cu-nanoparticles (Cu-NP) spiked soil. Exposure time was 48 h with a concentration range of 400 to 1000 mg Cu/kg. There were more down-regulated than up-regulated genes. The number of differently expressed genes (DEG) decreased with increasing concentration for CuCl(2) exposure, whereas for Cu-NP, the number did not change. The number of common DEG decreased with increasing concentration. Differences were mainly related to transcripts involved in energy metabolism (e.g. monosaccharide transporting ATPase, NADH dehydrogenase subunit 1, cytochrome c). Overall, our results indicated that Cu-salt and Cu-NP exposure induced different gene responses. Indirect estimates of Cu-NP related ion-release indicated little or no free Cu(2+) activity in soil solutions. Hence, it was concluded that the Cu-NP effects were probably caused by the nanoparticles themselves and not by released ions. PMID:21911081

  15. APPLICATION OF CDNA MICROARRAY TECHNOLOGY TO IN VITRO TOXICOLOGY AND THE SELECTION OF GENES FOR A REAL TIME RT-PCR-BASED SCREEN FOR OXIDATIVE STRESS IN HEP-G2 CELLS

    EPA Science Inventory

    Large-scale analysis of gene expression using cDNA microarrays promises the
    rapid detection of the mode of toxicity for drugs and other chemicals. cDNA
    microarrays were used to examine chemically-induced alterations of gene
    expression in HepG2 cells exposed to oxidative ...

  16. Correlation Index-Based Responsible-Enzyme Gene Screening (CIRES), a Novel DNA Microarray-Based Method for Enzyme Gene Involved in Glycan Biosynthesis

    PubMed Central

    Yamamoto, Harumi; Takematsu, Hiromu; Fujinawa, Reiko; Naito, Yuko; Okuno, Yasushi; Tsujimoto, Gozoh; Suzuki, Akemi; Kozutsumi, Yasunori

    2007-01-01

    Background Glycan biosynthesis occurs though a multi-step process that requires a variety of enzymes ranging from glycosyltransferases to those involved in cytosolic sugar metabolism. In many cases, glycan biosynthesis follows a glycan-specific, linear pathway. As glycosyltransferases are generally regulated at the level of transcription, assessing the overall transcriptional profile for glycan biosynthesis genes seems warranted. However, a systematic approach for assessing the correlation between glycan expression and glycan-related gene expression has not been reported previously. Methodology To facilitate genetic analysis of glycan biosynthesis, we sought to correlate the expression of genes involved in cell-surface glycan formation with the expression of the glycans, as detected by glycan-recognizing probes. We performed cross-sample comparisons of gene expression profiles using a newly developed, glycan-focused cDNA microarray. Cell-surface glycan expression profiles were obtained using flow cytometry of cells stained with plant lectins. Pearson's correlation coefficients were calculated for these profiles and were used to identify enzyme genes correlated with glycan biosynthesis. Conclusions This method, designated correlation index-based responsible-enzyme gene screening (CIRES), successfully identified genes already known to be involved in the biosynthesis of certain glycans. Our evaluation of CIRES indicates that it is useful for identifying genes involved in the biosynthesis of glycan chains that can be probed with lectins using flow cytometry. PMID:18043739

  17. cDNA microarray analysis of the effect of cantharidin on DNA damage, cell cycle and apoptosis-associated gene expression in NCI-H460 human lung cancer cells in vitro.

    PubMed

    Hsia, Te-Chun; Yu, Chien-Chih; Hsu, Shu-Chun; Tang, Nou-Ying; Lu, Hsu-Feng; Yu, Chun-Shu; Wu, Shin-Hwar; Lin, Jaung-Geng; Chung, Jing-Gung

    2015-07-01

    Cantharidin (CTD) induces cytotoxic effects in different types of human cancer cell; however, to date, there have been no studies on the effects of CTD on gene expression in human lung cancer cells and the potential associated signaling pathways. Therefore, the present study aimed to investigate how CTD affects the expression of key genes and functional pathways of human H460 lung cancer cells using complementary DNA microarray analysis. Human H460 lung cancer cells were cultured for 24 h in the presence or absence of 10 µM CTD; gene expression was then examined using microarray analysis. The results indicated that 8 genes were upregulated > 4-fold, 29 genes were upregulated >3-4-fold and 156 genes were upregulated >2-3-fold. In addition, 1 gene was downregulated >4 fold, 14 genes were downregulated >3-4-fold and 150 genes were downregulated >2-3 fold in H460 cells following exposure to CTD. It was found that CTD affected DNA damage genes, including DNIT3 and GADD45A, which were upregulated 2.26- and 2.60-fold, respectively, as well as DdiT4, which was downregulated 3.14-fold. In addition, the expression of genes associated with the cell cycle progression were altered, including CCND2, CDKL3 and RASA4, which were upregulated 2.72-, 2.19- and 2.72-fold, respectively; however, CDC42EP3 was downregulated 2.16-fold. Furthermore, apoptosis-associated genes were differentially expressed, including CARD6, which was upregulated 3.54-fold. In conclusion, the present study demonstrated that CTD affected the expression of genes associated with DNA damage, cell cycle progression and apoptotic cell death in human lung cancer H460 cells.

  18. A Review of Feature Extraction Software for Microarray Gene Expression Data

    PubMed Central

    Tan, Ching Siang; Ting, Wai Soon; Mohamad, Mohd Saberi; Chan, Weng Howe; Deris, Safaai; Ali Shah, Zuraini

    2014-01-01

    When gene expression data are too large to be processed, they are transformed into a reduced representation set of genes. Transforming large-scale gene expression data into a set of genes is called feature extraction. If the genes extracted are carefully chosen, this gene set can extract the relevant information from the large-scale gene expression data, allowing further analysis by using this reduced representation instead of the full size data. In this paper, we review numerous software applications that can be used for feature extraction. The software reviewed is mainly for Principal Component Analysis (PCA), Independent Component Analysis (ICA), Partial Least Squares (PLS), and Local Linear Embedding (LLE). A summary and sources of the software are provided in the last section for each feature extraction method. PMID:25250315

  19. Genes and environment - striking the fine balance between sophisticated biomonitoring and true functional environmental genomics.

    PubMed

    Steinberg, Christian E W; Stürzenbaum, Stephen R; Menzel, Ralph

    2008-08-01

    This article provides an overview how the application of the gene profiling (mainly via microarray technology) can be used in different organisms to address issues of environmental importance. Only recently, environmental sciences, including ecotoxicology, and molecular biology have started to mutually fertilize each other. This conceptual blend has enabled the identification of the interaction between molecular events and whole animal and population responses. Likewise, striking the fine balance between biomonitoring and functional environmental genomics will allow legislative and administrative measures to be based on a more robust platform. The application of DNA microarrays to ecotoxicogenomics links ecotoxicological effects of exposure with expression profiles of several thousand genes. The gene expression profiles are altered during toxicity, as either a direct or indirect result of toxicant exposure and the comparison of numerous specific expression profiles facilitates the differentiation between intoxication and true responses to environmental stressors. Furthermore, the application of microarrays provides the means to identify complex pathways and strategies that an exposed organism applies in response to environmental stressors. This review will present evidence that the widespread phenomenon of hormesis has a genetic basis that goes beyond an adaptive response. Some more practical advantages emerge: the toxicological assessment of complex mixtures, such as effluents or sediments, as well as drugs seems feasible, especially when classical ecotoxicological tests have failed. The review of available information demonstrates the advantages of microarray application to environmental issues spanning from bacteria, over algae and spermatophytes, to invertebrates (nematode Caenorhabditis elegans, crustacea Daphnia spp., earthworms), and various fish species. Microarrays have also highlighted why populations of a given species respond differently to similar

  20. In vivo corrosion, tumor outcome, and microarray gene expression for two types of muscle-implanted tungsten alloys

    SciTech Connect

    Schuster, B.E.; Roszell, L.E.; Murr, L.E.; Ramirez, D.A.; Demaree, J.D.; Klotz, B.R.; Rosencrance, A.B.; Dennis, W.E.; Bao, W.; Perkins, E.J.; Dillman, J.F.; Bannon, D.I.

    2012-11-15

    Tungsten alloys are composed of tungsten microparticles embedded in a solid matrix of transition metals such as nickel, cobalt, or iron. To understand the toxicology of these alloys, male F344 rats were intramuscularly implanted with pellets of tungsten/nickel/cobalt, tungsten/nickel/iron, or pure tungsten, with tantalum pellets as a negative control. Between 6 and 12 months, aggressive rhabdomyosarcomas formed around tungsten/nickel/cobalt pellets, while those of tungsten/nickel/iron or pure tungsten did not cause cancers. Electron microscopy showed a progressive corrosion of the matrix phase of tungsten/nickel/cobalt pellets over 6 months, accompanied by high urinary concentrations of nickel and cobalt. In contrast, non-carcinogenic tungsten/nickel/iron pellets were minimally corroded and urinary metals were low; these pellets having developed a surface oxide layer in vivo that may have restricted the mobilization of carcinogenic nickel. Microarray analysis of tumors revealed large changes in gene expression compared with normal muscle, with biological processes involving the cell cycle significantly up‐regulated and those involved with muscle development and differentiation significantly down‐regulated. Top KEGG pathways disrupted were adherens junction, p53 signaling, and the cell cycle. Chromosomal enrichment analysis of genes showed a highly significant impact at cytoband 7q22 (chromosome 7) which included mouse double minute (MDM2) and cyclin‐dependant kinase (CDK4) as well as other genes associated with human sarcomas. In conclusion, the tumorigenic potential of implanted tungsten alloys is related to mobilization of carcinogenic metals nickel and cobalt from corroding pellets, while gene expression changes in the consequent tumors are similar to radiation induced animal sarcomas as well as sporadic human sarcomas. -- Highlights: ► Tungsten/nickel/cobalt, tungsten/nickel/iron, and pure tungsten were studied. ► Male Fischer rats implanted with

  1. Development of the first oligonucleotide microarray for global gene expression profiling in guinea pigs: defining the transcription signature of infectious diseases

    PubMed Central

    2012-01-01

    Background The Guinea pig (Cavia porcellus) is one of the most extensively used animal models to study infectious diseases. However, despite its tremendous contribution towards understanding the establishment, progression and control of a number of diseases in general and tuberculosis in particular, the lack of fully annotated guinea pig genome sequence as well as appropriate molecular reagents has severely hampered detailed genetic and immunological analysis in this animal model. Results By employing the cross-species hybridization technique, we have developed an oligonucleotide microarray with 44,000 features assembled from different mammalian species, which to the best of our knowledge is the first attempt to employ microarray to study the global gene expression profile in guinea pigs. To validate and demonstrate the merit of this microarray, we have studied, as an example, the expression profile of guinea pig lungs during the advanced phase of M. tuberculosis infection. A significant upregulation of 1344 genes and a marked down regulation of 1856 genes in the lungs identified a disease signature of pulmonary tuberculosis infection. Conclusion We report the development of first comprehensive microarray for studying the global gene expression profile in guinea pigs and validation of its usefulness with tuberculosis as a case study. An important gap in the area of infectious diseases has been addressed and a valuable molecular tool is provided to optimally harness the potential of guinea pig model to develop better vaccines and therapies against human diseases. PMID:23031549

  2. Positive Adaptive State: Microarray Evaluation of Gene Expression in Salmonella Enterica Typhimurium Upon Exposure to Sub-Therapeutic Levels of Nalidixic Acid

    Technology Transfer Automated Retrieval System (TEKTRAN)

    In order to evaluate changes in gene expression that occur upon exposure to sub-therapeutic levels of a quinolones antibioitic, Salmonella enterica Typhimurium ATCC# 14028 was exposed to 1.6 ug/L of nalidixic acid (NA). Microarray analysis of the expression profile during exposure to NA was compared...

  3. DGEM--a microarray gene expression database for primary human disease tissues.

    PubMed

    Xia, Yuni; Campen, Andrew; Rigsby, Dan; Guo, Ying; Feng, Xingdong; Su, Eric W; Palakal, Mathew; Li, Shuyu

    2007-01-01

    Gene expression patterns can reflect gene regulations in human tissues under normal or pathologic conditions. Gene expression profiling data from studies of primary human disease samples are particularly valuable since these studies often span many years in order to collect patient clinical information and achieve a large sample size. Disease-to-Gene Expression Mapper (DGEM) provides a beneficial community resource to access and analyze these data; it currently includes Affymetrix oligonucleotide array datasets for more than 40 human diseases and 1400 samples. The data are normalized to the same scale and stored in a relational database. A statistical-analysis pipeline was implemented to identify genes abnormally expressed in disease tissues or genes whose expressions are associated with clinical parameters such as cancer patient survival. Data-mining results can be queried through a web-based interface at http://dgem.dhcp.iupui.edu/. The query tool enables dynamic generation of graphs and tables that are further linked to major gene and pathway resources that connect the data to relevant biology, including Entrez Gene and Kyoto Encyclopedia of Genes and Genomes (KEGG). In summary, DGEM provides scientists and physicians a valuable tool to study disease mechanisms, to discover potential disease biomarkers for diagnosis and prognosis, and to identify novel gene targets for drug discovery. The source code is freely available for non-profit use, on request to the authors. PMID:17570735

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

    PubMed Central

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

    2013-01-01

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

  5. Microarray profiling of gene expression patterns in glomerular cells of astaxanthin-treated diabetic mice: a nutrigenomic approach.

    PubMed

    Naito, Yuji; Uchiyama, Kazuhiko; Mizushima, Katsura; Kuroda, Masaaki; Akagiri, Satomi; Takagi, Tomohisa; Handa, Osamu; Kokura, Satoshi; Yoshida, Norimasa; Ichikawa, Hiroshi; Takahashi, Jiro; Yoshikawa, Toshikazu

    2006-10-01

    We have demonstrated that astaxanthin reduces glomerular oxidative stress as well as inhibits the increase in urinary albumin in diabetic db/db mice. The aim of the present study was to determine the gene expression patterns in the glomerular cells of the diabetic mouse kidney, and to investigate the effects of astaxanthin on the expression of these genes using a high-density DNA microarray. The diet administered to the astaxanthin-supplementation group was prepared by mixing a control powder with astaxanthin at a concentration of 0.02%. Glomerular cells were obtained from the kidneys of mice by laser capture microdissection. Preparation of cRNA and target hybridization were performed according to the Affymetrix GeneChip eukaryotic small sample target labeling assay protocol. The gene expression profile was evaluated by the mouse expression set 430A GeneChip. Array data analysis was carried out using Affymetrix GeneChip operating and Ingenuity Pathway analysis software. Comparison between diabetic db/db and non-diabetic db/m mice revealed that 779 probes (3.1%) were significantly affected, i.e. 550 probes were up-regulated, and 229 probes were down-regulated, both at levels of >/=1.5-fold in the diabetic mice. Ingenuity signal analysis of 550 up-regulated probes revealed the mitochondrial oxidative phosphorylation pathway as the most significantly affected caronical pathway. The affected genes were associated with complexes I, III, and IV located on the mitochondrial inner membrane, and the expression levels of these genes were decreased in mice treated with astaxanthin as compared to the levels in the control mice. In addition, the expression of many genes associated with oxidative stress, collagen synthesis, and transforming growth factor-beta signaling was enhanced in the diabetic mice, and this enhancement was slightly inhibited in the astaxanthin-treated mice. In conclusion, this genome-wide nutrigenomics approach provided insight into genes and putative

  6. Microarray Analysis of Microbial Weathering

    NASA Astrophysics Data System (ADS)

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

    2010-04-01

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

  7. Identification of Transcriptional Factors and Key Genes in Primary Osteoporosis by DNA Microarray

    PubMed Central

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

    2015-01-01

    Background A number of genes have been identified to be related with primary osteoporosis while less is known about the comprehensive interactions between regulating genes and proteins. We aimed to identify the differentially expressed genes (DEGs) and regulatory effects of transcription factors (TFs) involved in primary osteoporosis. Material/Methods The gene expression profile GSE35958 was obtained from Gene Expression Omnibus database, including 5 primary osteoporosis and 4 normal bone tissues. The differentially expressed genes between primary osteoporosis and normal bone tissues were identified by the same package in R language. The TFs of these DEGs were predicted with the Essaghir A method. DAVID (The Database for Annotation, Visualization and Integrated Discovery) was applied to perform the GO (Gene Ontology) and KEGG (Kyoto Encyclopedia of Genes and Genomes) pathway enrichment analysis of DEGs. After analyzing regulatory effects, a regulatory network was built between TFs and the related DEGs. Results A total of 579 DEGs was screened, including 310 up-regulated genes and 269 down-regulated genes in primary osteoporosis samples. In GO terms, more up-regulated genes were enriched in transcription regulator activity, and secondly in transcription factor activity. A total 10 significant pathways were enriched in KEGG analysis, including colorectal cancer, Wnt signaling pathway, Focal adhesion, and MAPK signaling pathway. Moreover, total 7 TFs were enriched, of which CTNNB1, SP1, and TP53 regulated most up-regulated DEGs. Conclusions The discovery of the enriched TFs might contribute to the understanding of the mechanism of primary osteoporosis. Further research on genes and TFs related to the WNT signaling pathway and MAPK pathway is urgent for clinical diagnosis and directing treatment of primary osteoporosis. PMID:25957414

  8. Monitoring expression profiles of rice genes under cold, drought, and high-salinity stresses and abscisic acid application using cDNA microarray and RNA gel-blot analyses.

    PubMed

    Rabbani, M Ashiq; Maruyama, Kyonoshin; Abe, Hiroshi; Khan, M Ayub; Katsura, Koji; Ito, Yusuke; Yoshiwara, Kyoko; Seki, Motoaki; Shinozaki, Kazuo; Yamaguchi-Shinozaki, Kazuko

    2003-12-01

    To identify cold-, drought-, high-salinity-, and/or abscisic acid (ABA)-inducible genes in rice (Oryza sativa), we prepared a rice cDNA microarray including about 1700 independent cDNAs derived from cDNA libraries prepared from drought-, cold-, and high-salinity-treated rice plants. We confirmed stress-inducible expression of the candidate genes selected by microarray analysis using RNA gel-blot analysis and finally identified a total of 73 genes as stress inducible including 58 novel unreported genes in rice. Among them, 36, 62, 57, and 43 genes were induced by cold, drought, high salinity, and ABA, respectively. We observed a strong association in the expression of stress-responsive genes and found 15 genes that responded to all four treatments. Venn diagram analysis revealed greater cross talk between signaling pathways for drought, ABA, and high-salinity stresses than between signaling pathways for cold and ABA stresses or cold and high-salinity stresses in rice. The rice genome database search enabled us not only to identify possible known cis-acting elements in the promoter regions of several stress-inducible genes but also to expect the existence of novel cis-acting elements involved in stress-responsive gene expression in rice stress-inducible promoters. Comparative analysis of Arabidopsis and rice showed that among the 73 stress-inducible rice genes, 51 already have been reported in Arabidopsis with similar function or gene name. Transcriptome analysis revealed novel stress-inducible genes, suggesting some differences between Arabidopsis and rice in their response to stress.

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

    PubMed

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

    2014-01-01

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

  10. Microarray Meta-Analysis Focused on the Response of Genes Involved in Redox Homeostasis to Diverse Abiotic Stresses in Rice

    PubMed Central

    de Abreu Neto, Joao B.; Frei, Michael

    2016-01-01

    Plants are exposed to a wide range of abiotic stresses (AS), which often occur in combination. Because physiological investigations typically focus on one stress, our understanding of unspecific stress responses remains limited. The plant redox homeostasis, i.e., the production and removal of reactive oxygen species (ROS), may be involved in many environmental stress conditions. Therefore, this study intended to identify genes, which are activated in diverse AS, focusing on ROS-related pathways. We conducted a meta-analysis (MA) of microarray experiments, focusing on rice. Transcriptome data were mined from public databases and fellow researchers, which represented 36 different experiments and investigated diverse AS, including ozone stress, drought, heat, cold, salinity, and mineral deficiencies/toxicities. To overcome the inherent artifacts of different MA methods, data were processed using Fisher, rOP, REM, and product of rank (GeneSelector), and genes identified by most approaches were considered as shared differentially expressed genes (DEGs). Two MA strategies were adopted: first, datasets were separated into shoot, root, and seedling experiments, and these tissues were analyzed separately to identify shared DEGs. Second, shoot and seedling experiments were classed into oxidative stress (OS), i.e., ozone and hydrogen peroxide treatments directly producing ROS in plant tissue, and other AS, in which ROS production is indirect. In all tissues and stress conditions, genes a priori considered as ROS-related were overrepresented among the DEGs, as they represented 4% of all expressed genes but 7–10% of the DEGs. The combined MA approach was substantially more conservative than individual MA methods and identified 1001 shared DEGs in shoots, 837 shared DEGs in root, and 1172 shared DEGs in seedlings. Within the OS and AS groups, 990 and 1727 shared DEGs were identified, respectively. In total, 311 genes were shared between OS and AS, including many regulatory

  11. Microarray gene cluster identification and annotation through cluster ensemble and EM-based informative textual summarization.

    PubMed

    Hu, Xiaohua; Park, E K; Zhang, Xiaodan

    2009-09-01

    Generating high-quality gene clusters and identifying the underlying biological mechanism of the gene clusters are the important goals of clustering gene expression analysis. To get high-quality cluster results, most of the current approaches rely on choosing the best cluster algorithm, in which the design biases and assumptions meet the underlying distribution of the dataset. There are two issues for this approach: 1) usually, the underlying data distribution of the gene expression datasets is unknown and 2) there are so many clustering algorithms available and it is very challenging to choose the proper one. To provide a textual summary of the gene clusters, the most explored approach is the extractive approach that essentially builds upon techniques borrowed from the information retrieval, in which the objective is to provide terms to be used for query expansion, and not to act as a stand-alone summary for the entire document sets. Another drawback is that the clustering quality and cluster interpretation are treated as two isolated research problems and are studied separately. In this paper, we design and develop a unified system Gene Expression Miner to address these challenging issues in a principled and general manner by integrating cluster ensemble, text clustering, and multidocument summarization and provide an environment for comprehensive gene expression data analysis. We present a novel cluster ensemble approach to generate high-quality gene cluster. In our text summarization module, given a gene cluster, our expectation-maximization based algorithm can automatically identify subtopics and extract most probable terms for each topic. Then, the extracted top k topical terms from each subtopic are combined to form the biological explanation of each gene cluster. Experimental results demonstrate that our system can obtain high-quality clusters and provide informative key terms for the gene clusters.

  12. Rapid analysis of gene expression changes caused by liver carcinogens and chemopreventive agents using a newly developed three-dimensional microarray system.

    PubMed

    Hokaiwado, Naomi; Asamoto, Makoto; Tsujimura, Kazunari; Hirota, Takeshi; Ichihara, Toshio; Satoh, Takatomo; Shirai, Tomoyuki

    2004-02-01

    We investigated changes of gene expression in livers of rats treated with carcinogens and tumor promoters using a novel three-dimensional microarray system developed by Olympus Optical Co., Ltd., to assess the feasibility of predicting modifying effects on hepatocarcinogenesis on the basis of changes in the patterns. For this purpose, two genotoxic carcinogens, two nongenotoxic carcinogens (promoters) and seven candidate chemopreventive agents were examined. Six-week-old male F344 rats were treated for 2 weeks with the 11 chemicals (0.05% phenobarbital, 0.3% clofibrate, 0.01% N-diethylnitrosamine (DEN), 0.01% 2-amino-3,8-dimethylimidazo[4,5-f]quinoxaline (MeIQx), 1% catechol, 1% caffeic acid, 0.05% nobiletin, 0.05% garcinol, 0.05% auraptene, 0.05% zermbone and 0.05% 1'-acetoxychavicol acetate (ACA). Test chemicals were mixed in food with the exception of DEN, which was administered in drinking water. RNAs from liver were then analyzed using two kinds of customized microarrays (PamChip(\\xa8) microarray A spotted for 28 genes of drug-metabolizing enzymes in duplicate, and PamChip microarray B spotted for 131 genes which are known to be up- or down-regulated in hepatocarcinoma cells). Hybridization and subsequent analysis were usually completed within 2 h and the data obtained were highly reproducible. Carcinogens were classified into genotoxic and nongenotoxic substances by clustering analysis. We could also divide test chemicals into carcinogens and chemopreventive agents from their effects on gene expression. In this study, we have thus shown that it is feasible to predict the modifying effects of chemicals on the basis of changes of gene expression patterns after only 2 weeks of exposure, using our novel three-dimensional microarrays.

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  14. Microarray analysis of gene expression patterns of high lycopene tomato generated from seeds after long-term space flight

    NASA Astrophysics Data System (ADS)

    Lu, Jinying; Ren, Chunxiao; Pan, Yi; Nechitailo, Galina S.; Liu, Min

    Lycopene content is a most vital trait of tomatoes due to the role of lycopene in reducing the risk of some kinds of cancers. In this experiment, we gained a high lycopene (hl) tomato (named HY-2), after seven generations of self-cross selection, from seeds Russian MNP-1 carried in Russia MIR space station for six years. HPLC result showed that the lycopene content was 1.6 times more than that in Russian MNP-1 (the wild type). Microarray analysis presented the general profile of differential expressed genes at the tomato developmental stage of 7DPB (days post breaker). One hundred and forty three differential expression genes were identified according to the following criterion: the average changes were no less than 1.5 folds with q-value (similar to FDR) less than 0.05 or changes were no less than 1.5 folds in all three biological replications. Most of the differential expressed genes were mainly involved in metabolism, response to stimulus, biosynthesis, development and regulation. Particularly, we discussed the genes involved in protein metabolism, response to unfolded protein, carotenoid biosynthesis and photosynthesis that might be related to the fruit development and the accumulation of lycopene. What's more, we conducted QRT-PCR validation of five key genes (Fps, CrtL-b, CrtR-b, Zep and Nxs) in the lycopene biosynthesis pathway through time courses and that provided the direct molecular evidence for the hl phenotype. Our results demonstrate that long-term space flight, as a rarely used tool, can positively cause some beneficial mutations in the seeds and thus to help to generate a high quality variety, combined with ground selections.

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

    PubMed Central

    2013-01-01

    Background Tibial dyschondroplasia (TD) is a common skeletal disorder in broiler chickens. It is characterized by the presence of a non-vascularized and unmineralized cartilage in the growth plate. Previous studies have investigated differential expression of genes related to cartilage development during latter stages of TD. The aim of our study was to identify differentially expressed genes (DEGs) in the growth plate of broiler chickens, which were associated with early stage TD. We induced TD using tetramethylthiuram disulfide (thiram) for 1, 2, and 6 days and determined DEGs with chicken Affymetrix GeneChip assays. The identified DEGs were verified by quantitative polymerase chain reaction (qPCR) assays. Results We identified 1630 DEGs, with 82, 1385, and 429 exhibiting at least 2.0-fold changes (P < 0.05) at days 1, 2, and 6, respectively. These DEGs participate in a variety of biological processes, including cytokine production, oxidation reduction, and cell surface receptor linked signal transduction on day 1; lipid biosynthesis, regulation of growth, cell cycle, positive and negative gene regulation, transcription and transcription regulation, and anti-apoptosis on day 2; and regulation of cell proliferation, transcription, dephosphorylation, catabolism, proteolysis, and immune responses on day 6. The identified DEGs were associated with the following pathways: neuroactive ligand-receptor interaction on day 1; synthesis and degradation of ketone bodies, terpenoid backbone biosynthesis, ether lipid metabolism, JAK-STAT, GnRH signaling pathway, ubiquitin mediated proteolysis, TGF-β signaling, focal adhesion, and Wnt signaling on day 2; and arachidonic acid metabolism, mitogen-activated protein kinase (MAPK) signaling, JAK-STAT, insulin signaling, and glycolysis on day 6. We validated seven DEGs by qPCR. Conclusions Our findings demonstrate previously unrecognized changes in gene transcription associated with early stage TD. The DEGs we identified by

  16. Microarray analysis of ox-LDL (oxidized low-density lipoprotein)-regulated genes in human coronary artery smooth muscle cells.

    PubMed

    Minta, Joe; Jungwon Yun, James; St Bernard, Rosanne

    2010-01-01

    Recent studies suggest that circulating LDL (low-density lipoproteins) play a central role in the pathogenesis of atherosclerosis, and the oxidized form (ox-LDL) is highly atherogenic. Deposits of ox-LDL have been found in atherosclerotic plaques, and ox-LDL has been shown to promote monocyte recruitment, foam cell formation and the transition of quiescent and contractile vascular SMCs (smooth muscle cells) to the migratory and proliferative phenotype. SMC phenotype transition and hyperplasia are the pivotal events in the pathogenesis of atherosclerosis. To comprehend the complex molecular mechanisms involved in ox-LDL-mediated SMC phenotype transition, we have compared the differential gene expression profiles of cultured quiescent human coronary artery SMCs with cells induced with ox-LDL for 3 and 21 h using Affymetrix HG-133UA cDNA microarray chips. Assignment of the regulated genes into functional groups indicated that several genes involved in metabolism, membrane transport, cell-cell interactions, signal transduction, transcription, translation, cell migration, proliferation and apoptosis were differentially expressed. Our data suggests that the interaction of ox-LDL with its cognate receptors on SMCs modulates the induction of several growth factors and cytokines, which activate a variety of intracellular signalling mechanisms (including PI3K, MAPK, Jak/STAT, sphingosine, Rho kinase pathways) that contribute to SMC transition from the quiescent and contractile phenotype to the proliferative and migratory phenotype. Our study has also identified several genes (including CDC27, cyclin A1, cyclin G2, glypican 1, MINOR, p15 and apolipoprotein) not previously implicated in ox-LDL-induced SMC phenotype transition and substantially extends the list of potential candidate genes involved in atherogenesis.

  17. Comparative study of Trichoderma gene expression in interactions with tomato plants using high-density oligonucleotide microarrays.

    PubMed

    Rubio, M Belén; Domínguez, Sara; Monte, Enrique; Hermosa, Rosa

    2012-01-01

    Trichoderma spp. are widely used as biopesticides and biofertilizers to control diseases and to promote positive physiological responses in plants. In vitro and in vivo assays with Trichoderma harzianum CECT 2413 (T34), Trichoderma virens Gv29-8 (T87) and Trichoderma hamatum IMI 224801 (T7) revealed that these strains affected the growth and development of lateral roots in tomato plants in different ways. The early expression profiles of these Trichoderma strains were studied after 20 h of incubation in the presence of tomato plants, using a high-density oligonucleotide (HDO) microarray, and compared to the profiles in the absence of plants. Out of the total 34 138 Trichoderma probe sets deposited on the microarray, 1077 (3.15 %) showed a significant change of at least 2-fold in expression in the presence of tomato plants. The numbers of probe sets identified in the individual Trichoderma strains were 593 in T. harzianum T34, 336 in T. virens T87 and 94 in T. hamatum T7. Carbohydrate metabolism - the chitin degradation enzymes N-acetylglucosamine-6-phosphate deacetylase, glucosamine-6-phosphate deaminase and chitinase - was the most significantly overrepresented process commonly observed in the three Trichoderma strains in early interactions with tomato plants. Strains T7 and T34, which had similar positive effects on plant development in biological assays, showed a significantly overrepresented hexokinase activity in interaction with tomato. In addition, genes encoding a 40S ribosomal protein and a P23 tumour protein were altered in both these strains.

  18. Sexual Dimorphism and Aging in the Human Hyppocampus: Identification, Validation, and Impact of Differentially Expressed Genes by Factorial Microarray and Network Analysis

    PubMed Central

    Guebel, Daniel V.; Torres, Néstor V.

    2016-01-01

    Motivation: In the brain of elderly-healthy individuals, the effects of sexual dimorphism and those due to normal aging appear overlapped. Discrimination of these two dimensions would powerfully contribute to a better understanding of the etiology of some neurodegenerative diseases, such as “sporadic” Alzheimer. Methods: Following a system biology approach, top-down and bottom-up strategies were combined. First, public transcriptome data corresponding to the transition from adulthood to the aging stage in normal, human hippocampus were analyzed through an optimized microarray post-processing (Q-GDEMAR method) together with a proper experimental design (full factorial analysis). Second, the identified genes were placed in context by building compatible networks. The subsequent ontology analyses carried out on these networks clarify the main functionalities involved. Results: Noticeably we could identify large sets of genes according to three groups: those that exclusively depend on the sex, those that exclusively depend on the age, and those that depend on the particular combinations of sex and age (interaction). The genes identified were validated against three independent sources (a proteomic study of aging, a senescence database, and a mitochondrial genetic database). We arrived to several new inferences about the biological functions compromised during aging in two ways: by taking into account the sex-independent effects of aging, and considering the interaction between age and sex where pertinent. In particular, we discuss the impact of our findings on the functions of mitochondria, autophagy, mitophagia, and microRNAs. Conclusions: The evidence obtained herein supports the occurrence of significant neurobiological differences in the hippocampus, not only between adult and elderly individuals, but between old-healthy women and old-healthy men. Hence, to obtain realistic results in further analysis of the transition from the normal aging to incipient

  19. Functional gene diversity of oolitic sands from Great Bahama Bank.

    PubMed

    Diaz, M R; Van Norstrand, J D; Eberli, G P; Piggot, A M; Zhou, J; Klaus, J S

    2014-05-01

    Despite the importance of oolitic depositional systems as indicators of climate and reservoirs of inorganic C, little is known about the microbial functional diversity, structure, composition, and potential metabolic processes leading to precipitation of carbonates. To fill this gap, we assess the metabolic gene carriage and extracellular polymeric substance (EPS) development in microbial communities associated with oolitic carbonate sediments from the Bahamas Archipelago. Oolitic sediments ranging from high-energy 'active' to lower energy 'non-active' and 'microbially stabilized' environments were examined as they represent contrasting depositional settings, mostly influenced by tidal flows and wave-generated currents. Functional gene analysis, which employed a microarray-based gene technology, detected a total of 12,432 of 95,847 distinct gene probes, including a large number of metabolic processes previously linked to mineral precipitation. Among these, gene-encoding enzymes for denitrification, sulfate reduction, ammonification, and oxygenic/anoxygenic photosynthesis were abundant. In addition, a broad diversity of genes was related to organic carbon degradation, and N2 fixation implying these communities has metabolic plasticity that enables survival under oligotrophic conditions. Differences in functional genes were detected among the environments, with higher diversity associated with non-active and microbially stabilized environments in comparison with the active environment. EPS showed a gradient increase from active to microbially stabilized communities, and when combined with functional gene analysis, which revealed genes encoding EPS-degrading enzymes (chitinases, glucoamylase, amylases), supports a putative role of EPS-mediated microbial calcium carbonate precipitation. We propose that carbonate precipitation in marine oolitic biofilms is spatially and temporally controlled by a complex consortium of microbes with diverse physiologies, including

  20. XENOBIOTIC INDUCED ORGAN-SPECIFIC GENE EXPRESSION AND MACRO/MICROARRAY DEVELOPMENT IN MEDAKA (ORYZIAS LATIPES)

    EPA Science Inventory

    As part of an ongoing effort to understand and address the short and long-term consequences of increasing levels of environmental contaminants, we used suppressive subtractive hydridization (SSH) to develop gene expression profiles from Japanese medaka (Oryzias latipes) exposed ...

  1. COMPARATIVE MICROARRAY EXPRESSION ANALYSIS OF SELECTED CANCER RELEVANT GENES IN HYPERTENSIVE RESISTANT VERSUS SUSCEPTIBLE RODENT STRAINS

    EPA Science Inventory

    Hypertension and cancer are prevalent diseases. Epidemiological studies suggest that hypertension may increase the long term risk of cancer. Identification of resistance and/or susceptibility genes using rodent models could provide important insights into the management and treat...

  2. Gene expression profiling of subcutaneous adipose tissue in morbid obesity using a focused microarray: Distinct expression of cell-cycle- and differentiation-related genes

    PubMed Central

    2010-01-01

    Background Obesity results from an imbalance between food intake and energy expenditure, which leads to an excess of adipose tissue. The excess of adipose tissue and adipocyte dysfunction associated with obesity are linked to the abnormal regulation of adipogenesis. The objective of this study was to analyze the expression profile of cell-cycle- and lipid-metabolism-related genes of adipose tissue in morbid obesity. Methods We used a custom-made focused cDNA microarray to determine the adipose tissue mRNA expression profile. Gene expression of subcutaneous abdominal fat samples from 15 morbidly obese women was compared with subcutaneous fat samples from 10 nonobese control patients. The findings were validated in an independent population of 31 obese women and 9 obese men and in an animal model of obesity (Lepob/ob mice) by real-time RT-PCR. Results Microarray analysis revealed that transcription factors that regulate the first stages of adipocyte differentiation, such as CCAAT/enhancer binding protein beta (C/EBPβ) and JUN, were upregulated in the adipose tissues of morbidly obese patients. The expression of peroxisome proliferator-activated receptor gamma (PPARγ), a transcription factor which controls lipid metabolism and the final steps of preadipocyte conversion into mature adipocytes, was downregulated. The expression of three cyclin-dependent kinase inhibitors that regulate clonal expansion and postmitotic growth arrest during adipocyte differentiation was also altered in obese subjects: p18 and p27 were downregulated, and p21 was upregulated. Angiopoietin-like 4 (ANGPTL4), which regulates angiogenesis, lipid and glucose metabolism and it is know to increase dramatically in the early stages of adipocyte differentiation, was upregulated. The expression of C/EBPβ, p18, p21, JUN, and ANGPTL4 presented similar alterations in subcutaneous adipose tissue of Lepob/ob mice. Conclusions Our microarray gene profiling study revealed that the expression of genes

  3. Layered Signaling Regulatory Networks Analysis of Gene Expression Involved in Malignant Tumorigenesis of Non-Resolving Ulcerative Colitis via Integration of Cross-Study Microarray Profiles

    PubMed Central

    Fan, Shengjun; Pan, Zhenyu; Geng, Qiang; Li, Xin; Wang, Yefan; An, Yu; Xu, Yan; Tie, Lu; Pan, Yan; Li, Xuejun

    2013-01-01

    Background Ulcerative colitis (UC) was the most frequently diagnosed inflammatory bowel disease (IBD) and closely linked to colorectal carcinogenesis. By far, the underlying mechanisms associated with the disease are still unclear. With the increasing accumulation of microarray gene expression profiles, it is profitable to gain a systematic perspective based on gene regulatory networks to better elucidate the roles of genes associated with disorders. However, a major challenge for microarray data analysis is the integration of multiple-studies generated by different groups. Methodology/Principal Findings In this study, firstly, we modeled a signaling regulatory network associated with colorectal cancer (CRC) initiation via integration of cross-study microarray expression data sets using Empirical Bayes (EB) algorithm. Secondly, a manually curated human cancer signaling map was established via comprehensive retrieval of the publicly available repositories. Finally, the co-differently-expressed genes were manually curated to portray the layered signaling regulatory networks. Results Overall, the remodeled signaling regulatory networks were separated into four major layers including extracellular, membrane, cytoplasm and nucleus, which led to the identification of five core biological processes and four signaling pathways associated with colorectal carcinogenesis. As a result, our biological interpretation highlighted the importance of EGF/EGFR signaling pathway, EPO signaling pathway, T cell signal transduction and members of the BCR signaling pathway, which were responsible for the malignant transition of CRC from the benign UC to the aggressive one. Conclusions The present study illustrated a standardized normalization approach for cross-study microarray expression data sets. Our model for signaling networks construction was based on the experimentally-supported interaction and microarray co-expression modeling. Pathway-based signaling regulatory networks analysis

  4. Orally administered lactoperoxidase increases expression of the FK506 binding protein 5 gene in epithelial cells of the small intestine of mice: a DNA microarray study.

    PubMed

    Wakabayashi, Hiroyuki; Miyauchi, Hirofumi; Shin, Kouichirou; Yamauchi, Koji; Matsumoto, Ichiro; Abe, Keiko; Takase, Mitsunori

    2007-09-01

    Lactoperoxidase (LPO) is a component of milk and other external secretions. To study the influence of ingested LPO on the digestive tract, we performed DNA microarray analysis of the small intestine of mice administered LPO. LPO administration upregulated 78 genes, including genes involved in metabolism, immunity, apoptosis, and the cell cycle, and downregulated nine genes, including immunity-related genes. The most upregulated gene was FK506 binding protein 5 (FKBP5), a glucocorticoid regulating immunophilin. The upregulation of this gene was confirmed by quantitative RT-PCR in other samples. In situ hybridization revealed that expression of the FKBP5 gene in the crypt epithelial cells of the small intestine was enhanced by LPO. These results suggest that ingested LPO modulates gene expression in the small intestine and especially increases FKBP5 gene expression in the epithelial cells of the intestine.

  5. Virulence Characterization of Salmonella enterica by a New Microarray: Detection and Evaluation of the Cytolethal Distending Toxin Gene Activity in the Unusual Host S. Typhimurium

    PubMed Central

    Figueiredo, Rui; Card, Roderick; Nunes, Carla; AbuOun, Manal; Bagnall, Mary C.; Nunez, Javier; Mendonça, Nuno; Anjum, Muna F.; da Silva, Gabriela Jorge

    2015-01-01

    Salmonella enterica is a zoonotic foodborne pathogen that causes acute gastroenteritis in humans. We assessed the virulence potential of one-hundred and six Salmonella strains isolated from food animals and products. A high through-put virulence genes microarray demonstrated Salmonella Pathogenicity Islands (SPI) and adherence genes were highly conserved, while prophages and virulence plasmid genes were variably present. Isolates were grouped by serotype, and virulence plasmids separated S. Typhimurium in two clusters. Atypical microarray results lead to whole genome sequencing (WGS) of S. Infantis Sal147, which identified deletion of thirty-eight SPI-1 genes. Sal147 was unable to invade HeLa cells and showed reduced mortality in Galleria mellonella infection model, in comparison to a SPI-1 harbouring S. Infantis. Microarray and WGS of S. Typhimurium Sal199, established for the first time in S. Typhimurium presence of cdtB and other Typhi-related genes. Characterization of Sal199 showed cdtB genes were upstream of transposase IS911, and co-expressed with other Typhi-related genes. Cell cycle arrest, cytoplasmic distension, and nuclear enlargement were detected i