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Sample records for functional gene microarray

  1. An Update on Soybean Functional Genomics and Microarray Resources for Gene Discovery and Crop Improvement

    Technology Transfer Automated Retrieval System (TEKTRAN)

    DNA microarrays are powerful tools to analyze the expression patterns of thousands of genes simultaneously. We review recent soybean genomics projects that have produced public-sector resources for this important legume crop. As part of the NSF-sponsored “Soybean Functional Genomics Program”, we hav...

  2. A Bayesian Approach to Pathway Analysis by Integrating Gene–Gene Functional Directions and Microarray Data

    PubMed Central

    Zhao, Yifang; Chen, Ming-Hui; Pei, Baikang; Rowe, David; Shin, Dong-Guk; Xie, Wangang; Yu, Fang; Kuo, Lynn

    2012-01-01

    Many statistical methods have been developed to screen for differentially expressed genes associated with specific phenotypes in the microarray data. However, it remains a major challenge to synthesize the observed expression patterns with abundant biological knowledge for more complete understanding of the biological functions among genes. Various methods including clustering analysis on genes, neural network, Bayesian network and pathway analysis have been developed toward this goal. In most of these procedures, the activation and inhibition relationships among genes have hardly been utilized in the modeling steps. We propose two novel Bayesian models to integrate the microarray data with the putative pathway structures obtained from the KEGG database and the directional gene–gene interactions in the medical literature. We define the symmetric Kullback–Leibler divergence of a pathway, and use it to identify the pathway(s) most supported by the microarray data. Monte Carlo Markov Chain sampling algorithm is given for posterior computation in the hierarchical model. The proposed method is shown to select the most supported pathway in an illustrative example. Finally, we apply the methodology to a real microarray data set to understand the gene expression profile of osteoblast lineage at defined stages of differentiation. We observe that our method correctly identifies the pathways that are reported to play essential roles in modulating bone mass. PMID:23482678

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

    PubMed

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

    2007-06-01

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

  4. Development of an Environmental Functional Gene Microarray for Soil Microbial Communities ▿

    PubMed Central

    McGrath, Ken C.; Mondav, Rhiannon; Sintrajaya, Regina; Slattery, Bill; Schmidt, Susanne; Schenk, Peer M.

    2010-01-01

    Functional attributes of microbial communities are difficult to study, and most current techniques rely on DNA- and rRNA-based profiling of taxa and genes, including microarrays containing sequences of known microorganisms. To quantify gene expression in environmental samples in a culture-independent manner, we constructed an environmental functional gene microarray (E-FGA) consisting of 13,056 mRNA-enriched anonymous microbial clones from diverse microbial communities to profile microbial gene transcripts. A new normalization method using internal spot standards was devised to overcome spotting and hybridization bias, enabling direct comparisons of microarrays. To evaluate potential applications of this metatranscriptomic approach for studying microbes in environmental samples, we tested the E-FGA by profiling the microbial activity of agricultural soils with a low or high flux of N2O. A total of 109 genes displayed expression that differed significantly between soils with low and high N2O emissions. We conclude that mRNA-based approaches such as the one presented here may complement existing techniques for assessing functional attributes of microbial communities. PMID:20851978

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

    PubMed

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

    2016-01-01

    Gene expression data (microarrays and RNA-sequencing data) as well as other kinds of genomic data can be extracted from publicly available genomic data. Here, we explain how to apply multivariate cluster and classification methods on gene expression data. These methods have become very popular and are implemented in freely available software in order to predict the participation of gene products in a specific functional category of interest. Taking into account the availability of data and of these methods, every biological study should apply them in order to obtain knowledge on the organism studied and functional category of interest. A special emphasis is made on the nonlinear kernel classification methods. PMID:25762300

  6. Association of genes with physiological functions by comparative analysis of pooled expression microarray data.

    PubMed

    Chen, Iuan-bor D; Rathi, Vinay K; DeAndrade, Diana S; Jay, Patrick Y

    2013-01-15

    The physiological functions of a tissue in the body are carried out by its complement of expressed genes. Genes that execute a particular function should be more specifically expressed in tissues that perform the function. Given this premise, we mined public microarray expression data to build a database of genes ranked by their specificity of expression in multiple organs. The database permitted the accurate identification of genes and functions known to be specific to individual organs. Next, we used the database to predict transcriptional regulators of brown adipose tissue (BAT) and validated two candidate genes. Based upon hypotheses regarding pathways shared between combinations of BAT or white adipose tissue (WAT) and other organs, we identified genes that met threshold criteria for specific or counterspecific expression in each tissue. By contrasting WAT to the heart and BAT, the two most mitochondria-rich tissues in the body, we discovered a novel function for the transcription factor ESRRG in the induction of BAT genes in white adipocytes. Because the heart and other estrogen-related receptor gamma (ESRRG)-rich tissues do not express BAT markers, we hypothesized that an adipocyte co-regulator acts with ESRRG. By comparing WAT and BAT to the heart, brain, kidney and skeletal muscle, we discovered that an isoform of the transcription factor sterol regulatory element binding transcription factor 1 (SREBF1) induces BAT markers in C2C12 myocytes in the presence of ESRRG. The results demonstrate a straightforward bioinformatic strategy to associate genes with functions. The database upon which the strategy is based is provided so that investigators can perform their own screens. PMID:23170034

  7. 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

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

    PubMed Central

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

    2013-01-01

    We report on the first study trialling a newly-developed, functional gene microarray (FGA) for characterising bacterial and archaeal ammonia oxidisers in activated sludge. Mixed liquor (ML) and media biofilm samples from a full-scale integrated fixed-film activated sludge (IFAS) plant were analysed with the FGA to profile the diversity and relative abundance of ammonia-oxidising archaea and bacteria (AOA and AOB respectively). FGA analyses of AOA and AOB communities revealed ubiquitous distribution of AOA across all samples – an important finding for these newly-discovered and poorly characterised organisms. Results also revealed striking differences in the functional ecology of attached versus suspended communities within the IFAS reactor. Quantitative assessment of AOB and AOA functional gene abundance revealed a dominance of AOB in the ML and approximately equal distribution of AOA and AOB in the media-attached biofilm. Subsequent correlations of functional gene abundance data with key water quality parameters suggested an important functional role for media-attached AOB in particular for IFAS reactor nitrification performance and indicate possible functional redundancy in some IFAS ammonia oxidiser communities. Results from this investigation demonstrate the capacity of the FGA to resolve subtle ecological shifts in key microbial communities in nitrifying activated sludge and indicate its value as a tool for better understanding the linkages between the ecology and performance of these engineered systems. PMID:24155925

  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. Screening and functional pathway analysis of genes associated with pediatric allergic asthma using a DNA microarray

    PubMed Central

    LU, LI-QUN; LIAO, WEI

    2015-01-01

    The present study aimed to identify differentially expressed genes (DEGs) associated with pediatric allergic asthma, and to analyze the functional pathways of the selected target genes, in order to explore the pathogenesis of the disease. The GSE18965 gene expression profile was downloaded from the Gene Expression Omnibus database and was preprocessed. This gene expression profile consisted of seven normal samples and nine samples from patients with pediatric allergic asthma. The DEGs between the normal and pediatric allergic asthma samples were screened using limma package in R, and the cut-off value was set at false discovery rate <0.05 and log fold change >1. Following hierarchical clustering of the DEGs based on the expression profiles, the up- and downregulated genes underwent a functional enrichment analysis by topological approach (P<0.05), using the Database for Annotation, Visualization and Integrated Discovery. A total of 127 DEGs were identified between the normal and pediatric allergic asthma samples. The up- and downregulated genes were significantly enriched in the actin filament-based process and the monosaccharide metabolic process, respectively. Seven downregulated DEGs (M6PR, TPP1, GLB1, NEU1, ACP2, LAMP1 and HGSNAT) were identified in the lysosomal pathway, with P=6.4×10−9. These results suggested that variation in lysosomal function, triggered by the seven downregulated genes, may lead to aberrant functioning of the T lymphocytes, resulting in asthma. Further research regarding the treatment of pediatric allergic asthma through targeting lysosomal function is required. PMID:25633562

  11. Comprehensive Screening of Gene Function and Networks by DNA Microarray Analysis in Japanese Patients with Idiopathic Portal Hypertension

    PubMed Central

    Kotani, Kohei; Kawabe, Joji; Morikawa, Hiroyasu; Akahoshi, Tomohiko; Hashizume, Makoto; Shiomi, Susumu

    2015-01-01

    The functions of genes involved in idiopathic portal hypertension (IPH) remain unidentified. The present study was undertaken to identify the functions of genes expressed in blood samples from patients with IPH through comprehensive analysis of gene expression using DNA microarrays. The data were compared with data from healthy individuals to explore the functions of genes showing increased or decreased expression in patients with IPH. In cluster analysis, no dominant probe group was shown to differ between patients with IPH and healthy controls. In functional annotation analysis using the Database for Annotation Visualization and Integrated Discovery tool, clusters showing dysfunction in patients with IPH involved gene terms related to the immune system. Analysis using network-based pathways revealed decreased expression of adenosine deaminase, ectonucleoside triphosphate diphosphohydrolase 4, ATP-binding cassette, subfamily C, member 1, transforming growth factor-β, and prostaglandin E receptor 2; increased expression of cytochrome P450, family 4, subfamily F, polypeptide 3, and glutathione peroxidase 3; and abnormalities in the immune system, nucleic acid metabolism, arachidonic acid/leukotriene pathways, and biological processes. These results suggested that IPH involved compromised function of immunocompetent cells and that such dysfunction may be associated with abnormalities in nucleic acid metabolism and arachidonic acid/leukotriene-related synthesis/metabolism. PMID:26549939

  12. Pineal function: impact of microarray analysis.

    PubMed

    Klein, David C; Bailey, Michael J; Carter, David A; Kim, Jong-so; Shi, Qiong; Ho, Anthony K; Chik, Constance L; 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

    2010-01-27

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

  13. 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

  14. Screening of differentially expressed genes associated with human glioblastoma and functional analysis using a DNA microarray.

    PubMed

    Wang, Lina; Wei, Bo; Hu, Guozhang; Wang, Le; Bi, Miaomiao; Sun, Zhigang; Jin, Ying

    2015-08-01

    Glioblastoma multiforme (GBM) is the most malignant type of human glioma, and has a poor prognosis. Screening differentially expressed genes (DEGs) in brain tumor samples and normal brain samples is of importance for identifying GBM and to design specific-targeting drugs. The transcriptional profile of GSE30563, containing three genechips of brain tumor samples and three genechips of normal brain samples, was downloaded from Gene Expression Omnibus to identify the DEGs. The differences in the expression of the DEGs in the two different samples were compared through hierarchical biclustering. The co-expression coefficient of the DEGs was calculated using the information from COXPRESdb, the network of the DEGs was constructed and functional enrichment and pathway analysis were performed. Finally, the transcription factors of important DEGs were predicted. A total of 1,006 DEGs, including 368 upregulated and 638 downregulated DEGs, were identified. A close correlation was demonstrated between six important genes, associated with immune response, HLA-DQB1, HLA-DRB1, HLA-DPA1, HLA-B, HLA-DMA and HLA-DRA, and the immune response. Allograft rejection was selected as the most significant pathway. A total of 17 transcription factors, including nuclear factor (NF)-κB and NF-κB1, and their binding sites containing these six DEGs, were also identified. The DEGs, including major histocompatibility complex (MHC) class II, DQβ1, MHC class II, DRβ1, MHC class IB, MHC class II, DMα, MHC class II, DPα1, MHC class II, DRα, may provide novel targets for the diagnosis and treatment of GBM. The transcription factors of these six genes and their binding sites may also provide evidence and direction for identifying target-specific drugs. PMID:25901754

  15. [Gene function and microbial community structure in sulfide minerals bioleaching system based on microarray analysis].

    PubMed

    Shen, Li; Liu, Xueduan; Qiu, Guanzhou

    2008-06-01

    Biohydrometallergy technology received more and more attention because of its simple process, low cost and kind to environment, especially in dealing with low-grade and complex minerals. However, it is difficult to optimize microorganism species and process parameters in bioleaching procedure because of the lack of suitable bacteria and quantitative analysis methods at micro-level for bioleaching system. This has resulted in the low efficiency and poor yield of the target metal in bioleaching. With the development of microarray and bacteria conservation technology, solutions to the above problems were being found. This article summarizes the latest findings on genetic elucidation and the community structure of microorganisms in sulfide minerals bioleaching system, in the aim of providing a better understanding on the significance of cross-field technology of biohydrometallergy and genomics. PMID:18807978

  16. Identification and functional analysis of light-responsive unique or paralogous gene family members in rice using a near genomic gene microarray

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Using a NSF45K-gene-microarray, we performed expression-profiling experiments on 2-week-old light- and dark-grown rice leaf tissue to identify mutants of light-responsive genes. We identified 356 genes that were at least 8-fold light induced genes at FDR of 1.00E-06. Then, we screened rice T-DNA i...

  17. 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

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  19. Functional assessment of time course microarray data

    PubMed Central

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

    2009-01-01

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

  20. 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.

  1. 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

  2. Application of Microarray and Functional-Based Screening Methods for the Detection of Antimicrobial Resistance Genes in the Microbiomes of Healthy Humans

    PubMed Central

    Card, Roderick M.; Warburton, Philip J.; MacLaren, Nikki; Mullany, Peter; Allan, Elaine; Anjum, Muna F.

    2014-01-01

    The aim of this study was to screen for the presence of antimicrobial resistance genes within the saliva and faecal microbiomes of healthy adult human volunteers from five European countries. Two non-culture based approaches were employed to obviate potential bias associated with difficult to culture members of the microbiota. In a gene target-based approach, a microarray was employed to screen for the presence of over 70 clinically important resistance genes in the saliva and faecal microbiomes. A total of 14 different resistance genes were detected encoding resistances to six antibiotic classes (aminoglycosides, β-lactams, macrolides, sulphonamides, tetracyclines and trimethoprim). The most commonly detected genes were erm(B), blaTEM, and sul2. In a functional-based approach, DNA prepared from pooled saliva samples was cloned into Escherichia coli and screened for expression of resistance to ampicillin or sulphonamide, two of the most common resistances found by array. The functional ampicillin resistance screen recovered genes encoding components of a predicted AcrRAB efflux pump. In the functional sulphonamide resistance screen, folP genes were recovered encoding mutant dihydropteroate synthase, the target of sulphonamide action. The genes recovered from the functional screens were from the chromosomes of commensal species that are opportunistically pathogenic and capable of exchanging DNA with related pathogenic species. Genes identified by microarray were not recovered in the activity-based screen, indicating that these two methods can be complementary in facilitating the identification of a range of resistance mechanisms present within the human microbiome. It also provides further evidence of the diverse reservoir of resistance mechanisms present in bacterial populations in the human gut and saliva. In future the methods described in this study can be used to monitor changes in the resistome in response to antibiotic therapy. PMID:24466089

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

    PubMed

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

    2005-03-01

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

  4. Microarrays

    ERIC Educational Resources Information Center

    Plomin, Robert; Schalkwyk, Leonard C.

    2007-01-01

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

  5. Protein microarrays as tools for functional proteomics.

    PubMed

    LaBaer, Joshua; Ramachandran, Niroshan

    2005-02-01

    Protein microarrays present an innovative and versatile approach to study protein abundance and function at an unprecedented scale. Given the chemical and structural complexity of the proteome, the development of protein microarrays has been challenging. Despite these challenges there has been a marked increase in the use of protein microarrays to map interactions of proteins with various other molecules, and to identify potential disease biomarkers, especially in the area of cancer biology. In this review, we discuss some of the promising advances made in the development and use of protein microarrays. PMID:15701447

  6. Coexpression analysis of human genes across many microarray data sets.

    PubMed

    Lee, Homin K; Hsu, Amy K; Sajdak, Jon; Qin, Jie; Pavlidis, Paul

    2004-06-01

    We present a large-scale analysis of mRNA coexpression based on 60 large human data sets containing a total of 3924 microarrays. We sought pairs of genes that were reliably coexpressed (based on the correlation of their expression profiles) in multiple data sets, establishing a high-confidence network of 8805 genes connected by 220,649 "coexpression links" that are observed in at least three data sets. Confirmed positive correlations between genes were much more common than confirmed negative correlations. We show that confirmation of coexpression in multiple data sets is correlated with functional relatedness, and show how cluster analysis of the network can reveal functionally coherent groups of genes. Our findings demonstrate how the large body of accumulated microarray data can be exploited to increase the reliability of inferences about gene function. PMID:15173114

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

    PubMed Central

    2012-01-01

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

  8. A review of independent component analysis application to microarray gene expression data

    PubMed Central

    Kong, Wei; Vanderburg, Charles R.; Gunshin, Hiromi; Rogers, Jack T.; Huang, Xudong

    2010-01-01

    Independent component analysis (ICA) methods have received growing attention as effective data-mining tools for microarray gene expression data. As a technique of higher-order statistical analysis, ICA is capable of extracting biologically relevant gene expression features from microarray data. Herein we have reviewed the latest applications and the extended algorithms of ICA in gene clustering, classification, and identification. The theoretical frameworks of ICA have been described to further illustrate its feature extraction function in microarray data analysis. PMID:19007336

  9. 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

  10. 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

  11. Consensus gene regulatory networks: combining multiple microarray gene expression datasets

    NASA Astrophysics Data System (ADS)

    Peeling, Emma; Tucker, Allan

    2007-09-01

    In this paper we present a method for modelling gene regulatory networks by forming a consensus Bayesian network model from multiple microarray gene expression datasets. Our method is based on combining Bayesian network graph topologies and does not require any special pre-processing of the datasets, such as re-normalisation. We evaluate our method on a synthetic regulatory network and part of the yeast heat-shock response regulatory network using publicly available yeast microarray datasets. Results are promising; the consensus networks formed provide a broader view of the potential underlying network, obtaining an increased true positive rate over networks constructed from a single data source.

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

    PubMed

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

    2014-01-25

    Gene set analysis (GSA) incorporates biological information into statistical knowledge to identify gene sets differently expressed between two or more phenotypes. It allows us to gain an insight into the functional working mechanism of cells beyond the detection of differently expressed gene sets. In order to evaluate the competence of GSA approaches, three self-contained GSA approaches with different statistical methods were chosen; Category, Globaltest and Hotelling's T(2) together with their assayed power to identify the differences expressed via simulation and real microarray data. The Category does not take care of the correlation structure, while the other two deal with correlations. In order to perform these methods, R and Bioconductor were used. Furthermore, venous thromboembolism and acute lymphoblastic leukemia microarray data were applied. The results of three GSAs showed that the competence of these methods depends on the distribution of gene expression in a dataset. It is very important to assay the distribution of gene expression data before choosing the GSA method to identify gene sets differently expressed between phenotypes. On the other hand, assessment of common genes among significant gene sets indicated that there was a significant agreement between the result of GSA and the findings of biologists. PMID:24012817

  13. Washing scaling of GeneChip microarray expression

    PubMed Central

    2010-01-01

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

  14. 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

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

    PubMed

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

    2016-03-01

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

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

    PubMed Central

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

    2015-01-01

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

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

    PubMed

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

    2015-01-01

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

  18. Amygdala-enriched genes identified by microarray technology are restricted to specific amygdaloid subnuclei

    PubMed Central

    Zirlinger, Mariela; Kreiman, Gabriel; Anderson, David J.

    2001-01-01

    Microarray technology represents a potentially powerful method for identifying cell type- and regionally restricted genes expressed in the brain. Here we have combined a microarray analysis of differential gene expression among five selected brain regions, including the amygdala, cerebellum, hippocampus, olfactory bulb, and periaqueductal gray, with in situ hybridization. On average, 0.3% of the 34,000 genes interrogated were highly enriched in each of the five regions, relative to the others. In situ hybridization performed on a subset of amygdala-enriched genes confirmed in most cases the overall region-specificity predicted by the microarray data and identified additional sites of brain expression not examined on the microarrays. Strikingly, the majority of these genes exhibited boundaries of expression within the amygdala corresponding to cytoarchitectonically defined subnuclei. These results define a unique set of molecular markers for amygdaloid subnuclei and provide tools to genetically dissect their functional roles in different emotional behaviors. PMID:11320257

  19. 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

  20. 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.

  1. Xylella fastidiosa gene expression analysis by DNA microarrays

    PubMed Central

    2009-01-01

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

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

    PubMed

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

    2016-01-10

    Microarray (MA) and high-throughput sequencing are two commonly used detection systems for global gene expression profiling. Although these two systems are frequently used in parallel, the differences in their final results have not been examined thoroughly. Transcriptomic analysis of housekeeping (HK) genes provides a unique opportunity to reliably examine the technical difference between these two systems. We investigated here the structure, genome location, expression quantity, microarray probe coverage, as well as biological functions of differentially identified human HK genes by 9 MA and 6 sequencing studies. These in-depth analyses allowed us to discover, for the first time, a subset of transcripts encoding membrane, cell surface and nuclear proteins that were prone to differential identification by the two platforms. We hope that the discovery can aid the future development of these technologies for comprehensive transcriptomic studies. PMID:26407868

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

    PubMed Central

    2010-01-01

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

  4. MIClique: An algorithm to identify differentially coexpressed disease gene subset from microarray data.

    PubMed

    Zhang, Huanping; Song, Xiaofeng; Wang, Huinan; Zhang, Xiaobai

    2009-01-01

    Computational analysis of microarray data has provided an effective way to identify disease-related genes. Traditional disease gene selection methods from microarray data such as statistical test always focus on differentially expressed genes in different samples by individual gene prioritization. These traditional methods might miss differentially coexpressed (DCE) gene subsets because they ignore the interaction between genes. In this paper, MIClique algorithm is proposed to identify DEC gene subsets based on mutual information and clique analysis. Mutual information is used to measure the coexpression relationship between each pair of genes in two different kinds of samples. Clique analysis is a commonly used method in biological network, which generally represents biological module of similar function. By applying the MIClique algorithm to real gene expression data, some DEC gene subsets which correlated under one experimental condition but uncorrelated under another condition are detected from the graph of colon dataset and leukemia dataset. PMID:20169000

  5. 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

  6. 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

  7. 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...

  8. DNA microarrays detect effects of soil contamination on Arabidopsis thaliana gene expression.

    PubMed

    Magrini, Kimberly D; Basu, Amit; Spotila, James R; Avery, Harold W; Bergman, Lawrence W; Hammond, Rachel; Anandan, Shivanthi

    2008-12-01

    Soil contamination, such as heavy metals and benzene compounds, is a widespread problem on military installations. It is important to be able to determine the effects of soil contamination before any adverse effects appear in organisms in surrounding areas. We examined gene expression in Arabidopsis thaliana grown in soil from three sites at the Radford Army Ammunition Plant in Radford, Virginia, USA, using DNA microarrays. We analyzed soil, germination, and growth rate to compare with the microarray data. Soil contamination affected both external phenotype and gene expression. Plants grown in soil with high levels of contaminants were chloritic and were smaller than control plants grown in potting soil. Plants grown in soil with the highest copper concentration had the lowest growth rates and had genes up-regulated across several functional groups. Plants grown in soils with elevated lead had many genes down-regulated that were related to photosystem II, metabolism, cellular transport, and protein synthesis. Genes consistently up-regulated across most microarrays were genes related to photosystem I, genes related to water deprivation and oxidative stress response, heat shock proteins, and toxin catabolism genes such as glutathiones. DNA microarrays, in concert with a model genetic organism such as A. thaliana, were an effective assessment tool to determine the presence of toxic substances in soil at a site used for the production of military explosives. PMID:18613744

  9. 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

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

    PubMed Central

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

    2012-01-01

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

  11. 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

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

    NASA Astrophysics Data System (ADS)

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

    2003-07-01

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

  13. 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

  14. RNAi targeting GPR4 influences HMEC-1 gene expression by microarray analysis

    PubMed Central

    Ren, Juan; Zhang, Yuelang; Cai, Hui; Ma, Hongbing; Zhao, Dongli; Zhang, Xiaozhi; Li, Zongfang; Wang, Shufeng; Wang, Jiangsheng; Liu, Rui; Li, Yi; Qian, Jiansheng; Wei, Hongxia; Niu, Liying; Liu, Yan; Xiao, Lisha; Ding, Muyang; Jiang, Shiwen

    2014-01-01

    G-protein coupled receptor 4 (GPR4) belongs to a protein family comprised of 3 closely related G protein-coupled receptors. Recent studies have shown that GPR4 plays important roles in angiogenesis, proton sensing, and regulating tumor cells as an oncogenic gene. How GPR4 conducts its functions? Rare has been known. In order to detect the genes related to GPR4, microarray technology was employed. GPR4 is highly expressed in human vascular endothelial cell HMEC-1. Small interfering RNA against GPR4 was used to knockdown GPR4 expression in HMEC-1. Then RNA from the GPR4 knockdown cells and control cells were analyzed through genome microarray. Microarray results shown that among the whole genes and expressed sequence tags, 447 differentially expressed genes were identified, containing 318 up-regulated genes and 129 down-regulated genes. These genes whose expression dramatically changed may be involved in the GPR4 functions. These genes were related to cell apoptosis, cytoskeleton and signal transduction, cell proliferation, differentiation and cell-cycle regulation, gene transcription and translation and cell material and energy metabolism. PMID:24753754

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

    PubMed Central

    2013-01-01

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

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

    PubMed

    Ishihara, Takeaki; Sato, Yukiyo; Takahashi, Hideki

    2015-01-01

    The complex process for host-plant resistance to viruses is precisely regulated by a number of genes and signaling compounds. Thus, global gene expression analysis can provide a powerful tool to grasp the complex molecular network for resistance to viruses. The procedures for comparative global gene expression profiling of virus-resistant and control plants by microarray analysis include RNA extraction, cDNA synthesis, cRNA labeling, hybridization, array scanning, and data mining steps. There are several platforms for the microarray analysis. Commercial services for the steps from cDNA synthesis to array scanning are now widely available; however, the data manipulation step is highly dependent on the experimental design and research focus. The protocols presented here are optimized for analyzing global gene expression during the R gene-conferred defense response using commercial oligonucleotide-based arrays. We also demonstrate a technique to screen for differentially expressed genes using Excel software and a simple Internet tool-based data mining approach for characterizing the identified genes. PMID:25287505

  17. Identification of Genes Expressed in Hyperpigmented Skin Using Meta-Analysis of Microarray Data Sets.

    PubMed

    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

    2015-10-01

    More than 375 genes have been identified that are involved in regulating skin pigmentation and these act during development, survival, differentiation, and/or responses of melanocytes to the environment. Many of these 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 with less pigmented skin to identify genes responsible for these differences. The rationale and goal for this study was to perform a meta-analysis on these 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 these individual studies alone. The meta-analysis demonstrates that 1,271 probes representing 921 genes are differentially expressed at significant levels in the 5 microarray data sets compared, providing new insights into the variety of genes involved in determining skin phenotype. Immunohistochemistry was used to validate two of these markers at the protein level (TRIM63 and QPCT), and we discuss the possible functions of these genes in regulating skin physiology. PMID:25950827

  18. 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

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

    PubMed Central

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

    2009-01-01

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

  20. 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. PMID:21392280

  1. Estimating RNA-quality using GeneChip microarrays

    PubMed Central

    2012-01-01

    Background Microarrays are a powerful tool for transcriptome analysis. Best results are obtained using high-quality RNA samples for preparation and hybridization. Issues with RNA integrity can lead to low data quality and failure of the microarray experiment. Results Microarray intensity data contains information to estimate the RNA quality of the sample. We here study the interplay of the characteristics of RNA surface hybridization with the effects of partly truncated transcripts on probe intensity. The 3′/5′ intensity gradient, the basis of microarray RNA quality measures, is shown to depend on the degree of competitive binding of specific and of non-specific targets to a particular probe, on the degree of saturation of the probes with bound transcripts and on the distance of the probe from the 3′-end of the transcript. Increasing degrees of non-specific hybridization or of saturation reduce the 3′/5′ intensity gradient and if not taken into account, this leads to biased results in common quality measures for GeneChip arrays such as affyslope or the control probe intensity ratio. We also found that short probe sets near the 3′-end of the transcripts are prone to non-specific hybridization presumable because of inaccurate positional assignment and the existence of transcript isoforms with variable 3′ UTRs. Poor RNA quality is associated with a decreased amount of RNA material hybridized on the array paralleled by a decreased total signal level. Additionally, it causes a gene-specific loss of signal due to the positional bias of transcript abundance which requires an individual, gene-specific correction. We propose a new RNA quality measure that considers the hybridization mode. Graphical characteristics are introduced allowing assessment of RNA quality of each single array (‘tongs plot’ and ‘degradation hook’). Furthermore, we suggest a method to correct for effects of RNA degradation on microarray intensities. Conclusions The presented RNA

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  3. 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.

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

    PubMed Central

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

    2007-01-01

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

  5. 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.

  6. GeneMesh: a web-based microarray analysis tool for relating differentially expressed genes to MeSH terms

    PubMed Central

    2010-01-01

    Background An important objective of DNA microarray-based gene expression experimentation is determining inter-relationships that exist between differentially expressed genes and biological processes, molecular functions, cellular components, signaling pathways, physiologic processes and diseases. Results Here we describe GeneMesh, a web-based program that facilitates analysis of DNA microarray gene expression data. GeneMesh relates genes in a query set to categories available in the Medical Subject Headings (MeSH) hierarchical index. The interface enables hypothesis driven relational analysis to a specific MeSH subcategory (e.g., Cardiovascular System, Genetic Processes, Immune System Diseases etc.) or unbiased relational analysis to broader MeSH categories (e.g., Anatomy, Biological Sciences, Disease etc.). Genes found associated with a given MeSH category are dynamically linked to facilitate tabular and graphical depiction of Entrez Gene information, Gene Ontology information, KEGG metabolic pathway diagrams and intermolecular interaction information. Expression intensity values of groups of genes that cluster in relation to a given MeSH category, gene ontology or pathway can be displayed as heat maps of Z score-normalized values. GeneMesh operates on gene expression data derived from a number of commercial microarray platforms including Affymetrix, Agilent and Illumina. Conclusions GeneMesh is a versatile web-based tool for testing and developing new hypotheses through relating genes in a query set (e.g., differentially expressed genes from a DNA microarray experiment) to descriptors making up the hierarchical structure of the National Library of Medicine controlled vocabulary thesaurus, MeSH. The system further enhances the discovery process by providing links between sets of genes associated with a given MeSH category to a rich set of html linked tabular and graphic information including Entrez Gene summaries, gene ontologies, intermolecular interactions

  7. Fibrin-mediated lentivirus gene transfer: implications for lentivirus microarrays

    PubMed Central

    Raut, Shruti; Lei, Pedro; Padmashali, Roshan; Andreadis, Stelios T.

    2010-01-01

    We employed fibrin hydrogel as bioactive matrix for lentivirus mediated gene transfer. Fibrin-mediated gene transfer was highly efficient and exhibited strong dependence on fibrinogen concentration. Efficient gene transfer was achieved with fibrinogen concentration between 3.75 – 7.5 mg/mL. Lower fibrinogen concentrations resulted in diffusion of virus out of the gel while higher concentrations led to ineffective fibrin degradation by target cells. Addition of fibrinolytic inhibitors decreased gene transfer in a dose-dependent manner suggesting that fibrin degradation by target cells may be necessary for successful gene delivery. Under these conditions transduction may be limited only to cells interacting with the matrix thereby providing a method for spatially localized gene delivery. Indeed, when lentivirus-containing fibrin microgels were spotted in an array format gene transfer was confined to virus-containing fibrin spots with minimal cross-contamination between neighboring sites. Collectively, our data suggest that fibrin may provide an effective matrix for spatially-localized gene delivery with potential applications in high-throughput lentiviral microarrays and in regenerative medicine. PMID:20153386

  8. 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

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

    PubMed Central

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

    2005-01-01

    Background Interpretation of simple microarray experiments is usually based on the fold-change of gene expression between a reference and a "treated" sample where the treatment can be of many types from drug exposure to genetic variation. Interpretation of the results usually combines lists of differentially expressed genes with previous knowledge about their biological function. Here we evaluate a method – based on the PageRank algorithm employed by the popular search engine Google – that tries to automate some of this procedure to generate prioritized gene lists by exploiting biological background information. Results GeneRank is an intuitive modification of PageRank that maintains many of its mathematical properties. It combines gene expression information with a network structure derived from gene annotations (gene ontologies) or expression profile correlations. Using both simulated and real data we find that the algorithm offers an improved ranking of genes compared to pure expression change rankings. Conclusion Our modification of the PageRank algorithm provides an alternative method of evaluating microarray experimental results which combines prior knowledge about the underlying network. GeneRank offers an improvement compared to assessing the importance of a gene based on its experimentally observed fold-change alone and may be used as a basis for further analytical developments. PMID:16176585

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

    PubMed Central

    Baty, Florent; Jaeger, Daniel; Preiswerk, Frank; Schumacher, Martin M; Brutsche, Martin H

    2008-01-01

    Background Multivariate ordination methods are powerful tools for the exploration of complex data structures present in microarray data. These methods have several advantages compared to common gene-by-gene approaches. However, due to their exploratory nature, multivariate ordination methods do not allow direct statistical testing of the stability of genes. Results In this study, we developed a computationally efficient algorithm for: i) the assessment of the significance of gene contributions and ii) the identification of sample outliers in multivariate analysis of microarray data. The approach is based on the use of resampling methods including bootstrapping and jackknifing. A statistical package of R functions was developed. This package includes tools for both inferring the statistical significance of gene contributions and identifying outliers among samples. Conclusion The methodology was successfully applied to three published data sets with varying levels of signal intensities. Its relevance was compared with alternative methods. Overall, it proved to be particularly effective for the evaluation of the stability of microarray data. PMID:18570644

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

    PubMed

    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

  12. 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

  13. Detection of influent virulence and resistance genes in microarray data through quasi likelihood modeling.

    PubMed

    Romeo, José S; Torres-Avilés, Francisco; López-Kleine, Liliana

    2013-02-01

    Publicly available genomic data are a great source of biological knowledge that can be extracted when appropriate data analysis is used. Predicting the biological function of genes is of interest to understand molecular mechanisms of virulence and resistance in pathogens and hosts and is important for drug discovery and disease control. This is commonly done by searching for similar gene expression behavior. Here, we used publicly available Streptococcus pyogenes microarray data obtained during primate infection to identify genes that have a potential influence on virulence and Phytophtora infestance inoculated tomato microarray data to identify genes potentially implicated in resistance processes. This approach goes beyond co-expression analysis. We employed a quasi-likelihood model separated by primate gender/inoculation condition to model median gene expression of known virulence/resistance factors. Based on this model, an influence analysis considering time course measurement was performed to detect genes with atypical expression. This procedure allowed for the detection of genes potentially implicated in the infection process. Finally, we discuss the biological meaning of these results, showing that influence analysis is an efficient and useful alternative for functional gene prediction. PMID:23296985

  14. Microarray data on gene modulation by HIV-1 in immune cells: 2000-2006.

    PubMed

    Giri, Malavika S; Nebozhyn, Michael; Showe, Louise; Montaner, Luis J

    2006-11-01

    Here, we review 34 HIV microarray studies in human immune cells over the period of 2000-March 2006 with emphasis on analytical approaches used and conceptual advances on HIV modulation of target cells (CD4 T cell, macrophage) and nontargets such as NK cell, B cell, and dendritic cell subsets. Results to date address advances on gene modulation associated with immune dysregulation, susceptibility to apoptosis, virus replication, and viral persistence following in vitro or in vivo infection/exposure to HIV-1 virus or HIV-1 accessory proteins. In addition to gene modulation associated with known functional correlates of HIV infection and replication (e.g., T cell apoptosis), microarray data have yielded novel, potential mechanisms of HIV-mediated pathogenesis such as modulation of cholesterol biosynthetic genes in CD4 T cells (relevant to virus replication and infectivity) and modulation of proteasomes and histone deacetylases in chronically infected cell lines (relevant to virus latency). Intrinsic challenges in summarizing gene modulation studies remain in development of sound approaches for comparing data obtained using different platforms and analytical tools, deriving unifying concepts to distil the large volumes of data collected, and the necessity to impose a focus for validation on a small fraction of genes. Notwithstanding these challenges, the field overall continues to demonstrate progress in expanding the pool of target genes validated to date in in vitro and in vivo datasets and understanding the functional correlates of gene modulation to HIV-1 pathogenesis in vivo. PMID:16940334

  15. 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

  16. An Efficient Ensemble Learning Method for Gene Microarray Classification

    PubMed Central

    Shadgar, Bita

    2013-01-01

    The gene microarray analysis and classification have demonstrated an effective way for the effective diagnosis of diseases and cancers. However, it has been also revealed that the basic classification techniques have intrinsic drawbacks in achieving accurate gene classification and cancer diagnosis. On the other hand, classifier ensembles have received increasing attention in various applications. Here, we address the gene classification issue using RotBoost ensemble methodology. This method is a combination of Rotation Forest and AdaBoost techniques which in turn preserve both desirable features of an ensemble architecture, that is, accuracy and diversity. To select a concise subset of informative genes, 5 different feature selection algorithms are considered. To assess the efficiency of the RotBoost, other nonensemble/ensemble techniques including Decision Trees, Support Vector Machines, Rotation Forest, AdaBoost, and Bagging are also deployed. Experimental results have revealed that the combination of the fast correlation-based feature selection method with ICA-based RotBoost ensemble is highly effective for gene classification. In fact, the proposed method can create ensemble classifiers which outperform not only the classifiers produced by the conventional machine learning but also the classifiers generated by two widely used conventional ensemble learning methods, that is, Bagging and AdaBoost. PMID:24024194

  17. Subpicomolar Iron Sensing Platform Based on Functional Lipid Monolayer Microarrays.

    PubMed

    Kenaan, Ahmad; Nguyen, Tuyen D; Dallaporta, Hervé; Raimundo, Jean-Manuel; Charrier, Anne M

    2016-04-01

    We report herein the fabrication of novel microarrays based on air-stable functional lipid monolayers over silicon using a combination of e-beam lithography and lift-off. We demonstrate these microarrays can be use as ultrasensitive platform for Kelvin probe force microscopy in sensing experiments. Specificity of the detection is given by the functional group grafted at the lipid headgroup. The arrays developed for the detection of ferric ions, Fe(3+), using a γ-pyrone derivative chelator, demonstrate subpicomolar limit of detection with high specificity. In addition, the technique takes advantage of the structure of the array with the silicon areas playing the role of reference for the measurement, and we determine critical pattern dimensions below which the probe size/shape impacts the measured results. PMID:26974586

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

    PubMed Central

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

    2015-01-01

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

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

    PubMed Central

    2010-01-01

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

  20. DNA Microarray Detection of Antimicrobial Resistance Genes in Bacteria Co-Cultured from Swine Feces

    Technology Transfer Automated Retrieval System (TEKTRAN)

    One factor leading to the spread of antimicrobial resistance (AR) in bacteria is the horizontal transfer of resistance genes. To study this, a DNA microarray was recently developed to detect these genes. To maximize the capability of this microarray, probes were designed and added to detect all AR g...

  1. 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...

  2. Electrosonic ejector microarray for drug and gene delivery.

    PubMed

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

    2008-04-01

    We report on development and experimental characterization of a novel cell manipulation device-the electrosonic ejector microarray-which establishes a pathway for drug and/or gene delivery with control of biophysical action on the length scale of an individual cell. The device comprises a piezoelectric transducer for ultrasound wave generation, a reservoir for storing the sample mixture and a set of acoustic horn structures that form a nozzle array for focused application of mechanical energy. The nozzles are micromachined in silicon or plastic using simple and economical batch fabrication processes. When the device is driven at a particular resonant frequency of the acoustic horn structures, the sample mixture of cells and desired transfection agents/molecules suspended in culture medium is ejected from orifices located at the nozzle tips. During sample ejection, focused mechanical forces (pressure and shear) are generated on a microsecond time scale (dictated by nozzle size/geometry and ejection velocity) resulting in identical "active" microenvironments for each ejected cell. This process enables a number of cellular bioeffects, from uptake of small molecules and gene delivery/transfection to cell lysis. Specifically, we demonstrate successful calcein uptake and transfection of DNA plasmid encoding green fluorescent protein (GFP) into human malignant glioma cells (cell line LN443) using electrosonic microarrays with 36, 45 and 50 mum diameter nozzle orifices and operating at ultrasound frequencies between 0.91 and 0.98 MHz. Our results suggest that efficacy and the extent of bioeffects are mainly controlled by nozzle orifice size and the localized intensity of the applied acoustic field. PMID:17994280

  3. 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

  4. Microarray analysis of differentially expressed gene responses to bisphenol A in Arabidopsis.

    PubMed

    Tian, Yong-Sheng; Jin, Xiao-Fen; Fu, Xiao-Yan; Zhao, Wei; Han, Hong-Juan; Zhu, Bo; Liu, Man-; Yao, Quan-Hong

    2014-08-01

    Environmental levels of bisphenol A (BPA) are a global concern because the compound can cause damage to reproductive organs, the thyroid gland, and brain tissues at developmental stages. Plants are important in removing BPA from the atmosphere, soil, and water. However, knowledge on the mechanism by which plants respond to this compound is limited. To determine the response mechanism of plants to BPA, we used a microarray system to analyze the gene expression patterns of Arabidopsis thaliana after irrigation with 3.0 mM BPA. We identified 651 genes that were differentially expressed upregulated and 470 genes that were downregulated by BPA. These genes may specifically contribute to BPA uptake, transformation, conjugation, and compartmentation in plants. The potential function of upregulated genes in plant defense against BPA was also determined. PMID:25056792

  5. 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

  6. [Differential gene expression analysis by DNA microarrays technology and its application in molecular oncology].

    PubMed

    Frolov, A E; Godwin, A K; Favorova, O O

    2003-01-01

    Accumulation of genetic and epigenetic aberrations leads to malignant transformation of normal cells. Functional studies of cancer using genomic and proteomic tools will help to reveal the true complexity of the processes leading to cancer development in humans. Until recently, diagnosis and prognosis of cancer was based on conventional pathologic criteria and epidemiological evidence. Certain tumors were divided only into relatively broad histological and morphological subcategories. Rapidly developing methods of differential gene expression analysis promote the search for clinically relevant genes changing their expression levels during malignant transformation. DNA microarrays offer a unique possibility to rapidly assess the global expression picture of thousands genes in any given time point and compare the detailed combinatory analysis results of global expression profiles for normal and malignant cells at various functional stages or separate experimental conditions. Acquisition of such "genetic portraits" allows searching for regularity and difference in expression patterns of certain genes, understanding their function and pathological importance, and ultimately developing the "molecular nosology" of cancer. This review describes the basis of DNA microarray technology and methodology, and focuses on their applications in molecular classification of tumors, drug sensitivity and resistance studies, and identification of biological markers of cancer. PMID:12942629

  7. Gene expression profiling in mitochondrial disease: assessment of microarray accuracy by high-throughput Q-PCR.

    PubMed

    Beckman, Kenneth B; Lee, Kathleen Y; Golden, Tamara; Melov, Simon

    2004-09-01

    Mitochondrial diseases are a heterogeneous array of disorders with a complex etiology. Use of microarrays as a tool to investigate complex human disease is increasingly common, however, a principle drawback of microarrays is their limited dynamic range, due to the poor quantification of weak signals. Although it is generally understood that low-intensity microarray 'spots' may be unreliable, there exists little documentation of their accuracy. Quantitative PCR (Q-PCR) is frequently used to validate microarray data, yet few Q-PCR validation studies have focused on the accuracy of low-intensity microarray signals. Hence, we have used Q-PCR to systematically assess microarray accuracy as a function of signal strength in a mouse model of mitochondrial disease, the superoxide dismutase 2 (SOD2) nullizygous mouse. We have focused on a unique category of data--spots with only one weak signal in a two-dye comparative hybridization--and show that such 'high-low' signal intensities are common for differentially expressed genes. This category of differential expression may be more important in mitochondrial disease in which there are often mosaic expression patterns due to the idiosyncratic distribution of mutant mtDNA in heteroplasmic individuals. Using RNA from the SOD2 mouse, we found that when spotted cDNA microarray data are filtered for quality (low variance between many technical replicates) and spot intensity (above a negative control threshold in both channels), there is an excellent quantitative concordance with Q-PCR (R2 = 0.94). The accuracy of gene expression ratios from low-intensity spots (R2 = 0.27) and 'high-low' spots (R2 = 0.32) is considerably lower. Our results should serve as guidelines for microarray interpretation and the selection of genes for validation in mitochondrial disorders. PMID:16120406

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

    EPA Science Inventory

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

  9. A statistical method to incorporate biological knowledge for generating testable novel gene regulatory interactions from microarray experiments

    PubMed Central

    Larsen, Peter; Almasri, Eyad; Chen, Guanrao; Dai, Yang

    2007-01-01

    Background The incorporation of prior biological knowledge in the analysis of microarray data has become important in the reconstruction of transcription regulatory networks in a cell. Most of the current research has been focused on the integration of multiple sets of microarray data as well as curated databases for a genome scale reconstruction. However, individual researchers are more interested in the extraction of most useful information from the data of their hypothesis-driven microarray experiments. How to compile the prior biological knowledge from literature to facilitate new hypothesis generation from a microarray experiment is the focus of this work. We propose a novel method based on the statistical analysis of reported gene interactions in PubMed literature. Results Using Gene Ontology (GO) Molecular Function annotation for reported gene regulatory interactions in PubMed literature, a statistical analysis method was proposed for the derivation of a likelihood of interaction (LOI) score for a pair of genes. The LOI-score and the Pearson correlation coefficient of gene profiles were utilized to check if a pair of query genes would be in the above specified interaction. The method was validated in the analysis of two gene sets formed from the yeast Saccharomyces cerevisiae cell cycle microarray data. It was found that high percentage of identified interactions shares GO Biological Process annotations (39.5% for a 102 interaction enriched gene set and 23.0% for a larger 999 cyclically expressed gene set). Conclusion This method can uncover novel biologically relevant gene interactions. With stringent confidence levels, small interaction networks can be identified for further establishment of a hypothesis testable by biological experiment. This procedure is computationally inexpensive and can be used as a preprocessing procedure for screening potential biologically relevant gene pairs subject to the analysis with sophisticated statistical methods. PMID

  10. 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.

  11. Microarray based analysis of gene regulation by microRNA in intervertebral disc degeneration

    PubMed Central

    HU, PENG; FENG, BO; WANG, GUANGLIN; NING, BIN; JIA, TANGHONG

    2015-01-01

    The present study aimed to explore the underlying mechanism of the development of intervertebral disc degeneration (IDD) by bioinformatics based on microarray datasets. GSE 19943 and GSE 34095 datasets downloaded from Gene Expression Omnibus data were used to screen the differentially expressed genes (DEGs) in IDD. The correlation between microRNAs and target genes was investigated using different algorithms. The underlying molecular mechanisms of the target genes were then explored using Kyoto Encyclopedia of Genes and Genomes pathway and Gene Ontology function enrichment analysis. A total of 9 differentially expressed microRNAs, including 3 down- and 6 upregulated microRNAs and 850 DEGs were identified in tissue from patients with IDD. Two regulation networks of the target genes by microRNAs were constructed, including 33 upregulated microRNA-target gene pairs and 4 downregulated microRNA-target gene pairs. Certain target genes had been demonstrated to be involved in IDD progression via various pathways, including in the cell cycle and pathways in cancer. In addition, two important microRNAs (microRNA-222 and microRNA-589) were identified that were pivotal for the development of IDD, and their target genes, CDKNAB and SMAD4. In conclusion, a comprehensive miRNA-target gene regulatory network was constructed, which was found to be important in IDD progression. PMID:26134418

  12. Microarray based analysis of gene regulation by microRNA in intervertebral disc degeneration.

    PubMed

    Hu, Peng; Feng, Bo; Wang, Guanglin; Ning, Bin; Jia, Tanghong

    2015-10-01

    The present study aimed to explore the underlying mechanism of the development of intervertebral disc degeneration (IDD) by bioinformatics based on microarray datasets. GSE 19943 and GSE 34095 datasets downloaded from Gene Expression Omnibus data were used to screen the differentially expressed genes (DEGs) in IDD. The correlation between microRNAs and target genes was investigated using different algorithms. The underlying molecular mechanisms of the target genes were then explored using Kyoto Encyclopedia of Genes and Genomes pathway and Gene Ontology function enrichment analysis. A total of 9 differentially expressed microRNAs, including 3 down‑ and 6 upregulated microRNAs and 850 DEGs were identified in tissue from patients with IDD. Two regulation networks of the target genes by microRNAs were constructed, including 33 upregulated microRNA‑target gene pairs and 4 downregulated microRNA‑target gene pairs. Certain target genes had been demonstrated to be involved in IDD progression via various pathways, including in the cell cycle and pathways in cancer. In addition, two important microRNAs (microRNA‑222 and microRNA‑589) were identified that were pivotal for the development of IDD, and their target genes, CDKNAB and SMAD4. In conclusion, a comprehensive miRNA‑target gene regulatory network was constructed, which was found to be important in IDD progression. PMID:26134418

  13. Functionally associated targets in mantle cell lymphoma as defined by DNA microarrays and RNA interference.

    PubMed

    Ortega-Paino, Eva; Fransson, Johan; Ek, Sara; Borrebaeck, Carl A K

    2008-02-01

    Mantle cell lymphoma (MCL) is a non-Hodgkin lymphoma with poor prognosis. Its hallmark is the translocation t(11:14)q (13;32), leading to overexpression of cyclin D1, a positive regulator of the cell cycle. As cyclin D1 up-regulation is not sufficient for inducing malignant transformation, we combined DNA microarray and RNA interference (RNAi) approaches to identify novel deregulated genes involved in the progression of MCL. DNA microarray analysis identified 46 genes specifically up-regulated in MCL compared with normal B cells; 20 of these were chosen for further studies based on their cellular functions, such as growth and proliferation. The Granta 519 cell line was selected as an MCL in vitro model, to set up the RNAi protocol. To confirm the functionality of overexpression of the 20 disease-associated genes, they were knocked down using small interfering RNAs (siRNAs). In particular, knockdown of 3 genes, encoding the hepatoma-derived growth factor related protein 3 (HDGFRP3), the frizzled homolog 2 (FZD2), and the dual specificity phosphatase 5 (DUSP5), induced proliferative arrest in Granta 519 MCL cells. These genes emerged as functionally associated in MCL, in relation to growth and survival, and interfering with their function would increase insight into lymphoma growth regulation, potentially leading to novel clinical intervention modalities. PMID:18024791

  14. 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

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

    PubMed Central

    2012-01-01

    Background Hepatitis C virus (HCV) causes liver fibrosis that may lead to liver cirrhosis or hepatocellular carcinoma (HCC), and may partially depend on infecting viral genotype. HCV genotype 3a is being more common in Asian population, especially Pakistan; the detail mechanism of infection still needs to be explored. In this study, we investigated and compared the gene expression profile between initial fibrosis stage and cirrhotic 3a genotype patients. Methods Gene expression profiling of human liver tissues was performed containing more than 22000 known genes. Using Oparray protocol, preparation and hybridization of slides was carried out and followed by scanning with GeneTAC integrator 4.0 software. Normalization of the data was obtained using MIDAS software and Significant Microarray Analysis (SAM) was performed to obtain differentially expressed candidate genes. Results Out of 22000 genes studied, 219 differentially regulated genes found with P ≤ 0.05 between both groups; 107 among those were up-regulated and 112 were down-regulated. These genes were classified into 31 categories according to their biological functions. The main categories included: apoptosis, immune response, cell signaling, kinase activity, lipid metabolism, protein metabolism, protein modulation, metabolism, vision, cell structure, cytoskeleton, nervous system, protein metabolism, protein modulation, signal transduction, transcriptional regulation and transport activity. Conclusion This is the first study on gene expression profiling in patients associated with genotype 3a using microarray analysis. These findings represent a broad portrait of genomic changes in early HCV associated fibrosis and cirrhosis. We hope that identified genes in this study will help in future to act as prognostic and diagnostic markers to differentiate fibrotic patients from cirrhotic ones. PMID:22397681

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

    PubMed Central

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

    2015-01-01

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

  17. 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

  18. 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.

  19. 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.

  20. 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

  1. 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

  2. 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

  3. DNA microarray gene expression analysis technology and its application to neurological disorders.

    PubMed

    Greenberg, S A

    2001-09-11

    DNA microarray technology is currently an area of great interest. Also called "genechip" technology, it incorporates molecular genetics and computer science on a massive scale. This technology can rapidly provide a detailed view of the simultaneous expression of entire genomes and provide new insights into gene function, disease pathophysiology, disease classification, and drug development. In this review, the author discusses the basic theory behind genechip and the other biologic chip technologies, their limitations given the current state of biologic knowledge and computational abilities, and their potential applications to the understanding of neurologic disorders. PMID:11575306

  4. 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...

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  7. 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 ...

  8. A Hybrid BPSO-CGA Approach for Gene Selection and Classification of Microarray Data

    PubMed Central

    Chuang, Li-Yeh; Yang, Cheng-Huei; Li, Jung-Chike

    2012-01-01

    Abstract Microarray analysis promises to detect variations in gene expressions, and changes in the transcription rates of an entire genome in vivo. Microarray gene expression profiles indicate the relative abundance of mRNA corresponding to the genes. The selection of relevant genes from microarray data poses a formidable challenge to researchers due to the high-dimensionality of features, multiclass categories being involved, and the usually small sample size. A classification process is often employed which decreases the dimensionality of the microarray data. In order to correctly analyze microarray data, the goal is to find an optimal subset of features (genes) which adequately represents the original set of features. A hybrid method of binary particle swarm optimization (BPSO) and a combat genetic algorithm (CGA) is to perform the microarray data selection. The K-nearest neighbor (K-NN) method with leave-one-out cross-validation (LOOCV) served as a classifier. The proposed BPSO-CGA approach is compared to ten microarray data sets from the literature. The experimental results indicate that the proposed method not only effectively reduce the number of genes expression level, but also achieves a low classification error rate. PMID:21210743

  9. Microarray Analyses of Gene Expression during Chondrocyte Differentiation Identifies Novel Regulators of Hypertrophy

    PubMed Central

    James, Claudine G.; Appleton, C. Thomas G.; Ulici, Veronica; Underhill, T. Michael; Beier, Frank

    2005-01-01

    Ordered chondrocyte differentiation and maturation is required for normal skeletal development, but the intracellular pathways regulating this process remain largely unclear. We used Affymetrix microarrays to examine temporal gene expression patterns during chondrogenic differentiation in a mouse micromass culture system. Robust normalization of the data identified 3300 differentially expressed probe sets, which corresponds to 1772, 481, and 249 probe sets exhibiting minimum 2-, 5-, and 10-fold changes over the time period, respectively. GeneOntology annotations for molecular function show changes in the expression of molecules involved in transcriptional regulation and signal transduction among others. The expression of identified markers was confirmed by RT-PCR, and cluster analysis revealed groups of coexpressed transcripts. One gene that was up-regulated at later stages of chondrocyte differentiation was Rgs2. Overexpression of Rgs2 in the chondrogenic cell line ATDC5 resulted in accelerated hypertrophic differentiation, thus providing functional validation of microarray data. Collectively, these analyses provide novel information on the temporal expression of molecules regulating endochondral bone development. PMID:16135533

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

    PubMed

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

    2004-07-01

    A codon-profile strategy was used to predict gene expression levels in Streptococcus pneumoniae. Predicted highly expressed (PHE) genes included those encoding glycolytic and fermentative enzymes, sugar-conversion systems and carbohydrate-transporters. Additionally, some genes required for infection that are involved in oxidative metabolism and hydrogen peroxide production were PHE. Low expression values were predicted for genes encoding specific regulatory proteins like two-component systems and competence genes. Correspondence analysis localized 484 ORFs which shared a distinctive codon profile in the right horn. These genes had a mean G+C content (33.4 %) that was lower than the bulk of the genome coding sequences (39.7 %), suggesting that many of them were acquired by horizontal transfer. Half of these genes (242) were pseudogenes, ORFs shorter than 80 codons or without assigned function. The remaining genes included several virulence factors, such as capsular genes, iga, lytB, nanB, pspA, choline-binding proteins, and functions related to DNA acquisition, such as restriction-modification systems and comDE. In order to compare predicted translation rate with the relative amounts of mRNA for each gene, the codon adaptation index (CAI) values were compared with microarray fluorescence intensity values following hybridization of labelled RNA from laboratory-grown cultures. High mRNA amounts were observed in 32.5 % of PHE genes and in 64 % of the 25 genes with the highest CAI values. However, high relative amounts of RNA were also detected in 10.4 % of non-PHE genes, such as those encoding fatty acid metabolism enzymes and proteases, suggesting that their expression might also be regulated at the level of transcription or mRNA stability under the conditions tested. The effects of codon bias and mRNA amount on different gene groups in S. pneumoniae are discussed. PMID:15256573

  11. Identification of critical genes in microarray experiments by a Neuro-Fuzzy approach.

    PubMed

    Chen, Chin-Fu; Feng, Xin; Szeto, Jack

    2006-10-01

    Gene expression profiling by microarray technology is usually difficult to interpret into a simpler pattern. One approach to resolve the complexity of gene expression profiles is the application of artificial neural networks (ANNs). A potential difficulty in this strategy, however, is that the non-linear nature of ANN makes it essentially a 'black-box' computation process. Addition of a fuzzy logic approach is useful because it can complement ANN by explicitly specifying membership function during computation. We employed a hybrid approach of neural network and fuzzy logic to further analyze a published microarray study of gene responses to eight bacteria in human macrophages. The original analysis by hierarchical clustering found common gene responses to all bacteria but did not address individual responses. Our method allowed exploration of the gene response of the host to individual bacterium. We implemented a two-layer, feed-forward neural network containing the principle of 'competitive learning' (i.e. 'winner-take-all'). The weights of the trained neural network were fed into a fuzzy logic inference system. A new measurement, called the impact rating (IR) was also introduced to explore the degree of importance of each gene. To assess the reliability of the IR value, a bootstrap re-sampling method was applied to the dataset and a confidence level for each IR was obtained. Our approach has successfully uncovered the unique features of host response to individual bacterium. Further, application of gene ontology (GO) annotation to the genes of high IR values in each response has suggested new biological pathways for individual host-pathogen interactions. PMID:16987708

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

    PubMed

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

    2010-11-01

    As diagnostic and surveillance activities are vital to determine measures needed to control antimicrobial resistance (AMR), new and rapid laboratory methods are necessary to facilitate this important effort. DNA microarray technology allows the detection of a large number of genes in a single reaction. This technology is simple, specific and high-throughput. We have developed a bacterial antimicrobial resistance gene DNA microarray that will allow rapid antimicrobial resistance gene screening for all Gram-positive and Gram-negative bacteria. A prototype microarray was designed using a 70-mer based oligonucleotide set targeting AMR genes of Gram-negative and Gram-positive bacteria. In the present version, the microarray consists of 182 oligonucleotides corresponding to 166 different acquired AMR gene targets, covering most of the resistance genes found in both Gram-negative and -positive bacteria. A test study was performed on a collection of Staphylococcus aureus isolates from milk samples from dairy farms in Québec, Canada. The reproducibility of the hybridizations was determined, and the microarray results were compared with those obtained by phenotypic resistance tests (either MIC or Kirby-Bauer). The microarray genotyping demonstrated a correlation between penicillin, tetracycline and erythromycin resistance phenotypes with the corresponding acquired resistance genes. The hybridizations showed that the 38 antimicrobial resistant S. aureus isolates possessed at least one AMR gene. PMID:21083822

  13. 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...

  14. 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.

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

    EPA Science Inventory

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

  16. 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

  17. 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

    2015-01-01

    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. PMID:26437396

  18. 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...

  19. 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, ...

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

    PubMed Central

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

    2015-01-01

    The vocal fold (VF) mucosa confers elegant biomechanical function for voice production but is susceptible to scar formation following injury. Current understanding of VF wound healing is hindered by a paucity of data and is therefore often generalized from research conducted in skin and other mucosal systems. Here, using a previously validated rat injury model, expression microarray technology and an empirical Bayes analysis approach, we generated a VF-specific transcriptome dataset to better capture the system-level complexity of wound healing in this specialized tissue. We measured differential gene expression at 3, 14 and 60 days post-injury compared to experimentally naïve controls, pursued functional enrichment analyses to refine and add greater biological definition to the previously proposed temporal phases of VF wound healing, and validated the expression and localization of a subset of previously unidentified repair- and regeneration-related genes at the protein level. Our microarray dataset is a resource for the wider research community and has the potential to stimulate new hypotheses and avenues of investigation, improve biological and mechanistic insight, and accelerate the identification of novel therapeutic targets. PMID:25592437

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

    SciTech Connect

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

    2005-02-01

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

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

    PubMed Central

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

    2005-01-01

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

  3. 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. PMID:23539565

  4. 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

  5. Genome-wide expression analysis of Saccharomyces pastorianus orthologous genes using oligonucleotide microarrays.

    PubMed

    Horinouchi, Takaaki; Yoshikawa, Katsunori; Kawaide, Risa; Furusawa, Chikara; Nakao, Yoshihiro; Hirasawa, Takashi; Shimizu, Hiroshi

    2010-11-01

    The lager brewing yeast, Saccharomyces pastorianus, an allopolyploid species hybrid, contains 2 diverged sub-genomes; one derived from Saccharomyces cerevisiae (Sc-type) and the other from Saccharomyces bayanus (Sb-type). We analyzed the functional roles of these orthologous genes in determining the phenotypic features of S. pastorianus. We used a custom-made oligonucleotide microarray containing probes designed for both Sc-type and Sb-type ORFs for a comprehensive expression analysis of S. pastorianus in a pilot-scale fermentation. We showed a high degree of correlation between the expression levels and the expression changes for a majority of orthologous gene sets during the fermentation process. We screened the functional categories and metabolic pathways where Sc- or Sb-type genes have higher expression levels than the corresponding orthologous genes. Our data showed that, for example, pathways for sulfur metabolism, cellular import, and production of branched amino acids are dominated by Sb-type genes. This comprehensive expression analysis of orthologous genes can provide valuable insights on understanding the phenotype of S. pastorianus. PMID:20547377

  6. Identification of marker genes for intestinal immunomodulating effect of a fructooligosaccharide by DNA microarray analysis.

    PubMed

    Fukasawa, Tomoyuki; Murashima, Koichiro; Matsumoto, Ichiro; Hosono, Akira; Ohara, Hiroki; Nojiri, Chuhei; Koga, Jinnichiro; Kubota, Hidetoshi; Kanegae, Minoru; Kaminogawa, Shuichi; Abe, Keiko; Kono, Toshiaki

    2007-04-18

    Prebiotic fructooligosaccharides are noted for their intestinal immunodulating effects, and the identification of markers for the effects is a matter of great concern. This study aimed to identify marker genes for physiological effects of a particular fructooligosaccharide (FOS) on a host animal and also to define the target of its function in the small intestine. DNA microarray technology was used to screen candidate marker genes, and comprehensive changes in gene expressions in the ileum of mice fed with FOS were investigated. One of the major physiological effects of FOS was intestinal immunomodulation. Marker genes were then identified for major histocompatibility complex classes I and II, interferon, and phosphatidylinositol metabolites. Also, the ileum was segmented into Peyer's patch (PP) and the other ileal organ (DeltaPP), and these were analyzed by quantitative RT-PCR method, with the result that the site for recognizing the FOS function was the DeltaPP rather than the PP. This is the first paper showing the markers for the physiological effects of FOS in the small intestine at gene expression level. Applying these marker genes would make it possible to clarify the mechanisms of how the administration of dietary FOS and associated changes in the intestinal environment are recognized by host organisms as well as how its immunomodulating effects are expressed in the body. PMID:17378576

  7. Differential Gene Expression Analysis of Placentas with Increased Vascular Resistance and Pre-Eclampsia Using Whole-Genome Microarrays

    PubMed Central

    Centlow, M.; Wingren, C.; Borrebaeck, C.; Brownstein, M. J.; Hansson, S. R.

    2011-01-01

    Pre-eclampsia is a pregnancy complication characterized by hypertension and proteinuria. There are several factors associated with an increased risk of developing pre-eclampsia, one of which is increased uterine artery resistance, referred to as “notching”. However, some women do not progress into pre-eclampsia whereas others may have a higher risk of doing so. The placenta, central in pre-eclampsia pathology, may express genes associated with either protection or progression into pre-eclampsia. In order to search for genes associated with protection or progression, whole-genome profiling was performed. Placental tissue from 15 controls, 10 pre-eclamptic, 5 pre-eclampsia with notching, and 5 with notching only were analyzed using microarray and antibody microarrays to study some of the same gene product and functionally related ones. The microarray showed 148 genes to be significantly altered between the four groups. In the preeclamptic group compared to notch only, there was increased expression of genes related to chemotaxis and the NF-kappa B pathway and decreased expression of genes related to antigen processing and presentation, such as human leukocyte antigen B. Our results indicate that progression of pre-eclampsia from notching may involve the development of inflammation. Increased expression of antigen-presenting genes, as seen in the notch-only placenta, may prevent this inflammatory response and, thereby, protect the patient from developing pre-eclampsia. PMID:21490790

  8. Comparing bioinformatic gene expression profiling methods: microarray and RNA-Seq.

    PubMed

    Mantione, Kirk J; Kream, Richard M; Kuzelova, Hana; Ptacek, Radek; Raboch, Jiri; Samuel, Joshua M; Stefano, George B

    2014-01-01

    Understanding the control of gene expression is critical for our understanding of the relationship between genotype and phenotype. The need for reliable assessment of transcript abundance in biological samples has driven scientists to develop novel technologies such as DNA microarray and RNA-Seq to meet this demand. This review focuses on comparing the two most useful methods for whole transcriptome gene expression profiling. Microarrays are reliable and more cost effective than RNA-Seq for gene expression profiling in model organisms. RNA-Seq will eventually be used more routinely than microarray, but right now the techniques can be complementary to each other. Microarrays will not become obsolete but might be relegated to only a few uses. RNA-Seq clearly has a bright future in bioinformatic data collection. PMID:25149683

  9. 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

  10. Microarray-Based Analysis of Cell-Cycle Gene Expression During Spermatogenesis in the Mouse1

    PubMed Central

    Roy Choudhury, Dipanwita; Small, Chris; Wang, Yufeng; Mueller, Paul R.; Rebel, Vivienne I.; Griswold, Michael D.; McCarrey, John R.

    2010-01-01

    Mammalian spermatogenesis is a continuum of cellular differentiation in a lineage that features three principal stages: 1) a mitotically active stage in spermatogonia, 2) a meiotic stage in spermatocytes, and 3) a postreplicative stage in spermatids. We used a microarray-based approach to identify changes in expression of cell-cycle genes that distinguish 1) mitotic type A spermatogonia from meiotic pachytene spermatocytes and 2) pachytene spermatocytes from postreplicative round spermatids. We detected expression of 550 genes related to cell-cycle function in one or more of these cell types. Although a majority of these genes were expressed during all three stages of spermatogenesis, we observed dramatic changes in levels of individual transcripts between mitotic spermatogonia and meiotic spermatocytes and between meiotic spermatocytes and postreplicative spermatids. Our results suggest that distinct cell-cycle gene regulatory networks or subnetworks are associated with each phase of the cell cycle in each spermatogenic cell type. In addition, we observed expression of different members of certain cell-cycle gene families in each of the three spermatogenic cell types investigated. Finally, we report expression of 221 cell-cycle genes that have not previously been annotated as part of the cell cycle network expressed during spermatogenesis, including eight novel genes that appear to be testis-specific. PMID:20631398

  11. Development of a soybean gene expression database to cross compare microarray experiments

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Microarrays are a revolutionary tool to estimate expression levels of genes within an organism. In a fairly quick and simple experiment, one can monitor expression of tens of thousands of genes. The relative ease of use and availability of array platforms for many commonly researched plants, is gene...

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

    PubMed

    Wang, Xi; Ning, Yujie; Guo, Xiong

    2015-09-01

    The aim of the present study was to identify differentially expressed (DE) genes in patients with osteoarthritis (OA), and biological processes associated with changes in gene expression that occur in this disease. Using the INMEX (integrative meta‑analysis of expression data) software tool, a meta‑analysis of publicly available microarray Gene Expression Omnibus (GEO) datasets of OA was performed. Gene ontology (GO) enrichment analysis was performed in order to detect enriched functional attributes based on gene‑associated GO terms. Three GEO datasets, containing 137 patients with OA and 52 healthy controls, were included in the meta‑analysis. The analysis identified 85 genes that were consistently differentially expressed in OA (30 genes were upregulated and 55 genes were downregulated). The upregulated gene with the lowest P‑value (P=5.36E‑07) was S‑phase kinase‑associated protein 2, E3 ubiquitin protein ligase (SKP2). The downregulated gene with the lowest P‑value (P=4.42E‑09) was Proline rich 5 like (PRR5L). Among the 210 GO terms that were associated with the set of DE genes, the most significant two enrichments were observed in the GO categories of 'Immune response', with a P‑value of 0.000129438, and 'Immune effectors process', with a P‑value of 0.000288619. The current meta‑analysis identified genes that were consistently DE in OA, in addition to biological pathways associated with changes in gene expression that occur during OA, which may provide insight into the molecular mechanisms underlying the pathogenesis of this disease. PMID:25975828

  13. 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.

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

    PubMed

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

    2002-02-01

    Clinical GeneOrganizer (CGO) is a novel windows-based archiving, organization and data mining software for the integration of gene expression profiling in clinical medicine. The program implements various user-friendly tools and extracts data for further statistical analysis. This software was written for Affymetrix GeneChip *.txt files, but can also be used for any other microarray-derived data. The MS-SQL server version acts as a data mart and links microarray data with clinical parameters of any other existing database and therefore represents a valuable tool for combining gene expression analysis and clinical disease characteristics. PMID:11847084

  15. 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

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

    PubMed Central

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

    2003-01-01

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

  17. 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.

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

    PubMed Central

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

    2009-01-01

    Commercial SNP microarrays now provide comprehensive and affordable coverage of the human genome. However, some diseases have biologically relevant genomic regions that may require additional coverage. Addiction, for example, is thought to be influenced by complex interactions among many relevant genes and pathways. We have assembled a list of 486 biologically relevant genes nominated by a panel of experts on addiction. We then added 424 genes that showed evidence of association with addiction phenotypes through mouse QTL mappings and gene co-expression analysis. We demonstrate that there are a substantial number of SNPs in these genes that are not well represented by commercial SNP platforms. We address this problem by introducing a publicly available SNP database for addiction. The database is annotated using numeric prioritization scores indicating the extent of biological relevance. The scores incorporate a number of factors such as SNP/gene functional properties (including synonymy and promoter regions), data from mouse systems genetics and measures of human/mouse evolutionary conservation. We then used HapMap genotyping data to determine if a SNP is tagged by a commercial microarray through linkage disequilibrium. This combination of biological prioritization scores and LD tagging annotation will enable addiction researchers to supplement commercial SNP microarrays to ensure comprehensive coverage of biologically relevant regions. PMID:19381300

  19. Quality Control Usage in High-Density Microarrays Reveals Differential Gene Expression Profiles in Ovarian Cancer.

    PubMed

    Villegas-Ruiz, Vanessa; Moreno, Jose; Jacome-Lopez, Karina; Zentella-Dehesa, Alejandro; Juarez-Mendez, Sergio

    2016-01-01

    There are several existing reports of microarray chip use for assessment of altered gene expression in different diseases. In fact, there have been over 1.5 million assays of this kind performed over the last twenty years, which have influenced clinical and translational research studies. The most commonly used DNA microarray platforms are Affymetrix GeneChip and Quality Control Software along with their GeneChip Probe Arrays. These chips are created using several quality controls to confirm the success of each assay, but their actual impact on gene expression profiles had not been previously analyzed until the appearance of several bioinformatics tools for this purpose. We here performed a data mining analysis, in this case specifically focused on ovarian cancer, as well as healthy ovarian tissue and ovarian cell lines, in order to confirm quality control results and associated variation in gene expression profiles. The microarray data used in our research were downloaded from ArrayExpress and Gene Expression Omnibus (GEO) and analyzed with Expression Console Software using RMA, MAS5 and Plier algorithms. The gene expression profiles were obtained using Partek Genomics Suite v6.6 and data were visualized using principal component analysis, heat map, and Venn diagrams. Microarray quality control analysis showed that roughly 40% of the microarray files were false negative, demonstrating over- and under-estimation of expressed genes. Additionally, we confirmed the results performing second analysis using independent samples. About 70% of the significant expressed genes were correlated in both analyses. These results demonstrate the importance of appropriate microarray processing to obtain a reliable gene expression profile. PMID:27268623

  20. 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

  1. 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

  2. Genomic interspecies microarray hybridization: rapid discovery of three thousand genes in the maize endophyte, Klebsiella pneumoniae 342, by microarray hybridization with Escherichia coli K-12 open reading frames.

    PubMed

    Dong, Y; Glasner, J D; Blattner, F R; Triplett, E W

    2001-04-01

    In an effort to efficiently discover genes in the diazotrophic endophyte of maize, Klebsiella pneumoniae 342, DNA from strain 342 was hybridized to a microarray containing 96% (n = 4,098) of the annotated open reading frames from Escherichia coli K-12. Using a criterion of 55% identity or greater, 3,000 (70%) of the E. coli K-12 open reading frames were also found to be present in strain 342. Approximately 24% (n = 1,030) of the E. coli K-12 open reading frames are absent in strain 342. For 1.6% (n = 68) of the open reading frames, the signal was too low to make a determination regarding the presence or absence of the gene. Genes with high identity between the two organisms are those involved in energy metabolism, amino acid metabolism, fatty acid metabolism, cofactor synthesis, cell division, DNA replication, transcription, translation, transport, and regulatory proteins. Functions that were less highly conserved included carbon compound metabolism, membrane proteins, structural proteins, putative transport proteins, cell processes such as adaptation and protection, and central intermediary metabolism. Open reading frames of E. coli K-12 with little or no identity in strain 342 included putative regulatory proteins, putative chaperones, surface structure proteins, mobility proteins, putative enzymes, hypothetical proteins, and proteins of unknown function, as well as genes presumed to have been acquired by lateral transfer from sources such as phage, plasmids, or transposons. The results were in agreement with the physiological properties of the two strains. Whole genome comparisons by genomic interspecies microarray hybridization are shown to rapidly identify thousands of genes in a previously uncharacterized bacterial genome provided that the genome of a close relative has been fully sequenced. This approach will become increasingly more useful as more full genome sequences become available. PMID:11282649

  3. Rank products: a simple, yet powerful, new method to detect differentially regulated genes in replicated microarray experiments.

    PubMed

    Breitling, Rainer; Armengaud, Patrick; Amtmann, Anna; Herzyk, Pawel

    2004-08-27

    One of the main objectives in the analysis of microarray experiments is the identification of genes that are differentially expressed under two experimental conditions. This task is complicated by the noisiness of the data and the large number of genes that are examined simultaneously. Here, we present a novel technique for identifying differentially expressed genes that does not originate from a sophisticated statistical model but rather from an analysis of biological reasoning. The new technique, which is based on calculating rank products (RP) from replicate experiments, is fast and simple. At the same time, it provides a straightforward and statistically stringent way to determine the significance level for each gene and allows for the flexible control of the false-detection rate and familywise error rate in the multiple testing situation of a microarray experiment. We use the RP technique on three biological data sets and show that in each case it performs more reliably and consistently than the non-parametric t-test variant implemented in Tusher et al.'s significance analysis of microarrays (SAM). We also show that the RP results are reliable in highly noisy data. An analysis of the physiological function of the identified genes indicates that the RP approach is powerful for identifying biologically relevant expression changes. In addition, using RP can lead to a sharp reduction in the number of replicate experiments needed to obtain reproducible results. PMID:15327980

  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. The use of logic relationships to model colon cancer gene expression networks with mRNA microarray data.

    PubMed

    Ruan, Xiaogang; Wang, Jinlian; Li, Hui; Perozzi, Rhoda E; Perozzi, Edmund F

    2008-08-01

    The ultimate goal of genomics research is to describe the network of molecules and interactions that govern all biological functions and disease processes in cells. Nonlinear interactions among genes in terms of their logic relationships play a key role for deciphering the networks of molecules that underlie cellular function. We present a method based on a graph coloring scheme and information theory to identify the gene expression network with lower and higher order logic interactions of genes. The analysis of oncogenes and suppressor genes from a colon cancer mRNA microarray dataset identifies a gene expression network with directionality and weights that reflects intracellular communication pathways. The success of the proposed method in mining hidden, complicated gene interactions and reliably interpreting experimental results suggests that the proposed method is a useful tool for understanding cancer systems. Extension of this method holds the potential to be fruitful for understanding other complex, nonsymmetric systems. PMID:18249040

  6. Patterns of gene expression in microarrays and expressed sequence tags from normal and cataractous lenses.

    PubMed

    Sousounis, Konstantinos; Tsonis, Panagiotis A

    2012-01-01

    In this contribution, we have examined the patterns of gene expression in normal and cataractous lenses as presented in five different papers using microarrays and expressed sequence tags. The purpose was to evaluate unique and common patterns of gene expression during development, aging and cataracts. PMID:23244575

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

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

    PubMed

    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

  10. 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

  11. 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

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

    PubMed Central

    2014-01-01

    Background The diagnosis and prognosis of several diseases can be shortened through the use of different large-scale genome experiments. In this context, microarrays can generate expression data for a huge set of genes. However, to obtain solid statistical evidence from the resulting data, it is necessary to train and to validate many classification techniques in order to find the best discriminative method. This is a time-consuming process that normally depends on intricate statistical tools. Results geneCommittee is a web-based interactive tool for routinely evaluating the discriminative classification power of custom hypothesis in the form of biologically relevant gene sets. While the user can work with different gene set collections and several microarray data files to configure specific classification experiments, the tool is able to run several tests in parallel. Provided with a straightforward and intuitive interface, geneCommittee is able to render valuable information for diagnostic analyses and clinical management decisions based on systematically evaluating custom hypothesis over different data sets using complementary classifiers, a key aspect in clinical research. Conclusions geneCommittee allows the enrichment of microarrays raw data with gene functional annotations, producing integrated datasets that simplify the construction of better discriminative hypothesis, and allows the creation of a set of complementary classifiers. The trained committees can then be used for clinical research and diagnosis. Full documentation including common use cases and guided analysis workflows is freely available at http://sing.ei.uvigo.es/GC/. PMID:24475928

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

    PubMed

    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 AND 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

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

    PubMed Central

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

    2016-01-01

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

  15. 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. PMID:26058835

  16. Protocol for Gene Expression Profiling Using DNA Microarrays in Neisseria gonorrhoeae

    PubMed Central

    Jackson, Lydgia A.; Dyer, David W.

    2016-01-01

    Gene expression profiling using DNA microarrays has become commonplace in current molecular biology practices, and has dramatically enhanced our understanding of the biology of Neisseria spp., and the interaction of these organisms with the host. With the choice of microarray platforms offered for gene expression profiling and commercially available arrays, investigators must ask several central questions to make decisions based on their research focus. Are arrays on hand for their organism and if not then would it be cost-effective to design custom arrays. Other important considerations; what types of specialized equipment for array hybridization and signal detection are required and is the specificity and sensitivity of the array adequate for your application. Here, we describe the use of a custom 12K CombiMatrix ElectraSense™ oligonucleotide microarray format for assessing global gene expression profiles in Neisseria spp. PMID:22782831

  17. Mouse strain specific gene expression differences for illumina microarray expression profiling in embryos

    PubMed Central

    2012-01-01

    Background In the field of mouse genetics the advent of technologies like microarray based expression profiling dramatically increased data availability and sensitivity, yet these advanced methods are often vulnerable to the unavoidable heterogeneity of in vivo material and might therefore reflect differentially expressed genes between mouse strains of no relevance to a targeted experiment. The aim of this study was not to elaborate on the usefulness of microarray analysis in general, but to expand our knowledge regarding this potential “background noise” for the widely used Illumina microarray platform surpassing existing data which focused primarily on the adult sensory and nervous system, by analyzing patterns of gene expression at different embryonic stages using wild type strains and modern transgenic models of often non-isogenic backgrounds. Results Wild type embryos of 11 mouse strains commonly used in transgenic and molecular genetic studies at three developmental time points were subjected to Illumina microarray expression profiling in a strain-by-strain comparison. Our data robustly reflects known gene expression patterns during mid-gestation development. Decreasing diversity of the input tissue and/or increasing strain diversity raised the sensitivity of the array towards the genetic background. Consistent strain sensitivity of some probes was attributed to genetic polymorphisms or probe design related artifacts. Conclusion Our study provides an extensive reference list of gene expression profiling background noise of value to anyone in the field of developmental biology and transgenic research performing microarray expression profiling with the widely used Illumina microarray platform. Probes identified as strain specific background noise further allow for microarray expression profiling on its own to be a valuable tool for establishing genealogies of mouse inbred strains. PMID:22583621

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

    PubMed

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

    2016-06-01

    Biomineralization is a common biological phenomenon resulting in strong tissue, such as bone, tooth, and shell. Pinctada fucata martensii is an ideal animal for the study of biomineralization. Here, microarray technique was used to identify biomineralization gene in mantle edge (ME), mantle center (MC), and both ME and MC (ME-MC) for this pearl oyster. Results revealed that 804, 306, and 1127 contigs expressed at least three times higher in ME, MC, and ME-MC as those in other tissues. Blast against non-redundant database showed that 130 contigs (16.17 %), 53 contigs (17.32 %), and 248 contigs (22.01 %) hit reference genes (E ≤ -10), among which 91 contigs, 48 contigs, and 168 contigs could be assigned to 32, 26, and 63 biomineralization genes in tissue of ME, MC, and ME-MC at a threshold of 3 times upregulated expression level. The ratios of biomineralization contigs to homologous contigs were similar at 3 times, 10 times, and 100 times of upregulated expression level in either ME, MC, or ME-MC. Moreover, the ratio of biomineralization contigs was highest in MC. Although mRNA distribution characters were similar to those in other studies for eight biomineralization genes of PFMG3, Pif, nacrein, MSI7, mantle gene 6, Pfty1, prismin, and the shematrin, most biomineralization genes presented different expression profiles from existing reports. These results provided massive fundamental information for further study of biomineralization gene function, and it may be helpful for revealing gene nets of biomineralization and the molecular mechanisms underlining formation of shell and pearl for the oyster. PMID:27184264

  19. 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

  20. A dolphin peripheral blood leukocyte cDNA microarray for studies of immune function and stress reactions.

    PubMed

    Mancia, Annalaura; Lundqvist, Mats L; Romano, Tracy A; Peden-Adams, Margie M; Fair, Patricia A; Kindy, Mark S; Ellis, Blake C; Gattoni-Celli, Sebastiano; McKillen, David J; Trent, Harold F; Chen, Yian Ann; Almeida, Jonas S; Gross, Paul S; Chapman, Robert W; Warr, Gregory W

    2007-01-01

    A microarray focused on stress response and immune function genes of the bottlenosed dolphin has been developed. Random expressed sequence tags (ESTs) were isolated and sequenced from two dolphin peripheral blood leukocyte (PBL) cDNA libraries biased towards T- and B-cell gene expression by stimulation with IL-2 and LPS, respectively. A total of 2784 clones were sequenced and contig analysis yielded 1343 unigenes (archived and annotated at ). In addition, 52 dolphin genes known to be important in innate and adaptive immune function and stress responses of terrestrial mammals were specifically targeted, cloned and added to the unigene collection. The set of dolphin sequences printed on a cDNA microarray comprised the 1343 unigenes, the 52 targeted genes and 2305 randomly selected (but unsequenced) EST clones. This set was printed in duplicate spots, side by side, and in two replicates per slide, such that the total number of features per microarray slide was 19,200, including controls. The dolphin arrays were validated and transcriptomic profiles were generated using PBL from a wild dolphin, a captive dolphin and dolphin skin cells. The results demonstrate that the array is a reproducible and informative tool for assessing differential gene expression in dolphin PBL and in other tissues. PMID:17084893

  1. 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.

  2. 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

  3. Hierarchical gene selection and genetic fuzzy system for cancer microarray data classification.

    PubMed

    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

  4. Analysis of gene expression on anodic porous alumina microarrays

    PubMed Central

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

    2013-01-01

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

  5. Detection of antimicrobial resistance genes by DNA microarray

    Technology Transfer Automated Retrieval System (TEKTRAN)

    To study the spread of antimicrobial resistance in bacteria it is necessary to detect and characterize the genes responsible for resistance. Currently, each gene must be screened individually in order to identify the gene(s) responsible for the observed resistance expressed by a bacterium. The inabi...

  6. Detection of antimicrobial resistance genes by DNA microarray

    Technology Transfer Automated Retrieval System (TEKTRAN)

    To study the spread of antimicrobial resistance in bacteria it is necessary to identify the genes responsible for resistance. Currently, each gene must be screened individually in order to identify the gene(s) responsible for the observed resistance expressed by a bacterium. The inability to rapidly...

  7. DETECTION OF ANTIMICROBIAL RESISTANCE GENES BY DNA MICROARRAY

    Technology Transfer Automated Retrieval System (TEKTRAN)

    To study the spread of antimicrobial resistance in bacteria it is necessary to identify the genes responsible for resistance. Currently, each gene must be screened individually in order to identify the gene(s) responsible for the observed resistance expressed by a bacterium. The inability to rapidly...

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

    PubMed

    Latkowski, Tomasz; Osowski, Stanislaw

    2015-01-01

    The aim of this paper is to provide a means to recognize a case of autism using gene expression microarrays. The crucial task is to discover the most important genes which are strictly associated with autism. The paper presents an application of different methods of gene selection, to select the most representative input attributes for an ensemble of classifiers. The set of classifiers is responsible for distinguishing autism data from the reference class. Simultaneous application of a few gene selection methods enables analysis of the ill-conditioned gene expression matrix from different points of view. The results of selection combined with a genetic algorithm and SVM classifier have shown increased accuracy of autism recognition. Early recognition of autism is extremely important for treatment of children and increases the probability of their recovery and return to normal social communication. The results of this research can find practical application in early recognition of autism on the basis of gene expression microarray analysis. PMID:25464350

  9. Fish and chips: Various methodologies demonstrate utility of a 16,006-gene salmonid microarray

    PubMed Central

    von Schalburg, Kristian R; Rise, Matthew L; Cooper, Glenn A; Brown, Gordon D; Gibbs, A Ross; Nelson, Colleen C; Davidson, William S; Koop, Ben F

    2005-01-01

    Background We have developed and fabricated a salmonid microarray containing cDNAs representing 16,006 genes. The genes spotted on the array have been stringently selected from Atlantic salmon and rainbow trout expressed sequence tag (EST) databases. The EST databases presently contain over 300,000 sequences from over 175 salmonid cDNA libraries derived from a wide variety of tissues and different developmental stages. In order to evaluate the utility of the microarray, a number of hybridization techniques and screening methods have been developed and tested. Results We have analyzed and evaluated the utility of a microarray containing 16,006 (16K) salmonid cDNAs in a variety of potential experimental settings. We quantified the amount of transcriptome binding that occurred in cross-species, organ complexity and intraspecific variation hybridization studies. We also developed a methodology to rapidly identify and confirm the contents of a bacterial artificial chromosome (BAC) library containing Atlantic salmon genomic DNA. Conclusion We validate and demonstrate the usefulness of the 16K microarray over a wide range of teleosts, even for transcriptome targets from species distantly related to salmonids. We show the potential of the use of the microarray in a variety of experimental settings through hybridization studies that examine the binding of targets derived from different organs and tissues. Intraspecific variation in transcriptome expression is evaluated and discussed. Finally, BAC hybridizations are demonstrated as a rapid and accurate means to identify gene content. PMID:16164747

  10. 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

  11. Microarray gene expression profiling and bioinformatics analysis of premature ovarian failure in a rat model.

    PubMed

    Li, Ji; Fan, Shengjun; Han, Dongwei; Xie, Jiaming; Kuang, Haixue; Ge, Pengling

    2014-12-01

    Premature ovarian failure (POF) remains one of the major gynecological problems worldwide which affected 1% of women. Even though tremendous achievements had been acquired as opposed to years past, molecular pathogenesis associated with POF is still unclear and needs to be well-defined. The aim of this study was to analyze the gene expression profiles in the POF rat model. To predict potential regulating factors, we firstly treated female Sprague Dawley (SD) rat with 4-vinylcyclohexene diepoxide (VCD). Total RNA from ovarian tissue was converted to cDNA and hybridized to mRNA Chip array. The differentially expressed genes (DEGs) were identified by two-sample t test and assessed using hierarchical clustering and Principal Component Analysis methods. Potential regulatory targets associated with these DEGs were constructed using BisoGenet in Cytoscape. Gene Ontology (GO) and functional enrichment analysis were performed using BiNGO and DAVID, respectively. As the results, 25 DEGs were found to be closely associated with POF initiation. Hierarchical clustering and Principal Component Analysis on the transcriptional profiles revealed an excellent separation of the vehicle and POF compartments. Pathway enrichment analysis based on the disease-gene interaction network analysis led to the identification of two core signaling pathways that were strongly affected during POF initiation and progression: immune response and cardiovascular disorders. In conclusion, we constructed a gene regulatory network associated with POF using the microarray gene expression profiling, and screened out some genes or transcription factors that may be used as potential molecular therapeutic targets for POF. PMID:25445499

  12. 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. PMID:26400303

  13. Gene expression profile analysis in astaxanthin-induced Haematococcus pluvialis using a cDNA microarray.

    PubMed

    Eom, Hyunsuk; Lee, Choul-Gyun; Jin, EonSeon

    2006-05-01

    The unicellular green alga Haematococcus pluvialis (Volvocales) is known for the ketocarotenoid astaxanthin (3, 3'-dihydroxy-beta, beta-carotene-4, 4'-dione) accumulation, which is induced under unfavorable culture conditions. In this work, we used cDNA microarray analysis to screen differentially expressed genes in H. pluvialis under astaxanthin-inductive culture conditions, such as combination of cell exposure to high irradiance and nutrient deprivation. Among the 965 genes in the cDNA array, there are 144 genes exhibiting differential expression (twofold changes) under these conditions. A significant decrease in the expression of photosynthesis-related genes was shown in astaxanthin-accumulating cells (red cells). Defense- or stress-related genes and signal transduction genes were also induced in the red cells. A comparison of microarray and real-time PCR analysis showed good correlation between the differentially expressed genes by the two methods. Our results indicate that the cDNA microarray approach, as employed in this work, can be relied upon and used to monitor gene expression profiles in H. pluvialis. In addition, the genes that were differentially expressed during astaxanthin induction are suitable candidates for further study and can be used as tools for dissecting the molecular mechanism of this unique pigment accumulation process in the green alga H. pluvialis. PMID:16320067

  14. 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…

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

    PubMed

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

    2014-03-01

    The aim of the present study was to identify key genes associated with atopic dermatitis (AD) using microarray data and bioinformatic analyses. The dataset GSE6012, downloaded from the Gene Expression Omnibus (GEO) database, contains gene expression data from 10 AD skin samples and 10 healthy skin samples. Following data preprocessing, differentially expressed genes (DEGs) were identified using the limma package of the R project. Interaction networks were constructed comprising DEGs that showed a degree of node of >3, >5 and >10, using the Osprey software. Functional enrichment and pathway enrichment analysis of the network comprising all DEGs and of the network comprising DEGs with a high degree of node, were performed with the DAVID and WebGestalt toolkits, respectively. A total of 337 DEGs were identified. The functional enrichment analysis revealed that the list of DEGs was significantly enriched for proteins related to epidermis development (P=2.95E-07), including loricrin (LOR), keratin 17 (KRT17), small proline-rich repeat proteins (SPRRs) and involucrin (IVL). The chemokine signaling pathway was the most significantly enriched pathway (P=0.0490978) in the network of all DEGs and in the network consisting of high degree‑node DEGs (>10), which comprised the genes coding for chemokine receptor 7 (CCR7), chemokine ligand (CCL19), signal transducer and activator of transcription 1 (STAT1), and phosphoinositide-3-kinase regulatory subunit 1 (PIK3R1). In conclusion, the list of AD-associated proteins identified in this study, including LOR, KRT17, SPRRs, IVL, CCR7, CCL19, PIK3R1 and STAT1 may prove useful for the development of methods to treat AD. From these proteins, PIK3R1 and KRT17 are novel and promising targets for AD therapy. PMID:24452877

  16. Comparison of molecular mechanisms of rheumatoid arthritis and osteoarthritis using gene microarrays

    PubMed Central

    LI, HONGQIANG; HAO, ZHENYONG; ZHAO, LIQIANG; LIU, WEI; HAN, YANLONG; BAI, YUNXING; WANG, JIAN

    2016-01-01

    The present study aimed to compare the molecular mechanisms of rheumatoid arthritis (RA) and osteoarthritis (OA). The microarray dataset no. GSE29746 was downloaded from Gene Expression Omnibus. After data pre-processing, differential expression analysis between the RA group and the control, as well as between the OA group and the control was performed using the LIMMA package in R and differentially expressed transcripts (DETs) with |log2fold change (FC)|>1 and P<0.01 were identified. DETs screened from each disease group were then subjected to functional annotation using DAVID. Next, DETs from each group were used to construct individual interaction networks using the BIND database, followed by sub-network mining using clusterONE. Significant functions of nodes in each sub-network were also investigated. In total, 19 and 281 DETs were screened from the RA and OA groups, respectively, with only six common DETs. DETs from the RA and OA groups were enriched in 8 and 130 gene ontology (GO) terms, respectively, with four common GO terms, of which to were associated with phospholipase C (PLC) activity. In addition, DETs screened from the OA group were enriched in immune response-associated GO terms, and those screened from the RA group were largely associated with biological processes linked with the cell cycle and chromosomes. Genes involved in PLC activity and its regulation were indicated to be altered in RA as well as in OA. Alterations in the expression of cell cycle-associated genes were indicated to be linked with the occurrence of OA, while genes participating in the immune response were involved in the occurrence of RA. PMID:27082252

  17. Comparison of molecular mechanisms of rheumatoid arthritis and osteoarthritis using gene microarrays.

    PubMed

    Li, Hongqiang; Hao, Zhenyong; Zhao, Liqiang; Liu, Wei; Han, Yanlong; Bai, Yunxing; Wang, Jian

    2016-06-01

    The present study aimed to compare the molecular mechanisms of rheumatoid arthritis (RA) and osteoarthritis (OA). The microarray dataset no. GSE29746 was downloaded from Gene Expression Omnibus. After data pre‑processing, differential expression analysis between the RA group and the control, as well as between the OA group and the control was performed using the LIMMA package in R and differentially expressed transcripts (DETs) with |log2fold change (FC)|>1 and P<0.01 were identified. DETs screened from each disease group were then subjected to functional annotation using DAVID. Next, DETs from each group were used to construct individual interaction networks using the BIND database, followed by sub‑network mining using clusterONE. Significant functions of nodes in each sub‑network were also investigated. In total, 19 and 281 DETs were screened from the RA and OA groups, respectively, with only six common DETs. DETs from the RA and OA groups were enriched in 8 and 130 gene ontology (GO) terms, respectively, with four common GO terms, of which to were associated with phospholipase C (PLC) activity. In addition, DETs screened from the OA group were enriched in immune response‑associated GO terms, and those screened from the RA group were largely associated with biological processes linked with the cell cycle and chromosomes. Genes involved in PLC activity and its regulation were indicated to be altered in RA as well as in OA. Alterations in the expression of cell cycle‑associated genes were indicated to be linked with the occurrence of OA, while genes participating in the immune response were involved in the occurrence of RA. PMID:27082252

  18. 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

  19. Gene microarray analyses for potential biomarkers of single and recurrent venous thromboembolism

    PubMed Central

    ZHOU, WUGANG; ZHANG, KE; CHEN, DONGRUI; GAO, PINGJIN; WANG, QIAO

    2015-01-01

    Venous thromboembolism is a major cause of morbidity and mortality with a high recurrence rate. The present study aimed to explore the molecular mechanisms and potential biomarkers of single venous thromboembolism (SVTE) and recurrent venous thromboembolism (RVTE). The microarray dataset GSE19151 was downloaded from Gene Expression Omnibus, which contained data from whole blood samples from 63 healthy controls, 32 SVTE and 38 RVTE patients. Differentially expressed genes (DEGs) in the SVTE and RVTE groups compared with those in the controls were identified using the t-test, followed by clustering analysis of DEGs and samples. Functional and pathway enrichment analyses were performed for DEGs in patients with RVTE and SVTE, as well as specific DEGs in patients with RVTE. The identified 42 DEGs in RVTE were mainly enriched in biological processes of cellular protein metabolism, gene expression and translational elongation as well as in pathways associated with ribosomes, Parkinson's disease and oxidative phosphorylation. In SVTE, 20 DEGs were identified, which were mainly involved in biological processes of biopolymer biosynthesis, translational elongation and cellular protein metabolism as well as pathways associated with ribosomes and cardiac muscle contraction. In RVTE, 22 specific DEGs were mainly involved in translational elongation, negative regulation of the force of heart contraction by chemical signals, cell proliferation, ribosomal pathways and protein export. The identified DEGs of SVTE, including COX7C and UQCRQ, may be potential biomarkers for SVTE, and the specific DEGs of RVTE, including ADRBK1, NDUFA5 and ATP5O, may be potential biomarkers for RVTE. PMID:26397997

  20. 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

  1. A Simple Method for Optimization of Reference Gene Identification and Normalization in DNA Microarray Analysis

    PubMed Central

    Casares, Federico M.

    2016-01-01

    Background Comparative DNA microarray analyses typically yield very large gene expression data sets that reflect complex patterns of change. Despite the wealth of information that is obtained, the identification of stable reference genes is required for normalization of disease- or drug-induced changes across tested groups. This is a prerequisite in quantitative real-time reverse transcription-PCR (qRT-PCR) and relative RT-PCR but rare in gene microarray analysis. The goal of the present study was to outline a simple method for identification of reliable reference genes derived from DNA microarray data sets by comparative statistical analysis of software-generated and manually calculated candidate genes. Material/Methods DNA microarray data sets derived from whole-blood samples obtained from 14 Zucker diabetic fatty (ZDF) rats (7 lean and 7 diabetic obese) were used for the method development. This involved the use of software-generated filtering parameters to accomplish the desired signal-to-noise ratios, 75th percentile signal manual normalizations, and the selection of reference genes as endogenous controls for target gene expression normalization. Results The combination of software-generated and manual normalization methods yielded a group of 5 stably expressed, suitable endogenous control genes which can be used in further target gene expression determinations in whole blood of ZDF rats. Conclusions This method can be used to correct for potentially false results and aid in the selection of suitable endogenous control genes. It is especially useful when aimed to aid the software in cases of borderline results, where the expression and/or the fold change values are just beyond the pre-established set of acceptable parameters. PMID:27122237

  2. 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

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

    PubMed Central

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

    2009-01-01

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

  4. 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

  5. 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

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

    PubMed Central

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

    2016-01-01

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

  7. 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.

  8. Detection of transcriptional difference of porcine imprinted genes using different microarray platforms

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Presently, multiple options exist for conducting gene expression profiling studies in swine. In order to determine the performance of some of the existing platforms, Affymetrix Porcine, Affymetrix Human U133+2.0, and the U.S. Pig Genome Coordination Program spotted glass oligonucleotide microarray p...

  9. 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...

  10. 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...

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

    PubMed

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

    2014-08-01

    Long-term cultivation in a laboratory could reduce the virulence of Acanthamoeba. To identify virulence factors of Acanthamoeba, the authors compared the transcription profiles of long-term cultivated Acanthamoeba healyi (OLD) and three times mouse-brain passaged A. healyi (MBP) using microarray analysis and eukaryotic orthologous group (KOG) assignments. Microarray analysis revealed that 601 genes were up-regulated by mouse-brain passage. The results of real-time PCR of 8 randomly selected genes up-regulated in the MBP strain confirmed microarray analysis findings. KOG assignments showed relatively higher percentages of the MBP strain up-regulated genes in T article (signal transduction mechanism), O article (posttranslational modification, protein turnover, chaperones), C article (energy production and conversion), and J article (translation, ribosomal structure and biogenesis). In particular, the MBP strain showed higher expressions of cysteine protease and metalloprotease. A comparison of KOG assignments by microarray analysis and previous EST (expressed sequence tags) analysis showed similar populations of up-regulated genes. These results provide important information regarding the identification of virulence factors of pathogenic Acanthamoeba. PMID:24859526

  12. Gene expression profiles of corn developing kernels of Tex6 using maize oligo-microarray

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Maize oligonuleotide microarray was used to analyze the temporal patterns of gene expression in late developmental maize kernels of Tex6 after 25 days after pollination (DAP). There was a total of 57,452 70-mer oligonucleotides on a set of two array-slides. Because of the resistant traits of Tex6, w...

  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. Intertwining Threshold Settings, Biological Data and Database Knowledge to Optimize the Selection of Differentially Expressed Genes from Microarray

    PubMed Central

    Chuchana, Paul; Holzmuller, Philippe; Vezilier, Frederic; Berthier, David; Chantal, Isabelle; Severac, Dany; Lemesre, Jean Loup; Cuny, Gerard; Nirdé, Philippe; Bucheton, Bruno

    2010-01-01

    Background Many tools used to analyze microarrays in different conditions have been described. However, the integration of deregulated genes within coherent metabolic pathways is lacking. Currently no objective selection criterion based on biological functions exists to determine a threshold demonstrating that a gene is indeed differentially expressed. Methodology/Principal Findings To improve transcriptomic analysis of microarrays, we propose a new statistical approach that takes into account biological parameters. We present an iterative method to optimise the selection of differentially expressed genes in two experimental conditions. The stringency level of gene selection was associated simultaneously with the p-value of expression variation and the occurrence rate parameter associated with the percentage of donors whose transcriptomic profile is similar. Our method intertwines stringency level settings, biological data and a knowledge database to highlight molecular interactions using networks and pathways. Analysis performed during iterations helped us to select the optimal threshold required for the most pertinent selection of differentially expressed genes. Conclusions/Significance We have applied this approach to the well documented mechanism of human macrophage response to lipopolysaccharide stimulation. We thus verified that our method was able to determine with the highest degree of accuracy the best threshold for selecting genes that are truly differentially expressed. PMID:20976008

  15. Identification of candidate genes for congenital splay leg in piglets by alternative analysis of DNA microarray data

    PubMed Central

    Maak, Steffen; Boettcher, Diana; Tetens, Jens; Wensch-Dorendorf, Monika; Nürnberg, Gerd; Wimmers, Klaus; Swalve, Hermann H.; Thaller, Georg

    2009-01-01

    The congenital splay leg syndrome in piglets is characterized by a temporarily impaired functionality of the hind leg muscles immediately after birth. Etiology and pathogenetic mechanisms for the disease are still not well understood. We compared genome wide gene expression of three hind leg muscles (M. adductores, M. gracilis and M. sartorius) between affected piglets and their healthy littermates with the GeneChip® Porcine Genome Array (Affymetrix) in order to identify candidate genes for the disease. Data analysis with standard algorithms revealed no significant differences between both groups. By application of an alternative approach, we identified 63 transcripts with differences in two muscles and 5 genes differing between the groups in three muscles. The expression of six selected genes (SQSTM1, SSRP1, DDIT4, ENAH, MAF, and PDK4) was investigated with SYBRGreen RT - Real time PCR. The differences obtained with the microarray analysis could be confirmed and demonstrate the validity of the alternative approach to microarray data analysis. Four genes with different expression levels in at least two muscles (SQSTM1, SSRP1, DDIT4, and MAF) are assigned to transcriptional cascades related to cell death and may thus indicate pathways for further investigations on congenital splay leg in piglets. PMID:19421343

  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. Parallel human genome analysis: Microarray-based expression monitoring of 1000 genes

    SciTech Connect

    Schena, M.; Heller, R.; Chai, A.; Davis, R.W.

    1996-10-01

    Microarrays containing 1046 human cDNAs of unknown sequence were printed on glass with high-speed robotics. These 1.0-cm{sup 2} DNA {open_quotes}chips{close_quotes} were used to quantitatively monitor differential expression of the cognate human genes using a highly sensitive two-color hybridization assay. Array elements that displayed differential expression patterns under given experimental conditions were characterized by sequencing. The identification of known and novel heat shock and phorbol ester-regulated genes in human T cells demonstrates the sensitivity of the assay. Parallel gene analysis with microarrays provides a rapid and efficient method for large-scale human gene discovery. 33 refs., 3 figs., 2 tabs.

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Background: Salmonids are of interest because of their relatively recent genome duplication, and their extensive use in wild fisheries and aquaculture. A comprehensive gene list and a comparison of genes in some of the different species provide valuable genomic information for one of the most wide...

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

    PubMed

    Park, Robin; Ji, Jong Dae

    2016-06-01

    The purpose of this study was to identify a gene expression signature in osteoarthritis (OA) synovium and genomic pathways likely to be involved in the pathogenesis of OA. Four publicly accessible microarray studies from synovium of OA patients were integrated, and a transcriptomic and network-based meta-analysis was performed. Based on pathways according to the Kyoto Encyclopedia of Genes and Genomes, functional enrichment analysis was performed. Meta-analysis results of OA synovium were compared to two previously published studies of OA cartilage to determine the relative number of common and specific DEGs of the cartilage and synovium. According to our meta-analysis, a total of 1350 genes were found to be differentially expressed in the synovium of OA patients as compared to that of healthy controls. Pathway analysis found 41 significant pathways in the total DEGs, and 22 and 16 pathways in the upregulated and downregulated DEGs, respectively. Cell adhesion molecules and cytokine-cytokine receptor interaction were the most significant pathway in the upregulated and downregulated DEGs, respectively. Comparison of meta-analysis results of OA synovium with results of two previous studies of OA cartilage identified 85 common genes and 1632 cartilage-specific DEGs and 1265 synovium-specific DEGs in the first study; and 142 common genes, and 856 cartilage-specific DEGs and 1208 synovium-specific DEGs in the second study. Our results show a small overlap between the DEGs of the synovium compared to DEGs of the cartilage, suggesting different pathogenic mechanisms that are specific to the synovium. PMID:26942917

  1. Gene network and canonical pathway analysis in canine myxomatous mitral valve disease: a microarray study.

    PubMed

    Lu, C-C; Liu, M-M; Culshaw, G; Clinton, M; Argyle, D J; Corcoran, B M

    2015-04-01

    Myxomatous mitral valve disease (MMVD) is the single most common acquired heart disease of the dog and is particularly common in small pedigree breed dogs such as the Cavalier King Charles spaniel (CKCS). There are limited data on the mitral valve transcriptome and the aim of this study was to use the microarray technology in conjunction with bioinformatics platforms to analyse transcript changes in MMVD in CKCS compared to normal dogs (non-CKCS). Differentially expressed genes (n = 5397) were identified using cut-off settings of fold change, false discovery rate (FDR) and P <0.05. In total, 4002 genes were annotated to a specific transcript in the Affymetrix canine database, and after further filtering, 591 annotated canine genes were identified: 322 (55%) were up-regulated and 269 (45%) were down-regulated. Canine microRNAs (cfa-miR; n = 59) were also identified. Gene ontology and network analysis platforms identified between six and 10 significantly different biological function clusters from which the following were selected as relevant to MMVD: inflammation, cell movement, cardiovascular development, extracellular matrix organisation and epithelial-to-mesenchymal (EMT) transition. Ingenuity Pathway Analysis identified three canonical pathways relevant to MMVD: caveolar-mediated endocytosis, remodelling of epithelial adherens junctions, and endothelin-1 signalling. Considering the biological relevance to MMVD, the gene families of importance with significant difference between groups included collagens, ADAMTS peptidases, proteoglycans, matrix metalloproteinases (MMPs) and their inhibitors, basement membrane components, cathepsin S, integrins, tight junction cell adhesion proteins, cadherins, other matrix-associated proteins, and members of the serotonin (5-HT)/transforming growth factor -β signalling pathway. PMID:25841900

  2. 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

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

    PubMed

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

    2015-04-01

    Esophageal atresia (EA) is a congenital defect of the esophagus involving the interruption of the esophagus with or without connection to the trachea (tracheoesophageal fistula [TEF]). EA/TEF may occur as an isolated anomaly, may be part of a complex of congenital defects (syndromic), or may develop within the context of a known syndrome or association. The molecular mechanisms underlying the development of EA are poorly understood. It is supposed that a combination of multigenic factors and epigenetic modification of genes play a role in its etiology. The aim of our work was to assess the human gene expression microarray study in esophageal tissue samples. Total RNA was extracted from 26 lower pouches of esophageal tissue collected during thoracoscopic EA repair in neonates with the isolated (IEA) and the syndromic form (SEA). We identified 787 downregulated and 841 upregulated transcripts between SEA and controls, and about 817 downregulated and 765 upregulated probes between IEA and controls. Fifty percent of these genes showed differential expression specific for either IEA or SEA. Functional pathway analysis revealed substantial enrichment for Wnt and Sonic hedgehog, as well as cytokine and chemokine signaling pathways. Moreover, we performed reverse transcription polymerase chain reaction study in a group of SHH and Wnt pathways genes with differential expression in microarray profiling to confirm the microarray expression results. We verified the altered expression in SFRP2 gene from the Wnt pathway as well as SHH, GLI1, GLI2, and GLI3 from the Sonic hedgehog pathway. The results suggest an important role of these pathways and genes for EA/TEF etiology. PMID:24460849

  4. 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

  5. ArrayExpress--a public repository for microarray gene expression data at the EBI.

    PubMed

    Brazma, Alvis; Parkinson, Helen; Sarkans, Ugis; Shojatalab, Mohammadreza; Vilo, Jaak; Abeygunawardena, Niran; Holloway, Ele; Kapushesky, Misha; Kemmeren, Patrick; Lara, Gonzalo Garcia; Oezcimen, Ahmet; Rocca-Serra, Philippe; Sansone, Susanna-Assunta

    2003-01-01

    ArrayExpress is a new public database of microarray gene expression data at the EBI, which is a generic gene expression database designed to hold data from all microarray platforms. ArrayExpress uses the annotation standard Minimum Information About a Microarray Experiment (MIAME) and the associated XML data exchange format Microarray Gene Expression Markup Language (MAGE-ML) and it is designed to store well annotated data in a structured way. The ArrayExpress infrastructure consists of the database itself, data submissions in MAGE-ML format or via an online submission tool MIAMExpress, online database query interface, and the Expression Profiler online analysis tool. ArrayExpress accepts three types of submission, arrays, experiments and protocols, each of these is assigned an accession number. Help on data submission and annotation is provided by the curation team. The database can be queried on parameters such as author, laboratory, organism, experiment or array types. With an increasing number of organisations adopting MAGE-ML standard, the volume of submissions to ArrayExpress is increasing rapidly. The database can be accessed at http://www.ebi.ac.uk/arrayexpress. PMID:12519949

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

    PubMed

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

    2014-06-01

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

  7. 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

  8. 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

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

    PubMed

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

    2015-01-01

    The objective of this study was to find common immune mechanism across different kinds of vaccines. A meta-analysis of microarray datasets was performed using publicly available microarray Gene Expression Omnibus (GEO) and Array Express data sets of vaccination records. Seven studies (out of 35) were selected for this meta-analysis. A total of 447 chips (145 pre-vaccination and 302 post-vaccination) were included. Significance analysis of microarrays (SAM) program was used for screening differentially expressed genes (DEGs). Functional pathway enrichment for the DEGs was conducted in DAVID Gene Ontology (GO) database. Twenty DEGs were identified, of which 10 up-regulated genes involved immune response. Six of which were type I interferon (IFN) related genes, including LY6E, MX1, OAS3, IFI44L, IFI6 and IFITM3. Ten down-regulated genes mainly mediated negative regulation of cell proliferation and cell motion. Results of a subgroup analysis showed that although the kinds of genes varied widely between days 3 and 7 post vaccination, the pathways between them are basically the same, such as immune response and response to viruses, etc. For an independent verification of these 6 type I IFN related genes, peripheral blood mononuclear cells (PBMCs) were collected at baseline and day 3 after the vaccination from 8 Enterovirus 71(EV71) vaccinees and were assayed by RT-PCR. Results showed that the 6 DEGs were also upregulated in EV71 vaccinees. In summary, meta-analysis methods were used to explore the immune mechanism of vaccines and results indicated that the type I IFN related genes and corresponding pathways were common in early immune responses for different kinds of vaccines. PMID:25839220

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

    PubMed Central

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

    2015-01-01

    The objective of this study was to find common immune mechanism across different kinds of vaccines. A meta-analysis of microarray datasets was performed using publicly available microarray Gene Expression Omnibus (GEO) and Array Express data sets of vaccination records. Seven studies (out of 35) were selected for this meta-analysis. A total of 447 chips (145 pre-vaccination and 302 post-vaccination) were included. Significance analysis of microarrays (SAM) program was used for screening differentially expressed genes (DEGs). Functional pathway enrichment for the DEGs was conducted in DAVID Gene Ontology (GO) database. Twenty DEGs were identified, of which 10 up-regulated genes involved immune response. Six of which were type I interferon (IFN) related genes, including LY6E, MX1, OAS3, IFI44L, IFI6 and IFITM3. Ten down-regulated genes mainly mediated negative regulation of cell proliferation and cell motion. Results of a subgroup analysis showed that although the kinds of genes varied widely between days 3 and 7 post vaccination, the pathways between them are basically the same, such as immune response and response to viruses, etc. For an independent verification of these 6 type I IFN related genes, peripheral blood mononuclear cells (PBMCs) were collected at baseline and day 3 after the vaccination from 8 Enterovirus 71(EV71) vaccinees and were assayed by RT-PCR. Results showed that the 6 DEGs were also upregulated in EV71 vaccinees. In summary, meta-analysis methods were used to explore the immune mechanism of vaccines and results indicated that the type I IFN related genes and corresponding pathways were common in early immune responses for different kinds of vaccines. PMID:25839220

  11. Spectral Biclustering of Microarray Data: Coclustering Genes and Conditions

    PubMed Central

    Kluger, Yuval; Basri, Ronen; Chang, Joseph T.; Gerstein, Mark

    2003-01-01

    Global analyses of RNA expression levels are useful for classifying genes and overall phenotypes. Often these classification problems are linked, and one wants to find “marker genes” that are differentially expressed in particular sets of “conditions.” We have developed a method that simultaneously clusters genes and conditions, finding distinctive “checkerboard” patterns in matrices of gene expression data, if they exist. In a cancer context, these checkerboards correspond to genes that are markedly up- or downregulated in patients with particular types of tumors. Our method, spectral biclustering, is based on the observation that checkerboard structures in matrices of expression data can be found in eigenvectors corresponding to characteristic expression patterns across genes or conditions. In addition, these eigenvectors can be readily identified by commonly used linear algebra approaches, in particular the singular value decomposition (SVD), coupled with closely integrated normalization steps. We present a number of variants of the approach, depending on whether the normalization over genes and conditions is done independently or in a coupled fashion. We then apply spectral biclustering to a selection of publicly available cancer expression data sets, and examine the degree to which the approach is able to identify checkerboard structures. Furthermore, we compare the performance of our biclustering methods against a number of reasonable benchmarks (e.g., direct application of SVD or normalized cuts to raw data). PMID:12671006

  12. Microarray analysis provides new insights into the function of apolipoprotein O in HepG2 cell line

    PubMed Central

    2013-01-01

    Background Apolipoprotein O (apoO) is a new member of the apolipoprotein family. However, data on its physiological functions are limited and inconsistent. Using a microarray expression analysis, this study explored the function of apoO in liver cells. Methods HepG2 cells were treated either with oleic acid or tumor necrosis factor-α for 24 h. mRNA and protein expression of apoO were assessed by quantitative real-time PCR (qRT-PCR) and Western blot respectively. An efficient lentiviral siRNA vector targeting the human apoO gene was designed and constructed. The gene expression profile of HepG2 human hepatocellular carcinoma cells transfected with the apoO silencing vector was investigated using a whole-genome oligonucleotide microarray. The expression levels of some altered genes were validated using qRT-PCR. Results ApoO expression in HepG2 cells was dramatically affected by lipid and inflammatory stimuli. A total of 282 differentially expressed genes in apoO-silenced HepG2 cells were identified by microarray analysis. These genes included those participating in fatty acid metabolism, such as ACSL4, RGS16, CROT and CYP4F11, and genes participating in the inflammatory response, such as NFKBIZ, TNFSF15, USP2, IL-17, CCL23, NOTCH2, APH-1B and N2N. The gene Uncoupling protein 2 (UCP2), which is involved in both these metabolic pathways, demonstrated significant changes in mRNA level after transfection. Conclusions It is likely that apoO participates in fatty acid metabolism and the inflammatory response in HepG2 cells, and UCP2 may act as a mediator between lipid metabolism and inflammation in apoO-silenced HepG2 cells. PMID:24341743

  13. 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

  14. A Microarray-Based Gene Expression Analysis to Identify Diagnostic Biomarkers for Unknown Primary Cancer

    PubMed Central

    Kurahashi, Issei; Fujita, Yoshihiko; Arao, Tokuzo; Kurata, Takayasu; Koh, Yasuhiro; Sakai, Kazuko; Matsumoto, Koji; Tanioka, Maki; Takeda, Koji; Takiguchi, Yuichi; Yamamoto, Nobuyuki; Tsuya, Asuka; Matsubara, Nobuaki; Mukai, Hirofumi; Minami, Hironobu; Chayahara, Naoko; Yamanaka, Yasuhiro; Miwa, Keisuke; Takahashi, Shin; Takahashi, Shunji; Nakagawa, Kazuhiko; Nishio, Kazuto

    2013-01-01

    Background The biological basis for cancer of unknown primary (CUP) at the molecular level remains largely unknown, with no evidence of whether a common biological entity exists. Here, we assessed the possibility of identifying a common diagnostic biomarker for CUP using a microarray gene expression analysis. Methods Tumor mRNA samples from 60 patients with CUP were analyzed using the Affymetrix U133A Plus 2.0 GeneChip and were normalized by asinh (hyperbolic arc sine) transformation to construct a mean gene-expression profile specific to CUP. A gene-expression profile specific to non-CUP group was constructed using publicly available raw microarray datasets. The t-tests were performed to compare the CUP with non-CUP groups and the top 59 CUP specific genes with the highest fold change were selected (p-value<0.001). Results Among the 44 genes that were up-regulated in the CUP group, 6 genes for ribosomal proteins were identified. Two of these genes (RPS7 and RPL11) are known to be involved in the Mdm2–p53 pathway. We also identified several genes related to metastasis and apoptosis, suggesting a biological attribute of CUP. Conclusions The protein products of the up-regulated and down-regulated genes identified in this study may be clinically useful as unique biomarkers for CUP. PMID:23671674

  15. 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

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

    PubMed Central

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

    2004-01-01

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

  17. Fusarium verticillioides gene expression profiling by microarray analysis

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  18. 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

  19. 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

  20. 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.

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

    PubMed

    Alshamlan, Hala; Badr, Ghada; Alohali, Yousef

    2015-01-01

    An artificial bee colony (ABC) is a relatively recent swarm intelligence optimization approach. In this paper, we propose the first attempt at applying ABC algorithm in analyzing a microarray gene expression profile. In addition, we propose an innovative feature selection algorithm, minimum redundancy maximum relevance (mRMR), and combine it with an ABC algorithm, mRMR-ABC, to select informative genes from microarray profile. The new approach is based on a support vector machine (SVM) algorithm to measure the classification accuracy for selected genes. We evaluate the performance of the proposed mRMR-ABC algorithm by conducting extensive experiments on six binary and multiclass gene expression microarray datasets. Furthermore, we compare our proposed mRMR-ABC algorithm with previously known techniques. We reimplemented two of these techniques for the sake of a fair comparison using the same parameters. These two techniques are mRMR when combined with a genetic algorithm (mRMR-GA) and mRMR when combined with a particle swarm optimization algorithm (mRMR-PSO). The experimental results prove that the proposed mRMR-ABC algorithm achieves accurate classification performance using small number of predictive genes when tested using both datasets and compared to previously suggested methods. This shows that mRMR-ABC is a promising approach for solving gene selection and cancer classification problems. PMID:25961028

  2. 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

  3. Gene Expression Profiling and Identification of Resistance Genes to Aspergillus flavus Infection in Peanut through EST and Microarray Strategies

    PubMed Central

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

    2011-01-01

    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 Aspergillus flavus 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

  4. Transfection microarrays for high-throughput phenotypic screening of genes involved in cell migration.

    PubMed

    Onuki-Nagasaki, Reiko; Nagasaki, Akira; Hakamada, Kazumi; Uyeda, Taro Q P; Fujita, Satoshi; Miyake, Masato; Miyake, Jun

    2010-01-01

    Cell migration is important in several biological phenomena, such as cancer metastasis. Therefore, the identification of genes involved in cell migration might facilitate the discovery of antimetastatic drugs. However, screening of genes by the current methods can be complicated by factors related to cell stimulation, for example, abolition of contact inhibition and the release inflammatory cytokines from wounded cells during examinations of wound healing in vitro. To overcome these problems and identify genes involved in cell migration, in this chapter we describe the use of transfection microarrays for high-throughput phenotypic screening. PMID:20387151

  5. Microarray expression profiling identifies genes with altered expression in HDL-deficient mice

    SciTech Connect

    Callow, Matthew J.; Dudoit, Sandrine; Gong, Elaine L.; Speed, Terence P.; Rubin, Edward M.

    2000-05-05

    Based on the assumption that severe alterations in the expression of genes known to be involved in HDL metabolism may affect the expression of other genes we screened an array of over 5000 mouse expressed sequence tags (ESTs) for altered gene expression in the livers of two lines of mice with dramatic decreases in HDL plasma concentrations. Labeled cDNA from livers of apolipoprotein AI (apo AI) knockout mice, Scavenger Receptor BI (SR-BI) transgenic mice and control mice were co-hybridized to microarrays. Two-sample t-statistics were used to identify genes with altered expression levels in the knockout or transgenic mice compared with the control mice. In the SR-BI group we found 9 array elements representing at least 5 genes to be significantly altered on the basis of an adjusted p value of less than 0.05. In the apo AI knockout group 8 array elements representing 4 genes were altered compared with the control group (p < 0.05). Several of the genes identified in the SR-BI transgenic suggest altered sterol metabolism and oxidative processes. These studies illustrate the use of multiple-testing methods for the identification of genes with altered expression in replicated microarray experiments of apo AI knockout and SR-BI transgenic mice.

  6. Microarray gene expression analysis of the human airway in patients exposed to sulfur mustard.

    PubMed

    Najafi, Ali; Masoudi-Nejad, Ali; Imani Fooladi, Abbas Ali; Ghanei, Mostafa; Nourani, Mohamad Reza

    2014-08-01

    There is much data about the acute effects of sulfur mustard gas on humans, animals and cells. But less is known regarding the molecular basics of chronic complications in humans. Basically, mustard gas, as an alkylating agent, causes several chronic problems in the eyes, skin and more importantly in the pulmonary system which is the main cause of death. Although recent proteomic research has been carried out on bronchoalveolar lavage (BAL) and serum, but high-throughput transcriptomics have not yet been applied to chronic airway remodeling. This is the first cDNA-microarray report on the chronic human mustard lung disease, 25 years after exposure during the Iran-Iraq war. Microarray transcriptional profiling indicated that a total of 122 genes were significantly dysregulated in tissues located in the airway of patients. These genes are associated with the extracellular matrix components, apoptosis, stress response, inflammation and mucus secretion. PMID:24823320

  7. Methods for gene expression profiling in dermatology research using DermArray nylon filter DNA microarrays.

    PubMed

    Davis, Richard L; DuBreuil, Rusla M; Reddy, Shanker P; Dooley, Thomas P

    2005-01-01

    Here we present methods of gene expression profiling using nylon filter deoxyribonucleic acid (DNA) microarrays and radiolabeled and nonradiolabeled hybridization probes. DermArray(R) nylon filter DNA microarrays were designed specifically for use in dermatology research. A patent-pending method was used to select approx 4400 highly informative, sequence-verified human cDNA clones for this DNA micro array. Using DermArray(R) filters, biomarkers have been discovered for normal and pathologic cells from skin, and for responses to dermatologic drugs. As an example, gene expression profiling was performed with hydroquinone-treated SKMel-28 cells, a melanoma cell line. Also included are the methods for bioinformatic analysis using Pathwaystrade mark software. PMID:15502201

  8. Interactive Exploration of Microarray Gene Expression Patterns in a Reduced Dimensional Space

    PubMed Central

    Misra, Jatin; Schmitt, William; Hwang, Daehee; Hsiao, Li-Li; Gullans, Steve; Stephanopoulos, George; Stephanopoulos, Gregory

    2002-01-01

    The very high dimensional space of gene expression measurements obtained by DNA microarrays impedes the detection of underlying patterns in gene expression data and the identification of discriminatory genes. In this paper we show the use of projection methods such as principal components analysis (PCA) to obtain a direct link between patterns in the genes and patterns in samples. This feature is useful in the initial interactive pattern exploration of gene expression data and data-driven learning of the nature and types of samples. Using oligonucleotide microarray measurements of 40 samples from different normal human tissues, we show that distinct patterns are obtained when the genes are projected on a two-dimensional plane spanned by the loadings of the two major principal components. These patterns define the particular genes associated with a sample class (i.e., tissue). When used separately from the other genes, these class-specific (i.e., tissue-specific) genes in turn define distinct tissue patterns in the projection space spanned by the scores of the two major principal components. In this study, PCA projection facilitated discriminatory gene selection for different tissues and identified tissue-specific gene expression signatures for liver, skeletal muscle, and brain samples. Furthermore, it allowed the classification of nine new samples belonging to these three types using the linear combination of the expression levels of the tissue-specific genes determined from the first set of samples. The application of the technique to other published data sets is also discussed. [Online supplementary material available at www.genome.org.] PMID:12097349

  9. Interval based fuzzy systems for identification of important genes from microarray gene expression data: Application to carcinogenic development.

    PubMed

    De, Rajat K; Ghosh, Anupam

    2009-12-01

    In the present article, we develop two interval based fuzzy systems for identification of some possible genes mediating the carcinogenic development in various tissues. The methodology involves dimensionality reduction, classifying the genes through incorporation of the notion of linguistic fuzzy sets low, medium and high, and finally selection of some possible genes mediating a particular disease, obtained by a rule generation/grouping technique. The effectiveness of the proposed methodology, is demonstrated using five microarray gene expression datasets dealing with human lung, colon, sarcoma, breast cancer and leukemia. Moreover, the superior capability of the methodology in selecting important genes, over five other existing gene selection methods, viz., Significance Analysis of Microarrays (SAM), Signal-to-Noise Ratio (SNR), Neighborhood analysis (NA), Bayesian Regularization (BR) and Data-adaptive (DA) is demonstrated, in terms of the enrichment of each GO category of the important genes based on P-values. The results are appropriately validated by earlier investigations, gene expression profiles and t-test. The proposed methodology has been able to select genes that are more biologically significant in mediating the development of a disease than those obtained by the others. PMID:19591962

  10. 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

  11. 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

  12. Sex-related gene expression profiles in the adrenal cortex in the mature rat: microarray analysis with emphasis on genes involved in steroidogenesis.

    PubMed

    Trejter, Marcin; Hochol, Anna; Tyczewska, Marianna; Ziolkowska, Agnieszka; Jopek, Karol; Szyszka, Marta; Malendowicz, Ludwik K; Rucinski, Marcin

    2015-03-01

    Notable sex-related differences exist in mammalian adrenal cortex structure and function. In adult rats, the adrenal weight and the average volume of zona fasciculata cells of females are larger and secrete greater amounts of corticosterone than those of males. The molecular bases of these sex-related differences are poorly understood. In this study, to explore the molecular background of these differences, we defined zone- and sex-specific transcripts in adult male and female (estrous cycle phase) rats. Twelve-week-old rats of both genders were used and samples were taken from the zona glomerulosa (ZG) and zona fasciculata/reticularis (ZF/R) zones. Transcriptome identification was carried out using the Affymetrix(®) Rat Gene 1.1 ST Array. The microarray data were compared by fold change with significance according to moderated t-statistics. Subsequently, we performed functional annotation clustering using the Gene Ontology (GO) and Database for Annotation, Visualization and Integrated Discovery (DAVID). In the first step, we explored differentially expressed transcripts in the adrenal ZG and ZF/R. The number of differentially expressed transcripts was notably higher in the female than in the male rats (702 vs. 571). The differentially expressed genes which were significantly enriched included genes involved in steroid hormone metabolism, and their expression levels in the ZF/R of adult female rats were significantly higher compared with those in the male rats. In the female ZF/R, when compared with that of the males, prevailing numbers of genes linked to cell fraction, oxidation/reduction processes, response to nutrients and to extracellular stimuli or steroid hormone stimuli were downregulated. The microarray data for key genes involved directly in steroidogenesis were confirmed by qPCR. Thus, when compared with that of the males, in the female ZF/R, higher expression levels of genes involved directly in steroid hormone synthesis were accompanied by lower

  13. 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

  14. 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

  15. 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

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

    PubMed Central

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

    2015-01-01

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

  17. Microarray analysis of active cardiac remodeling genes in a familial hypertrophic cardiomyopathy mouse model rescued by a phospholamban knockout

    PubMed Central

    Rajan, Sudarsan; Pena, James R.; Jegga, Anil G.; Aronow, Bruce J.; Wolska, Beata M.

    2013-01-01

    Familial hypertrophic cardiomyopathy (FHC) is a disease characterized by ventricular hypertrophy, fibrosis, and aberrant systolic and/or diastolic function. Our laboratories have previously developed two mouse models that affect cardiac performance. One mouse model encodes an FHC-associated mutation in α-tropomyosin: Glu → Gly at amino acid 180, designated as Tm180. These mice display a phenotype that is characteristic of FHC, including severe cardiac hypertrophy with fibrosis and impaired physiological performance. The other model was a gene knockout of phospholamban (PLN KO), a regulator of calcium uptake in the sarcoplasmic reticulum of cardiomyocytes; these hearts exhibit hypercontractility with no pathological abnormalities. Previous work in our laboratories shows that when mice were genetically crossed between the PLN KO and Tm180, the progeny (PLN KO/Tm180) display a rescued hypertrophic phenotype with improved morphology and cardiac function. To understand the changes in gene expression that occur in these models undergoing cardiac remodeling (Tm180, PLN KO, PLN KO/Tm180, and nontransgenic control mice), we conducted microarray analyses of left ventricular tissue at 4 and 12 mo of age. Expression profiling reveals that 1,187 genes changed expression in direct response to the three genetic models. With these 1,187 genes, 11 clusters emerged showing normalization of transcript expression in the PLN KO/Tm180 hearts. In addition, 62 transcripts are highly involved in suppression of the hypertrophic phenotype. Confirmation of the microarray analysis was conducted by quantitative RT-PCR. These results provide insight into genes that alter expression during cardiac remodeling and are active during modulation of the cardiomyopathic phenotype. PMID:23800848

  18. 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.

  19. 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

  20. [Advances of microarray analysis on plant gene expression under environmental stresses].

    PubMed

    Lin, Hai-Jian; Zhang, Zhi-Ming; Shen, Ya-Ou; Gao, Shi-Bin; Pan, Guang-Tang

    2009-12-01

    Different stressed conditions impair plant growth and further, cause great loss of crop yield and even lead to lose production completely. Increasing resistance/tolerance of crops under stressed conditions is a major goal of numerous plant breeders, and many elegant works are focusing on this area to uncover these complicated mechanisms underlying it. However, the traditional strategies including physiological and biochemical methods, as well as studies on a few genes, can not well understand the overall biological mechanism. Microarray analysis opens a door to uncover these cryptic mechanisms, and has the ability of detecting gene transcription and regulation at genomic level in different plant tissues. And works in association with related methods of proteomics and metabolomics. Therefore, it is possible to locate genes in certain key metabolism pathways. Through these procedures, it is also possible to look for critical genes in the pathway and to well understand the molecular mechanism of resistance/tolerance. These results can be as a guidance for increasing the resistance/tolerance of stressed conditions using biotechnology methods in future. This paper mainly focused on and discussed the advances of microarray analysis of stressed conditions-related genes in plants. PMID:20042386

  1. 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

  2. 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

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

    PubMed Central

    2012-01-01

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

  4. Classification of microarrays; synergistic effects between normalization, gene selection and machine learning

    PubMed Central

    2011-01-01

    Background Machine learning is a powerful approach for describing and predicting classes in microarray data. Although several comparative studies have investigated the relative performance of various machine learning methods, these often do not account for the fact that performance (e.g. error rate) is a result of a series of analysis steps of which the most important are data normalization, gene selection and machine learning. Results In this study, we used seven previously published cancer-related microarray data sets to compare the effects on classification performance of five normalization methods, three gene selection methods with 21 different numbers of selected genes and eight machine learning methods. Performance in term of error rate was rigorously estimated by repeatedly employing a double cross validation approach. Since performance varies greatly between data sets, we devised an analysis method that first compares methods within individual data sets and then visualizes the comparisons across data sets. We discovered both well performing individual methods and synergies between different methods. Conclusion Support Vector Machines with a radial basis kernel, linear kernel or polynomial kernel of degree 2 all performed consistently well across data sets. We show that there is a synergistic relationship between these methods and gene selection based on the T-test and the selection of a relatively high number of genes. Also, we find that these methods benefit significantly from using normalized data, although it is hard to draw general conclusions about the relative performance of different normalization procedures. PMID:21982277

  5. 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. PMID:25880524

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

    PubMed Central

    2013-01-01

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

  7. A New Symbolic Representation for the Identification of Informative Genes in Replicated Microarray Experiments

    PubMed Central

    Scheff, Jeremy D.; Almon, Richard R.; DuBois, Debra C.; Jusko, William J.

    2010-01-01

    Abstract Microarray experiments generate massive amounts of data, necessitating innovative algorithms to distinguish biologically relevant information from noise. Because the variability of gene expression data is an important factor in determining which genes are differentially expressed, analysis techniques that take into account repeated measurements are critically important. Additionally, the selection of informative genes is typically done by searching for the individual genes that vary the most across conditions. Yet because genes tend to act in groups rather than individually, it may be possible to glean more information from the data by searching specifically for concerted behavior in a set of genes. Applying a symbolic transformation to the gene expression data allows the detection overrepresented patterns in the data, in contrast to looking only for genes that exhibit maximal differential expression. These challenges are approached by introducing an algorithm based on a new symbolic representation that searches for concerted gene expression patterns; furthermore, the symbolic representation takes into account the variance in multiple replicates and can be applied to long time series data. The proposed algorithm's ability to discover biologically relevant signals in gene expression data is exhibited by applying it to three datasets that measure gene expression in the rat liver. PMID:20455749

  8. Gene-expression profiling of human mononuclear cells from welders using cDNA microarray.

    PubMed

    Rim, Kyung Taek; Park, Kun Koo; Kim, Yang Ho; Lee, Yong Hwan; Han, Jeong Hee; Chung, Yong Hyun; Yu, Il Je

    2007-08-01

    A toxicogenomic chip developed to detect welding-related diseases was tested and validated for field trials. To verify the suitability of the microarray, white blood cells (WBC) or whole blood was purified and characterized from 20 subjects in the control group (average work experience of 7 yr) and 20 welders in the welding-fume exposed group (welders with an average work experience of 23 yr). Two hundred and fifty-three rat genes homologous to human genes were obtained and spotted on the chip slide. Meanwhile, a human cDNA chip spotted with 8600 human genes was also used to detect any increased or decreased levels of gene expression among the welders. After comparing the levels of gene expression between the control and welder groups using the toxicogenomic chips, 103 genes were identified as likely to be specifically changed by welding-fume exposure. Eighteen of the 253 rat genes were specifically changed in the welders, while 103 genes from the human cDNA chip were specifically changed. The genes specifically expressed by the welders were associated with inflammatory responses, toxic chemical metabolism, stress proteins, transcription factors, and signal transduction. In contrast, there was no significant change in the genes related to short-term welding-fume exposure, such as tumor necrosis factor (TNF)-alpha and interleukin. In conclusion, if further validation studies are conducted, the present toxicogenomic gene chips could be used for the effective monitoring of welding-fume-exposure-related diseases among welders. PMID:17654244

  9. 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

  10. Development of a microarray for two rice subspecies: characterization and validation of gene expression in rice tissues

    PubMed Central

    2014-01-01

    Background Rice is one of the major crop species in the world helping to sustain approximately half of the global population’s diet especially in Asia. However, due to the impact of extreme climate change and global warming, rice crop production and yields may be adversely affected resulting in a world food crisis. Researchers have been keen to understand the effects of drought, temperature and other environmental stress factors on rice plant growth and development. Gene expression microarray technology represents a key strategy for the identification of genes and their associated expression patterns in response to stress. Here, we report on the development of the rice OneArray® microarray platform which is suitable for two major rice subspecies, japonica and indica. Results The rice OneArray® 60-mer, oligonucleotide microarray consists of a total of 21,179 probes covering 20,806 genes of japonica and 13,683 genes of indica. Through a validation study, total RNA isolated from rice shoots and roots were used for comparison of gene expression profiles via microarray examination. The results were submitted to NCBI’s Gene Expression Omnibus (GEO). Data can be found under the GEO accession number GSE50844 (http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE50844). A list of significantly differentially expressed genes was generated; 438 shoot-specific genes were identified among 3,138 up-regulated genes, and 463 root-specific genes were found among 3,845 down-regulated genes. GO enrichment analysis demonstrates these results are in agreement with the known physiological processes of the different organs/tissues. Furthermore, qRT-PCR validation was performed on 66 genes, and found to significantly correlate with the microarray results (R = 0.95, p < 0.001***). Conclusion The rice OneArray® 22 K microarray, the first rice microarray, covering both japonica and indica subspecies was designed and validated in a comprehensive study of gene expression in