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Sample records for approaches gene expression

  1. A constructive approach to gene expression dynamics

    International Nuclear Information System (INIS)

    Recently, experiments on mRNA abundance (gene expression) have revealed that gene expression shows a stationary organization described by a scale-free distribution. Here we propose a constructive approach to gene expression dynamics which restores the scale-free exponent and describes the intermediate state dynamics. This approach requires only one assumption: Markov property

  2. Evolutionary Approach for Relative Gene Expression Algorithms

    OpenAIRE

    Marcin Czajkowski; Marek Kretowski

    2014-01-01

    A Relative Expression Analysis (RXA) uses ordering relationships in a small collection of genes and is successfully applied to classiffication using microarray data. As checking all possible subsets of genes is computationally infeasible, the RXA algorithms require feature selection and multiple restrictive assumptions. Our main contribution is a specialized evolutionary algorithm (EA) for top-scoring pairs called EvoTSP which allows finding more advanced gene relations. We managed to unify t...

  3. A stochastic approach to multi-gene expression dynamics

    International Nuclear Information System (INIS)

    In the last years, tens of thousands gene expression profiles for cells of several organisms have been monitored. Gene expression is a complex transcriptional process where mRNA molecules are translated into proteins, which control most of the cell functions. In this process, the correlation among genes is crucial to determine the specific functions of genes. Here, we propose a novel multi-dimensional stochastic approach to deal with the gene correlation phenomena. Interestingly, our stochastic framework suggests that the study of the gene correlation requires only one theoretical assumption-Markov property-and the experimental transition probability, which characterizes the gene correlation system. Finally, a gene expression experiment is proposed for future applications of the model

  4. Analysis of bHLH coding genes using gene co-expression network approach.

    Science.gov (United States)

    Srivastava, Swati; Sanchita; Singh, Garima; Singh, Noopur; Srivastava, Gaurava; Sharma, Ashok

    2016-07-01

    Network analysis provides a powerful framework for the interpretation of data. It uses novel reference network-based metrices for module evolution. These could be used to identify module of highly connected genes showing variation in co-expression network. In this study, a co-expression network-based approach was used for analyzing the genes from microarray data. Our approach consists of a simple but robust rank-based network construction. The publicly available gene expression data of Solanum tuberosum under cold and heat stresses were considered to create and analyze a gene co-expression network. The analysis provide highly co-expressed module of bHLH coding genes based on correlation values. Our approach was to analyze the variation of genes expression, according to the time period of stress through co-expression network approach. As the result, the seed genes were identified showing multiple connections with other genes in the same cluster. Seed genes were found to be vary in different time periods of stress. These analyzed seed genes may be utilized further as marker genes for developing the stress tolerant plant species. PMID:27178572

  5. Regulation of gene expression by hypoxia: a molecular approach.

    Science.gov (United States)

    Beitner-Johnson, D; Shull, G E; Dedman, J R; Millhorn, D E

    1997-11-01

    Oxygen is a strict requirement for cell function. The cellular mechanisms by which organisms detect and respond to changes in oxygen tension remain a major unanswered question in pulmonary physiology. Part of the difficulty in addressing this question is due to the limited scope of experiments that can be performed in vivo. In the past few years, several laboratories have begun to make progress in this area, using a variety of cell culture model systems and sophisticated genetic manipulations. Here, we review the current state of knowledge of regulation of gene expression by hypoxia, and describe novel experimental approaches that promise to broaden our understanding of how cells and whole organisms respond to alterations in O2 tension. PMID:9407603

  6. Biclustering using Parallel Fuzzy Approach for Analysis of Microarray Gene Expression Data

    OpenAIRE

    Dwitiya Tyagi-Tiwari; Sujoy Das; Manoj Jha; Namita Srivastava

    2015-01-01

    Biclusters are required to analyzing gene expression patterns of genes comparing rows in expression profiles and analyzing expression profiles of samples by comparing columns in gene expression matrix. In the process of biclustering we need to cluster genes and samples. The algorithm presented in this paper is based upon the two-way clustering approach in which the genes and samples are clustered using parallel fuzzy C-means clustering using message passing interface, we call it MFCM. MFCM ap...

  7. Randomized Algorithmic Approach for Biclustering of Gene Expression Data

    OpenAIRE

    Sradhanjali Nayak; Debahuti Mishra; Satyabrata Das; Amiya Kumar Rath

    2011-01-01

    Microarray data processing revolves around the pivotal issue of locating genes altering their expression in response to pathogens, other organisms or other multiple environmental conditions resulted out of a comparison between infected and uninfected cells or tissues. To have a comprehensive analysis of the corollaries of certain treatments, deseases and developmental stages embodied as a data matrix on gene expression data is possible through simultaneous observation and monitoring of the ex...

  8. Clustering based gene expression feature selection method: A computational approach to enrich the classifier efficiency of differentially expressed genes

    KAUST Repository

    Abusamra, Heba

    2016-07-20

    The native nature of high dimension low sample size of gene expression data make the classification task more challenging. Therefore, feature (gene) selection become an apparent need. Selecting a meaningful and relevant genes for classifier not only decrease the computational time and cost, but also improve the classification performance. Among different approaches of feature selection methods, however most of them suffer from several problems such as lack of robustness, validation issues etc. Here, we present a new feature selection technique that takes advantage of clustering both samples and genes. Materials and methods We used leukemia gene expression dataset [1]. The effectiveness of the selected features were evaluated by four different classification methods; support vector machines, k-nearest neighbor, random forest, and linear discriminate analysis. The method evaluate the importance and relevance of each gene cluster by summing the expression level for each gene belongs to this cluster. The gene cluster consider important, if it satisfies conditions depend on thresholds and percentage otherwise eliminated. Results Initial analysis identified 7120 differentially expressed genes of leukemia (Fig. 15a), after applying our feature selection methodology we end up with specific 1117 genes discriminating two classes of leukemia (Fig. 15b). Further applying the same method with more stringent higher positive and lower negative threshold condition, number reduced to 58 genes have be tested to evaluate the effectiveness of the method (Fig. 15c). The results of the four classification methods are summarized in Table 11. Conclusions The feature selection method gave good results with minimum classification error. Our heat-map result shows distinct pattern of refines genes discriminating between two classes of leukemia.

  9. Biclustering using Parallel Fuzzy Approach for Analysis of Microarray Gene Expression Data

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    Dwitiya Tyagi-Tiwari

    2015-09-01

    Full Text Available Biclusters are required to analyzing gene expression patterns of genes comparing rows in expression profiles and analyzing expression profiles of samples by comparing columns in gene expression matrix. In the process of biclustering we need to cluster genes and samples. The algorithm presented in this paper is based upon the two-way clustering approach in which the genes and samples are clustered using parallel fuzzy C-means clustering using message passing interface, we call it MFCM. MFCM applied for clustering on genes and samples which maximize membership function values of the data set. It is a parallelized rework of a parallel fuzzy two-way clustering algorithm for microarray gene expression data [9], to study the efficiency and parallelization improvement of the algorithm. The algorithm uses gene entropy measure to filter the clustered data to find biclusters. The method is able to get highly correlated biclusters of the gene expression dataset.

  10. Gene expression

    International Nuclear Information System (INIS)

    We prepared probes for isolating functional pieces of the metallothionein locus. The probes enabled a variety of experiments, eventually revealing two mechanisms for metallothionein gene expression, the order of the DNA coding units at the locus, and the location of the gene site in its chromosome. Once the switch regulating metallothionein synthesis was located, it could be joined by recombinant DNA methods to other, unrelated genes, then reintroduced into cells by gene-transfer techniques. The expression of these recombinant genes could then be induced by exposing the cells to Zn2+ or Cd2+. We would thus take advantage of the clearly defined switching properties of the metallothionein gene to manipulate the expression of other, perhaps normally constitutive, genes. Already, despite an incomplete understanding of how the regulatory switch of the metallothionein locus operates, such experiments have been performed successfully

  11. Bayesian forecasting of temporal gene expression by using an autoregressive panel data approach.

    Science.gov (United States)

    Nascimento, M; E Silva, F F; Sáfadi, T; Nascimento, A C C; Barroso, L M A; Glória, L S; de S Carvalho, B

    2016-01-01

    We propose and evaluate a novel approach for forecasting gene expression over non-observed times in longitudinal trials under a Bayesian viewpoint. One of the aims is to cluster genes that share similar expression patterns over time and then use this similarity to predict relative expression at time points of interest. Expression values of 106 genes expressed during the cell cycle of Saccharomyces cerevisiae were used and genes were partitioned into five distinct clusters of sizes 33, 32, 21, 16, and 4. After removing the last observed time point, the agreements of signals (upregulated or downregulated) considering the predicted expression level were 72.7, 81.3, 76.2, 68.8, and 50.0%, respectively, for each cluster. The percentage of credibility intervals that contained the true values of gene expression for a future time was ~90%. The methodology performed well, providing a valid forecast of gene expression values by fitting an autoregressive panel data model. This approach is easily implemented with other time-series models and when Poisson and negative binomial probability distributions are assumed for the gene expression data. PMID:27323205

  12. A graphical model approach for inferring large-scale networks integrating gene expression and genetic polymorphism

    Directory of Open Access Journals (Sweden)

    Carey Vincent J

    2009-05-01

    Full Text Available Abstract Background Graphical models (e.g., Bayesian networks have been used frequently to describe complex interaction patterns and dependent structures among genes and other phenotypes. Estimation of such networks has been a challenging problem when the genes considered greatly outnumber the samples, and the situation is exacerbated when one wishes to consider the impact of polymorphisms (SNPs in genes. Results Here we describe a multistep approach to infer a gene-SNP network from gene expression and genotyped SNP data. Our approach is based on 1 construction of a graphical Gaussian model (GGM based on small sample estimation of partial correlation and false-discovery rate multiple testing; 2 extraction of a subnetwork of genes directly linked to a target candidate gene of interest; 3 identification of cis-acting regulatory variants for the genes composing the subnetwork; and 4 evaluating the identified cis-acting variants for trans-acting regulatory effects of the target candidate gene. This approach identifies significant gene-gene and gene-SNP associations not solely on the basis of gene co-expression but rather through whole-network modeling. We demonstrate the method by building two complex gene-SNP networks around Interferon Receptor 12B2 (IL12RB2 and Interleukin 1B (IL1B, two biologic candidates in asthma pathogenesis, using 534,290 genotyped variants and gene expression data on 22,177 genes from total RNA derived from peripheral blood CD4+ lymphocytes from 154 asthmatics. Conclusion Our results suggest that graphical models based on integrative genomic data are computationally efficient, work well with small samples, and can describe complex interactions among genes and polymorphisms that could not be identified by pair-wise association testing.

  13. Determination of the Ultimate Limit States of Shallow Foundations using Gene Expression Programming (GEP) Approach

    DEFF Research Database (Denmark)

    Tahmasebi poor, A; Barari, Amin; Behnia, M;

    2015-01-01

    In this study, a gene expression programming (GEP) approach was employed to develop modified expressions for predicting the bearing capacity of shallow foundations founded on granular material. The model was validate against the results of load tests on full-scale and model footings obtained from...

  14. A combinatorial bidirectional and bicistronic approach for coordinated multi-gene expression in corn.

    Science.gov (United States)

    Kumar, Sandeep; AlAbed, Diaa; Whitteck, John T; Chen, Wei; Bennett, Sara; Asberry, Andrew; Wang, Xiujuan; DeSloover, Daniel; Rangasamy, Murugesan; Wright, Terry R; Gupta, Manju

    2015-03-01

    Transgene stacking in trait development process through genetic engineering is becoming complex with increased number of desired traits and multiple modes of action for each trait. We demonstrate here a novel gene stacking strategy by combining bidirectional promoter (BDP) and bicistronic approaches to drive coordinated expression of multi-genes in corn. A unidirectional promoter, Ubiquitin-1 (ZMUbi1), from Zea mays was first converted into a synthetic BDP, such that a single promoter can direct the expression of two genes from each end of the promoter. The BDP system was then combined with a bicistronic organization of genes at both ends of the promoter by using a Thosea asigna virus 2A auto-cleaving domain. With this gene stacking configuration, we have successfully obtained expression in transgenic corn of four transgenes; three transgenes conferring insect (cry34Ab1 and cry35Ab1) and herbicide (aad1) resistance, and a phiyfp reporter gene using a single ZMUbi1 bidirectional promoter. Gene expression analyses of transgenic corn plants confirmed better coordinated expression of the four genes compared to constructs driving each gene by independent unidirectional ZmUbi1 promoter. To our knowledge, this is the first report that demonstrates application of a single promoter for co-regulation of multiple genes in a crop plant. This stacking technology would be useful for engineering metabolic pathways both for basic and applied research. PMID:25657118

  15. Hybrid particle swarm optimization and tabu search approach for selecting genes for tumor classification using gene expression data.

    Science.gov (United States)

    Shen, Qi; Shi, Wei-Min; Kong, Wei

    2008-02-01

    Gene expression data are characterized by thousands even tens of thousands of measured genes on only a few tissue samples. This can lead either to possible overfitting and dimensional curse or even to a complete failure in analysis of microarray data. Gene selection is an important component for gene expression-based tumor classification systems. In this paper, we develop a hybrid particle swarm optimization (PSO) and tabu search (HPSOTS) approach for gene selection for tumor classification. The incorporation of tabu search (TS) as a local improvement procedure enables the algorithm HPSOTS to overleap local optima and show satisfactory performance. The proposed approach is applied to three different microarray data sets. Moreover, we compare the performance of HPSOTS on these datasets to that of stepwise selection, the pure TS and PSO algorithm. It has been demonstrated that the HPSOTS is a useful tool for gene selection and mining high dimension data. PMID:18093877

  16. A robust approach based on Weibull distribution for clustering gene expression data

    Directory of Open Access Journals (Sweden)

    Gong Binsheng

    2011-05-01

    Full Text Available Abstract Background Clustering is a widely used technique for analysis of gene expression data. Most clustering methods group genes based on the distances, while few methods group genes according to the similarities of the distributions of the gene expression levels. Furthermore, as the biological annotation resources accumulated, an increasing number of genes have been annotated into functional categories. As a result, evaluating the performance of clustering methods in terms of the functional consistency of the resulting clusters is of great interest. Results In this paper, we proposed the WDCM (Weibull Distribution-based Clustering Method, a robust approach for clustering gene expression data, in which the gene expressions of individual genes are considered as the random variables following unique Weibull distributions. Our WDCM is based on the concept that the genes with similar expression profiles have similar distribution parameters, and thus the genes are clustered via the Weibull distribution parameters. We used the WDCM to cluster three cancer gene expression data sets from the lung cancer, B-cell follicular lymphoma and bladder carcinoma and obtained well-clustered results. We compared the performance of WDCM with k-means and Self Organizing Map (SOM using functional annotation information given by the Gene Ontology (GO. The results showed that the functional annotation ratios of WDCM are higher than those of the other methods. We also utilized the external measure Adjusted Rand Index to validate the performance of the WDCM. The comparative results demonstrate that the WDCM provides the better clustering performance compared to k-means and SOM algorithms. The merit of the proposed WDCM is that it can be applied to cluster incomplete gene expression data without imputing the missing values. Moreover, the robustness of WDCM is also evaluated on the incomplete data sets. Conclusions The results demonstrate that our WDCM produces clusters

  17. Biclustering of gene expression data: hybridization of GRASP with other heuristic/metaheuristic approaches

    OpenAIRE

    Musacchia, Francesco

    2013-01-01

    Researchers who work on large amount of data have to face vari- ous problems such as data mining and information retrieval: this is the case of gene expression. The general scope of these experiments is to find co-regulated genes, in order to understand the biologic pathways underlying a particular phenomenon. A clustering con- cept can be used to find out if co-regulated genes can be active only over some conditions. Recently, some biclustering approaches have been used to find groups of co-...

  18. From System-Wide Differential Gene Expression to Perturbed Regulatory Factors: A Combinatorial Approach.

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    Gaurang Mahajan

    Full Text Available High-throughput experiments such as microarrays and deep sequencing provide large scale information on the pattern of gene expression, which undergoes extensive remodeling as the cell dynamically responds to varying environmental cues or has its function disrupted under pathological conditions. An important initial step in the systematic analysis and interpretation of genome-scale expression alteration involves identification of a set of perturbed transcriptional regulators whose differential activity can provide a proximate hypothesis to account for these transcriptomic changes. In the present work, we propose an unbiased and logically natural approach to transcription factor enrichment. It involves overlaying a list of experimentally determined differentially expressed genes on a background regulatory network coming from e.g. literature curation or computational motif scanning, and identifying that subset of regulators whose aggregated target set best discriminates between the altered and the unaffected genes. In other words, our methodology entails testing of all possible regulatory subnetworks, rather than just the target sets of individual regulators as is followed in most standard approaches. We have proposed an iterative search method to efficiently find such a combination, and benchmarked it on E. coli microarray and regulatory network data available in the public domain. Comparative analysis carried out on artificially generated differential expression profiles, as well as empirical factor overexpression data for M. tuberculosis, shows that our methodology provides marked improvement in accuracy of regulatory inference relative to the standard method that involves evaluating factor enrichment in an individual manner.

  19. An effective fuzzy kernel clustering analysis approach for gene expression data.

    Science.gov (United States)

    Sun, Lin; Xu, Jiucheng; Yin, Jiaojiao

    2015-01-01

    Fuzzy clustering is an important tool for analyzing microarray data. A major problem in applying fuzzy clustering method to microarray gene expression data is the choice of parameters with cluster number and centers. This paper proposes a new approach to fuzzy kernel clustering analysis (FKCA) that identifies desired cluster number and obtains more steady results for gene expression data. First of all, to optimize characteristic differences and estimate optimal cluster number, Gaussian kernel function is introduced to improve spectrum analysis method (SAM). By combining subtractive clustering with max-min distance mean, maximum distance method (MDM) is proposed to determine cluster centers. Then, the corresponding steps of improved SAM (ISAM) and MDM are given respectively, whose superiority and stability are illustrated through performing experimental comparisons on gene expression data. Finally, by introducing ISAM and MDM into FKCA, an effective improved FKCA algorithm is proposed. Experimental results from public gene expression data and UCI database show that the proposed algorithms are feasible for cluster analysis, and the clustering accuracy is higher than the other related clustering algorithms. PMID:26405958

  20. Using intron splicing trick for preferential gene expression in transduced cells: an approach for suicide gene therapy.

    Science.gov (United States)

    Pourzadegan, F; Shariati, L; Taghizadeh, R; Khanahmad, H; Mohammadi, Z; Tabatabaiefar, M A

    2016-01-01

    Suicide gene therapy is one of the most innovative approaches in which a potential toxic gene is delivered to the targeted cancer cell by different target delivery methods. We constructed a transfer vector to express green fluorescent protein (GFP) in transduced cells but not in packaging cells. We placed gfp under the control of the cytomegalovirus (CMV) promoter, which is positioned between the two long-terminal repeats in reverse direction. The intron-2 sequence of the human beta globin gene with two poly-A signals and several stop codons on the antisense strand was placed on the leading strand between the CMV promoter and gfp. For lentiviral production, the HEK293T and line were co-transfected with the PMD2G, psPAX2 and pLentiGFP-Ins2 plasmids. The HEK293T and line were transduced with this virus. PCR was performed for evaluation of intron splicing in transduced cells. The GFP expression was seen in 65% of the cells transduced. The PCR amplification of the genomic DNA of transduced cells confirmed the splicing of intron 2. The strategy is significant to accomplish our goal for preserving the packaging cells from the toxic gene expression during viral assembly and the resultant reduction in viral titration. Also it serves to address several other issues in the gene therapy. PMID:26679755

  1. A novel approach for discovering condition-specific correlations of gene expressions within biological pathways by using cloud computing technology.

    Science.gov (United States)

    Chang, Tzu-Hao; Wu, Shih-Lin; Wang, Wei-Jen; Horng, Jorng-Tzong; Chang, Cheng-Wei

    2014-01-01

    Microarrays are widely used to assess gene expressions. Most microarray studies focus primarily on identifying differential gene expressions between conditions (e.g., cancer versus normal cells), for discovering the major factors that cause diseases. Because previous studies have not identified the correlations of differential gene expression between conditions, crucial but abnormal regulations that cause diseases might have been disregarded. This paper proposes an approach for discovering the condition-specific correlations of gene expressions within biological pathways. Because analyzing gene expression correlations is time consuming, an Apache Hadoop cloud computing platform was implemented. Three microarray data sets of breast cancer were collected from the Gene Expression Omnibus, and pathway information from the Kyoto Encyclopedia of Genes and Genomes was applied for discovering meaningful biological correlations. The results showed that adopting the Hadoop platform considerably decreased the computation time. Several correlations of differential gene expressions were discovered between the relapse and nonrelapse breast cancer samples, and most of them were involved in cancer regulation and cancer-related pathways. The results showed that breast cancer recurrence might be highly associated with the abnormal regulations of these gene pairs, rather than with their individual expression levels. The proposed method was computationally efficient and reliable, and stable results were obtained when different data sets were used. The proposed method is effective in identifying meaningful biological regulation patterns between conditions. PMID:24579087

  2. Snapshot of the eukaryotic gene expression in muskoxen rumen--a metatranscriptomic approach.

    Directory of Open Access Journals (Sweden)

    Meng Qi

    Full Text Available BACKGROUND: Herbivores rely on digestive tract lignocellulolytic microorganisms, including bacteria, fungi and protozoa, to derive energy and carbon from plant cell wall polysaccharides. Culture independent metagenomic studies have been used to reveal the genetic content of the bacterial species within gut microbiomes. However, the nature of the genes encoded by eukaryotic protozoa and fungi within these environments has not been explored using metagenomic or metatranscriptomic approaches. METHODOLOGY/PRINCIPAL FINDINGS: In this study, a metatranscriptomic approach was used to investigate the functional diversity of the eukaryotic microorganisms within the rumen of muskoxen (Ovibos moschatus, with a focus on plant cell wall degrading enzymes. Polyadenylated RNA (mRNA was sequenced on the Illumina Genome Analyzer II system and 2.8 gigabases of sequences were obtained and 59129 contigs assembled. Plant cell wall degrading enzyme modules including glycoside hydrolases, carbohydrate esterases and polysaccharide lyases were identified from over 2500 contigs. These included a number of glycoside hydrolase family 6 (GH6, GH48 and swollenin modules, which have rarely been described in previous gut metagenomic studies. CONCLUSIONS/SIGNIFICANCE: The muskoxen rumen metatranscriptome demonstrates a much higher percentage of cellulase enzyme discovery and an 8.7x higher rate of total carbohydrate active enzyme discovery per gigabase of sequence than previous rumen metagenomes. This study provides a snapshot of eukaryotic gene expression in the muskoxen rumen, and identifies a number of candidate genes coding for potentially valuable lignocellulolytic enzymes.

  3. Sensitive and robust gene expression changes in fish exposed to estrogen – a microarray approach

    Directory of Open Access Journals (Sweden)

    Nerman Olle

    2007-06-01

    Full Text Available Abstract Background Vitellogenin is a well established biomarker for estrogenic exposure in fish. However, effects on gonadal differentiation at concentrations of estrogen not sufficient to give rise to a measurable vitellogenin response suggest that more sensitive biomarkers would be useful. Induction of zona pellucida genes may be more sensitive but their specificities are not as clear. The objective of this study was to find additional sensitive and robust candidate biomarkers of estrogenic exposure. Results Hepatic mRNA expression profiles were characterized in juvenile rainbow trout exposed to a measured concentration of 0.87 and 10 ng ethinylestradiol/L using a salmonid cDNA microarray. The higher concentration was used to guide the subsequent identification of generally more subtle responses at the low concentration not sufficient to induce vitellogenin. A meta-analysis was performed with data from the present study and three similar microarray studies using different fish species and platforms. Within the generated list of presumably robust responses, several well-known estrogen-regulated genes were identified. Two genes, confirmed by quantitative RT-PCR (qPCR, fulfilled both the criteria of high sensitivity and robustness; the induction of the genes encoding zona pellucida protein 3 and a nucleoside diphosphate kinase (nm23. Conclusion The cross-species, cross-platform meta-analysis correctly identified several robust responses. This adds confidence to our approach used for identifying candidate biomarkers. Specifically, we propose that analyses of an nm23 gene together with zona pellucida genes may increase the possibilities to detect an exposure to low levels of estrogenic compounds in fish.

  4. A novel approach for a foreign gene expression by Newcastle disease virus

    Science.gov (United States)

    Newcastle disease virus (NDV) has been developed as vectors using reverse genetics technology to express foreign genes for vaccine, anticancer and gene therapy purposes. The foreign genes are usually inserted into the intergenic region of the NDV genome as an additional transcription unit. Based on ...

  5. A bi-ordering approach to linking gene expression with clinical annotations in gastric cancer

    OpenAIRE

    Leckie Christopher; Shi Fan; MacIntyre Geoff; Haviv Izhak; Boussioutas Alex; Kowalczyk Adam

    2010-01-01

    Abstract Background In the study of cancer genomics, gene expression microarrays, which measure thousands of genes in a single assay, provide abundant information for the investigation of interesting genes or biological pathways. However, in order to analyze the large number of noisy measurements in microarrays, effective and efficient bioinformatics techniques are needed to identify the associations between genes and relevant phenotypes. Moreover, systematic tests are needed to validate the ...

  6. A Hybrid SOM-SVM Approach for the Zebrafish Gene Expression Analysis

    Institute of Scientific and Technical Information of China (English)

    Wei Wu; Xin Liu; Min Xu; Jin-Rong Peng; Rudy Setiono

    2005-01-01

    Microarray technology can be employed to quantitatively measure the expression of thousands of genes in a single experiment. It has become one of the main tools for global gene expression analysis in molecular biology research in recent years. The large amount of expression data generated by this technology makes the study of certain complex biological problems possible, and machine learning methods are expected to play a crucial role in the analysis process. In this paper,we present our results from integrating the self-organizing map (SOM) and the support vector machine (SVM) for the analysis of the various functions of zebrafish genes based on their expression. The most distinctive characteristic of our zebrafish gene expression is that the number of samples of different classes is imbalanced. We discuss how SOM can be used as a data-filtering tool to improve the classification performance of the SVM on this data set.

  7. Transgenic approach to express the channelrhodopsin 2 gene in arginine vasopressin neurons of rats.

    Science.gov (United States)

    Ishii, Masahiro; Hashimoto, Hirofumi; Ohkubo, Jun-Ichi; Ohbuchi, Toyoaki; Saito, Takeshi; Maruyama, Takashi; Yoshimura, Mitsuhiro; Yamamoto, Yukiyo; Kusuhara, Koichi; Ueta, Yoichi

    2016-09-01

    Optogenetics provides a powerful tool to regulate neuronal activity by light-sensitive ion channels such as channelrhodopsin 2 (ChR2). Arginine vasopressin (AVP; also known as the anti-diuretic hormone) is a multifunctional hormone which is synthesized in the magnocellular neurosecretory cells (MNCs) of the hypothalamus. Here, we have generated a transgenic rat that expresses an AVP-ChR2-enhanced green fluorescent protein (eGFP) fusion gene in the MNCs of the hypothalamus. The eGFP fluorescence that indicates the expression of ChR2-eGFP was observed in the supraoptic nucleus (SON) and in the magnocellular division of the paraventricular nucleus (PVN) that is known to contain AVP-secreting neurons. The eGFP fluorescence intensities in those nuclei and posterior pituitary were markedly increased after chronic salt loading (2% NaCl in drinking water for 5days). ChR2-eGFP was localized mainly in the membrane of AVP-positive MNCs. Whole-cell patch-clamp recordings were performed from single MNCs isolated from the SON of the transgenic rats, and blue light evoked repetitive action potentials. Our work provides for the first time an optogenetic approach to selectively activate AVP neurons in the rat. PMID:27493075

  8. A PSO-Based Approach for Pathway Marker Identification From Gene Expression Data.

    Science.gov (United States)

    Mandal, Monalisa; Mondal, Jyotirmay; Mukhopadhyay, Anirban

    2015-09-01

    In this article, a new and robust pathway activity inference scheme is proposed from gene expression data using Particle Swarm Optimization (PSO). From microarray gene expression data, the corresponding pathway information of the genes are collected from a public database. For identifying the pathway markers, the expression values of each pathway consisting of genes, termed as pathway activity, are summarized. To measure the goodness of a pathway activity vector, t-score is widely used in the existing literature. The weakness of existing techniques for inferring pathway activity is that they intend to consider all the member genes of a pathway. But in reality, all the member genes may not be significant to the corresponding pathway. Therefore, those genes, which are responsible in the corresponding pathway, should be included only. Motivated by this, in the proposed method, using PSO, important genes with respect to each pathway are identified. The objective is to maximize the average t-score. For the pathway activities inferred from different percentage of significant pathways, the average absolute t -scores are plotted. In addition, the top 50% pathway markers are evaluated using 10-fold cross validation and its performance is compared with that of other existing techniques. Biological relevance of the results is also studied. PMID:25935045

  9. Correlating overrepresented upstream motifs to gene expression a computational approach to regulatory element discovery in eukaryotes

    CERN Document Server

    Caselle, M; Provero, P

    2002-01-01

    Gene regulation in eukaryotes is mainly effected through transcription factors binding to rather short recognition motifs generally located upstream of the coding region. We present a novel computational method to identify regulatory elements in the upstream region of eukaryotic genes. The genes are grouped in sets sharing an overrepresented short motif in their upstream sequence. For each set, the average expression level from a microarray experiment is determined: If this level is significantly higher or lower than the average taken over the whole genome, then the overerpresented motif shared by the genes in the set is likely to play a role in their regulation. The method was tested by applying it to the genome of Saccharomyces cerevisiae, using the publicly available results of a DNA microarray experiment, in which expression levels for virtually all the genes were measured during the diauxic shift from fermentation to respiration. Several known motifs were correctly identified, and a new candidate regulat...

  10. PR gene families of citrus: their organ specific-biotic and abiotic inducible expression profiles based on ESTs approach

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    Magnólia A. Campos

    2007-01-01

    Full Text Available In silico expression profiles, of the discovered 3,103 citrus ESTs putatively encoding for PR protein families (PR-1 to PR-17, were evaluated using the Brazil citrus genome EST CitEST/database. Hierarchical clustering was displayed to identify similarities in expression patterns among citrus PR-like gene families (PRlgf in 33 selected cDNA libraries. In this way, PRlgf preferentially expressed by organ and citrus species, and library conditions were highlighted. Changes in expression profiles of clusters for each of the 17 PRlgf expressed in organs infected by pathogens or drought-stressed citrus species were displayed for relative suppression or induction gene expression in relation to the counterpart control. Overall, few PRlgf showed expression 2-fold higher in pathogen-infected than in uninfected organs, even though the differential expression profiles displayed have been quite diverse among studied species and organs. Furthermore, an insight into some contigs from four PRlgf pointed out putative members of multigene families. They appear to be evolutionarily conserved within citrus species and/or organ- or stress-specifically expressed. Our results represent a starting point regarding the extent of expression pattern differences underlying PRlgf expression and reveal genes that may prove to be useful in studies regarding biotechnological approaches or citrus resistance markers.

  11. Regulation of gene expression

    International Nuclear Information System (INIS)

    In order to define in molecular terms the mechanisms controlling expression of specific genes in mammalian cells, how gene expression is activated, how tissue-specific expression is effected, how expression is modulated by hormones and other specific effectors, and how genetic control mechanisms are altered in the dysfunction of gene expression in cells transformed to malignancy were studied. Much of this work has focused on expression of the rat liver enzyme tyrosine aminotransferase

  12. A bi-ordering approach to linking gene expression with clinical annotations in gastric cancer

    Directory of Open Access Journals (Sweden)

    Leckie Christopher

    2010-09-01

    Full Text Available Abstract Background In the study of cancer genomics, gene expression microarrays, which measure thousands of genes in a single assay, provide abundant information for the investigation of interesting genes or biological pathways. However, in order to analyze the large number of noisy measurements in microarrays, effective and efficient bioinformatics techniques are needed to identify the associations between genes and relevant phenotypes. Moreover, systematic tests are needed to validate the statistical and biological significance of those discoveries. Results In this paper, we develop a robust and efficient method for exploratory analysis of microarray data, which produces a number of different orderings (rankings of both genes and samples (reflecting correlation among those genes and samples. The core algorithm is closely related to biclustering, and so we first compare its performance with several existing biclustering algorithms on two real datasets - gastric cancer and lymphoma datasets. We then show on the gastric cancer data that the sample orderings generated by our method are highly statistically significant with respect to the histological classification of samples by using the Jonckheere trend test, while the gene modules are biologically significant with respect to biological processes (from the Gene Ontology. In particular, some of the gene modules associated with biclusters are closely linked to gastric cancer tumorigenesis reported in previous literature, while others are potentially novel discoveries. Conclusion In conclusion, we have developed an effective and efficient method, Bi-Ordering Analysis, to detect informative patterns in gene expression microarrays by ranking genes and samples. In addition, a number of evaluation metrics were applied to assess both the statistical and biological significance of the resulting bi-orderings. The methodology was validated on gastric cancer and lymphoma datasets.

  13. Classification of Micro Array Gene Expression Data using Factor Analysis Approach with Naïve Bayesian Classifier

    OpenAIRE

    Tamilselvi Madeswaran; G.M.Kadhar Nawaz

    2013-01-01

    Microarray data studies produce large number of data and in order to analyze such large micro array data lies on Data mining or Statistical Analysis. Our objective is to classify the micro arraygene expression data. Usually before going for the classification the dimensionality reduction will be performed on the micro array gene expression dataset. A statistical approach for the extraction of thegene has been proposed. The drawback in the statistical analysis is that, it doesn’t identify the ...

  14. A novel biclustering approach with iterative optimization to analyze gene expression data

    Directory of Open Access Journals (Sweden)

    Ohta H

    2012-09-01

    Full Text Available Sawannee Sutheeworapong,1,2 Motonori Ota,4 Hiroyuki Ohta,1 Kengo Kinoshita2,31Department of Biological Sciences, Graduate School of Biosciences and Biotechnology, Tokyo Institute of Technology, Tokyo, Japan; 2Graduate School of Information Sciences, 3Institute of Development, Aging and Cancer, Tohoku University, Miyagi, Japan; 4Graduate School of Information Sciences, Nagoya University, Nagoya, JapanObjective: With the dramatic increase in microarray data, biclustering has become a promising tool for gene expression analysis. Biclustering has been proven to be superior over clustering in identifying multifunctional genes and searching for co-expressed genes under a few specific conditions; that is, a subgroup of all conditions. Biclustering based on a genetic algorithm (GA has shown better performance than greedy algorithms, but the overlap state for biclusters must be treated more systematically.Results: We developed a new biclustering algorithm (binary-iterative genetic algorithm [BIGA], based on an iterative GA, by introducing a novel, ternary-digit chromosome encoding function. BIGA searches for a set of biclusters by iterative binary divisions that allow the overlap state to be explicitly considered. In addition, the average of the Pearson’s correlation coefficient was employed to measure the relationship of genes within a bicluster, instead of the mean square residual, the popular classical index. As compared to the six existing algorithms, BIGA found highly correlated biclusters, with large gene coverage and reasonable gene overlap. The gene ontology (GO enrichment showed that most of the biclusters are significant, with at least one GO term over represented.Conclusion: BIGA is a powerful tool to analyze large amounts of gene expression data, and will facilitate the elucidation of the underlying functional mechanisms in living organisms.Keywords: biclustering, microarray data, genetic algorithm, Pearson’s correlation coefficient

  15. Ascidian gene-expression profiles

    OpenAIRE

    William R Jeffery

    2002-01-01

    With the advent of gene-expression profiling, a large number of genes can now be investigated simultaneously during critical stages of development. This approach will be particularly informative in studies of ascidians, basal chordates whose genomes and embryology are uniquely suited for mapping developmental gene networks.

  16. Effect of Thyrotropin Releasing Hormone (TRH on Gene Expressions in Rat Pancreas: Approach by Microarray Hybridization

    Directory of Open Access Journals (Sweden)

    Luo LG

    2004-07-01

    Full Text Available CONTEXT: Thyrotropin releasing hormone (TRH, originally identified as a hypothalamic hormone, expresses in the pancreas. The effects of TRH such as, inhibiting amylase secretion in rats through a direct effect on acinar cells, enhancing basal glucagon secretion from isolated perfused rat pancreas, and potentiating glucose-stimulated insulin secretion in perfused rat islets and insulin-secreting clonal beta-cell lines, suggest that TRH may play a role in pancreas. TRH also enlarged pancreas and increased pancreatic DNA content but deletion of TRH gene expression caused hyperglycemia in mice, suggesting that TRH may play a critical role in pancreatic development; however, the biological mechanisms of TRH in the adult pancreas remains unclear. OBJECTIVES: This study explored the effect of TRH on rat pancreas. SUBJECTS: Four male-Sprague-Dawley-rats (200-250 g were given 10 microg/kg BW of TRH intraperitoneally on 1st and 3rd day and sacrificed on 7th day. Four same-strain rats without TRH injection served as controls. MAIN OUTCOME MEASURES: Wet pancreatic weights were measured. Pancreatic tissues were homogenized and extracted. The insulin levels of the extracts were measured by ELISA. Total RNA from the pancreases were fluorescently labeled and hybridized to microarray with 1,081 spot genes. RESULTS: TRH increased pancreatic wet weight and insulin contents. About 75% of the 1,081 genes were detected in the pancreas. TRH regulated up 99 genes and down 76 genes. The administration of TRH induced various types of gene expressions, such as G-protein coupled receptors (GPCR and signal transduction related genes (GPCR kinase 4, transducin beta subunit 5, arrestin beta1MAPK3, MAPK5, c-Src kinase, PKCs, PI3 kinase, growth factors (PDGF-B, IGF-2, IL-18, IGF-1, IL-2, IL-6, endothelin-1 and apoptotic factors (Bcl2, BAD, Bax. CONCLUSION: Reprogramming of transcriptome may be a way for TRH-regulation of pancreatic cellular functions.

  17. A new experimental approach for studying bacterial genomic island evolution identifies island genes with bacterial host-specific expression patterns

    Directory of Open Access Journals (Sweden)

    Nickerson Cheryl A

    2006-01-01

    Full Text Available Abstract Background Genomic islands are regions of bacterial genomes that have been acquired by horizontal transfer and often contain blocks of genes that function together for specific processes. Recently, it has become clear that the impact of genomic islands on the evolution of different bacterial species is significant and represents a major force in establishing bacterial genomic variation. However, the study of genomic island evolution has been mostly performed at the sequence level using computer software or hybridization analysis to compare different bacterial genomic sequences. We describe here a novel experimental approach to study the evolution of species-specific bacterial genomic islands that identifies island genes that have evolved in such a way that they are differentially-expressed depending on the bacterial host background into which they are transferred. Results We demonstrate this approach by using a "test" genomic island that we have cloned from the Salmonella typhimurium genome (island 4305 and transferred to a range of Gram negative bacterial hosts of differing evolutionary relationships to S. typhimurium. Systematic analysis of the expression of the island genes in the different hosts compared to proper controls allowed identification of genes with genera-specific expression patterns. The data from the analysis can be arranged in a matrix to give an expression "array" of the island genes in the different bacterial backgrounds. A conserved 19-bp DNA site was found upstream of at least two of the differentially-expressed island genes. To our knowledge, this is the first systematic analysis of horizontally-transferred genomic island gene expression in a broad range of Gram negative hosts. We also present evidence in this study that the IS200 element found in island 4305 in S. typhimurium strain LT2 was inserted after the island had already been acquired by the S. typhimurium lineage and that this element is likely not

  18. Comparison of Merging and Meta-Analysis as Alternative Approaches for Integrative Gene Expression Analysis

    OpenAIRE

    Jonatan Taminau; Cosmin Lazar; Stijn Meganck; Ann Nowé

    2014-01-01

    An increasing amount of microarray gene expression data sets is available through public repositories. Their huge potential in making new findings is yet to be unlocked by making them available for large-scale analysis. In order to do so it is essential that independent studies designed for similar biological problems can be integrated, so that new insights can be obtained. These insights would remain undiscovered when analyzing the individual data sets because it is well known that the small...

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

    Science.gov (United States)

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

    2016-01-01

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

  20. Swarm Intelligence Approach Based on Adaptive ELM Classifier with ICGA Selection for Microarray Gene Expression and Cancer Classification

    Directory of Open Access Journals (Sweden)

    T. Karthikeyan

    2014-05-01

    Full Text Available The aim of this research study is based on efficient gene selection and classification of microarray data analysis using hybrid machine learning algorithms. The beginning of microarray technology has enabled the researchers to quickly measure the position of thousands of genes expressed in an organic/biological tissue samples in a solitary experiment. One of the important applications of this microarray technology is to classify the tissue samples using their gene expression representation, identify numerous type of cancer. Cancer is a group of diseases in which a set of cells shows uncontrolled growth, instance that interrupts upon and destroys nearby tissues and spreading to other locations in the body via lymph or blood. Cancer has becomes a one of the major important disease in current scenario. DNA microarrays turn out to be an effectual tool utilized in molecular biology and cancer diagnosis. Microarrays can be measured to establish the relative quantity of mRNAs in two or additional organic/biological tissue samples for thousands/several thousands of genes at the same time. As the superiority of this technique become exactly analysis/identifying the suitable assessment of microarray data in various open issues. In the field of medical sciences multi-category cancer classification play a major important role to classify the cancer types according to the gene expression. The need of the cancer classification has been become indispensible, because the numbers of cancer victims are increasing steadily identified by recent years. To perform this proposed a combination of Integer-Coded Genetic Algorithm (ICGA and Artificial Bee Colony algorithm (ABC, coupled with an Adaptive Extreme Learning Machine (AELM, is used for gene selection and cancer classification. ICGA is used with ABC based AELM classifier to chose an optimal set of genes which results in an efficient hybrid algorithm that can handle sparse data and sample imbalance. The

  1. Classification of Micro Array Gene Expression Data using Factor Analysis Approach with Naïve Bayesian Classifier

    Directory of Open Access Journals (Sweden)

    Tamilselvi Madeswaran

    2013-10-01

    Full Text Available Microarray data studies produce large number of data and in order to analyze such large micro array data lies on Data mining or Statistical Analysis. Our objective is to classify the micro arraygene expression data. Usually before going for the classification the dimensionality reduction will be performed on the micro array gene expression dataset. A statistical approach for the extraction of thegene has been proposed. The drawback in the statistical analysis is that, it doesn’t identify the important genes. Here for the classification process we use k-nearest neighbor and SVM and Naïve Bayesian classifiers. From the experimental result our proposed classifiers show increase in the efficiency and accuracy.

  2. New Insights into the Genetic Control of Gene Expression using a Bayesian Multi-tissue Approach

    Czech Academy of Sciences Publication Activity Database

    Petretto, E.; Bottolo, L.; Langley, S. R.; Heinig, M.; McDermott-Roe, Ch.; Sarwar, R.; Pravenec, Michal; Hübner, N.; Aitman, T. J.; Cook, S.A.; Richardson, S.

    2010-01-01

    Roč. 6, č. 4 (2010), e1000737. ISSN 1553-734X R&D Projects: GA ČR(CZ) GA301/08/0166; GA MŠk(CZ) 1M0520; GA ČR GAP301/10/0290 Grant ostatní: EC(XE) LSHG-CT-2005-019015; Fondation Leducq(FR) 06 CVD 03 Institutional research plan: CEZ:AV0Z50110509 Keywords : expression profiles * Bayesian multi- tissue approach * genetical genomics Subject RIV: EB - Genetics ; Molecular Biology Impact factor: 5.515, year: 2010

  3. Dietary approaches to stop hypertension influence on insulin receptor substrate-1gene expression: A randomized controlled clinical trial

    Directory of Open Access Journals (Sweden)

    Marzieh Kafeshani

    2015-01-01

    Full Text Available Background: Insulin receptor substrate (IRS Type 1 is a main substrate for the insulin receptor, controls insulin signaling in skeletal muscle, adipose tissue, and the vascular, so it is an important candidate gene for insulin resistance (IR. We aimed to compare the effects of the Dietary Approaches to Stop Hypertension (DASH and Usual Dietary Advices (UDA on IRS1 gene expression in women at risk for cardiovascular disease. Materials and Methods: A randomized controlled clinical trial was performed in 44 women at risk for cardiovascular disease. Participants were randomly assigned to a UDA diet or the DASH diet. The DASH diet was rich in fruits, vegetables, whole grains, and low-fat dairy products and low in saturated fat, total fat, cholesterol, refined grains, and sweets, with a total of 2400 mg/day sodium. The UDA diet was a regular diet with healthy dietary advice. Gene expression was assessed by the real-time polymerase chain reaction at the first of study and after 12 weeks. Independent sample t-test and paired-samples t-test were used to compare means of all variables within and between two groups respectively. Results: IRS1 gene expression was increased in DASH group compared with UDA diet (P = 0.00. Weight and waist circumference decreased in DASH group significantly compared to the UDA group (P < 0.05 but the results between the two groups showed no significant difference. Conclusion: DASH diet increased IRS1 gene expression and probably has beneficial effects on IR risks.

  4. Unintended Changes in Genetically Modified Rice Expressing the Lysine-Rich Fusion Protein Gene Revealed by a Proteomics Approach

    Institute of Scientific and Technical Information of China (English)

    ZHAO Xiang-xiang; TANG Tang; LIU Fu-xia; LU Chang-li; HU Xiao-lan; JI Li-lian; LIU Qiao-quan

    2013-01-01

    Development of new technologies for evaluating genetically modiifed (GM) crops has revealed that there are unintended insertions and expression changes in GM crops. Proifling techniques are non-targeted approaches and are capable of detecting more unintended changes in GM crops. Here, we report the application of a comparative proteomic approach to investigate the protein proifle differences between a GM rice line, which has a lysine-rich protein gene, and its non-transgenic parental line. Proteome analysis by two-dimensional gel electrophoresis (2-DE) and mass spectrum analysis of the seeds identiifed 22 differentially expressed protein spots. Apart from a number of glutelins that were detected as targeted proteins in the GM line, the majority of the other changed proteins were involved in carbohydrate metabolism, protein synthesis and stress responses. These results indicated that the altered proteins were not associated with plant allergens or toxicity.

  5. An efficient approach to finding Siraitia grosvenorii triterpene biosynthetic genes by RNA-seq and digital gene expression analysis

    Directory of Open Access Journals (Sweden)

    Song Cai

    2011-07-01

    Full Text Available Abstract Background Siraitia grosvenorii (Luohanguo is an herbaceous perennial plant native to southern China and most prevalent in Guilin city. Its fruit contains a sweet, fleshy, edible pulp that is widely used in traditional Chinese medicine. The major bioactive constituents in the fruit extract are the cucurbitane-type triterpene saponins known as mogrosides. Among them, mogroside V is nearly 300 times sweeter than sucrose. However, little is known about mogrosides biosynthesis in S. grosvenorii, especially the late steps of the pathway. Results In this study, a cDNA library generated from of equal amount of RNA taken from S. grosvenorii fruit at 50 days after flowering (DAF and 70 DAF were sequenced using Illumina/Solexa platform. More than 48,755,516 high-quality reads from a cDNA library were generated that was assembled into 43,891 unigenes. De novo assembly and gap-filling generated 43,891 unigenes with an average sequence length of 668 base pairs. A total of 26,308 (59.9% unique sequences were annotated and 11,476 of the unique sequences were assigned to specific metabolic pathways by the Kyoto Encyclopedia of Genes and Genomes. cDNA sequences for all of the known enzymes involved in mogrosides backbone synthesis were identified from our library. Additionally, a total of eighty-five cytochrome P450 (CYP450 and ninety UDP-glucosyltransferase (UDPG unigenes were identified, some of which appear to encode enzymes responsible for the conversion of the mogroside backbone into the various mogrosides. Digital gene expression profile (DGE analysis using Solexa sequencing was performed on three important stages of fruit development, and based on their expression pattern, seven CYP450s and five UDPGs were selected as the candidates most likely to be involved in mogrosides biosynthesis. Conclusion A combination of RNA-seq and DGE analysis based on the next generation sequencing technology was shown to be a powerful method for identifying

  6. Ecotoxicological diagnosis of striped dolphin (Stenella coeruleoalba) from the Mediterranean basin by skin biopsy and gene expression approach.

    Science.gov (United States)

    Panti, Cristina; Spinsanti, Giacomo; Marsili, Letizia; Casini, Silvia; Frati, Francesco; Fossi, Maria Cristina

    2011-11-01

    Mediterranean cetacean odontocetes are exposed to environmental stress, in particular to persistent organic pollutants, polycyclic aromatic hydrocarbons and trace elements. In the present study, the response of "gene-expression biomarkers" was evaluated in Mediterranean striped dolphin (Stenella coeruleoalba) skin biopsies collected in three sampling areas: Pelagos sanctuary (Ligurian sea), Ionian sea, and Strait of Gibraltar. The mRNA levels of five putative biomarker genes (aryl hydrocarbon receptor, E2F-1 transcription factor, cytochrome P450 1A, estrogen receptor 1, and heat shock protein 70) were measured for the first time by quantitative real-time PCR in cetacean skin biopsies. The different responses of most of the genes reflected contamination levels in the three sampling areas. Pelagos sanctuary dolphins appeared to be the most exposed to toxicological stress, having the highest up-regulation of CYP1A and AHR. Moreover, a cluster analysis distinguished the populations on the basis of the gene expression biomarker used in our study, showing different pattern between Mediterranean sea and Strait of Gibraltar. Our results suggest that this molecular approach applied to non-destructive biopsy material is a powerful diagnostic tool for evaluating ecotoxicological impact on cetacean populations. PMID:21695511

  7. Meta-analysis of microarray data using a pathway-based approach identifies a 37-gene expression signature for systemic lupus erythematosus in human peripheral blood mononuclear cells

    OpenAIRE

    Arasappan, Dhivya; Tong, Weida; Mummaneni, Padmaja; Fang, Hong; Amur, Shashi

    2011-01-01

    Background A number of publications have reported the use of microarray technology to identify gene expression signatures to infer mechanisms and pathways associated with systemic lupus erythematosus (SLE) in human peripheral blood mononuclear cells. However, meta-analysis approaches with microarray data have not been well-explored in SLE. Methods In this study, a pathway-based meta-analysis was applied to four independent gene expression oligonucleotide microarray data sets to identify gene ...

  8. Gene Expression Omnibus (GEO)

    Data.gov (United States)

    U.S. Department of Health & Human Services — Gene Expression Omnibus is a public functional genomics data repository supporting MIAME-compliant submissions of array- and sequence-based data. Tools are provided...

  9. Quality Measures for Gene Expression Biclusters

    OpenAIRE

    Beatriz Pontes; Ral Girldez; Aguilar-Ruiz, Jess S.

    2015-01-01

    An noticeable number of biclustering approaches have been proposed proposed for the study of gene expression data, especially for discovering functionally related gene sets under different subsets of experimental conditions. In this context, recognizing groups of co-expressed or co-regulated genes, that is, genes which follow a similar expression pattern, is one of the main objectives. Due to the problem complexity, heuristic searches are usually used instead of exhaustive algorithms. Further...

  10. Meta-analysis of microarray data using a pathway-based approach identifies a 37-gene expression signature for systemic lupus erythematosus in human peripheral blood mononuclear cells

    OpenAIRE

    Fang Hong; Mummaneni Padmaja; Tong Weida; Arasappan Dhivya; Amur Shashi

    2011-01-01

    Abstract Background A number of publications have reported the use of microarray technology to identify gene expression signatures to infer mechanisms and pathways associated with systemic lupus erythematosus (SLE) in human peripheral blood mononuclear cells. However, meta-analysis approaches with microarray data have not been well-explored in SLE. Methods In this study, a pathway-based meta-analysis was applied to four independent gene expression oligonucleotide microarray data sets to ident...

  11. PR gene families of citrus: their organ specific-biotic and abiotic inducible expression profiles based on ESTs approach

    OpenAIRE

    Magnólia A. Campos; Daniel D. Rosa; Juliana Érika C. Teixeira; Maria Luisa P.N. Targon; De Souza, Alessandra A.; Paiva, Luciano V.; Dagmar R. Stach-Machado; Machado, Marcos A

    2007-01-01

    In silico expression profiles, of the discovered 3,103 citrus ESTs putatively encoding for PR protein families (PR-1 to PR-17), were evaluated using the Brazil citrus genome EST CitEST/database. Hierarchical clustering was displayed to identify similarities in expression patterns among citrus PR-like gene families (PRlgf) in 33 selected cDNA libraries. In this way, PRlgf preferentially expressed by organ and citrus species, and library conditions were highlighted. Changes in expression profil...

  12. Effect of Thyrotropin Releasing Hormone (TRH) on Gene Expressions in Rat Pancreas: Approach by Microarray Hybridization

    OpenAIRE

    Luo LG; Yano N

    2004-01-01

    CONTEXT: Thyrotropin releasing hormone (TRH), originally identified as a hypothalamic hormone, expresses in the pancreas. The effects of TRH such as, inhibiting amylase secretion in rats through a direct effect on acinar cells, enhancing basal glucagon secretion from isolated perfused rat pancreas, and potentiating glucose-stimulated insulin secretion in perfused rat islets and insulin-secreting clonal beta-cell lines, suggest that TRH may play a role in pancreas. TRH also enlarged pancreas a...

  13. Gene expression in the Parkinson's disease brain

    OpenAIRE

    Lewis, Patrick A.; Cookson, Mark R.

    2012-01-01

    The study of gene expression has undergone a transformation in the past decade as the benefits of the sequencing of the human genome have made themselves felt. Increasingly, genome wide approaches are being applied to the analysis of gene expression in human disease as a route to understanding the underlying pathogenic mechanisms. In this review, we will summarise current state of gene expression studies of the brain in Parkinson's disease, and examine how these techniques can be used to gain...

  14. The approaches to mathematical modeling of recA, umuD genes expression in bacteria Escherichia coli after UV-irradiation

    International Nuclear Information System (INIS)

    The modern data of recA, umuD genes expression of the system of SOS-repair at classical object of radiation genetic researches - bacteria Escherichia coli, after ultraviolet irradiation are presented. Essentially a new method of analysis of SOS-genes expression is considered. It was shown that using this method it is possible to determine the character of induction of some SOS-genes more precisely. The possible approach to the mathematical description of SOS-response of cells by construction of the system of the differential equations is presented

  15. Modulation of gene expression made easy

    DEFF Research Database (Denmark)

    Solem, Christian; Jensen, Peter Ruhdal

    2002-01-01

    A new approach for modulating gene expression, based on randomization of promoter (spacer) sequences, was developed. The method was applied to chromosomal genes in Lactococcus lactis and shown to generate libraries of clones with broad ranges of expression levels of target genes. In one example...... beta-glucuronidase, resulting in an operon structure in which both genes are transcribed from a common promoter. We show that there is a linear correlation between the expressions of the two genes, which facilitates screening for mutants with suitable enzyme activities. In a second example, we show...... that the method can be applied to modulating the expression of native genes on the chromosome. We constructed a series of strains in which the expression of the las operon, containing the genes pfk, pyk, and ldh, was modulated by integrating a truncated copy of the pfk gene. Importantly, the modulation...

  16. Decreased approach behavior and nucleus accumbens immediate early gene expression in response to Parkinsonian ultrasonic vocalizations in rats.

    Science.gov (United States)

    Pultorak, Joshua D; Kelm-Nelson, Cynthia A; Holt, Lauren R; Blue, Katherine V; Ciucci, Michelle R; Johnson, Aaron M

    2016-08-01

    Many individuals with Parkinson disease (PD) have difficulty producing normal speech and voice, resulting in problems with interpersonal communication and reduced quality of life. Translational animal models of communicative dysfunction have been developed to assess disease pathology. However, it is unknown whether acoustic feature changes associated with vocal production deficits in these animal models lead to compromised communication. In rodents, male ultrasonic vocalizations (USVs) have a well-established role in functional inter-sexual communication. To test whether acoustic deficits in USVs observed in a PTEN-induced putative kinase 1 (PINK1) knockout (KO) PD rat model compromise communication, we presented recordings of male PINK1 KO USVs and normal wild-type (WT) USVs to female rat listeners. We measured approached behavior and immediate early gene expression (c-Fos) in brain regions implicated in auditory processing and sexual motivation. Our results suggest that females show reduced approach in response to PINK1 KO USVs compared with WT. Moreover, females exposed to PINK1 KO USVs had lower c-Fos immunolabeling in the nucleus accumbens, a region implicated in sexual motivation. These results are the first to demonstrate that vocalization deficits in a rat PD model result in compromised communication. Thus, the PINK1 KO PD model may be valuable for assessing treatments aimed at restoring vocal communicative function. PMID:26313334

  17. Quality measures for gene expression biclusters.

    Science.gov (United States)

    Pontes, Beatriz; Girldez, Ral; Aguilar-Ruiz, Jess S

    2015-01-01

    An noticeable number of biclustering approaches have been proposed proposed for the study of gene expression data, especially for discovering functionally related gene sets under different subsets of experimental conditions. In this context, recognizing groups of co-expressed or co-regulated genes, that is, genes which follow a similar expression pattern, is one of the main objectives. Due to the problem complexity, heuristic searches are usually used instead of exhaustive algorithms. Furthermore, most of biclustering approaches use a measure or cost function that determines the quality of biclusters. Having a suitable quality metric for bicluster is a critical aspect, not only for guiding the search, but also for establishing a comparison criteria among the results obtained by different biclustering techniques. In this paper, we analyse a large number of existing approaches to quality measures for gene expression biclusters, as well as we present a comparative study of them based on their capability to recognize different expression patterns in biclusters. PMID:25763839

  18. Synthetic promoter libraries- tuning of gene expression

    DEFF Research Database (Denmark)

    Hammer, Karin; Mijakovic, Ivan; Jensen, Peter Ruhdal

    2006-01-01

    The study of gene function often requires changing the expression of a gene and evaluating the consequences. In principle, the expression of any given gene can be modulated in a quasi-continuum of discrete expression levels but the traditional approaches are usually limited to two extremes: gene...... knockout and strong overexpression. However, applications such as metabolic optimization and control analysis necessitate a continuous set of expression levels with only slight increments in strength to cover a specific window around the wildtype expression level of the studied gene; this requirement can...... be met by using promoter libraries. This approach generally consists of inserting a library of promoters in front of the gene to be studied, whereby the individual promoters might deviate either in their spacer sequences or bear slight deviations from the consensus sequence of a vegetative promoter...

  19. A Latent Variable Approach for Meta-Analysis of Gene Expression Data from Multiple Microarray Experiments

    Directory of Open Access Journals (Sweden)

    Chinnaiyan Arul M

    2007-09-01

    Full Text Available Abstract Background With the explosion in data generated using microarray technology by different investigators working on similar experiments, it is of interest to combine results across multiple studies. Results In this article, we describe a general probabilistic framework for combining high-throughput genomic data from several related microarray experiments using mixture models. A key feature of the model is the use of latent variables that represent quantities that can be combined across diverse platforms. We consider two methods for estimation of an index termed the probability of expression (POE. The first, reported in previous work by the authors, involves Markov Chain Monte Carlo (MCMC techniques. The second method is a faster algorithm based on the expectation-maximization (EM algorithm. The methods are illustrated with application to a meta-analysis of datasets for metastatic cancer. Conclusion The statistical methods described in the paper are available as an R package, metaArray 1.8.1, which is at Bioconductor, whose URL is http://www.bioconductor.org/.

  20. Positron emission tomography imaging of gene expression

    International Nuclear Information System (INIS)

    The merging of molecular biology and nuclear medicine is developed into molecular nuclear medicine. Positron emission tomography (PET) of gene expression in molecular nuclear medicine has become an attractive area. Positron emission tomography imaging gene expression includes the antisense PET imaging and the reporter gene PET imaging. It is likely that the antisense PET imaging will lag behind the reporter gene PET imaging because of the numerous issues that have not yet to be resolved with this approach. The reporter gene PET imaging has wide application into animal experimental research and human applications of this approach will likely be reported soon

  1. cis sequence effects on gene expression

    Directory of Open Access Journals (Sweden)

    Jacobs Kevin

    2007-08-01

    Full Text Available Abstract Background Sequence and transcriptional variability within and between individuals are typically studied independently. The joint analysis of sequence and gene expression variation (genetical genomics provides insight into the role of linked sequence variation in the regulation of gene expression. We investigated the role of sequence variation in cis on gene expression (cis sequence effects in a group of genes commonly studied in cancer research in lymphoblastoid cell lines. We estimated the proportion of genes exhibiting cis sequence effects and the proportion of gene expression variation explained by cis sequence effects using three different analytical approaches, and compared our results to the literature. Results We generated gene expression profiling data at N = 697 candidate genes from N = 30 lymphoblastoid cell lines for this study and used available candidate gene resequencing data at N = 552 candidate genes to identify N = 30 candidate genes with sufficient variance in both datasets for the investigation of cis sequence effects. We used two additive models and the haplotype phylogeny scanning approach of Templeton (Tree Scanning to evaluate association between individual SNPs, all SNPs at a gene, and diplotypes, with log-transformed gene expression. SNPs and diplotypes at eight candidate genes exhibited statistically significant (p cis sequence effects in our study, respectively. Conclusion Based on analysis of our results and the extant literature, one in four genes exhibits significant cis sequence effects, and for these genes, about 30% of gene expression variation is accounted for by cis sequence variation. Despite diverse experimental approaches, the presence or absence of significant cis sequence effects is largely supported by previously published studies.

  2. Tumor-specific gene expression patterns with gene expression profiles

    Institute of Scientific and Technical Information of China (English)

    RUAN; Xiaogang; LI; Yingxin; LI; Jiangeng; GONG; Daoxiong

    2006-01-01

    Gene expression profiles of 14 common tumors and their counterpart normal tissues were analyzed with machine learning methods to address the problem of selection of tumor-specific genes and analysis of their differential expressions in tumor tissues. First, a variation of the Relief algorithm, "RFE_Relief algorithm" was proposed to learn the relations between genes and tissue types. Then, a support vector machine was employed to find the gene subset with the best classification performance for distinguishing cancerous tissues and their counterparts. After tissue-specific genes were removed, cross validation experiments were employed to demonstrate the common deregulated expressions of the selected gene in tumor tissues. The results indicate the existence of a specific expression fingerprint of these genes that is shared in different tumor tissues, and the hallmarks of the expression patterns of these genes in cancerous tissues are summarized at the end of this paper.

  3. Transcriptional stochasticity in gene expression.

    Science.gov (United States)

    Lipniacki, Tomasz; Paszek, Pawel; Marciniak-Czochra, Anna; Brasier, Allan R; Kimmel, Marek

    2006-01-21

    Due to the small number of copies of molecular species involved, such as DNA, mRNA and regulatory proteins, gene expression is a stochastic phenomenon. In eukaryotic cells, the stochastic effects primarily originate in regulation of gene activity. Transcription can be initiated by a single transcription factor binding to a specific regulatory site in the target gene. Stochasticity of transcription factor binding and dissociation is then amplified by transcription and translation, since target gene activation results in a burst of mRNA molecules, and each mRNA copy serves as a template for translating numerous protein molecules. In the present paper, we explore a mathematical approach to stochastic modeling. In this approach, the ordinary differential equations with a stochastic component for mRNA and protein levels in a single cells yield a system of first-order partial differential equations (PDEs) for two-dimensional probability density functions (pdf). We consider the following examples: Regulation of a single auto-repressing gene, and regulation of a system of two mutual repressors and of an activator-repressor system. The resulting PDEs are approximated by a system of many ordinary equations, which are then numerically solved. PMID:16039671

  4. Meta-analysis of microarray data using a pathway-based approach identifies a 37-gene expression signature for systemic lupus erythematosus in human peripheral blood mononuclear cells

    Directory of Open Access Journals (Sweden)

    Fang Hong

    2011-05-01

    Full Text Available Abstract Background A number of publications have reported the use of microarray technology to identify gene expression signatures to infer mechanisms and pathways associated with systemic lupus erythematosus (SLE in human peripheral blood mononuclear cells. However, meta-analysis approaches with microarray data have not been well-explored in SLE. Methods In this study, a pathway-based meta-analysis was applied to four independent gene expression oligonucleotide microarray data sets to identify gene expression signatures for SLE, and these data sets were confirmed by a fifth independent data set. Results Differentially expressed genes (DEGs were identified in each data set by comparing expression microarray data from control samples and SLE samples. Using Ingenuity Pathway Analysis software, pathways associated with the DEGs were identified in each of the four data sets. Using the leave one data set out pathway-based meta-analysis approach, a 37-gene metasignature was identified. This SLE metasignature clearly distinguished SLE patients from controls as observed by unsupervised learning methods. The final confirmation of the metasignature was achieved by applying the metasignature to a fifth independent data set. Conclusions The novel pathway-based meta-analysis approach proved to be a useful technique for grouping disparate microarray data sets. This technique allowed for validated conclusions to be drawn across four different data sets and confirmed by an independent fifth data set. The metasignature and pathways identified by using this approach may serve as a source for identifying therapeutic targets for SLE and may possibly be used for diagnostic and monitoring purposes. Moreover, the meta-analysis approach provides a simple, intuitive solution for combining disparate microarray data sets to identify a strong metasignature. Please see Research Highlight: http://genomemedicine.com/content/3/5/30

  5. Global Identification of Significantly Expressed Genes in Developing Endosperm of Rice by Expression Sequence Tags and cDNA Array Approaches

    Institute of Scientific and Technical Information of China (English)

    Qichao Tu; Haitao Dong; Haigen Yao; Yongqi Fang; Cheng'en Dai; Hongmei Luo; Jian Yao; Dong Zhao; Debao Li

    2008-01-01

    Rice endosperm plays a very important role in seedling germination and determines the qualities of fice grain.Although studies on specific gene categories in endosperm have been carried out,global view of gene expression at a transcription level in rice endosperm is still limited.To gain a better understanding of the global and tissue-specific gene expression profiles in rice endosperm,a cDNA library from rice endosperm of immature seeds was sequenced.A cDNA array was constructed based on the tentative unique transcripts derived from expression sequence tag (EST) assembling results and then hybridized with cONAs from five different tissues or organs including endosperm,embryo,leaf,stem and root of rice.Significant redundancy was found for genes encoding prolamin,glutelin,allergen,and starch synthesis proteins,accounting for~34% of the total ESTs obtained.The cDNA array revealed 87 significantly expressed genes in endosperm compared with the other four organs or tissues.These genes included 13 prolamin family proteins,17 glutelin family proteins,12 binding proteins,nine catalytic proteins and four ribosomal proteins,indicating a complicated biological processing in rice endosperm.In addition,Northern verification of 1,4-alpha-glucan branching enzyme detected two isoforms in rice endosperm,the larger one of which only existed in endosperm.

  6. Imaging gene expression in gene therapy

    Energy Technology Data Exchange (ETDEWEB)

    Wiebe, Leonard I. [Alberta Univ., Edmonton (Canada). Noujaim Institute for Pharmaceutical Oncology Research

    1997-12-31

    Full text. Gene therapy can be used to introduce new genes, or to supplement the function of indigenous genes. At the present time, however, there is non-invasive test to demonstrate efficacy of the gene transfer and expression processes. It has been postulated that scintigraphic imaging can offer unique information on both the site at which the transferred gene is expressed, and the degree of expression, both of which are critical issue for safety and clinical efficacy. Many current studies are based on `suicide gene therapy` of cancer. Cells modified to express these genes commit metabolic suicide in the presence of an enzyme encoded by the transferred gene and a specifically-convertible pro drug. Pro drug metabolism can lead to selective metabolic trapping, required for scintigraphy. Herpes simplex virus type-1 thymidine kinase (H S V-1 t k{sup +}) has been use for `suicide` in vivo tumor gene therapy. It has been proposed that radiolabelled nucleosides can be used as radiopharmaceuticals to detect H S V-1 t k{sup +} gene expression where the H S V-1 t k{sup +} gene serves a reporter or therapeutic function. Animal gene therapy models have been studied using purine-([{sup 18} F]F H P G; [{sup 18} F]-A C V), and pyrimidine- ([{sup 123}/{sup 131} I]I V R F U; [{sup 124}/{sup 131I}]) antiviral nucleosides. Principles of gene therapy and gene therapy imaging will be reviewed and experimental data for [{sup 123}/{sup 131I}]I V R F U imaging with the H S V-1 t k{sup +} reporter gene will be presented

  7. Imaging gene expression in gene therapy

    International Nuclear Information System (INIS)

    Full text. Gene therapy can be used to introduce new genes, or to supplement the function of indigenous genes. At the present time, however, there is non-invasive test to demonstrate efficacy of the gene transfer and expression processes. It has been postulated that scintigraphic imaging can offer unique information on both the site at which the transferred gene is expressed, and the degree of expression, both of which are critical issue for safety and clinical efficacy. Many current studies are based on 'suicide gene therapy' of cancer. Cells modified to express these genes commit metabolic suicide in the presence of an enzyme encoded by the transferred gene and a specifically-convertible pro drug. Pro drug metabolism can lead to selective metabolic trapping, required for scintigraphy. Herpes simplex virus type-1 thymidine kinase (H S V-1 t k+) has been use for 'suicide' in vivo tumor gene therapy. It has been proposed that radiolabelled nucleosides can be used as radiopharmaceuticals to detect H S V-1 t k+ gene expression where the H S V-1 t k+ gene serves a reporter or therapeutic function. Animal gene therapy models have been studied using purine-([18 F]F H P G; [18 F]-A C V), and pyrimidine- ([123/131 I]I V R F U; [124/131I]) antiviral nucleosides. Principles of gene therapy and gene therapy imaging will be reviewed and experimental data for [123/131I]I V R F U imaging with the H S V-1 t k+ reporter gene will be presented

  8. A gene sets approach for identifying prognostic gene signatures for outcome prediction

    OpenAIRE

    Kim Yong Sung; Kim Seon-Young

    2008-01-01

    Abstract Background Gene expression profiling is a promising approach to better estimate patient prognosis; however, there are still unresolved problems, including little overlap among similarly developed gene sets and poor performance of a developed gene set in other datasets. Results We applied a gene sets approach to develop a prognostic gene set from multiple gene expression datasets. By analyzing 12 independent breast cancer gene expression datasets comprising 1,756 tissues with 2,411 pr...

  9. Gene expression in colorectal cancer

    DEFF Research Database (Denmark)

    Birkenkamp-Demtroder, Karin; Christensen, Lise Lotte; Olesen, Sanne Harder;

    2002-01-01

    Understanding molecular alterations in colorectal cancer (CRC) is needed to define new biomarkers and treatment targets. We used oligonucleotide microarrays to monitor gene expression of about 6,800 known genes and 35,000 expressed sequence tags (ESTs) on five pools (four to six samples in each...... high frequency of loss of heterozygosity. The genes and ESTs presented in this study encode new potential tumor markers as well as potential novel therapeutic targets for prevention or therapy of CRC....

  10. Seeking gene relationships in gene expression data using support vector machine regression

    OpenAIRE

    Yu Robert; DeHoff Kevin; Amos Christopher I; Shete Sanjay

    2007-01-01

    Abstract Several genetic determinants responsible for individual variation in gene expression have been located using linkage and association analyses. These analyses have revealed regulatory relationships between genes. The heritability of expression variation as a quantitative phenotype reflects its underlying genetic architecture. Using support vector machine regression (SVMR) and gene ontological information, we proposed an approach to identify gene relationships in expression data provid...

  11. A functional genomics approach using radiation-induced changes in gene expression to study low dose radiation effects in vitro and in vivo

    Energy Technology Data Exchange (ETDEWEB)

    Fornace, Jr, A J

    2007-03-03

    Abstract for final report for project entitled A functional genomics approach using radiation-induced changes in gene expression to study low dose radiation effects in vitro and in vivo which has been supported by the DOE Low Dose Radiation Research Program for approximately 7 years. This project has encompassed two sequential awards, ER62683 and then ER63308, in the Gene Response Section in the Center for Cancer Research at the National Cancer Institute. The project was temporarily suspended during the relocation of the Principal Investigators laboratory to the Dept. of Genetics and Complex Diseases at Harvard School of Public Health at the end of 2004. Remaining support for the final year was transferred to this new site later in 2005 and was assigned the DOE Award Number ER64065. The major aims of this project have been 1) to characterize changes in gene expression in response to low-dose radiation responses; this includes responses in human cells lines, peripheral blood lymphocytes (PBL), and in vivo after human or murine exposures, as well as the effect of dose-rate on gene responses; 2) to characterize changes in gene expression that may be involved in bystander effects, such as may be mediated by cytokines and other intercellular signaling proteins; and 3) to characterize responses in transgenic mouse models with relevance to genomic stability. A variety of approaches have been used to study transcriptional events including microarray hybridization, quantitative single-probe hybridization which was developed in this laboratory, quantitative RT-PCR, and promoter microarray analysis using genomic regulatory motifs. Considering the frequent responsiveness of genes encoding cytokines and related signaling proteins that can affect cellular metabolism, initial efforts were initiated to study radiation responses at the metabolomic level and to correlate with radiation-responsive gene expression. Productivity includes twenty-four published and in press manuscripts

  12. Shuffling Yeast Gene Expression Data

    OpenAIRE

    Bilke, Sven

    2000-01-01

    A new method to sort gene expression patterns into functional groups is presented. The method is based on a sorting algorithm using a non-local similarity score, which takes all other patterns in the dataset into account. The method is therefore very robust with respect to noise. Using the expression data for yeast, we extract information about functional groups. Without prior knowledge of parameters the cell cycle regulated genes in yeast can be identified. Furthermore a second, independent ...

  13. Vascular gene expression: a hypothesis

    OpenAIRE

    Martínez-Navarro, Angélica C.; Galván-Gordillo, Santiago V.; Xoconostle-Cázares, Beatriz; Ruiz-Medrano, Roberto

    2013-01-01

    The phloem is the conduit through which photoassimilates are distributed from autotrophic to heterotrophic tissues and is involved in the distribution of signaling molecules that coordinate plant growth and responses to the environment. Phloem function depends on the coordinate expression of a large array of genes. We have previously identified conserved motifs in upstream regions of the Arabidopsis genes, encoding the homologs of pumpkin phloem sap mRNAs, displaying expression in vascular ti...

  14. Zipf's Law in Gene Expression

    OpenAIRE

    Furusawa, Chikara; Kaneko, Kunihiko

    2002-01-01

    Using data from gene expression databases on various organisms and tissues, including yeast, nematodes, human normal and cancer tissues, and embryonic stem cells, we found that the abundances of expressed genes exhibit a power-law distribution with an exponent close to -1, i.e., they obey Zipf's law. Furthermore, by simulations of a simple model with an intra-cellular reaction network, we found that Zipf's law of chemical abundance is a universal feature of cells where such a network optimize...

  15. Quality measures for gene expression biclusters.

    Directory of Open Access Journals (Sweden)

    Beatriz Pontes

    Full Text Available An noticeable number of biclustering approaches have been proposed proposed for the study of gene expression data, especially for discovering functionally related gene sets under different subsets of experimental conditions. In this context, recognizing groups of co-expressed or co-regulated genes, that is, genes which follow a similar expression pattern, is one of the main objectives. Due to the problem complexity, heuristic searches are usually used instead of exhaustive algorithms. Furthermore, most of biclustering approaches use a measure or cost function that determines the quality of biclusters. Having a suitable quality metric for bicluster is a critical aspect, not only for guiding the search, but also for establishing a comparison criteria among the results obtained by different biclustering techniques. In this paper, we analyse a large number of existing approaches to quality measures for gene expression biclusters, as well as we present a comparative study of them based on their capability to recognize different expression patterns in biclusters.

  16. Mining Association Rules among Gene Functions in Clusters of Similar Gene Expression Maps

    OpenAIRE

    An, Li; Obradovic, Zoran; Smith, Desmond; Bodenreider, Olivier; Megalooikonomou, Vasileios

    2009-01-01

    Association rules mining methods have been recently applied to gene expression data analysis to reveal relationships between genes and different conditions and features. However, not much effort has focused on detecting the relation between gene expression maps and related gene functions. Here we describe such an approach to mine association rules among gene functions in clusters of similar gene expression maps on mouse brain. The experimental results show that the detected association rules ...

  17. Application of multidisciplinary analysis to gene expression.

    Energy Technology Data Exchange (ETDEWEB)

    Wang, Xuefel (University of New Mexico, Albuquerque, NM); Kang, Huining (University of New Mexico, Albuquerque, NM); Fields, Chris (New Mexico State University, Las Cruces, NM); Cowie, Jim R. (New Mexico State University, Las Cruces, NM); Davidson, George S.; Haaland, David Michael; Sibirtsev, Valeriy (New Mexico State University, Las Cruces, NM); Mosquera-Caro, Monica P. (University of New Mexico, Albuquerque, NM); Xu, Yuexian (University of New Mexico, Albuquerque, NM); Martin, Shawn Bryan; Helman, Paul (University of New Mexico, Albuquerque, NM); Andries, Erik (University of New Mexico, Albuquerque, NM); Ar, Kerem (University of New Mexico, Albuquerque, NM); Potter, Jeffrey (University of New Mexico, Albuquerque, NM); Willman, Cheryl L. (University of New Mexico, Albuquerque, NM); Murphy, Maurice H. (University of New Mexico, Albuquerque, NM)

    2004-01-01

    Molecular analysis of cancer, at the genomic level, could lead to individualized patient diagnostics and treatments. The developments to follow will signal a significant paradigm shift in the clinical management of human cancer. Despite our initial hopes, however, it seems that simple analysis of microarray data cannot elucidate clinically significant gene functions and mechanisms. Extracting biological information from microarray data requires a complicated path involving multidisciplinary teams of biomedical researchers, computer scientists, mathematicians, statisticians, and computational linguists. The integration of the diverse outputs of each team is the limiting factor in the progress to discover candidate genes and pathways associated with the molecular biology of cancer. Specifically, one must deal with sets of significant genes identified by each method and extract whatever useful information may be found by comparing these different gene lists. Here we present our experience with such comparisons, and share methods developed in the analysis of an infant leukemia cohort studied on Affymetrix HG-U95A arrays. In particular, spatial gene clustering, hyper-dimensional projections, and computational linguistics were used to compare different gene lists. In spatial gene clustering, different gene lists are grouped together and visualized on a three-dimensional expression map, where genes with similar expressions are co-located. In another approach, projections from gene expression space onto a sphere clarify how groups of genes can jointly have more predictive power than groups of individually selected genes. Finally, online literature is automatically rearranged to present information about genes common to multiple groups, or to contrast the differences between the lists. The combination of these methods has improved our understanding of infant leukemia. While the complicated reality of the biology dashed our initial, optimistic hopes for simple answers from

  18. Approaches to systems biology. Four methods to study single-cell gene expression, cell motility, antibody reactivity, and respiratory metabolism

    DEFF Research Database (Denmark)

    Hagedorn, Peter

    To understand how complex systems, such as cells, function, comprehensive Measurements of their constituent parts must be made. This can be achieved by combining methods that are each optimized to measure specific parts of the system. Four such methods,each covering a different area, are presented......: Transcript profiling of one cell type extracted from a complex tissue containing several cell types; observation and recording of cell motility; measurement of antibody reactivities using microarrays; and invivo measurement of free and bound NADH in mitochondria. Detailed statistical analysis of the data...... from such measurements allows models of the system to be developed and tested. For each of the methods, such analysis and modelling approaches have beenapplied and are presented: Differentially regulated genes are identified and classified according to function; cell-specfic motility models are...

  19. A joint modeling approach for uncovering associations between gene expression, bioactivity and chemical structure in early drug discovery to guide lead selection and genomic biomarker development.

    Science.gov (United States)

    Perualila-Tan, Nolen; Kasim, Adetayo; Talloen, Willem; Verbist, Bie; Göhlmann, Hinrich W H; Shkedy, Ziv

    2016-08-01

    The modern drug discovery process involves multiple sources of high-dimensional data. This imposes the challenge of data integration. A typical example is the integration of chemical structure (fingerprint features), phenotypic bioactivity (bioassay read-outs) data for targets of interest, and transcriptomic (gene expression) data in early drug discovery to better understand the chemical and biological mechanisms of candidate drugs, and to facilitate early detection of safety issues prior to later and expensive phases of drug development cycles. In this paper, we discuss a joint model for the transcriptomic and the phenotypic variables conditioned on the chemical structure. This modeling approach can be used to uncover, for a given set of compounds, the association between gene expression and biological activity taking into account the influence of the chemical structure of the compound on both variables. The model allows to detect genes that are associated with the bioactivity data facilitating the identification of potential genomic biomarkers for compounds efficacy. In addition, the effect of every structural feature on both genes and pIC50 and their associations can be simultaneously investigated. Two oncology projects are used to illustrate the applicability and usefulness of the joint model to integrate multi-source high-dimensional information to aid drug discovery. PMID:27269248

  20. Correction of gene expression data

    DEFF Research Database (Denmark)

    Darbani Shirvanehdeh, Behrooz; Stewart, C. Neal, Jr.; Noeparvar, Shahin;

    2014-01-01

    This report investigates for the first time the potential inter-treatment bias source of cell number for gene expression studies. Cell-number bias can affect gene expression analysis when comparing samples with unequal total cellular RNA content or with different RNA extraction efficiencies. For...... maximal reliability of analysis, therefore, comparisons should be performed at the cellular level. This could be accomplished using an appropriate correction method that can detect and remove the inter-treatment bias for cell-number. Based on inter-treatment variations of reference genes, we introduce an...

  1. Shuffling Yeast Gene Expression Data

    CERN Document Server

    Bilke, S

    2000-01-01

    A new method to sort gene expression patterns into functional groups is presented. The method is based on a sorting algorithm using a non-local similarity score, which takes all other patterns in the dataset into account. The method is therefore very robust with respect to noise. Using the expression data for yeast, we extract information about functional groups. Without prior knowledge of parameters the cell cycle regulated genes in yeast can be identified. Furthermore a second, independent cell clock is identified. The capability of the algorithm to extract information about signal flow in the regulatory network underlying the expression patterns is demonstrated.

  2. Homeobox gene expression in Brachiopoda

    DEFF Research Database (Denmark)

    Altenburger, Andreas; Martinez, Pedro; Wanninger, Andreas

    2011-01-01

    . Not is a homeobox containing gene that regulates the formation of the notochord in chordates, while Cdx (caudal) is a ParaHox gene involved in the formation of posterior tissues of various animal phyla. The T. transversa homolog, TtrNot, is expressed in the ectoderm from the beginning of gastrulation until...... (ectoderm) specification with co-opted functions in notochord formation in chordates and left/right determination in ambulacrarians and vertebrates. The caudal ortholog, TtrCdx, is first expressed in the ectoderm of the gastrulating embryo in the posterior region of the blastopore. Its expression stays...... metazoans, where genes belonging to the Cdx/caudal family are predominantly localized in posterior domains during gastrulation. Later in development this gene will play a fundamental role in the formation of posterior tissues....

  3. The acute impact of polyphenols from Hibiscus sabdariffa in metabolic homeostasis: an approach combining metabolomics and gene-expression analyses.

    Science.gov (United States)

    Beltrán-Debón, Raúl; Rodríguez-Gallego, Esther; Fernández-Arroyo, Salvador; Senan-Campos, Oriol; Massucci, Francesco A; Hernández-Aguilera, Anna; Sales-Pardo, Marta; Guimerà, Roger; Camps, Jordi; Menendez, Javier A; Joven, Jorge

    2015-09-01

    We explored the acute multifunctional effects of polyphenols from Hibiscus sabdariffa in humans to assess possible consequences on the host's health. The expected dynamic response was studied using a combination of transcriptomics and metabolomics to integrate specific functional pathways through network-based methods and to generate hypotheses established by acute metabolic effects and/or modifications in the expression of relevant genes. Data were obtained from healthy male volunteers after 3 hours of ingestion of an aqueous Hibiscus sabdariffa extract. The data were compared with data obtained prior to the ingestion, and the overall findings suggest that these particular polyphenols had a simultaneous role in mitochondrial function, energy homeostasis and protection of the cardiovascular system. These findings suggest beneficial actions in inflammation, endothelial dysfunction, and oxidation, which are interrelated mechanisms. Among other effects, the activation of the heme oxygenase-biliverdin reductase axis, the systemic inhibition of the renin-angiotensin system, the inhibition of the angiotensin-converting enzyme, and several actions mirroring those of the peroxisome proliferator-activated receptor agonists further support this notion. We also found concordant findings in the serum of the participants, which include a decrease in cortisol levels and a significant increase in the active vasodilator metabolite of bradykinin (des-Arg(9)-bradykinin). Therefore, our data support the view that polyphenols from Hibiscus sabdariffa play a regulatory role in metabolic health and in the maintenance of blood pressure, thus implying a multi-faceted impact in metabolic and cardiovascular diseases. PMID:26234931

  4. Transgenic Arabidopsis Gene Expression System

    Science.gov (United States)

    Ferl, Robert; Paul, Anna-Lisa

    2009-01-01

    The Transgenic Arabidopsis Gene Expression System (TAGES) investigation is one in a pair of investigations that use the Advanced Biological Research System (ABRS) facility. TAGES uses Arabidopsis thaliana, thale cress, with sensor promoter-reporter gene constructs that render the plants as biomonitors (an organism used to determine the quality of the surrounding environment) of their environment using real-time nondestructive Green Fluorescent Protein (GFP) imagery and traditional postflight analyses.

  5. Zipf's Law in Gene Expression

    CERN Document Server

    Furusawa, C; Furusawa, Chikara; Kaneko, Kunihiko

    2002-01-01

    Using data from gene expression databases on various organisms and tissues, including yeast, nematodes, human normal and cancer tissues, and embryonic stem cells, we found that the abundances of expressed genes exhibit a power-law distribution with an exponent close to -1, i.e., they obey Zipf's law. Furthermore, by simulations of a simple model with an intra-cellular reaction network, we found that Zipf's law of chemical abundance is a universal feature of cells where such a network optimizes the efficiency and faithfulness of self-reproduction. These findings provide novel insights into the nature of the organization of reaction dynamics in living cells.

  6. Manipulation of P450 gene expression in tumours; a novel approach for targeted activation of bioreductive prodrugs

    International Nuclear Information System (INIS)

    We are developing a gene-directed enzyme prodrug therapy (GDEPT) strategy to enhance the metabolism of a novel bioreductive drug, AQ4N. Bioreductive drugs are metabolically activated in the hypoxic cell environment allowing effective targeting of hypoxic radioresistant tumour regions. We aim to achieve additional layers of selectivity by using an X-ray inducible promoter linked to our therapeutic gene (cytochrome P450s). This strategy would enhance metabolism of the drug only within the radiation field. Furthermore, normal tissue would be unaffected as the bioreductive drug is only activated in hypoxic conditions. We have identified several human cytochrome P450s which are important for AQ4N prodrug activation, these include CYP3A4, 1A1 and 2B6. RIF1 murine tumour cells transfected with cDNA from any one of these CYPs displayed increased DNA damage and clonogenic cell kill following treatment with AQ4N under hypoxia compared to controls. We are presently testing the ability of these transfectants to enhance anti-tumour effectiveness of AQ4N in combination with radiation in vivo. We have shown that a single CYP3A4 injection using a simple non-optimized approach can increase metabolism of AQ4N and when used in combination with radiation 3 out of 4 tumours are locally controlled for > 60 days (McCarthy et al., 2002). This result is remarkable considering the large enhancement of the radiation effect achieved by adding AQ4N alone. This implies that the bioreduction of AQ4N by CYPs in this tumour system is sub-optimal and this strategy could therefore be very promising for clinical use where CYP levels are known to be variable. We are now exploring the CYP/AQ4N GDEPT strategy in combination with cyclophosphamide, which is also metabolised by CYPs and aim to link these CYPs to the radiation and hypoxia inducible WAF1 promoter for selective activation in vivo

  7. Regulatory mechanisms for floral homeotic gene expression.

    Science.gov (United States)

    Liu, Zhongchi; Mara, Chloe

    2010-02-01

    Proper regulation of floral homeotic gene (or ABCE gene) expression ensures the development of floral organs in the correct number, type, and precise spatial arrangement. This review summarizes recent advances on the regulation of floral homeotic genes, highlighting the variety and the complexity of the regulatory mechanisms involved. As flower development is one of the most well characterized developmental processes in higher plants, it facilitates the discovery of novel regulatory mechanisms. To date, mechanisms for the regulation of floral homeotic genes range from transcription to post-transcription, from activators to repressors, and from microRNA- to ubiquitin-mediated post-transcriptional regulation. Region-specific activation of floral homeotic genes is dependent on the integration of a flower-specific activity provided by LEAFY (LFY) and a region- and stage-specific activating function provided by one of the LFY cofactors. Two types of regulatory loops, the feed-forward and the feedback loop, provide properly timed gene activation and subsequent maintenance and refinement in proper spatial and temporal domains of ABCE genes. Two different microRNA/target modules may have been independently recruited in different plant species to regulate C gene expression. Additionally, competition among different MADS box proteins for common interacting partners may represent a mechanism in whorl boundary demarcation. Future work using systems approaches and the development of non-model plants will provide integrated views on floral homeotic gene regulation and insights into the evolution of morphological diversity in flowering plants. PMID:19922812

  8. Gene expression profiles in irradiated cancer cells

    International Nuclear Information System (INIS)

    Knowledge of the molecular and genetic mechanisms underlying cellular response to radiation may provide new avenues to develop innovative predictive tests of radiosensitivity of tumours and normal tissues and to improve individual therapy. Nowadays very few studies describe molecular changes induced by hadrontherapy treatments, therefore this field has to be explored and clarified. High-throughput methodologies, such as DNA microarray, allow us to analyse mRNA expression of thousands of genes simultaneously in order to discover new genes and pathways as targets of response to hadrontherapy. Our aim is to elucidate the molecular networks involved in the sensitivity/resistance of cancer cell lines subjected to hadrontherapy treatments with a genomewide approach by using cDNA microarray technology to identify gene expression profiles and candidate genes responsible of differential cellular responses

  9. Identifying Gene Interaction Enrichment for Gene Expression Data

    OpenAIRE

    Jigang Zhang; Jian Li; Hong-Wen Deng

    2009-01-01

    Gene set analysis allows the inclusion of knowledge from established gene sets, such as gene pathways, and potentially improves the power of detecting differentially expressed genes. However, conventional methods of gene set analysis focus on gene marginal effects in a gene set, and ignore gene interactions which may contribute to complex human diseases. In this study, we propose a method of gene interaction enrichment analysis, which incorporates knowledge of predefined gene sets (e.g. gene ...

  10. Microarray Data Analysis of Gene Expression Evolution

    OpenAIRE

    Honghuang Lin

    2009-01-01

    Microarrays are becoming a widely used tool to study gene expression evolution. A recent paper by Wang and Rekaya describes a comprehensive study of gene expression evolution by microarray.1 The work provides a perspective to study gene expression evolution in terms of functional enrichment and promoter conservation. It was found that gene expression patterns are highly conserved in some biological processes, but the correlation between promoter and gene expression is insignificant. This scop...

  11. Human papillomavirus gene expression

    International Nuclear Information System (INIS)

    To determine the role of tissue differentiation on expression of each of the papillomavirus mRNA species identified by electron microscopy, the authors prepared exon-specific RNA probes that could distinguish the alternatively spliced mRNA species. Radioactively labeled single-stranded RNA probes were generated from a dual promoter vector system and individually hybridized to adjacent serial sections of formalin-fixed, paraffin-embedded biopsies of condylomata. Autoradiography showed that each of the message species had a characteristic tissue distribution and relative abundance. The authors have characterized a portion of the regulatory network of the HPVs by showing that the E2 ORF encodes a trans-acting enhancer-stimulating protein, as it does in BPV-1 (Spalholz et al. 1985). The HPV-11 enhancer was mapped to a 150-bp tract near the 3' end of the URR. Portions of this region are duplicated in some aggressive strains of HPV-6 (Boshart and zur Hausen 1986; Rando et al. 1986). To test the possible biological relevance of these duplications, they cloned tandem arrays of the enhancer and demonstrated, using a chloramphenicol acetyltransferase (CAT) assay, that they led to dramatically increased transcription proportional to copy number. Using the CAT assays, the authors found that the E2 proteins of several papillomavirus types can cross-stimulate the enhancers of most other types. This suggests that prior infection of a tissue with one papillomavirus type may provide a helper effect for superinfection and might account fo the HPV-6/HPV-16 coinfections in condylomata that they have observed

  12. Identifying Driver Genes in Cancer by Triangulating Gene Expression, Gene Location, and Survival Data

    Science.gov (United States)

    Rouam, Sigrid; Miller, Lance D; Karuturi, R Krishna Murthy

    2014-01-01

    Driver genes are directly responsible for oncogenesis and identifying them is essential in order to fully understand the mechanisms of cancer. However, it is difficult to delineate them from the larger pool of genes that are deregulated in cancer (ie, passenger genes). In order to address this problem, we developed an approach called TRIAngulating Gene Expression (TRIAGE through clinico-genomic intersects). Here, we present a refinement of this approach incorporating a new scoring methodology to identify putative driver genes that are deregulated in cancer. TRIAGE triangulates – or integrates – three levels of information: gene expression, gene location, and patient survival. First, TRIAGE identifies regions of deregulated expression (ie, expression footprints) by deriving a newly established measure called the Local Singular Value Decomposition (LSVD) score for each locus. Driver genes are then distinguished from passenger genes using dual survival analyses. Incorporating measurements of gene expression and weighting them according to the LSVD weight of each tumor, these analyses are performed using the genes located in significant expression footprints. Here, we first use simulated data to characterize the newly established LSVD score. We then present the results of our application of this refined version of TRIAGE to gene expression data from five cancer types. This refined version of TRIAGE not only allowed us to identify known prominent driver genes, such as MMP1, IL8, and COL1A2, but it also led us to identify several novel ones. These results illustrate that TRIAGE complements existing tools, allows for the identification of genes that drive cancer and could perhaps elucidate potential future targets of novel anticancer therapeutics. PMID:25949096

  13. Vascular Gene Expression: A Hypothesis

    Directory of Open Access Journals (Sweden)

    Angélica Concepción eMartínez-Navarro

    2013-07-01

    Full Text Available The phloem is the conduit through which photoassimilates are distributed from autotrophic to heterotrophic tissues and is involved in the distribution of signaling molecules that coordinate plant growth and responses to the environment. Phloem function depends on the coordinate expression of a large array of genes. We have previously identified conserved motifs in upstream regions of the Arabidopsis genes, encoding the homologs of pumpkin phloem sap mRNAs, displaying expression in vascular tissues. This tissue-specific expression in Arabidopsis is predicted by the overrepresentation of GA/CT-rich motifs in gene promoters. In this work we have searched for common motifs in upstream regions of the homologous genes from plants considered to possess a primitive vascular tissue (a lycophyte, as well as from others that lack a true vascular tissue (a bryophyte, and finally from chlorophytes. Both lycophyte and bryophyte display motifs similar to those found in Arabidopsis with a significantly low E-value, while the chlorophytes showed either a different conserved motif or no conserved motif at all. These results suggest that these same genes are expressed coordinately in non- vascular plants; this coordinate expression may have been one of the prerequisites for the development of conducting tissues in plants. We have also analyzed the phylogeny of conserved proteins that may be involved in phloem function and development. The presence of CmPP16, APL, FT and YDA in chlorophytes suggests the recruitment of ancient regulatory networks for the development of the vascular tissue during evolution while OPS is a novel protein specific to vascular plants.

  14. Analysis of multiplex gene expression maps obtained by voxelation

    Directory of Open Access Journals (Sweden)

    Smith Desmond J

    2009-04-01

    Full Text Available Abstract Background Gene expression signatures in the mammalian brain hold the key to understanding neural development and neurological disease. Researchers have previously used voxelation in combination with microarrays for acquisition of genome-wide atlases of expression patterns in the mouse brain. On the other hand, some work has been performed on studying gene functions, without taking into account the location information of a gene's expression in a mouse brain. In this paper, we present an approach for identifying the relation between gene expression maps obtained by voxelation and gene functions. Results To analyze the dataset, we chose typical genes as queries and aimed at discovering similar gene groups. Gene similarity was determined by using the wavelet features extracted from the left and right hemispheres averaged gene expression maps, and by the Euclidean distance between each pair of feature vectors. We also performed a multiple clustering approach on the gene expression maps, combined with hierarchical clustering. Among each group of similar genes and clusters, the gene function similarity was measured by calculating the average gene function distances in the gene ontology structure. By applying our methodology to find similar genes to certain target genes we were able to improve our understanding of gene expression patterns and gene functions. By applying the clustering analysis method, we obtained significant clusters, which have both very similar gene expression maps and very similar gene functions respectively to their corresponding gene ontologies. The cellular component ontology resulted in prominent clusters expressed in cortex and corpus callosum. The molecular function ontology gave prominent clusters in cortex, corpus callosum and hypothalamus. The biological process ontology resulted in clusters in cortex, hypothalamus and choroid plexus. Clusters from all three ontologies combined were most prominently expressed in

  15. A Gene Selection Algorithm using Bayesian Classification Approach

    OpenAIRE

    Alok Sharma; Kuldip K. Paliwal

    2012-01-01

    In this study, we propose a new feature (or gene) selection algorithm using Bayes classification approach. The algorithm can find gene subset crucial for cancer classification problem. Problem statement: Gene identification plays important role in human cancer classification problem. Several feature selection algorithms have been proposed for analyzing and understanding influential genes using gene expression profiles. Approach: The feature selection algorithms aim to explore genes that are c...

  16. Gene expression profile of pulpitis.

    Science.gov (United States)

    Galicia, J C; Henson, B R; Parker, J S; Khan, A A

    2016-06-01

    The cost, prevalence and pain associated with endodontic disease necessitate an understanding of the fundamental molecular aspects of its pathogenesis. This study was aimed to identify the genetic contributors to pulpal pain and inflammation. Inflamed pulps were collected from patients diagnosed with irreversible pulpitis (n=20). Normal pulps from teeth extracted for various reasons served as controls (n=20). Pain level was assessed using a visual analog scale (VAS). Genome-wide microarray analysis was performed using Affymetrix GeneTitan Multichannel Instrument. The difference in gene expression levels were determined by the significance analysis of microarray program using a false discovery rate (q-value) of 5%. Genes involved in immune response, cytokine-cytokine receptor interaction and signaling, integrin cell surface interactions, and others were expressed at relatively higher levels in the pulpitis group. Moreover, several genes known to modulate pain and inflammation showed differential expression in asymptomatic and mild pain patients (⩾30 mm on VAS) compared with those with moderate to severe pain. This exploratory study provides a molecular basis for the clinical diagnosis of pulpitis. With an enhanced understanding of pulpal inflammation, future studies on treatment and management of pulpitis and on pain associated with it can have a biological reference to bridge treatment strategies with pulpal biology. PMID:27052691

  17. Gene Expression in Trypanosomatid Parasites

    Directory of Open Access Journals (Sweden)

    Santiago Martínez-Calvillo

    2010-01-01

    Full Text Available The parasites Leishmania spp., Trypanosoma brucei, and Trypanosoma cruzi are the trypanosomatid protozoa that cause the deadly human diseases leishmaniasis, African sleeping sickness, and Chagas disease, respectively. These organisms possess unique mechanisms for gene expression such as constitutive polycistronic transcription of protein-coding genes and trans-splicing. Little is known about either the DNA sequences or the proteins that are involved in the initiation and termination of transcription in trypanosomatids. In silico analyses of the genome databases of these parasites led to the identification of a small number of proteins involved in gene expression. However, functional studies have revealed that trypanosomatids have more general transcription factors than originally estimated. Many posttranslational histone modifications, histone variants, and chromatin modifying enzymes have been identified in trypanosomatids, and recent genome-wide studies showed that epigenetic regulation might play a very important role in gene expression in this group of parasites. Here, we review and comment on the most recent findings related to transcription initiation and termination in trypanosomatid protozoa.

  18. Integrating heterogeneous gene expression data for gene regulatory network modelling.

    Science.gov (United States)

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

    2012-06-01

    Gene regulatory networks (GRNs) are complex biological systems that have a large impact on protein levels, so that discovering network interactions is a major objective of systems biology. Quantitative GRN models have been inferred, to date, from time series measurements of gene expression, but at small scale, and with limited application to real data. Time series experiments are typically short (number of time points of the order of ten), whereas regulatory networks can be very large (containing hundreds of genes). This creates an under-determination problem, which negatively influences the results of any inferential algorithm. Presented here is an integrative approach to model inference, which has not been previously discussed to the authors' knowledge. Multiple heterogeneous expression time series are used to infer the same model, and results are shown to be more robust to noise and parameter perturbation. Additionally, a wavelet analysis shows that these models display limited noise over-fitting within the individual datasets. PMID:21948152

  19. Gene Expression Data Knowledge Discovery using Global and Local Clustering

    OpenAIRE

    H, Swathi.

    2010-01-01

    To understand complex biological systems, the research community has produced huge corpus of gene expression data. A large number of clustering approaches have been proposed for the analysis of gene expression data. However, extracting important biological knowledge is still harder. To address this task, clustering techniques are used. In this paper, hybrid Hierarchical k-Means algorithm is used for clustering and biclustering gene expression data is used. To discover both local and global cl...

  20. Whole-body gene expression pattern registration in Platynereis larvae

    OpenAIRE

    Asadulina Albina; Panzera Aurora; Verasztó Csaba; Liebig Christian; Jékely Gáspár

    2012-01-01

    Abstract Background Digital anatomical atlases are increasingly used in order to depict different gene expression patterns and neuronal morphologies within a standardized reference template. In evo-devo, a discipline in which the comparison of gene expression patterns is a widely used approach, such standardized anatomical atlases would allow a more rigorous assessment of the conservation of and changes in gene expression patterns during micro- and macroevolutionary time scales. Due to its sm...

  1. The Gene Expression Omnibus database

    Science.gov (United States)

    Clough, Emily; Barrett, Tanya

    2016-01-01

    The Gene Expression Omnibus (GEO) database is an international public repository that archives and freely distributes high-throughput gene expression and other functional genomics data sets. Created in 2000 as a worldwide resource for gene expression studies, GEO has evolved with rapidly changing technologies and now accepts high-throughput data for many other data applications, including those that examine genome methylation, chromatin structure, and genome–protein interactions. GEO supports community-derived reporting standards that specify provision of several critical study elements including raw data, processed data, and descriptive metadata. The database not only provides access to data for tens of thousands of studies, but also offers various Web-based tools and strategies that enable users to locate data relevant to their specific interests, as well as to visualize and analyze the data. This chapter includes detailed descriptions of methods to query and download GEO data and use the analysis and visualization tools. The GEO homepage is at http://www.ncbi.nlm.nih.gov/geo/. PMID:27008011

  2. A new experimental approach for studying bacterial genomic island evolution identifies island genes with bacterial host-specific expression patterns

    OpenAIRE

    Nickerson Cheryl A; Wilson James W

    2006-01-01

    Abstract Background Genomic islands are regions of bacterial genomes that have been acquired by horizontal transfer and often contain blocks of genes that function together for specific processes. Recently, it has become clear that the impact of genomic islands on the evolution of different bacterial species is significant and represents a major force in establishing bacterial genomic variation. However, the study of genomic island evolution has been mostly performed at the sequence level usi...

  3. A systematic screen for genes expressed in definitive endoderm by Serial Analysis of Gene Expression (SAGE

    Directory of Open Access Journals (Sweden)

    Jones Steven JM

    2007-08-01

    Full Text Available Abstract Background The embryonic definitive endoderm (DE gives rise to organs of the gastrointestinal and respiratory tract including the liver, pancreas and epithelia of the lung and colon. Understanding how DE progenitor cells generate these tissues is critical to understanding the cause of visceral organ disorders and cancers, and will ultimately lead to novel therapies including tissue and organ regeneration. However, investigation into the molecular mechanisms of DE differentiation has been hindered by the lack of early DE-specific markers. Results We describe the identification of novel as well as known genes that are expressed in DE using Serial Analysis of Gene Expression (SAGE. We generated and analyzed three longSAGE libraries from early DE of murine embryos: early whole definitive endoderm (0–6 somite stage, foregut (8–12 somite stage, and hindgut (8–12 somite stage. A list of candidate genes enriched for expression in endoderm was compiled through comparisons within these three endoderm libraries and against 133 mouse longSAGE libraries generated by the Mouse Atlas of Gene Expression Project encompassing multiple embryonic tissues and stages. Using whole mount in situ hybridization, we confirmed that 22/32 (69% genes showed previously uncharacterized expression in the DE. Importantly, two genes identified, Pyy and 5730521E12Rik, showed exclusive DE expression at early stages of endoderm patterning. Conclusion The high efficiency of this endoderm screen indicates that our approach can be successfully used to analyze and validate the vast amount of data obtained by the Mouse Atlas of Gene Expression Project. Importantly, these novel early endoderm-expressing genes will be valuable for further investigation into the molecular mechanisms that regulate endoderm development.

  4. A NGS approach to the encrusting Mediterranean sponge Crella elegans (Porifera, Demospongiae, Poecilosclerida): transcriptome sequencing, characterization and overview of the gene expression along three life cycle stages.

    Science.gov (United States)

    Pérez-Porro, A R; Navarro-Gómez, D; Uriz, M J; Giribet, G

    2013-05-01

    Sponges can be dominant organisms in many marine and freshwater habitats where they play essential ecological roles. They also represent a key group to address important questions in early metazoan evolution. Recent approaches for improving knowledge on sponge biological and ecological functions as well as on animal evolution have focused on the genetic toolkits involved in ecological responses to environmental changes (biotic and abiotic), development and reproduction. These approaches are possible thanks to newly available, massive sequencing technologies-such as the Illumina platform, which facilitate genome and transcriptome sequencing in a cost-effective manner. Here we present the first NGS (next-generation sequencing) approach to understanding the life cycle of an encrusting marine sponge. For this we sequenced libraries of three different life cycle stages of the Mediterranean sponge Crella elegans and generated de novo transcriptome assemblies. Three assemblies were based on sponge tissue of a particular life cycle stage, including non-reproductive tissue, tissue with sperm cysts and tissue with larvae. The fourth assembly pooled the data from all three stages. By aggregating data from all the different life cycle stages we obtained a higher total number of contigs, contigs with blast hit and annotated contigs than from one stage-based assemblies. In that multi-stage assembly we obtained a larger number of the developmental regulatory genes known for metazoans than in any other assembly. We also advance the differential expression of selected genes in the three life cycle stages to explore the potential of RNA-seq for improving knowledge on functional processes along the sponge life cycle. PMID:23437888

  5. Comparative genomics of the relationship between gene structure and expression

    NARCIS (Netherlands)

    Ren, X.

    2006-01-01

    The relationship between the structure of genes and their expression is a relatively new aspect of genome organization and regulation. With more genome sequences and expression data becoming available, bioinformatics approaches can help the further elucidation of the relationships between gene struc

  6. Combinatorial approaches to gene recognition.

    Science.gov (United States)

    Roytberg, M A; Astakhova, T V; Gelfand, M S

    1997-01-01

    Recognition of genes via exon assembly approaches leads naturally to the use of dynamic programming. We consider the general graph-theoretical formulation of the exon assembly problem and analyze in detail some specific variants: multicriterial optimization in the case of non-linear gene-scoring functions; context-dependent schemes for scoring exons and related procedures for exon filtering; and highly specific recognition of arbitrary gene segments, oligonucleotide probes and polymerase chain reaction (PCR) primers. PMID:9440930

  7. Mitochondrial RNA granules: Compartmentalizing mitochondrial gene expression.

    Science.gov (United States)

    Jourdain, Alexis A; Boehm, Erik; Maundrell, Kinsey; Martinou, Jean-Claude

    2016-03-14

    In mitochondria, DNA replication, gene expression, and RNA degradation machineries coexist within a common nondelimited space, raising the question of how functional compartmentalization of gene expression is achieved. Here, we discuss the recently characterized "mitochondrial RNA granules," mitochondrial subdomains with an emerging role in the regulation of gene expression. PMID:26953349

  8. Gene ordering in partitive clustering using microarray expressions

    Indian Academy of Sciences (India)

    Shubhra Sankar Ray; Sanghamitra Bandyopadhyay; Sankar K Pal

    2007-08-01

    A central step in the analysis of gene expression data is the identification of groups of genes that exhibit similar expression patterns. Clustering and ordering the genes using gene expression data into homogeneous groups was shown to be useful in functional annotation, tissue classification, regulatory motif identification, and other applications. Although there is a rich literature on gene ordering in hierarchical clustering framework for gene expression analysis, there is no work addressing and evaluating the importance of gene ordering in partitive clustering framework, to the best knowledge of the authors. Outside the framework of hierarchical clustering, different gene ordering algorithms are applied on the whole data set, and the domain of partitive clustering is still unexplored with gene ordering approaches. A new hybrid method is proposed for ordering genes in each of the clusters obtained from partitive clustering solution, using microarray gene expressions. Two existing algorithms for optimally ordering cities in travelling salesman problem (TSP), namely, FRAG_GALK and Concorde, are hybridized individually with self organizing MAP to show the importance of gene ordering in partitive clustering framework. We validated our hybrid approach using yeast and fibroblast data and showed that our approach improves the result quality of partitive clustering solution, by identifying subclusters within big clusters, grouping functionally correlated genes within clusters, minimization of summation of gene expression distances, and the maximization of biological gene ordering using MIPS categorization. Moreover, the new hybrid approach, finds comparable or sometimes superior biological gene order in less computation time than those obtained by optimal leaf ordering in hierarchical clustering solution.

  9. Gene expression analysis identifies global gene dosage sensitivity in cancer

    DEFF Research Database (Denmark)

    Fehrmann, Rudolf S. N.; Karjalainen, Juha M.; Krajewska, Malgorzata;

    2015-01-01

    expression. We reanalyzed 77,840 expression profiles and observed a limited set of 'transcriptional components' that describe well-known biology, explain the vast majority of variation in gene expression and enable us to predict the biological function of genes. On correcting expression profiles for these...

  10. From gene expressions to genetic networks

    Science.gov (United States)

    Cieplak, Marek

    2009-03-01

    A method based on the principle of entropy maximization is used to identify the gene interaction network with the highest probability of giving rise to experimentally observed transcript profiles [1]. In its simplest form, the method yields the pairwise gene interaction network, but it can also be extended to deduce higher order correlations. Analysis of microarray data from genes in Saccharomyces cerevisiae chemostat cultures exhibiting energy metabollic oscillations identifies a gene interaction network that reflects the intracellular communication pathways. These pathways adjust cellular metabolic activity and cell division to the limiting nutrient conditions that trigger metabolic oscillations. The success of the present approach in extracting meaningful genetic connections suggests that the maximum entropy principle is a useful concept for understanding living systems, as it is for other complex, nonequilibrium systems. The time-dependent behavior of the genetic network is found to involve only a few fundamental modes [2,3]. [4pt] REFERENCES:[0pt] [1] T. R. Lezon, J. R. Banavar, M. Cieplak, A. Maritan, and N. Fedoroff, Using the principle of entropy maximization to infer genetic interaction networks from gene expression patterns, Proc. Natl. Acad. Sci. (USA) 103, 19033-19038 (2006) [0pt] [2] N. S. Holter, M. Mitra, A. Maritan, M. Cieplak, J. R. Banavar, and N. V. Fedoroff, Fundamental patterns underlying gene expression profiles: simplicity from complexity, Proc. Natl. Acad. Sci. USA 97, 8409-8414 (2000) [0pt] [3] N. S. Holter, A. Maritan, M. Cieplak, N. V. Fedoroff, and J. R. Banavar, Dynamic modeling of gene expression data, Proc. Natl. Acad. Sci. USA 98, 1693-1698 (2001)

  11. Correlating Expression Data with Gene Function Using Gene Ontology

    Institute of Scientific and Technical Information of China (English)

    LIU,Qi; DENG,Yong; WANG,Chuan; SHI,Tie-Liu; LI,Yi-Xue

    2006-01-01

    Clustering is perhaps one of the most widely used tools for microarray data analysis. Proposed roles for genes of unknown function are inferred from clusters of genes similarity expressed across many biological conditions.However, whether function annotation by similarity metrics is reliable or not and to what extent the similarity in gene expression patterns is useful for annotation of gene functions, has not been evaluated. This paper made a comprehensive research on the correlation between the similarity of expression data and of gene functions using Gene Ontology. It has been found that although the similarity in expression patterns and the similarity in gene functions are significantly dependent on each other, this association is rather weak. In addition, among the three categories of Gene Ontology, the similarity of expression data is more useful for cellular component annotation than for biological process and molecular function. The results presented are interesting for the gene functions prediction research area.

  12. Daunomycin-TFO Conjugates for Downregulation of Gene Expression

    Science.gov (United States)

    Capobianco, Massimo L.; Catapano, Carlo V.

    Daunomycin has shown interesting properties as a stabilizing agent for the antigene methodology. This approach consists of targeting a polypurine region of a given gene, with a triplex forming oligonucleotide (TFO), realizing a triple helix complex (triplex), with the aim of down-regulating gene expression. This chapter describes the basic principles of the triplex approach, the chemistry underlining the binding of daunomycin to oligonucleotides, and some results of gene-inhibition obtained with daunomycin-TFO conjugates with different targets.

  13. Quantitative Real Time PCR approach to study gene expression profile during prenatal growth of skeletal muscle in pig of Duroc and Pietrain breeds

    Directory of Open Access Journals (Sweden)

    M. Cagnazzo

    2010-01-01

    Full Text Available The quantitative real time-PCR (QRT-PCR is a very sensitive method used to quantify mRNA level in gene expression analysis. Combining amplification, detection and quantification in a single step, allows a more accurate measurement compared to the traditional PCR end point analysis (Pfaffl, 2001; Bustin, 2002.

  14. Gene expression regulators--MicroRNAs

    Institute of Scientific and Technical Information of China (English)

    CHEN Fang; YIN Q. James

    2005-01-01

    A large class of non-coding RNAs found in small molecule RNAs are closely associated with the regulation of gene expression, which are called microRNA (miRNA). MiRNAs are coded in intergenic or intronic regions and can be formed into foldback hairpin RNAs. These transcripts are cleaved by Dicer, generating mature miRNAs that can silence their target genes in different modes of action. Now, research on small molecule RNAs has gotten breakthrough advance in biology. To discover miRNA genes and their target genes has become hot topics in RNA research. This review attempts to look back the history of miRNA discovery, to introduce the methods of screening miRNAs, to localize miRNA loci in genome, to seek miRNA target genes and the biological function, and to discuss the working mechanisms of miRNAs. Finally, we will discuss the potential important roles of miRNAs in modulating the genesis, development, growth, and differentiation of organisms. Thus, it can be predicted that a complete understanding of miRNA functions will bring us some new concepts, approaches and strategies for the study of living beings.

  15. Bayesian biclustering of gene expression data

    OpenAIRE

    Liu Jun S; Gu Jiajun

    2008-01-01

    Abstract Background Biclustering of gene expression data searches for local patterns of gene expression. A bicluster (or a two-way cluster) is defined as a set of genes whose expression profiles are mutually similar within a subset of experimental conditions/samples. Although several biclustering algorithms have been studied, few are based on rigorous statistical models. Results We developed a Bayesian biclustering model (BBC), and implemented a Gibbs sampling procedure for its statistical in...

  16. Methods for monitoring multiple gene expression

    Energy Technology Data Exchange (ETDEWEB)

    Berka, Randy; Bachkirova, Elena; Rey, Michael

    2013-10-01

    The present invention relates to methods for monitoring differential expression of a plurality of genes in a first filamentous fungal cell relative to expression of the same genes in one or more second filamentous fungal cells using microarrays containing Trichoderma reesei ESTs or SSH clones, or a combination thereof. The present invention also relates to computer readable media and substrates containing such array features for monitoring expression of a plurality of genes in filamentous fungal cells.

  17. Methods for monitoring multiple gene expression

    Energy Technology Data Exchange (ETDEWEB)

    Berka, Randy (Davis, CA); Bachkirova, Elena (Davis, CA); Rey, Michael (Davis, CA)

    2012-05-01

    The present invention relates to methods for monitoring differential expression of a plurality of genes in a first filamentous fungal cell relative to expression of the same genes in one or more second filamentous fungal cells using microarrays containing Trichoderma reesei ESTs or SSH clones, or a combination thereof. The present invention also relates to computer readable media and substrates containing such array features for monitoring expression of a plurality of genes in filamentous fungal cells.

  18. A comparative expression analysis of gene transcripts in brain tissue of non-transgenic and GH-transgenic zebrafish (Danio rerio using a DDRT-PCR approach

    Directory of Open Access Journals (Sweden)

    Fernanda A. Alves-Costa

    2012-06-01

    Full Text Available The presence of higher level of exogenous growth hormone (GH in transgenic animals could lead to several physiological alterations. A GH transgenic zebrafish (Danio rerio line was compared to nontransgenic (NT samples of the species through a DDRT-PCR approach, with the goal of identifying candidate differentially expressed transcripts in brain tissues that could be involved in GH overexpression. Densitometric analyses of two selected amplification products, p300 and ADCY2, pointed to a significant lower gene expression in the transgenic zebrafish (104.02 ± 57.71; 224.10 ± 91.73 when compared to NT samples (249.75 ± 30.08; 342.95 ± 65.19. The present data indicate that p300 and ADCY2 are involved in a regulation system for GH when high circulating levels of this hormone are found in zebrafishes.A presença de níveis mais elevados do hormônio de crescimento (GH em animais transgênicos poderia levar a várias alterações fisiológicas. Uma linhagem transgênica de paulistinha (Danio rerio para o GH foi comparada com amostras não transgênicas (NT desta espécie, através de uma abordagem de DDRT-PCR, com o objetivo de identificar transcritos candidatos diferencialmente expressos em tecido cerebral que poderiam estar envolvidos na superexpressão de GH. Análises densitométricas de dois produtos de amplificação selecionados, p300 e ADCY2, apontaram uma expressão gênica significativamente menor nas amostras transgênicas de paulistinha (104.02 ± 57.71; 224.10 ± 91.73, quando comparadas com as amostras NT (249.75 ± 30.08; 342.95±65.19. Os presentes dados indicam que p300 e ADCY2 estão envolvidos em um sistema de regulação do GH, quando altos níveis circulantes desse hormônio são encontrados em paulistinha.

  19. Analysis of Gene Expression Patterns Using Biclustering.

    Science.gov (United States)

    Roy, Swarup; Bhattacharyya, Dhruba K; Kalita, Jugal K

    2016-01-01

    Mining microarray data to unearth interesting expression profile patterns for discovery of in silico biological knowledge is an emerging area of research in computational biology. A group of functionally related genes may have similar expression patterns under a set of conditions or at some time points. Biclustering is an important data mining tool that has been successfully used to analyze gene expression data for biologically significant cluster discovery. The purpose of this chapter is to introduce interesting patterns that may be observed in expression data and discuss the role of biclustering techniques in detecting interesting functional gene groups with similar expression patterns. PMID:26350227

  20. Gene Expression Profiling in the Hibernating Primate, Cheirogaleus Medius.

    Science.gov (United States)

    Faherty, Sheena L; Villanueva-Cañas, José Luis; Klopfer, Peter H; Albà, M Mar; Yoder, Anne D

    2016-01-01

    Hibernation is a complex physiological response that some mammalian species employ to evade energetic demands. Previous work in mammalian hibernators suggests that hibernation is activated not by a set of genes unique to hibernators, but by differential expression of genes that are present in all mammals. This question of universal genetic mechanisms requires further investigation and can only be tested through additional investigations of phylogenetically dispersed species. To explore this question, we use RNA-Seq to investigate gene expression dynamics as they relate to the varying physiological states experienced throughout the year in a group of primate hibernators-Madagascar's dwarf lemurs (genus Cheirogaleus). In a novel experimental approach, we use longitudinal sampling of biological tissues as a method for capturing gene expression profiles from the same individuals throughout their annual hibernation cycle. We identify 90 candidate genes that have variable expression patterns when comparing two active states (Active 1 and Active 2) with a torpor state. These include genes that are involved in metabolic pathways, feeding behavior, and circadian rhythms, as might be expected to correlate with seasonal physiological state changes. The identified genes appear to be critical for maintaining the health of an animal that undergoes prolonged periods of metabolic depression concurrent with the hibernation phenotype. By focusing on these differentially expressed genes in dwarf lemurs, we compare gene expression patterns in previously studied mammalian hibernators. Additionally, by employing evolutionary rate analysis, we find that hibernation-related genes do not evolve under positive selection in hibernating species relative to nonhibernators. PMID:27412611

  1. Clustering gene expression data using graph separators.

    Science.gov (United States)

    Kaba, Bangaly; Pinet, Nicolas; Lelandais, Gaëlle; Sigayret, Alain; Berry, Anne

    2007-01-01

    Recent work has used graphs to modelize expression data from microarray experiments, in view of partitioning the genes into clusters. In this paper, we introduce the use of a decomposition by clique separators. Our aim is to improve the classical clustering methods in two ways: first we want to allow an overlap between clusters, as this seems biologically sound, and second we want to be guided by the structure of the graph to define the number of clusters. We test this approach with a well-known yeast database (Saccharomyces cerevisiae). Our results are good, as the expression profiles of the clusters we find are very coherent. Moreover, we are able to organize into another graph the clusters we find, and order them in a fashion which turns out to respect the chronological order defined by the the sporulation process. PMID:18391236

  2. Deriving Trading Rules Using Gene Expression Programming

    Directory of Open Access Journals (Sweden)

    Adrian VISOIU

    2011-01-01

    Full Text Available This paper presents how buy and sell trading rules are generated using gene expression programming with special setup. Market concepts are presented and market analysis is discussed with emphasis on technical analysis and quantitative methods. The use of genetic algorithms in deriving trading rules is presented. Gene expression programming is applied in a form where multiple types of operators and operands are used. This gives birth to multiple gene contexts and references between genes in order to keep the linear structure of the gene expression programming chromosome. The setup of multiple gene contexts is presented. The case study shows how to use the proposed gene setup to derive trading rules encoded by Boolean expressions, using a dataset with the reference exchange rates between the Euro and the Romanian leu. The conclusions highlight the positive results obtained in deriving useful trading rules.

  3. The Role of Multiple Transcription Factors In Archaeal Gene Expression

    Energy Technology Data Exchange (ETDEWEB)

    Charles J. Daniels

    2008-09-23

    Since the inception of this research program, the project has focused on two central questions: What is the relationship between the 'eukaryal-like' transcription machinery of archaeal cells and its counterparts in eukaryal cells? And, how does the archaeal cell control gene expression using its mosaic of eukaryal core transcription machinery and its bacterial-like transcription regulatory proteins? During the grant period we have addressed these questions using a variety of in vivo approaches and have sought to specifically define the roles of the multiple TATA binding protein (TBP) and TFIIB-like (TFB) proteins in controlling gene expression in Haloferax volcanii. H. volcanii was initially chosen as a model for the Archaea based on the availability of suitable genetic tools; however, later studies showed that all haloarchaea possessed multiple tbp and tfb genes, which led to the proposal that multiple TBP and TFB proteins may function in a manner similar to alternative sigma factors in bacterial cells. In vivo transcription and promoter analysis established a clear relationship between the promoter requirements of haloarchaeal genes and those of the eukaryal RNA polymerase II promoter. Studies on heat shock gene promoters, and the demonstration that specific tfb genes were induced by heat shock, provided the first indication that TFB proteins may direct expression of specific gene families. The construction of strains lacking tbp or tfb genes, coupled with the finding that many of these genes are differentially expressed under varying growth conditions, provided further support for this model. Genetic tools were also developed that led to the construction of insertion and deletion mutants, and a novel gene expression scheme was designed that allowed the controlled expression of these genes in vivo. More recent studies have used a whole genome array to examine the expression of these genes and we have established a linkage between the expression of

  4. Genetic architecture of gene expression in ovine skeletal muscle

    DEFF Research Database (Denmark)

    Kogelman, Lisette Johanna Antonia; Byrne, Keren; Vuocolo, Tony;

    2011-01-01

    -based gene expression data we directly tested the hypothesis that there is genetic structure in the gene expression program in ovine skeletal muscle.Results: The genetic performance of six sires for a well defined muscling trait, longissimus lumborum muscle depth, was measured using extensive progeny testing...... architecture to the gene expression data, which also discriminated the sire-based Estimated Breeding Value for the trait. An integrated systems biology approach was then used to identify the major functional pathways contributing to the genetics of enhanced muscling by using both Estimated Breeding Value...

  5. Biologically supervised hierarchical clustering algorithms for gene expression data.

    Science.gov (United States)

    Boratyn, Grzegorz M; Datta, Susmita; Datta, Somnath

    2006-01-01

    Cluster analysis has become a standard part of gene expression analysis. In this paper, we propose a novel semi-supervised approach that offers the same flexibility as that of a hierarchical clustering. Yet it utilizes, along with the experimental gene expression data, common biological information about different genes that is being complied at various public, Web accessible databases. We argue that such an approach is inherently superior than the standard unsupervised approach of grouping genes based on expression data alone. It is shown that our biologically supervised methods produce better clustering results than the corresponding unsupervised methods as judged by the distance from the model temporal profiles. R-codes of the clustering algorithm are available from the authors upon request. PMID:17947147

  6. Gene expression of the endolymphatic sac

    DEFF Research Database (Denmark)

    Friis, Morten; Martin-Bertelsen, Tomas; Friis-Hansen, Lennart;

    2011-01-01

    endolymphatic sac has multiple and diverse functions in the inner ear. Objectives:The objective of this study was to provide a comprehensive review of the genes expressed in the endolymphatic sac in the rat and perform a functional characterization based on measured mRNA abundance. Methods:Microarray technology...... was used to investigate the gene expression of the endolymphatic sac with the surrounding dura. Characteristic and novel endolymphatic sac genes were determined by comparing with expressions in pure dura. Results: In all, 463 genes were identified specific for the endolymphatic sac. Functional...

  7. Gene expression profiling in autoimmune diseases

    DEFF Research Database (Denmark)

    Bovin, Lone Frier; Brynskov, Jørn; Hegedüs, Laszlo;

    2007-01-01

    A central issue in autoimmune disease is whether the underlying inflammation is a repeated stereotypical process or whether disease specific gene expression is involved. To shed light on this, we analysed whether genes previously found to be differentially regulated in rheumatoid arthritis (RA...... differences in peripheral blood mononuclear cell (MNC) gene expression patterns between 15 newly diagnosed HT patients and 15 matched healthy controls. However, the MNC expression levels of five genes were significantly upregulated in 25 IBD patients, compared to 18 matched healthy controls (CD14, FACL2, FCN1......, RNASE2, VNN2). There was concordance in the directional change for all genes between IBD and RA patients, i.e. increased expression compared to controls. These data show that one third of the genes significantly upregulated in MNC from RA patients were upregulated in patients with other chronic...

  8. Gene expression trees in lymphoid development

    Directory of Open Access Journals (Sweden)

    Schliep Alexander

    2007-10-01

    Full Text Available Abstract Background The regulatory processes that govern cell proliferation and differentiation are central to developmental biology. Particularly well studied in this respect is the lymphoid system due to its importance for basic biology and for clinical applications. Gene expression measured in lymphoid cells in several distinguishable developmental stages helps in the elucidation of underlying molecular processes, which change gradually over time and lock cells in either the B cell, T cell or Natural Killer cell lineages. Large-scale analysis of these gene expression trees requires computational support for tasks ranging from visualization, querying, and finding clusters of similar genes, to answering detailed questions about the functional roles of individual genes. Results We present the first statistical framework designed to analyze gene expression data as it is collected in the course of lymphoid development through clusters of co-expressed genes and additional heterogeneous data. We introduce dependence trees for continuous variates, which model the inherent dependencies during the differentiation process naturally as gene expression trees. Several trees are combined in a mixture model to allow inference of potentially overlapping clusters of co-expressed genes. Additionally, we predict microRNA targets. Conclusion Computational results for several data sets from the lymphoid system demonstrate the relevance of our framework. We recover well-known biological facts and identify promising novel regulatory elements of genes and their functional assignments. The implementation of our method (licensed under the GPL is available at http://algorithmics.molgen.mpg.de/Supplements/ExpLym/.

  9. The functional landscape of mouse gene expression

    Directory of Open Access Journals (Sweden)

    Zhang Wen

    2004-12-01

    Full Text Available Abstract Background Large-scale quantitative analysis of transcriptional co-expression has been used to dissect regulatory networks and to predict the functions of new genes discovered by genome sequencing in model organisms such as yeast. Although the idea that tissue-specific expression is indicative of gene function in mammals is widely accepted, it has not been objectively tested nor compared with the related but distinct strategy of correlating gene co-expression as a means to predict gene function. Results We generated microarray expression data for nearly 40,000 known and predicted mRNAs in 55 mouse tissues, using custom-built oligonucleotide arrays. We show that quantitative transcriptional co-expression is a powerful predictor of gene function. Hundreds of functional categories, as defined by Gene Ontology 'Biological Processes', are associated with characteristic expression patterns across all tissues, including categories that bear no overt relationship to the tissue of origin. In contrast, simple tissue-specific restriction of expression is a poor predictor of which genes are in which functional categories. As an example, the highly conserved mouse gene PWP1 is widely expressed across different tissues but is co-expressed with many RNA-processing genes; we show that the uncharacterized yeast homolog of PWP1 is required for rRNA biogenesis. Conclusions We conclude that 'functional genomics' strategies based on quantitative transcriptional co-expression will be as fruitful in mammals as they have been in simpler organisms, and that transcriptional control of mammalian physiology is more modular than is generally appreciated. Our data and analyses provide a public resource for mammalian functional genomics.

  10. Bimodal gene expression patterns in breast cancer

    OpenAIRE

    Nikolsky Yuri; Bugrim Andrej; Shi Weiwei; Kirillov Eugene; Bessarabova Marina; Nikolskaya Tatiana

    2010-01-01

    Abstract We identified a set of genes with an unexpected bimodal distribution among breast cancer patients in multiple studies. The property of bimodality seems to be common, as these genes were found on multiple microarray platforms and in studies with different end-points and patient cohorts. Bimodal genes tend to cluster into small groups of four to six genes with synchronised expression within the group (but not between the groups), which makes them good candidates for robust conditional ...

  11. Topological Features In Cancer Gene Expression Data

    OpenAIRE

    Lockwood, Svetlana; Krishnamoorthy, Bala

    2014-01-01

    We present a new method for exploring cancer gene expression data based on tools from algebraic topology. Our method selects a small relevant subset from tens of thousands of genes while simultaneously identifying nontrivial higher order topological features, i.e., holes, in the data. We first circumvent the problem of high dimensionality by dualizing the data, i.e., by studying genes as points in the sample space. Then we select a small subset of the genes as landmarks to construct topologic...

  12. Identity Gene Expression in Proteus Mirabilis

    OpenAIRE

    Gibbs, Karine Alexine; Wenren, Larissa Man-Yin; Greenberg, E. Peter

    2011-01-01

    Swarming colonies of independent Proteus mirabilis isolates recognize each other as foreign and do not merge together, whereas apposing swarms of clonal isolates merge with each other. Swarms of mutants with deletions in the ids gene cluster do not merge with their parent. Thus, ids genes are involved in the ability of P. mirabilis to distinguish self from nonself. Here we have characterized expression of the ids genes. We show that idsABCDEF genes are transcribed as an operon, and we define ...

  13. Pathway level analysis of gene expression using singular value decomposition

    Directory of Open Access Journals (Sweden)

    Kepler Thomas B

    2005-09-01

    Full Text Available Abstract Background A promising direction in the analysis of gene expression focuses on the changes in expression of specific predefined sets of genes that are known in advance to be related (e.g., genes coding for proteins involved in cellular pathways or complexes. Such an analysis can reveal features that are not easily visible from the variations in the individual genes and can lead to a picture of expression that is more biologically transparent and accessible to interpretation. In this article, we present a new method of this kind that operates by quantifying the level of 'activity' of each pathway in different samples. The activity levels, which are derived from singular value decompositions, form the basis for statistical comparisons and other applications. Results We demonstrate our approach using expression data from a study of type 2 diabetes and another of the influence of cigarette smoke on gene expression in airway epithelia. A number of interesting pathways are identified in comparisons between smokers and non-smokers including ones related to nicotine metabolism, mucus production, and glutathione metabolism. A comparison with results from the related approach, 'gene-set enrichment analysis', is also provided. Conclusion Our method offers a flexible basis for identifying differentially expressed pathways from gene expression data. The results of a pathway-based analysis can be complementary to those obtained from one more focused on individual genes. A web program PLAGE (Pathway Level Analysis of Gene Expression for performing the kinds of analyses described here is accessible at http://dulci.biostat.duke.edu/pathways.

  14. Monoallelic expression of multiple genes in the CNS.

    Science.gov (United States)

    Wang, Jinhui; Valo, Zuzana; Smith, David; Singer-Sam, Judith

    2007-01-01

    The inheritance pattern of a number of major genetic disorders suggests the possible involvement of genes that are expressed from one allele and silent on the other, but such genes are difficult to detect. Since DNA methylation in regulatory regions is often a mark of gene silencing, we modified existing microarray-based assays to detect both methylated and unmethylated DNA sequences in the same sample, a variation we term the MAUD assay. We probed a 65 Mb region of mouse Chr 7 for gene-associated sequences that show two distinct DNA methylation patterns in the mouse CNS. Selected genes were then tested for allele-specific expression in clonal neural stem cell lines derived from reciprocal F(1) (C57BL/6xJF1) hybrid mice. In addition, using a separate approach, we directly analyzed allele-specific expression of a group of genes interspersed within clusters of OlfR genes, since the latter are subject to allelic exclusion. Altogether, of the 500 known genes in the chromosomal region surveyed, five show monoallelic expression, four identified by the MAUD assay (Agc1, p (pink-eyed dilution), P4ha3 and Thrsp), and one by its proximity to OlfR genes (Trim12). Thrsp (thyroid hormone responsive SPOT14 homolog) is expressed in hippocampus, but the human protein homolog, S14, has also been implicated in aggressive breast cancer. Monoallelic expression of the five genes is not coordinated at a chromosome-wide level, but rather regulated at individual loci. Taken together, our results suggest that at least 1% of previously untested genes are subject to allelic exclusion, and demonstrate a dual approach to expedite their identification. PMID:18074017

  15. Gene expression signatures for colorectal cancer microsatellite status and HNPCC

    DEFF Research Database (Denmark)

    Kruhøffer, M; Jensen, J L; Laiho, P;

    2005-01-01

    is correlated to prognosis and response to chemotherapy. Gene expression signatures as predictive markers are being developed for many cancers, and the identification of a signature for MMR deficiency would be of interest both clinically and biologically. To address this issue, we profiled the gene...... expression of 101 stage II and III colorectal cancers (34 MSI, 67 microsatellite stable (MSS)) using high-density oligonucleotide microarrays. From these data, we constructed a nine-gene signature capable of separating the mismatch repair proficient and deficient tumours. Subsequently, we demonstrated the......-deficient tumours into sporadic MSI and HNPCC cases, and validated this by a mathematical cross-validation approach. The demonstration that this two-step classification approach can identify MSI as well as HNPCC cases merits further gene expression studies to identify prognostic signatures....

  16. A comparative gene expression database for invertebrates

    Directory of Open Access Journals (Sweden)

    Ormestad Mattias

    2011-08-01

    Full Text Available Abstract Background As whole genome and transcriptome sequencing gets cheaper and faster, a great number of 'exotic' animal models are emerging, rapidly adding valuable data to the ever-expanding Evo-Devo field. All these new organisms serve as a fantastic resource for the research community, but the sheer amount of data, some published, some not, makes detailed comparison of gene expression patterns very difficult to summarize - a problem sometimes even noticeable within a single lab. The need to merge existing data with new information in an organized manner that is publicly available to the research community is now more necessary than ever. Description In order to offer a homogenous way of storing and handling gene expression patterns from a variety of organisms, we have developed the first web-based comparative gene expression database for invertebrates that allows species-specific as well as cross-species gene expression comparisons. The database can be queried by gene name, developmental stage and/or expression domains. Conclusions This database provides a unique tool for the Evo-Devo research community that allows the retrieval, analysis and comparison of gene expression patterns within or among species. In addition, this database enables a quick identification of putative syn-expression groups that can be used to initiate, among other things, gene regulatory network (GRN projects.

  17. Differential gene expression during Trypanosoma cruzi metacyclogenesis

    Directory of Open Access Journals (Sweden)

    Marco Aurelio Krieger

    1999-09-01

    Full Text Available The transformation of epimastigotes into metacyclic trypomastigotes involves changes in the pattern of expressed genes, resulting in important morphological and functional differences between these developmental forms of Trypanosoma cruzi. In order to identify and characterize genes involved in triggering the metacyclogenesis process and in conferring to metacyclic trypomastigotes their stage specific biological properties, we have developed a method allowing the isolation of genes specifically expressed when comparing two close related cell populations (representation of differential expression or RDE. The method is based on the PCR amplification of gene sequences selected by hybridizing and subtracting the populations in such a way that after some cycles of hybridization-amplification genes specific to a given population are highly enriched. The use of this method in the analysis of differential gene expression during T. cruzi metacyclogenesis (6 hr and 24 hr of differentiation and metacyclic trypomastigotes resulted in the isolation of several clones from each time point. Northern blot analysis showed that some genes are transiently expressed (6 hr and 24 hr differentiating cells, while others are present in differentiating cells and in metacyclic trypomastigotes. Nucleotide sequencing of six clones characterized so far showed that they do not display any homology to gene sequences available in the GeneBank.

  18. Global gene expression in Escherichia coli biofilms

    DEFF Research Database (Denmark)

    Schembri, Mark; Kjærgaard, K.; Klemm, Per

    2003-01-01

    antimicrobial treatments and host immune defence responses. Escherichia coli has been used as a model organism to study the mechanisms of growth within adhered communities. In this study, we use DNA microarray technology to examine the global gene expression profile of E. coli during sessile growth compared...... with planktonic growth. Genes encoding proteins involved in adhesion (type 1 fimbriae) and, in particular, autoaggregation (Antigen 43) were highly expressed in the adhered population in a manner that is consistent with current models of sessile community development. Several novel gene clusters were...... induced upon the transition to biofilm growth, and these included genes expressed under oxygen-limiting conditions, genes encoding (putative) transport proteins, putative oxidoreductases and genes associated with enhanced heavy metal resistance. Of particular interest was the observation that many of the...

  19. Network Security via Biometric Recognition of Patterns of Gene Expression

    Science.gov (United States)

    Shaw, Harry C.

    2016-01-01

    Molecular biology provides the ability to implement forms of information and network security completely outside the bounds of legacy security protocols and algorithms. This paper addresses an approach which instantiates the power of gene expression for security. Molecular biology provides a rich source of gene expression and regulation mechanisms, which can be adopted to use in the information and electronic communication domains. Conventional security protocols are becoming increasingly vulnerable due to more intensive, highly capable attacks on the underlying mathematics of cryptography. Security protocols are being undermined by social engineering and substandard implementations by IT organizations. Molecular biology can provide countermeasures to these weak points with the current security approaches. Future advances in instruments for analyzing assays will also enable this protocol to advance from one of cryptographic algorithms to an integrated system of cryptographic algorithms and real-time expression and assay of gene expression products.

  20. Phytochrome-regulated Gene Expression

    Institute of Scientific and Technical Information of China (English)

    Peter H. Quail

    2007-01-01

    Identification of all genes involved in the phytochrome (phy)-mediated responses of plants to their light environment is an important goal in providing an overall understanding of light-regulated growth and development. This article highlights and integrates the central findings of two recent comprehensive studies in Arabidopsis that have identified the genome-wide set of phy-regulated genes that respond rapidly to red-light signals upon first exposure of dark-grown seedlings, and have tested the functional relevance to normal seedling photomorphogenesis of an initial subset of these genes. The data: (a) reveal considerable complexity in the channeling of the light signals through the different phy-family members (phyA to phyE) to responsive genes; (b) identify a diversity of transcription-factor-encoding genes as major early, if not primary, targets of phy signaling, and, therefore, as potentially important regulators in the transcriptional-network hierarchy; and (c) identify auxin-related genes as the dominant class among rapidly-regulated, hormone-related genes. However, reverse-genetic functional profiling of a selected subset of these genes reveals that only a limited fraction are necessary for optimal phy-induced seedling deetiolation.

  1. Meta-analysis of differentially expressed genes in osteosarcoma based on gene expression data

    OpenAIRE

    Yang, Zuozhang; Chen, Yongbin; Fu, Yu; Yang, Yihao; Zhang, Ya; Chen, Yanjin; Li, Dongqi

    2014-01-01

    Background To uncover the genes involved in the development of osteosarcoma (OS), we performed a meta-analysis of OS microarray data to identify differentially expressed genes (DEGs) and biological functions associated with gene expression changes between OS and normal control (NC) tissues. Methods We used publicly available GEO datasets of OS to perform a meta-analysis. We performed Gene Ontology (GO) enrichment analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis and Pr...

  2. Visually Relating Gene Expression and in vivo DNA Binding Data

    Energy Technology Data Exchange (ETDEWEB)

    Huang, Min-Yu; Mackey, Lester; Ker?,; nen, Soile V. E.; Weber, Gunther H.; Jordan, Michael I.; Knowles, David W.; Biggin, Mark D.; Hamann, Bernd

    2011-09-20

    Gene expression and in vivo DNA binding data provide important information for understanding gene regulatory networks: in vivo DNA binding data indicate genomic regions where transcription factors are bound, and expression data show the output resulting from this binding. Thus, there must be functional relationships between these two types of data. While visualization and data analysis tools exist for each data type alone, there is a lack of tools that can easily explore the relationship between them. We propose an approach that uses the average expression driven by multiple of ciscontrol regions to visually relate gene expression and in vivo DNA binding data. We demonstrate the utility of this tool with examples from the network controlling early Drosophila development. The results obtained support the idea that the level of occupancy of a transcription factor on DNA strongly determines the degree to which the factor regulates a target gene, and in some cases also controls whether the regulation is positive or negative.

  3. Expression of streptavidin gene in bacteria and plants

    International Nuclear Information System (INIS)

    Six biotin-containing proteins are present in plants, representing at least four different biotin enzymes. The physiological function of these biotin enzymes is not understood. Streptavidin, a protein from Streptomyces avidinii, binds tightly and specifically to biotin causing inactivation of biotin enzymes. One approach to elucidating the physiological function of biotin enzymes in plant metabolism is to create transgenic plants expressing the streptavidin gene. A plasmid containing a fused streptavidin-beta-galactosidase gene has been expressed in E. coli. We also have constructed various fusion genes that include an altered CaMV 35S promoter, signal peptides to target the streptavidin protein to specific organelles, and the streptavidin coding gene. We are examining the expression of these genes in cells of carrot

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

    Directory of Open Access Journals (Sweden)

    Sigvardsson Mikael

    2003-09-01

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

  5. Selection of low-variance expressed Malus x domestica (apple) genes for use as quantitative PCR reference genes (housekeepers)

    Science.gov (United States)

    To accurately measure gene expression using PCR-based approaches, there is the need for reference genes that have low variance in expression (housekeeping genes) to normalise the data for RNA quantity and quality. For non-model species such as Malus x domestica (apples), previously, the selection of...

  6. Complexity, Post-genomic Biology and Gene Expression Programs

    Science.gov (United States)

    Williams, Rohan B. H.; Luo, Oscar Junhong

    Gene expression represents the fundamental phenomenon by which information encoded in a genome is utilised for the overall biological objectives of the organism. Understanding this level of information transfer is therefore essential for dissecting the mechanistic basis of form and function of organisms. We survey recent developments in the methodology of the life sciences that is relevant for understanding the organisation and function of the genome and review our current understanding of the regulation of gene expression, and finally, outline some new approaches that may be useful in understanding the organisation of gene regulatory systems.

  7. Extracting expression modules from perturbational gene expression compendia

    OpenAIRE

    Van Dijck Patrick; Maere Steven; Kuiper Martin

    2008-01-01

    Abstract Background Compendia of gene expression profiles under chemical and genetic perturbations constitute an invaluable resource from a systems biology perspective. However, the perturbational nature of such data imposes specific challenges on the computational methods used to analyze them. In particular, traditional clustering algorithms have difficulties in handling one of the prominent features of perturbational compendia, namely partial coexpression relationships between genes. Biclus...

  8. Gene expression in periodontal tissues following treatment

    Directory of Open Access Journals (Sweden)

    Eisenacher Martin

    2008-07-01

    Full Text Available Abstract Background In periodontitis, treatment aimed at controlling the periodontal biofilm infection results in a resolution of the clinical and histological signs of inflammation. Although the cell types found in periodontal tissues following treatment have been well described, information on gene expression is limited to few candidate genes. Therefore, the aim of the study was to determine the expression profiles of immune and inflammatory genes in periodontal tissues from sites with severe chronic periodontitis following periodontal therapy in order to identify genes involved in tissue homeostasis. Gingival biopsies from 12 patients with severe chronic periodontitis were taken six to eight weeks following non-surgical periodontal therapy, and from 11 healthy controls. As internal standard, RNA of an immortalized human keratinocyte line (HaCaT was used. Total RNA was subjected to gene expression profiling using a commercially available microarray system focusing on inflammation-related genes. Post-hoc confirmation of selected genes was done by Realtime-PCR. Results Out of the 136 genes analyzed, the 5% most strongly expressed genes compared to healthy controls were Interleukin-12A (IL-12A, Versican (CSPG-2, Matrixmetalloproteinase-1 (MMP-1, Down syndrome critical region protein-1 (DSCR-1, Macrophage inflammatory protein-2β (Cxcl-3, Inhibitor of apoptosis protein-1 (BIRC-1, Cluster of differentiation antigen 38 (CD38, Regulator of G-protein signalling-1 (RGS-1, and Finkel-Biskis-Jinkins murine osteosarcoma virus oncogene (C-FOS; the 5% least strongly expressed genes were Receptor-interacting Serine/Threonine Kinase-2 (RIP-2, Complement component 3 (C3, Prostaglandin-endoperoxide synthase-2 (COX-2, Interleukin-8 (IL-8, Endothelin-1 (EDN-1, Plasminogen activator inhibitor type-2 (PAI-2, Matrix-metalloproteinase-14 (MMP-14, and Interferon regulating factor-7 (IRF-7. Conclusion Gene expression profiles found in periodontal tissues following

  9. Transcription factor oscillations induce differential gene expressions.

    Science.gov (United States)

    Wee, Keng Boon; Yio, Wee Kheng; Surana, Uttam; Chiam, Keng Hwee

    2012-06-01

    Intracellular protein levels of diverse transcription factors (TFs) vary periodically with time. However, the effects of TF oscillations on gene expression, the primary role of TFs, are poorly understood. In this study, we determined these effects by comparing gene expression levels induced in the presence and in the absence of TF oscillations under same mean intracellular protein level of TF. For all the nonlinear TF transcription kinetics studied, an oscillatory TF is predicted to induce gene expression levels that are distinct from a nonoscillatory TF. The conditions dictating whether TF oscillations induce either higher or lower average gene expression levels were elucidated. Subsequently, the predicted effects from an oscillatory TF, which follows sigmoid transcription kinetics, were applied to demonstrate how oscillatory dynamics provide a mechanism for differential target gene transactivation. Generally, the mean TF concentration at which oscillations occur relative to the promoter binding affinity of a target gene determines whether the gene is up- or downregulated whereas the oscillation amplitude amplifies the magnitude of the differential regulation. Notably, the predicted trends of differential gene expressions induced by oscillatory NF-κB and glucocorticoid receptor match the reported experimental observations. Furthermore, the biological function of p53 oscillations is predicted to prime the cell for death upon DNA damage via differential upregulation of apoptotic genes. Lastly, given N target genes, an oscillatory TF can generate between (N-1) and (2N-1) distinct patterns of differential transactivation. This study provides insights into the mechanism for TF oscillations to induce differential gene expressions, and underscores the importance of TF oscillations in biological regulations. PMID:22713556

  10. SIGNATURE: A workbench for gene expression signature analysis

    Directory of Open Access Journals (Sweden)

    Chang Jeffrey T

    2011-11-01

    Full Text Available Abstract Background The biological phenotype of a cell, such as a characteristic visual image or behavior, reflects activities derived from the expression of collections of genes. As such, an ability to measure the expression of these genes provides an opportunity to develop more precise and varied sets of phenotypes. However, to use this approach requires computational methods that are difficult to implement and apply, and thus there is a critical need for intelligent software tools that can reduce the technical burden of the analysis. Tools for gene expression analyses are unusually difficult to implement in a user-friendly way because their application requires a combination of biological data curation, statistical computational methods, and database expertise. Results We have developed SIGNATURE, a web-based resource that simplifies gene expression signature analysis by providing software, data, and protocols to perform the analysis successfully. This resource uses Bayesian methods for processing gene expression data coupled with a curated database of gene expression signatures, all carried out within a GenePattern web interface for easy use and access. Conclusions SIGNATURE is available for public use at http://genepattern.genome.duke.edu/signature/.

  11. OryzaExpress: An Integrated Database of Gene Expression Networks and Omics Annotations in Rice

    Science.gov (United States)

    Hamada, Kazuki; Hongo, Kohei; Suwabe, Keita; Shimizu, Akifumi; Nagayama, Taishi; Abe, Reina; Kikuchi, Shunsuke; Yamamoto, Naoki; Fujii, Takaaki; Yokoyama, Koji; Tsuchida, Hiroko; Sano, Kazumi; Mochizuki, Takako; Oki, Nobuhiko; Horiuchi, Youko; Fujita, Masahiro; Watanabe, Masao; Matsuoka, Makoto; Kurata, Nori; Yano, Kentaro

    2011-01-01

    Similarity of gene expression profiles provides important clues for understanding the biological functions of genes, biological processes and metabolic pathways related to genes. A gene expression network (GEN) is an ideal choice to grasp such expression profile similarities among genes simultaneously. For GEN construction, the Pearson correlation coefficient (PCC) has been widely used as an index to evaluate the similarities of expression profiles for gene pairs. However, calculation of PCCs for all gene pairs requires large amounts of both time and computer resources. Based on correspondence analysis, we developed a new method for GEN construction, which takes minimal time even for large-scale expression data with general computational circumstances. Moreover, our method requires no prior parameters to remove sample redundancies in the data set. Using the new method, we constructed rice GENs from large-scale microarray data stored in a public database. We then collected and integrated various principal rice omics annotations in public and distinct databases. The integrated information contains annotations of genome, transcriptome and metabolic pathways. We thus developed the integrated database OryzaExpress for browsing GENs with an interactive and graphical viewer and principal omics annotations (http://riceball.lab.nig.ac.jp/oryzaexpress/). With integration of Arabidopsis GEN data from ATTED-II, OryzaExpress also allows us to compare GENs between rice and Arabidopsis. Thus, OryzaExpress is a comprehensive rice database that exploits powerful omics approaches from all perspectives in plant science and leads to systems biology. PMID:21186175

  12. The rules of gene expression in plants: Organ identity and gene body methylation are key factors for regulation of gene expression in Arabidopsis thaliana

    Directory of Open Access Journals (Sweden)

    Gutiérrez Rodrigo A

    2008-09-01

    Full Text Available Abstract Background Microarray technology is a widely used approach for monitoring genome-wide gene expression. For Arabidopsis, there are over 1,800 microarray hybridizations representing many different experimental conditions on Affymetrix™ ATH1 gene chips alone. This huge amount of data offers a unique opportunity to infer the principles that govern the regulation of gene expression in plants. Results We used bioinformatics methods to analyze publicly available data obtained using the ATH1 chip from Affymetrix. A total of 1887 ATH1 hybridizations were normalized and filtered to eliminate low-quality hybridizations. We classified and compared control and treatment hybridizations and determined differential gene expression. The largest differences in gene expression were observed when comparing samples obtained from different organs. On average, ten-fold more genes were differentially expressed between organs as compared to any other experimental variable. We defined "gene responsiveness" as the number of comparisons in which a gene changed its expression significantly. We defined genes with the highest and lowest responsiveness levels as hypervariable and housekeeping genes, respectively. Remarkably, housekeeping genes were best distinguished from hypervariable genes by differences in methylation status in their transcribed regions. Moreover, methylation in the transcribed region was inversely correlated (R2 = 0.8 with gene responsiveness on a genome-wide scale. We provide an example of this negative relationship using genes encoding TCA cycle enzymes, by contrasting their regulatory responsiveness to nitrate and methylation status in their transcribed regions. Conclusion Our results indicate that the Arabidopsis transcriptome is largely established during development and is comparatively stable when faced with external perturbations. We suggest a novel functional role for DNA methylation in the transcribed region as a key determinant

  13. Optogenetic Control of Gene Expression in Drosophila.

    Directory of Open Access Journals (Sweden)

    Yick-Bun Chan

    Full Text Available To study the molecular mechanism of complex biological systems, it is important to be able to artificially manipulate gene expression in desired target sites with high precision. Based on the light dependent binding of cryptochrome 2 and a cryptochrome interacting bHLH protein, we developed a split lexA transcriptional activation system for use in Drosophila that allows regulation of gene expression in vivo using blue light or two-photon excitation. We show that this system offers high spatiotemporal resolution by inducing gene expression in tissues at various developmental stages. In combination with two-photon excitation, gene expression can be manipulated at precise sites in embryos, potentially offering an important tool with which to examine developmental processes.

  14. Dynamic modeling of gene expression data

    Science.gov (United States)

    Holter, N. S.; Maritan, A.; Cieplak, M.; Fedoroff, N. V.; Banavar, J. R.

    2001-01-01

    We describe the time evolution of gene expression levels by using a time translational matrix to predict future expression levels of genes based on their expression levels at some initial time. We deduce the time translational matrix for previously published DNA microarray gene expression data sets by modeling them within a linear framework by using the characteristic modes obtained by singular value decomposition. The resulting time translation matrix provides a measure of the relationships among the modes and governs their time evolution. We show that a truncated matrix linking just a few modes is a good approximation of the full time translation matrix. This finding suggests that the number of essential connections among the genes is small.

  15. Determinants of human adipose tissue gene expression

    DEFF Research Database (Denmark)

    Viguerie, Nathalie; Montastier, Emilie; Maoret, Jean-José;

    2012-01-01

    Weight control diets favorably affect parameters of the metabolic syndrome and delay the onset of diabetic complications. The adaptations occurring in adipose tissue (AT) are likely to have a profound impact on the whole body response as AT is a key target of dietary intervention. Identification ...... controlled AT gene expression. These analyses help understanding the relative importance of environmental and individual factors that control the expression of human AT genes and therefore may foster strategies aimed at improving AT function in metabolic diseases....

  16. Facilitated diffusion buffers noise in gene expression

    OpenAIRE

    Schoech, Armin; Zabet, Nicolae Radu

    2014-01-01

    Transcription factors perform facilitated diffusion (3D diffusion in the cytosol and 1D diffusion on the DNA) when binding to their target sites to regulate gene expression. Here, we investigated the influence of this binding mechanism on the noise in gene expression. Our results showed that, for biologically relevant parameters, the binding process can be represented by a two-state Markov model and that the accelerated target finding due to facilitated diffusion leads to a reduction in both ...

  17. Transcription Factor Oscillations Induce Differential Gene Expressions

    OpenAIRE

    Wee, Keng Boon; Yio, Wee Kheng; Surana, Uttam; Chiam, Keng Hwee

    2012-01-01

    Intracellular protein levels of diverse transcription factors (TFs) vary periodically with time. However, the effects of TF oscillations on gene expression, the primary role of TFs, are poorly understood. In this study, we determined these effects by comparing gene expression levels induced in the presence and in the absence of TF oscillations under same mean intracellular protein level of TF. For all the nonlinear TF transcription kinetics studied, an oscillatory TF is predicted to induce ge...

  18. Blood gene expression signatures predict exposure levels

    OpenAIRE

    P.R. Bushel; Heinloth, A. N.; Li, J.; Huang, L.; Chou, J. W.; Boorman, G A; Malarkey, D.E.; Houle, C. D.; S. M. Ward; Wilson, R. E.; Fannin, R. D.; Russo, M W; Watkins, P B; Tennant, R. W.; Paules, R S

    2007-01-01

    To respond to potential adverse exposures properly, health care providers need accurate indicators of exposure levels. The indicators are particularly important in the case of acetaminophen (APAP) intoxication, the leading cause of liver failure in the U.S. We hypothesized that gene expression patterns derived from blood cells would provide useful indicators of acute exposure levels. To test this hypothesis, we used a blood gene expression data set from rats exposed to APAP to train classifie...

  19. Energy intake and adiponectin gene expression

    OpenAIRE

    Qiao, Liping; Lee, Bonggi; Kinney, Brice; Yoo, Hyung sun; Shao, Jianhua

    2011-01-01

    Hypoadiponectinemia and decreased adiponectin gene expression in white adipose tissue (WAT) have been well observed in obese subjects and animal models. However, the mechanism for obesity-associated hypoadiponectinemia is still largely unknown. To investigate the regulatory role of energy intake, dietary fat, and adiposity in adiponectin gene expression and blood adiponectin level, a series of feeding regimens was employed to manipulate energy intake and dietary fat in obese-prone C57BL/6, ge...

  20. Profiling of chicken adipose tissue gene expression by genome array

    Directory of Open Access Journals (Sweden)

    Wang Shou-Zhi

    2007-06-01

    Full Text Available Abstract Background Excessive accumulation of lipids in the adipose tissue is a major problem in the present-day broiler industry. However, few studies have analyzed the expression of adipose tissue genes that are involved in pathways and mechanisms leading to adiposity in chickens. Gene expression profiling of chicken adipose tissue could provide key information about the ontogenesis of fatness and clarify the molecular mechanisms underlying obesity. In this study, Chicken Genome Arrays were used to construct an adipose tissue gene expression profile of 7-week-old broilers, and to screen adipose tissue genes that are differentially expressed in lean and fat lines divergently selected over eight generations for high and low abdominal fat weight. Results The gene expression profiles detected 13,234–16,858 probe sets in chicken adipose tissue at 7 weeks, and genes involved in lipid metabolism and immunity such as fatty acid binding protein (FABP, thyroid hormone-responsive protein (Spot14, lipoprotein lipase(LPL, insulin-like growth factor binding protein 7(IGFBP7 and major histocompatibility complex (MHC, were highly expressed. In contrast, some genes related to lipogenesis, such as leptin receptor, sterol regulatory element binding proteins1 (SREBP1, apolipoprotein B(ApoB and insulin-like growth factor 2(IGF2, were not detected. Moreover, 230 genes that were differentially expressed between the two lines were screened out; these were mainly involved in lipid metabolism, signal transduction, energy metabolism, tumorigenesis and immunity. Subsequently, real-time RT-PCR was performed to validate fifteen differentially expressed genes screened out by the microarray approach and high consistency was observed between the two methods. Conclusion Our results establish the groundwork for further studies of the basic genetic control of growth and development of chicken adipose tissue, and will be beneficial in clarifying the molecular mechanism of

  1. Comparative gene expression between two yeast species

    Directory of Open Access Journals (Sweden)

    Guan Yuanfang

    2013-01-01

    Full Text Available Abstract Background Comparative genomics brings insight into sequence evolution, but even more may be learned by coupling sequence analyses with experimental tests of gene function and regulation. However, the reliability of such comparisons is often limited by biased sampling of expression conditions and incomplete knowledge of gene functions across species. To address these challenges, we previously systematically generated expression profiles in Saccharomyces bayanus to maximize functional coverage as compared to an existing Saccharomyces cerevisiae data repository. Results In this paper, we take advantage of these two data repositories to compare patterns of ortholog expression in a wide variety of conditions. First, we developed a scalable metric for expression divergence that enabled us to detect a significant correlation between sequence and expression conservation on the global level, which previous smaller-scale expression studies failed to detect. Despite this global conservation trend, between-species gene expression neighborhoods were less well-conserved than within-species comparisons across different environmental perturbations, and approximately 4% of orthologs exhibited a significant change in co-expression partners. Furthermore, our analysis of matched perturbations collected in both species (such as diauxic shift and cell cycle synchrony demonstrated that approximately a quarter of orthologs exhibit condition-specific expression pattern differences. Conclusions Taken together, these analyses provide a global view of gene expression patterns between two species, both in terms of the conditions and timing of a gene's expression as well as co-expression partners. Our results provide testable hypotheses that will direct future experiments to determine how these changes may be specified in the genome.

  2. PRAME gene expression profile in medulloblastoma

    Directory of Open Access Journals (Sweden)

    Tânia Maria Vulcani-Freitas

    2011-02-01

    Full Text Available Medulloblastoma is the most common malignant tumors of central nervous system in the childhood. The treatment is severe, harmful and, thus, has a dismal prognosis. As PRAME is present in various cancers, including meduloblastoma, and has limited expression in normal tissues, this antigen can be an ideal vaccine target for tumor immunotherapy. In order to find a potential molecular target, we investigated PRAME expression in medulloblastoma fragments and we compare the results with the clinical features of each patient. Analysis of gene expression was performed by real-time quantitative PCR from 37 tumor samples. The Mann-Whitney test was used to analysis the relationship between gene expression and clinical characteristics. Kaplan-Meier curves were used to evaluate survival. PRAME was overexpressed in 84% samples. But no statistical association was found between clinical features and PRAME overexpression. Despite that PRAME gene could be a strong candidate for immunotherapy since it is highly expressed in medulloblastomas.

  3. Bayesian biclustering of gene expression data

    Directory of Open Access Journals (Sweden)

    Liu Jun S

    2008-03-01

    Full Text Available Abstract Background Biclustering of gene expression data searches for local patterns of gene expression. A bicluster (or a two-way cluster is defined as a set of genes whose expression profiles are mutually similar within a subset of experimental conditions/samples. Although several biclustering algorithms have been studied, few are based on rigorous statistical models. Results We developed a Bayesian biclustering model (BBC, and implemented a Gibbs sampling procedure for its statistical inference. We showed that Bayesian biclustering model can correctly identify multiple clusters of gene expression data. Using simulated data both from the model and with realistic characters, we demonstrated the BBC algorithm outperforms other methods in both robustness and accuracy. We also showed that the model is stable for two normalization methods, the interquartile range normalization and the smallest quartile range normalization. Applying the BBC algorithm to the yeast expression data, we observed that majority of the biclusters we found are supported by significant biological evidences, such as enrichments of gene functions and transcription factor binding sites in the corresponding promoter sequences. Conclusions The BBC algorithm is shown to be a robust model-based biclustering method that can discover biologically significant gene-condition clusters in microarray data. The BBC model can easily handle missing data via Monte Carlo imputation and has the potential to be extended to integrated study of gene transcription networks.

  4. Inferring gene networks from discrete expression data

    KAUST Repository

    Zhang, L.

    2013-07-18

    The modeling of gene networks from transcriptional expression data is an important tool in biomedical research to reveal signaling pathways and to identify treatment targets. Current gene network modeling is primarily based on the use of Gaussian graphical models applied to continuous data, which give a closedformmarginal likelihood. In this paper,we extend network modeling to discrete data, specifically data from serial analysis of gene expression, and RNA-sequencing experiments, both of which generate counts of mRNAtranscripts in cell samples.We propose a generalized linear model to fit the discrete gene expression data and assume that the log ratios of the mean expression levels follow a Gaussian distribution.We restrict the gene network structures to decomposable graphs and derive the graphs by selecting the covariance matrix of the Gaussian distribution with the hyper-inverse Wishart priors. Furthermore, we incorporate prior network models based on gene ontology information, which avails existing biological information on the genes of interest. We conduct simulation studies to examine the performance of our discrete graphical model and apply the method to two real datasets for gene network inference. © The Author 2013. Published by Oxford University Press. All rights reserved.

  5. Translational control of gene expression and disease

    NARCIS (Netherlands)

    Calkhoven, Cornelis F; Müller, Christine; Leutz, Achim

    2002-01-01

    In the past decade, translational control has been shown to be crucial in the regulation of gene expression. Research in this field has progressed rapidly, revealing new control mechanisms and adding constantly to the list of translationally regulated genes. There is accumulating evidence that trans

  6. Familial aggregation analysis of gene expressions

    OpenAIRE

    Rao Shao-Qi; Xu Liang-De; Zhang Guang-Mei; Li Xia; Li Lin; Shen Gong-Qing; Jiang Yang; Yang Yue-Ying; Gong Bin-Sheng; Jiang Wei; Zhang Fan; Xiao Yun; Wang Qing K

    2007-01-01

    Abstract Traditional studies of familial aggregation are aimed at defining the genetic (and non-genetic) causes of a disease from physiological or clinical traits. However, there has been little attempt to use genome-wide gene expressions, the direct phenotypic measures of genes, as the traits to investigate several extended issues regarding the distributions of familially aggregated genes on chromosomes or in functions. In this study we conducted a genome-wide familial aggregation analysis b...

  7. Diagnostic Utility of Gene Expression Profiles

    OpenAIRE

    Xiong, Chengjie; Yan, Yan; Gao, Feng

    2013-01-01

    Two crucial problems arise from a microarray experiment in which the primary objective is to locate differentially expressed genes for the diagnosis of diseases such as cancer and Alzheimer’s. The first problem is the detection of a subset of genes which provides an optimum discriminatory power between diseased and normal subjects, and the second problem is the statistical estimation of discriminatory power from the optimum subset of genes between two groups of subjects. We develop a new meth...

  8. FARO server: Meta-analysis of gene expression by matching gene expression signatures to a compendium of public gene expression data

    OpenAIRE

    Nielsen Henrik B; Manijak Mieszko P

    2011-01-01

    Abstract Background Although, systematic analysis of gene annotation is a powerful tool for interpreting gene expression data, it sometimes is blurred by incomplete gene annotation, missing expression response of key genes and secondary gene expression responses. These shortcomings may be partially circumvented by instead matching gene expression signatures to signatures of other experiments. Findings To facilitate this we present the Functional Association Response by Overlap (FARO) server, ...

  9. Functional clustering of time series gene expression data by Granger causality

    Directory of Open Access Journals (Sweden)

    Fujita André

    2012-10-01

    Full Text Available Abstract Background A common approach for time series gene expression data analysis includes the clustering of genes with similar expression patterns throughout time. Clustered gene expression profiles point to the joint contribution of groups of genes to a particular cellular process. However, since genes belong to intricate networks, other features, besides comparable expression patterns, should provide additional information for the identification of functionally similar genes. Results In this study we perform gene clustering through the identification of Granger causality between and within sets of time series gene expression data. Granger causality is based on the idea that the cause of an event cannot come after its consequence. Conclusions This kind of analysis can be used as a complementary approach for functional clustering, wherein genes would be clustered not solely based on their expression similarity but on their topological proximity built according to the intensity of Granger causality among them.

  10. Network Security via Biometric Recognition of Patterns of Gene Expression

    Science.gov (United States)

    Shaw, Harry C.

    2016-01-01

    Molecular biology provides the ability to implement forms of information and network security completely outside the bounds of legacy security protocols and algorithms. This paper addresses an approach which instantiates the power of gene expression for security. Molecular biology provides a rich source of gene expression and regulation mechanisms, which can be adopted to use in the information and electronic communication domains. Conventional security protocols are becoming increasingly vulnerable due to more intensive, highly capable attacks on the underlying mathematics of cryptography. Security protocols are being undermined by social engineering and substandard implementations by IT (Information Technology) organizations. Molecular biology can provide countermeasures to these weak points with the current security approaches. Future advances in instruments for analyzing assays will also enable this protocol to advance from one of cryptographic algorithms to an integrated system of cryptographic algorithms and real-time assays of gene expression products.

  11. Clock gene expression during development

    Czech Academy of Sciences Publication Activity Database

    Sumová, Alena; Bendová, Zdeňka; Sládek, Martin; Kováčiková, Zuzana; El-Hennamy, Rehab; Laurinová, Kristýna; Illnerová, Helena

    2007-01-01

    Roč. 191, Suppl.658 (2007), s. 18-18. ISSN 1748-1708. [Joint meeting of The Slovak Physiological Society, The Physiological Society and The Federation of European Physiological Societies. 11.09.2007-14.09.2007, Bratislava] Institutional research plan: CEZ:AV0Z50110509 Keywords : cpr1 * clock genes * suprachiasmatic nucleus * rat Subject RIV: FB - Endocrinology, Diabetology, Metabolism, Nutrition

  12. Gene expression profiles in skeletal muscle after gene electrotransfer

    DEFF Research Database (Denmark)

    Hojman, Pernille; Zibert, John R; Gissel, Hanne;

    2007-01-01

    BACKGROUND: Gene transfer by electroporation (DNA electrotransfer) to muscle results in high level long term transgenic expression, showing great promise for treatment of e.g. protein deficiency syndromes. However little is known about the effects of DNA electrotransfer on muscle fibres. We have...... therefore investigated transcriptional changes through gene expression profile analyses, morphological changes by histological analysis, and physiological changes by force generation measurements. DNA electrotransfer was obtained using a combination of a short high voltage pulse (HV, 1000 V/cm, 100 mus......) followed by a long low voltage pulse (LV, 100 V/cm, 400 ms); a pulse combination optimised for efficient and safe gene transfer. Muscles were transfected with green fluorescent protein (GFP) and excised at 4 hours, 48 hours or 3 weeks after treatment. RESULTS: Differentially expressed genes were...

  13. Gene expression profiling: can we identify the right target genes?

    Directory of Open Access Journals (Sweden)

    J. E. Loyd

    2008-12-01

    Full Text Available Gene expression profiling allows the simultaneous monitoring of the transcriptional behaviour of thousands of genes, which may potentially be involved in disease development. Several studies have been performed in idiopathic pulmonary fibrosis (IPF, which aim to define genetic links to the disease in an attempt to improve the current understanding of the underlying pathogenesis of the disease and target pathways for intervention. Expression profiling has shown a clear difference in gene expression between IPF and normal lung tissue, and has identified a wide range of candidate genes, including those known to encode for proteins involved in extracellular matrix formation and degradation, growth factors and chemokines. Recently, familial pulmonary fibrosis cohorts have been examined in an attempt to detect specific genetic mutations associated with IPF. To date, these studies have identified families in which IPF is associated with mutations in the gene encoding surfactant protein C, or with mutations in genes encoding components of telomerase. Although rare and clearly not responsible for the disease in all individuals, the nature of these mutations highlight the importance of the alveolar epithelium in disease pathogenesis and demonstrate the potential for gene expression profiling in helping to advance the current understanding of idiopathic pulmonary fibrosis.

  14. Regulation of immunoglobulin gene rearrangement and expression.

    Science.gov (United States)

    Taussig, M J; Sims, M J; Krawinkel, U

    1989-05-01

    The molecular genetic events leading to Ig expression and their control formed the topic of a recent EMBO workshop. This report by Michael Taussig, Martin Sims and Ulrich Krawinkel discusses contributions dealing with genes expressed in early pre-B cells, the mechanism of rearrangement, aberrant rearrangements seen in B cells of SCID mice, the feedback control of rearrangement as studied in transgenic mice, the control of Ig expression at the transcriptional and post-transcriptional levels, and class switching. PMID:2787158

  15. Gene Expression Profiling in the Hibernating Primate, Cheirogaleus Medius

    Science.gov (United States)

    Faherty, Sheena L.; Villanueva-Cañas, José Luis; Klopfer, Peter H.; Albà, M. Mar; Yoder, Anne D.

    2016-01-01

    Hibernation is a complex physiological response that some mammalian species employ to evade energetic demands. Previous work in mammalian hibernators suggests that hibernation is activated not by a set of genes unique to hibernators, but by differential expression of genes that are present in all mammals. This question of universal genetic mechanisms requires further investigation and can only be tested through additional investigations of phylogenetically dispersed species. To explore this question, we use RNA-Seq to investigate gene expression dynamics as they relate to the varying physiological states experienced throughout the year in a group of primate hibernators—Madagascar’s dwarf lemurs (genus Cheirogaleus). In a novel experimental approach, we use longitudinal sampling of biological tissues as a method for capturing gene expression profiles from the same individuals throughout their annual hibernation cycle. We identify 90 candidate genes that have variable expression patterns when comparing two active states (Active 1 and Active 2) with a torpor state. These include genes that are involved in metabolic pathways, feeding behavior, and circadian rhythms, as might be expected to correlate with seasonal physiological state changes. The identified genes appear to be critical for maintaining the health of an animal that undergoes prolonged periods of metabolic depression concurrent with the hibernation phenotype. By focusing on these differentially expressed genes in dwarf lemurs, we compare gene expression patterns in previously studied mammalian hibernators. Additionally, by employing evolutionary rate analysis, we find that hibernation-related genes do not evolve under positive selection in hibernating species relative to nonhibernators. PMID:27412611

  16. Gene expressions changes in bronchial epithelial cells

    DEFF Research Database (Denmark)

    Remy, S.; Verstraelen, S.; Van Den Heuvel, R.;

    2014-01-01

    cells were exposed during 6, 10, and 24 h to 4 respiratory sensitizers and 6 non-respiratory sensitizers (3 skin sensitizers and 3 respiratory irritants) at a concentration inducing 20% cell viability loss after 24 h. Changes in gene expression were evaluated using Agilent Whole Human Genome 4 x 44 K...... differentially expressed compared to vehicle control for each chemical. The results show that the NRF2-mediated oxidative stress response is activated in the cell line after stimulation with all of the chemicals that were selected in our study, and that - at the level of gene expression - this pathway shows no...

  17. Introduction to the Gene Expression Analysis.

    Science.gov (United States)

    Segundo-Val, Ignacio San; Sanz-Lozano, Catalina S

    2016-01-01

    In 1941, Beadle and Tatum published experiments that would explain the basis of the central dogma of molecular biology, whereby the DNA through an intermediate molecule, called RNA, results proteins that perform the functions in cells. Currently, biomedical research attempts to explain the mechanisms by which develops a particular disease, for this reason, gene expression studies have proven to be a great resource. Strictly, the term "gene expression" comprises from the gene activation until the mature protein is located in its corresponding compartment to perform its function and contribute to the expression of the phenotype of cell.The expression studies are directed to detect and quantify messenger RNA (mRNA) levels of a specific gene. The development of the RNA-based gene expression studies began with the Northern Blot by Alwine et al. in 1977. In 1969, Gall and Pardue and John et al. independently developed the in situ hybridization, but this technique was not employed to detect mRNA until 1986 by Coghlan. Today, many of the techniques for quantification of RNA are deprecated because other new techniques provide more information. Currently the most widely used techniques are qPCR, expression microarrays, and RNAseq for the transcriptome analysis. In this chapter, these techniques will be reviewed. PMID:27300529

  18. Biclustering Methods: Biological Relevance and Application in Gene Expression Analysis

    OpenAIRE

    Ali Oghabian; Sami Kilpinen; Sampsa Hautaniemi; Elena Czeizler

    2014-01-01

    DNA microarray technologies are used extensively to profile the expression levels of thousands of genes under various conditions, yielding extremely large data-matrices. Thus, analyzing this information and extracting biologically relevant knowledge becomes a considerable challenge. A classical approach for tackling this challenge is to use clustering (also known as one-way clustering) methods where genes (or respectively samples) are grouped together based on the similarity of their expressi...

  19. Regulation of gene expression in human tendinopathy

    Directory of Open Access Journals (Sweden)

    Archambault Joanne M

    2011-05-01

    Full Text Available Abstract Background Chronic tendon injuries, also known as tendinopathies, are common among professional and recreational athletes. These injuries result in a significant amount of morbidity and health care expenditure, yet little is known about the molecular mechanisms leading to tendinopathy. Methods We have used histological evaluation and molecular profiling to determine gene expression changes in 23 human patients undergoing surgical procedures for the treatment of chronic tendinopathy. Results Diseased tendons exhibit altered extracellular matrix, fiber disorientation, increased cellular content and vasculature, and the absence of inflammatory cells. Global gene expression profiling identified 983 transcripts with significantly different expression patterns in the diseased tendons. Global pathway analysis further suggested altered expression of extracellular matrix proteins and the lack of an appreciable inflammatory response. Conclusions Identification of the pathways and genes that are differentially regulated in tendinopathy samples will contribute to our understanding of the disease and the development of novel therapeutics.

  20. Radiation-modulated gene expression in C. elegans

    International Nuclear Information System (INIS)

    Full text: We use the nematode C. elegans to characterize the genotoxic and cytotoxic effects of ionizing radiation with emphasis effects of charged particle radiation and have described the fluence vs. response relationships for mutation, chromosome aberration and certain developmental errors. These endpoints quantify the biological after repair and compensation pathways have completed their work. In order to address the control of these reactions we have turned to gene expression profiling to identify genes that uniquely respond to high LET species or respond differentially as a function of radiation properties. We have employed whole genome microarray methods to map gene expression following exposure to gamma rays, protons and accelerated iron ions. We found that 599 of 17871 genes analyzed showed differential expression 3 hrs after exposure to 3 Gy of at least one radiation types. 193 were up-regulated, 406 were down-regulated, and 90% were affected by only one species of radiation. Genes whose transcription levels responded significantly mapped to definite statistical clusters that were unique for each radiation type. We are now trying to establish the functional relationships of the genes their relevance to mitigation of radiation-induced damage. Three approaches are being used. First, bioinformatics tools are being used to determine the roles of genes in co-regulated gene sets. Second, we are applying the technique of RNA interference to determine whether our radiation-induced genes affect cell survival (measured in terms of embryo survival) and chromosome aberration (intestinal anaphase bridges). Finally we are focussing on the response of the most strongly-regulated gene in our data set. This is the autosomal gene, F36D3.9, whose predicted structure is that of a cysteine protease resembling cathepsin B. An enzymological approach is being used to characterize this gene at the protein level. This work was supported by NASA Cooperative Agreement NCC9-149

  1. Biclustering methods: biological relevance and application in gene expression analysis.

    Science.gov (United States)

    Oghabian, Ali; Kilpinen, Sami; Hautaniemi, Sampsa; Czeizler, Elena

    2014-01-01

    DNA microarray technologies are used extensively to profile the expression levels of thousands of genes under various conditions, yielding extremely large data-matrices. Thus, analyzing this information and extracting biologically relevant knowledge becomes a considerable challenge. A classical approach for tackling this challenge is to use clustering (also known as one-way clustering) methods where genes (or respectively samples) are grouped together based on the similarity of their expression profiles across the set of all samples (or respectively genes). An alternative approach is to develop biclustering methods to identify local patterns in the data. These methods extract subgroups of genes that are co-expressed across only a subset of samples and may feature important biological or medical implications. In this study we evaluate 13 biclustering and 2 clustering (k-means and hierarchical) methods. We use several approaches to compare their performance on two real gene expression data sets. For this purpose we apply four evaluation measures in our analysis: (1) we examine how well the considered (bi)clustering methods differentiate various sample types; (2) we evaluate how well the groups of genes discovered by the (bi)clustering methods are annotated with similar Gene Ontology categories; (3) we evaluate the capability of the methods to differentiate genes that are known to be specific to the particular sample types we study and (4) we compare the running time of the algorithms. In the end, we conclude that as long as the samples are well defined and annotated, the contamination of the samples is limited, and the samples are well replicated, biclustering methods such as Plaid and SAMBA are useful for discovering relevant subsets of genes and samples. PMID:24651574

  2. Biclustering methods: biological relevance and application in gene expression analysis.

    Directory of Open Access Journals (Sweden)

    Ali Oghabian

    Full Text Available DNA microarray technologies are used extensively to profile the expression levels of thousands of genes under various conditions, yielding extremely large data-matrices. Thus, analyzing this information and extracting biologically relevant knowledge becomes a considerable challenge. A classical approach for tackling this challenge is to use clustering (also known as one-way clustering methods where genes (or respectively samples are grouped together based on the similarity of their expression profiles across the set of all samples (or respectively genes. An alternative approach is to develop biclustering methods to identify local patterns in the data. These methods extract subgroups of genes that are co-expressed across only a subset of samples and may feature important biological or medical implications. In this study we evaluate 13 biclustering and 2 clustering (k-means and hierarchical methods. We use several approaches to compare their performance on two real gene expression data sets. For this purpose we apply four evaluation measures in our analysis: (1 we examine how well the considered (biclustering methods differentiate various sample types; (2 we evaluate how well the groups of genes discovered by the (biclustering methods are annotated with similar Gene Ontology categories; (3 we evaluate the capability of the methods to differentiate genes that are known to be specific to the particular sample types we study and (4 we compare the running time of the algorithms. In the end, we conclude that as long as the samples are well defined and annotated, the contamination of the samples is limited, and the samples are well replicated, biclustering methods such as Plaid and SAMBA are useful for discovering relevant subsets of genes and samples.

  3. Noise minimization in eukaryotic gene expression

    Energy Technology Data Exchange (ETDEWEB)

    Fraser, Hunter B.; Hirsh, Aaron E.; Giaever, Guri; Kumm, Jochen; Eisen, Michael B.

    2004-01-15

    All organisms have elaborate mechanisms to control rates of protein production. However, protein production is also subject to stochastic fluctuations, or noise. Several recent studies in Saccharomyces cerevisiae and Escherichia coli have investigated the relationship between transcription and translation rates and stochastic fluctuations in protein levels, or more generally, how such randomness is a function of intrinsic and extrinsic factors. However, the fundamental question of whether stochasticity in protein expression is generally biologically relevant has not been addressed, and it remains unknown whether random noise in the protein production rate of most genes significantly affects the fitness of any organism. We propose that organisms should be particularly sensitive to variation in the protein levels of two classes of genes: genes whose deletion is lethal to the organism and genes that encode subunits of multiprotein complexes. Using an experimentally verified model of stochastic gene expression in S. cerevisiae, we estimate the noise in protein production for nearly every yeast gene, and confirm our prediction that the production of essential and complex-forming proteins involves lower levels of noise than does the production of most other genes. Our results support the hypothesis that noise in gene expression is a biologically important variable, is generally detrimental to organismal fitness, and is subject to natural selection.

  4. Whole-body gene expression pattern registration in Platynereis larvae

    Directory of Open Access Journals (Sweden)

    Asadulina Albina

    2012-12-01

    Full Text Available Abstract Background Digital anatomical atlases are increasingly used in order to depict different gene expression patterns and neuronal morphologies within a standardized reference template. In evo-devo, a discipline in which the comparison of gene expression patterns is a widely used approach, such standardized anatomical atlases would allow a more rigorous assessment of the conservation of and changes in gene expression patterns during micro- and macroevolutionary time scales. Due to its small size and invariant early development, the annelid Platynereis dumerilii is particularly well suited for such studies. Recently a reference template with registered gene expression patterns has been generated for the anterior part (episphere of the Platynereis trochophore larva and used for the detailed study of neuronal development. Results Here we introduce and evaluate a method for whole-body gene expression pattern registration for Platynereis trochophore and nectochaete larvae based on whole-mount in situ hybridization, confocal microscopy, and image registration. We achieved high-resolution whole-body scanning using the mounting medium 2,2’-thiodiethanol (TDE, which allows the matching of the refractive index of the sample to that of glass and immersion oil thereby reducing spherical aberration and improving depth penetration. This approach allowed us to scan entire whole-mount larvae stained with nitroblue tetrazolium/5-bromo-4-chloro-3-indolyl phosphate (NBT/BCIP in situ hybridization and counterstained fluorescently with an acetylated-tubulin antibody and the nuclear stain 4’6-diamidino-2-phenylindole (DAPI. Due to the submicron isotropic voxel size whole-mount larvae could be scanned in any orientation. Based on the whole-body scans, we generated four different reference templates by the iterative registration and averaging of 40 individual image stacks using either the acetylated-tubulin or the nuclear-stain signal for each developmental

  5. VESPUCCI: exploring patterns of gene expression in grapevine

    Directory of Open Access Journals (Sweden)

    Marco eMoretto

    2016-05-01

    Full Text Available Large-scale transcriptional studies aim to decipher the dynamic cellular responses to a stimulus, like different environmental conditions. In the era of high-throughput omics biology, the most used technologies for these purposes are microarray and RNA-Seq, whose data are usually required to be deposited in public repositories upon publication. Such repositories have the enormous potential to provide a comprehensive view of how different experimental conditions lead to expression changes, by comparing gene expression across all possible measured conditions. Unfortunately, this task is greatly impaired by differences among experimental platforms that make direct comparisons difficult.In this paper we present the Vitis Expression Studies Platform Using COLOMBOS Compendia Instances (VESPUCCI, a gene expression compendium for grapevine which was built by adapting an approach originally developed for bacteria, and show how it can be used to investigate complex gene expression patterns. We integrated nearly all publicly available microarray and RNA-Seq expression data: 1608 gene expression samples from 10 different technological platforms. Each sample has been manually annotated using a controlled vocabulary developed ad hoc to ensure both human readability and computational tractability. Expression data in the compendium can be visually explored using several tools provided by the web interface or can be programmatically accessed using the REST interface. VESPUCCI is freely accessible at http://vespucci.colombos.fmach.it.

  6. VESPUCCI: Exploring Patterns of Gene Expression in Grapevine

    Science.gov (United States)

    Moretto, Marco; Sonego, Paolo; Pilati, Stefania; Malacarne, Giulia; Costantini, Laura; Grzeskowiak, Lukasz; Bagagli, Giorgia; Grando, Maria Stella; Moser, Claudio; Engelen, Kristof

    2016-01-01

    Large-scale transcriptional studies aim to decipher the dynamic cellular responses to a stimulus, like different environmental conditions. In the era of high-throughput omics biology, the most used technologies for these purposes are microarray and RNA-Seq, whose data are usually required to be deposited in public repositories upon publication. Such repositories have the enormous potential to provide a comprehensive view of how different experimental conditions lead to expression changes, by comparing gene expression across all possible measured conditions. Unfortunately, this task is greatly impaired by differences among experimental platforms that make direct comparisons difficult. In this paper, we present the Vitis Expression Studies Platform Using COLOMBOS Compendia Instances (VESPUCCI), a gene expression compendium for grapevine which was built by adapting an approach originally developed for bacteria, and show how it can be used to investigate complex gene expression patterns. We integrated nearly all publicly available microarray and RNA-Seq expression data: 1608 gene expression samples from 10 different technological platforms. Each sample has been manually annotated using a controlled vocabulary developed ad hoc to ensure both human readability and computational tractability. Expression data in the compendium can be visually explored using several tools provided by the web interface or can be programmatically accessed using the REST interface. VESPUCCI is freely accessible at http://vespucci.colombos.fmach.it.

  7. Comparison of gene expression methods to identify genes responsive to perfluorooctane sulfonic acid.

    Science.gov (United States)

    Hu, Wenyue; Jones, Paul D; Decoen, Wim; Newsted, John L; Giesy, John P

    2005-01-01

    Genome-wide expression techniques are being increasingly used to assess the effects of environmental contaminants. Oligonucleotide or cDNA microarray methods make possible the screening of large numbers of known sequences for a given model species, while differential display analysis makes possible analysis of the expression of all the genes from any species. We report a comparison of two currently popular methods for genome-wide expression analysis in rat hepatoma cells treated with perfluorooctane sulfonic acid. The two analyses provided 'complimentary' information. Approximately 5% of the 8000 genes analyzed by the GeneChip array, were altered by a factor of three or greater. Differential display results were more difficult to interpret, since multiple gene products were present in most gel bands so a probabilistic approach was used to determine which pathways were affected. The mechanistic interpretation derived from these two methods was in agreement, both showing similar alterations in a specific set of genes. PMID:21783471

  8. Gene expression following acute morphine administration.

    Science.gov (United States)

    Loguinov, A V; Anderson, L M; Crosby, G J; Yukhananov, R Y

    2001-08-28

    The long-term response to neurotropic drugs depends on drug-induced neuroplasticity and underlying changes in gene expression. However, alterations in neuronal gene expression can be observed even following single injection. To investigate the extent of these changes, gene expression in the medial striatum and lumbar part of the spinal cord was monitored by cDNA microarray following single injection of morphine. Using robust and resistant linear regression (MM-estimator) with simultaneous prediction confidence intervals, we detected differentially expressed genes. By combining the results with cluster analysis, we have found that a single morphine injection alters expression of two major groups of genes, for proteins involved in mitochondrial respiration and for cytoskeleton-related proteins. RNAs for these proteins were mostly downregulated both in the medial striatum and in lumbar part of the spinal cord. These transitory changes were prevented by coadministration of the opioid antagonist naloxone. Data indicate that microarray analysis by itself is useful in describing the effect of well-known substances on the nervous system and provides sufficient information to propose a potentially novel pathway mediating its activity. PMID:11526201

  9. Geometry of the Gene Expression Space of Individual Cells.

    Directory of Open Access Journals (Sweden)

    Yael Korem

    2015-07-01

    Full Text Available There is a revolution in the ability to analyze gene expression of single cells in a tissue. To understand this data we must comprehend how cells are distributed in a high-dimensional gene expression space. One open question is whether cell types form discrete clusters or whether gene expression forms a continuum of states. If such a continuum exists, what is its geometry? Recent theory on evolutionary trade-offs suggests that cells that need to perform multiple tasks are arranged in a polygon or polyhedron (line, triangle, tetrahedron and so on, generally called polytopes in gene expression space, whose vertices are the expression profiles optimal for each task. Here, we analyze single-cell data from human and mouse tissues profiled using a variety of single-cell technologies. We fit the data to shapes with different numbers of vertices, compute their statistical significance, and infer their tasks. We find cases in which single cells fill out a continuum of expression states within a polyhedron. This occurs in intestinal progenitor cells, which fill out a tetrahedron in gene expression space. The four vertices of this tetrahedron are each enriched with genes for a specific task related to stemness and early differentiation. A polyhedral continuum of states is also found in spleen dendritic cells, known to perform multiple immune tasks: cells fill out a tetrahedron whose vertices correspond to key tasks related to maturation, pathogen sensing and communication with lymphocytes. A mixture of continuum-like distributions and discrete clusters is found in other cell types, including bone marrow and differentiated intestinal crypt cells. This approach can be used to understand the geometry and biological tasks of a wide range of single-cell datasets. The present results suggest that the concept of cell type may be expanded. In addition to discreet clusters in gene-expression space, we suggest a new possibility: a continuum of states within a

  10. Alternative-splicing-mediated gene expression

    Science.gov (United States)

    Wang, Qianliang; Zhou, Tianshou

    2014-01-01

    Alternative splicing (AS) is a fundamental process during gene expression and has been found to be ubiquitous in eukaryotes. However, how AS impacts gene expression levels both quantitatively and qualitatively remains to be fully explored. Here, we analyze two common models of gene expression, each incorporating a simple splice mechanism that a pre-mRNA is spliced into two mature mRNA isoforms in a probabilistic manner. In the constitutive expression case, we show that the steady-state molecular numbers of two mature mRNA isoforms follow mutually independent Poisson distributions. In the bursting expression case, we demonstrate that the tail decay of the steady-state distribution for both mature mRNA isoforms that in general are not mutually independent can be characterized by the product of mean burst size and splicing probability. In both cases, we find that AS can efficiently modulate both the variability (measured by variance) and the noise level of the total mature mRNA, and in particular, the latter is always lower than the noise level of the pre-mRNA, implying that AS always reduces the noise. These results altogether reveal that AS is a mechanism of efficiently controlling the gene expression noise.

  11. Gene expression analysis of flax seed development

    Directory of Open Access Journals (Sweden)

    Sharpe Andrew

    2011-04-01

    Full Text Available Abstract Background Flax, Linum usitatissimum L., is an important crop whose seed oil and stem fiber have multiple industrial applications. Flax seeds are also well-known for their nutritional attributes, viz., omega-3 fatty acids in the oil and lignans and mucilage from the seed coat. In spite of the importance of this crop, there are few molecular resources that can be utilized toward improving seed traits. Here, we describe flax embryo and seed development and generation of comprehensive genomic resources for the flax seed. Results We describe a large-scale generation and analysis of expressed sequences in various tissues. Collectively, the 13 libraries we have used provide a broad representation of genes active in developing embryos (globular, heart, torpedo, cotyledon and mature stages seed coats (globular and torpedo stages and endosperm (pooled globular to torpedo stages and genes expressed in flowers, etiolated seedlings, leaves, and stem tissue. A total of 261,272 expressed sequence tags (EST (GenBank accessions LIBEST_026995 to LIBEST_027011 were generated. These EST libraries included transcription factor genes that are typically expressed at low levels, indicating that the depth is adequate for in silico expression analysis. Assembly of the ESTs resulted in 30,640 unigenes and 82% of these could be identified on the basis of homology to known and hypothetical genes from other plants. When compared with fully sequenced plant genomes, the flax unigenes resembled poplar and castor bean more than grape, sorghum, rice or Arabidopsis. Nearly one-fifth of these (5,152 had no homologs in sequences reported for any organism, suggesting that this category represents genes that are likely unique to flax. Digital analyses revealed gene expression dynamics for the biosynthesis of a number of important seed constituents during seed development. Conclusions We have developed a foundational database of expressed sequences and collection of plasmid

  12. Parsimonious selection of useful genes in microarray gene expression data

    OpenAIRE

    González Navarro, Félix Fernando; Belanche Muñoz, Luis Antonio

    2011-01-01

    Machine Learning methods have of late made significant efforts to solving multidisciplinary problems in the field of cancer classification in microarray gene expression data. These tasks are characterized by a large number of features and a few observations, making the modeling a non-trivial undertaking. In this work we apply entropic filter methods for gene selection, in combination with several off-the-shelf classifiers. The introduction of bootstrap resampling techniques permits the achiev...

  13. BioGPS and GXD: mouse gene expression data - the benefits and challenges of data integration

    OpenAIRE

    Ringwald, Martin; Wu, Chunlei; Su, Andrew I.

    2012-01-01

    Mouse gene expression data are complex and voluminous. To maximize the utility of these data, they must be made readily accessible through databases, and those resources need to place the expression data in the larger biological context. Here we describe two community resources that approach these problems in different but complementary ways: BioGPS and the Mouse Gene Expression Database (GXD). BioGPS connects its large and homogenous microarray gene expression reference data sets via plugins...

  14. Sequencing and Gene Expression Analysis of Leishmania tropica LACK Gene.

    Directory of Open Access Journals (Sweden)

    Nour Hammoudeh

    2014-12-01

    Full Text Available Leishmania Homologue of receptors for Activated C Kinase (LACK antigen is a 36-kDa protein, which provokes a very early immune response against Leishmania infection. There are several reports on the expression of LACK through different life-cycle stages of genus Leishmania, but only a few of them have focused on L.tropica.The present study provides details of the cloning, DNA sequencing and gene expression of LACK in this parasite species. First, several local isolates of Leishmania parasites were typed in our laboratory using PCR technique to verify of Leishmania parasite species. After that, LACK gene was amplified and cloned into a vector for sequencing. Finally, the expression of this molecule in logarithmic and stationary growth phase promastigotes, as well as in amastigotes, was evaluated by Reverse Transcription-PCR (RT-PCR technique.The typing result confirmed that all our local isolates belong to L.tropica. LACK gene sequence was determined and high similarity was observed with the sequences of other Leishmania species. Furthermore, the expression of LACK gene in both promastigotes and amastigotes forms was confirmed.Overall, the data set the stage for future studies of the properties and immune role of LACK gene products.

  15. Extracting expression modules from perturbational gene expression compendia

    Directory of Open Access Journals (Sweden)

    Van Dijck Patrick

    2008-04-01

    Full Text Available Abstract Background Compendia of gene expression profiles under chemical and genetic perturbations constitute an invaluable resource from a systems biology perspective. However, the perturbational nature of such data imposes specific challenges on the computational methods used to analyze them. In particular, traditional clustering algorithms have difficulties in handling one of the prominent features of perturbational compendia, namely partial coexpression relationships between genes. Biclustering methods on the other hand are specifically designed to capture such partial coexpression patterns, but they show a variety of other drawbacks. For instance, some biclustering methods are less suited to identify overlapping biclusters, while others generate highly redundant biclusters. Also, none of the existing biclustering tools takes advantage of the staple of perturbational expression data analysis: the identification of differentially expressed genes. Results We introduce a novel method, called ENIGMA, that addresses some of these issues. ENIGMA leverages differential expression analysis results to extract expression modules from perturbational gene expression data. The core parameters of the ENIGMA clustering procedure are automatically optimized to reduce the redundancy between modules. In contrast to the biclusters produced by most other methods, ENIGMA modules may show internal substructure, i.e. subsets of genes with distinct but significantly related expression patterns. The grouping of these (often functionally related patterns in one module greatly aids in the biological interpretation of the data. We show that ENIGMA outperforms other methods on artificial datasets, using a quality criterion that, unlike other criteria, can be used for algorithms that generate overlapping clusters and that can be modified to take redundancy between clusters into account. Finally, we apply ENIGMA to the Rosetta compendium of expression profiles for

  16. Gene expression profiling in sinonasal adenocarcinoma.

    OpenAIRE

    Sébille-Rivain Véronique; Malard Olivier; Guisle-Marsollier Isabelle; Ferron Christophe; Renaudin Karine; Quéméner Sylvia; Tripodi Dominique; Verger Christian; Géraut Christian; Gratas-Rabbia-Ré Catherine

    2009-01-01

    Abstract Background Sinonasal adenocarcinomas are uncommon tumors which develop in the ethmoid sinus after exposure to wood dust. Although the etiology of these tumors is well defined, very little is known about their molecular basis and no diagnostic tool exists for their early detection in high-risk workers. Methods To identify genes involved in this disease, we performed gene expression profiling using cancer-dedicated microarrays, on nine matched samples of sinonasal adenocarcinomas and n...

  17. Sp1 regulates human huntingtin gene expression.

    Science.gov (United States)

    Wang, Ruitao; Luo, Yawen; Ly, Philip T T; Cai, Fang; Zhou, Weihui; Zou, Haiyan; Song, Weihong

    2012-06-01

    Huntington's disease (HD) is a hereditary neurodegenerative disorder resulting from the expansion of a polyglutamine tract in the huntingtin protein. The expansion of cytosine-adenine-guanine repeats results in neuronal loss in the striatum and cortex. Mutant huntingtin (HTT) may cause toxicity via a range of different mechanisms. Recent studies indicate that impairment of wild-type HTT function may also contribute to HD pathogenesis. However, the mechanisms regulating HTT expression have not been well defined. In this study, we cloned 1,795 bp of the 5' flanking region of the human huntingtin gene (htt) and identified a 106-bp fragment containing the transcription start site as the minimal region necessary for promoter activity. Sequence analysis reveals several putative regulatory elements including Sp1, NF-κB, HIF, CREB, NRSF, P53, YY1, AP1, and STAT in the huntingtin promoter. We found functional Sp1 response elements in the huntingtin promoter region. The expression of Sp1 enhanced huntingtin gene transcription and the inhibition of Sp1-mediated transcriptional activation reduced huntingtin gene expression. These results suggest that Sp1 plays an important role in the regulation of the human huntingtin gene expression at the mRNA and protein levels. Our study suggests that the dysregulation of Sp1-mediated huntingtin transcription, combining with mutant huntingtin's detrimental effect on other Sp1-mediated downstream gene function, may contribute to the pathogenesis of HD. PMID:22399227

  18. Differential expression of cell adhesion genes

    DEFF Research Database (Denmark)

    Stein, Wilfred D; Litman, Thomas; Fojo, Tito;

    2005-01-01

    It is well known that tumors arising from tissues such as kidney, pancreas, liver and stomach are particularly refractory to treatment. Searching for new anticancer drugs using cells in culture has yielded some effective therapies, but these refractory tumors remain intractable. Studies that...... survival might, therefore, act through such a matrix-to-cell suppression of apoptosis. Indeed, correlative mining of gene expression and patient survival databases suggests that poor survival in patients with metastatic cancer correlates highly with tumor expression of a common theme: the genes involved in...

  19. Epigenetic control of antioxidant gene expression

    OpenAIRE

    Wild, Brigitte

    2015-01-01

    Tesis doctoral inédita leída en la Universidad Autónoma de Madrid, Facultad de Ciencias, Departamento de Biología Molecular. Fecha de lectura: 29-10-2015 To respond to exogenous and endogenous stimuli, organisms have developed a variety of mechanisms to modulate the quantity, duration and the type of response to these stimuli. Of these mechanisms, one of the most important is the regulation of gene expression. This regulation of gene expression occurs at various levels but especially by th...

  20. Argudas: arguing with gene expression information

    CERN Document Server

    McLeod, Kenneth; Burger, Albert

    2010-01-01

    In situ hybridisation gene expression information helps biologists identify where a gene is expressed. However, the databases that republish the experimental information are often both incomplete and inconsistent. This paper examines a system, Argudas, designed to help tackle these issues. Argudas is an evolution of an existing system, and so that system is reviewed as a means of both explaining and justifying the behaviour of Argudas. Throughout the discussion of Argudas a number of issues will be raised including the appropriateness of argumentation in biology and the challenges faced when integrating apparently similar online biological databases.

  1. Applications of queueing theory to stochastic models of gene expression

    Science.gov (United States)

    Kulkarni, Rahul

    2012-02-01

    The intrinsic stochasticity of cellular processes implies that analysis of fluctuations (`noise') is often essential for quantitative modeling of gene expression. Recent single-cell experiments have carried out such analysis to characterize moments and entire probability distributions for quantities of interest, e.g. mRNA and protein levels across a population of cells. Correspondingly, there is a need to develop general analytical tools for modeling and interpretation of data obtained from such single-cell experiments. One such approach involves the mapping between models of stochastic gene expression and systems analyzed in queueing theory. The talk will provide an overview of this approach and discuss how theorems from queueing theory (e.g. Little's Law) can be used to derive exact results for general stochastic models of gene expression. In the limit that gene expression occurs in bursts, analytical results can be obtained which provide insight into the effects of different regulatory mechanisms on the noise in protein steady-state distributions. In particular, the approach can be used to analyze the effect of post-transcriptional regulation by non-coding RNAs leading to new insights and experimentally testable predictions.

  2. Visualizing Gene Expression In Situ

    Energy Technology Data Exchange (ETDEWEB)

    Burlage, R.S.

    1998-11-02

    Visualizing bacterial cells and describing their responses to the environment are difficult tasks. Their small size is the chief reason for the difficulty, which means that we must often use many millions of cells in a sample in order to determine what the average response of the bacteria is. However, an average response can sometimes mask important events in bacterial physiology, which means that our understanding of these organisms will suffer. We have used a variety of instruments to visualize bacterial cells, all of which tell us something different about the sample. We use a fluorescence activated cell sorter to sort cells based on the fluorescence provided by bioreporter genes, and these can be used to select for particular genetic mutations. Cells can be visualized by epifluorescent microscopy, and sensitive photodetectors can be added that allow us to find a single bacterial cell that is fluorescent or bioluminescent. We have also used standard photomultipliers to examine cell aggregates as field bioreporter microorganisms. Examples of each of these instruments show how our understanding of bacterial physiology has changed with the technology.

  3. Validation of commonly used reference genes for sleep-related gene expression studies

    Directory of Open Access Journals (Sweden)

    Castro Rosa MRPS

    2009-05-01

    Full Text Available Abstract Background Sleep is a restorative process and is essential for maintenance of mental and physical health. In an attempt to understand the complexity of sleep, multidisciplinary strategies, including genetic approaches, have been applied to sleep research. Although quantitative real time PCR has been used in previous sleep-related gene expression studies, proper validation of reference genes is currently lacking. Thus, we examined the effect of total or paradoxical sleep deprivation (TSD or PSD on the expression stability of the following frequently used reference genes in brain and blood: beta-actin (b-actin, beta-2-microglobulin (B2M, glyceraldehyde-3-phosphate dehydrogenase (GAPDH, and hypoxanthine guanine phosphoribosyl transferase (HPRT. Results Neither TSD nor PSD affected the expression stability of all tested genes in both tissues indicating that b-actin, B2M, GAPDH and HPRT are appropriate reference genes for the sleep-related gene expression studies. In order to further verify these results, the relative expression of brain derived neurotrophic factor (BDNF and glycerol-3-phosphate dehydrogenase1 (GPD1 was evaluated in brain and blood, respectively. The normalization with each of four reference genes produced similar pattern of expression in control and sleep deprived rats, but subtle differences in the magnitude of expression fold change were observed which might affect the statistical significance. Conclusion This study demonstrated that sleep deprivation does not alter the expression stability of commonly used reference genes in brain and blood. Nonetheless, the use of multiple reference genes in quantitative RT-PCR is required for the accurate results.

  4. Development of Gene Expression Signatures for Practical Radiation Biodosimetry

    International Nuclear Information System (INIS)

    Purpose: In a large-scale radiologic emergency, estimates of exposure doses and radiation injury would be required for individuals without physical dosimeters. Current methods are inadequate for the task, so we are developing gene expression profiles for radiation biodosimetry. This approach could provide both an estimate of physical radiation dose and an indication of the extent of individual injury or future risk. Methods and Materials: We used whole genome microarray expression profiling as a discovery platform to identify genes with the potential to predict radiation dose across an exposure range relevant for medical decision making in a radiologic emergency. Human peripheral blood from 10 healthy donors was irradiated ex vivo, and global gene expression was measured both 6 and 24 h after exposure. Results: A 74-gene signature was identified that distinguishes between four radiation doses (0.5, 2, 5, and 8 Gy) and controls. More than one third of these genes are regulated by TP53. A nearest centroid classifier using these same 74 genes correctly predicted 98% of samples taken either 6 h or 24 h after treatment as unexposed, exposed to 0.5, 2, or ≥5 Gy. Expression patterns of five genes (CDKN1A, FDXR, SESN1, BBC3, and PHPT1) from this signature were also confirmed by real-time polymerase chain reaction. Conclusion: The ability of a single gene set to predict radiation dose throughout a window of time without need for individual pre-exposure controls represents an important advance in the development of gene expression for biodosimetry

  5. Referring Expressions: A Unified Approach

    Institute of Scientific and Technical Information of China (English)

    K.M. Jaszczolt

    2001-01-01

    @@ 0. Introduction Expressions used by speakers to refer are commonly divided into two categories: that of directly referring expressions and that of expressions whose referring function is secured by the context of utterance. Directly referring expressions are normally said to include proper names, some pronouns including demonstrative, and demonstrative phrases. The other category comprises mainly definite and indefinite descriptions, the first being their most acclaimed representative. Definite descriptions are widely acknowledged to have referential uses. They are not referring expressions, so to speak, by default,but rather as a result of a contextually determined interpretation. As a category, they are frequently said to belong with quantifiers (Neale 1990; Recanati 1993). However, the arguments for classifying them with referring expressions are ample (Bach 1987a; Larson & Segal 1995; Brown 1995; Jaszczolt 1997a,1997b, 1999b). It is argued in Part I of this paper that although definite descriptions exhibit an ambiguity of use between the referential and the attributive reading, they also exhibit the property of having an unmarked, salient interpretation which makes them akin to directly referential terms. This salient reading is the referential interpretation, arrived at with the help of the hearer′s presumption of the presence of strong referential intention that supports the speaker′s utterance.

  6. Gene Expression Data Knowledge Discovery using Global and Local Clustering

    CERN Document Server

    H, Swathi

    2010-01-01

    To understand complex biological systems, the research community has produced huge corpus of gene expression data. A large number of clustering approaches have been proposed for the analysis of gene expression data. However, extracting important biological knowledge is still harder. To address this task, clustering techniques are used. In this paper, hybrid Hierarchical k-Means algorithm is used for clustering and biclustering gene expression data is used. To discover both local and global clustering structure biclustering and clustering algorithms are utilized. A validation technique, Figure of Merit is used to determine the quality of clustering results. Appropriate knowledge is mined from the clusters by embedding a BLAST similarity search program into the clustering and biclustering process. To discover both local and global clustering structure biclustering and clustering algorithms are utilized. To determine the quality of clustering results, a validation technique, Figure of Merit is used. Appropriate ...

  7. Gene expression and 18FDG uptake in atherosclerotic carotid plaques

    DEFF Research Database (Denmark)

    Pedersen, Sune Folke; Græbe, Martin; Hag, Anne Mette Fisker;

    2010-01-01

    PURPOSE: Metabolic assessment of vascular inflammation by 2-[F]fluoro-2-deoxy-D-glucose positron emission tomography (FDG)-PET is a promising new approach for the evaluation of the vulnerability of atherosclerotic plaques. Quantitative real-time PCR allows measurement of gene expression of markers...... of atherosclerotic plaque vulnerability. These techniques were applied in advanced atherosclerotic disease to relate metabolism and inflammatory activity to the gene expression profile of the vulnerable atherosclerotic plaque. METHODS: Seventeen patients with clinical symptoms of cerebral vascular...... subsequently recovered by carotid endarterectomy. The gene expression of markers of vulnerability - CD68, IL-18, matrix metalloproteinase 9, cathepsin K, GLUT-1, and hexokinase type II (HK2) - were measured in plaques by quantitative PCR. RESULTS: In a multivariate linear regression model, GLUT-1, CD68...

  8. Transcriptomic analysis in the developing zebrafish embryo after compound exposure: Individual gene expression and pathway regulation

    Energy Technology Data Exchange (ETDEWEB)

    Hermsen, Sanne A.B., E-mail: Sanne.Hermsen@rivm.nl [Centre for Health Protection, National Institute for Public Health and the Environment (RIVM), P.O. Box 1, 3720 BA Bilthoven (Netherlands); Department of Toxicogenomics, Maastricht University, P.O. Box 616, 6200 MD, Maastricht (Netherlands); Institute for Risk Assessment Sciences (IRAS), Utrecht University, P.O. Box 80.178, 3508 TD, Utrecht (Netherlands); Pronk, Tessa E. [Centre for Health Protection, National Institute for Public Health and the Environment (RIVM), P.O. Box 1, 3720 BA Bilthoven (Netherlands); Department of Toxicogenomics, Maastricht University, P.O. Box 616, 6200 MD, Maastricht (Netherlands); Brandhof, Evert-Jan van den [Centre for Environmental Quality, National Institute for Public Health and the Environment (RIVM), P.O. Box 1, 3720 BA Bilthoven (Netherlands); Ven, Leo T.M. van der [Centre for Health Protection, National Institute for Public Health and the Environment (RIVM), P.O. Box 1, 3720 BA Bilthoven (Netherlands); Piersma, Aldert H. [Centre for Health Protection, National Institute for Public Health and the Environment (RIVM), P.O. Box 1, 3720 BA Bilthoven (Netherlands); Institute for Risk Assessment Sciences (IRAS), Utrecht University, P.O. Box 80.178, 3508 TD, Utrecht (Netherlands)

    2013-10-01

    The zebrafish embryotoxicity test is a promising alternative assay for developmental toxicity. Classically, morphological assessment of the embryos is applied to evaluate the effects of compound exposure. However, by applying differential gene expression analysis the sensitivity and predictability of the test may be increased. For defining gene expression signatures of developmental toxicity, we explored the possibility of using gene expression signatures of compound exposures based on commonly expressed individual genes as well as based on regulated gene pathways. Four developmental toxic compounds were tested in concentration-response design, caffeine, carbamazepine, retinoic acid and valproic acid, and two non-embryotoxic compounds, D-mannitol and saccharin, were included. With transcriptomic analyses we were able to identify commonly expressed genes, which were mostly development related, after exposure to the embryotoxicants. We also identified gene pathways regulated by the embryotoxicants, suggestive of their modes of action. Furthermore, whereas pathways may be regulated by all compounds, individual gene expression within these pathways can differ for each compound. Overall, the present study suggests that the use of individual gene expression signatures as well as pathway regulation may be useful starting points for defining gene biomarkers for predicting embryotoxicity. - Highlights: • The zebrafish embryotoxicity test in combination with transcriptomics was used. • We explored two approaches of defining gene biomarkers for developmental toxicity. • Four compounds in concentration-response design were tested. • We identified commonly expressed individual genes as well as regulated gene pathways. • Both approaches seem suitable starting points for defining gene biomarkers.

  9. Gene expression profiling analysis of ovarian cancer

    Science.gov (United States)

    YIN, JI-GANG; LIU, XIAN-YING; WANG, BIN; WANG, DAN-YANG; WEI, MAN; FANG, HUA; XIANG, MEI

    2016-01-01

    As a gynecological oncology, ovarian cancer has high incidence and mortality. To study the mechanisms of ovarian cancer, the present study analyzed the GSE37582 microarray. GSE37582 was downloaded from Gene Expression Omnibus and included data from 74 ovarian cancer cases and 47 healthy controls. The differentially-expressed genes (DEGs) were screened using linear models for microarray data package in R and were further screened for functional annotation. Next, Gene Ontology and pathway enrichment analysis of the DEGs was conducted. The interaction associations of the proteins encoded by the DEGs were searched using the Search Tool for the Retrieval of Interacting Genes, and the protein-protein interaction (PPI) network was visualized by Cytoscape. Moreover, module analysis of the PPI network was performed using the BioNet analysis tool in R. A total of 284 DEGs were screened, consisting of 145 upregulated genes and 139 downregulated genes. In particular, downregulated FBJ murine osteosarcoma viral oncogene homolog (FOS) was an oncogene, while downregulated cyclin-dependent kinase inhibitor 1A (CDKN1A) was a tumor suppressor gene and upregulated cluster of differentiation 44 (CD44) was classed as an ‘other’ gene. The enriched functions included collagen catabolic process, stress-activated mitogen-activated protein kinases cascade and insulin receptor signaling pathway. Meanwhile, FOS (degree, 15), CD44 (degree, 9), B-cell CLL/lymphoma 2 (BCL2; degree, 7), CDKN1A (degree, 7) and matrix metallopeptidase 3 (MMP3; degree, 6) had higher connectivity degrees in the PPI network for the DEGs. These genes may be involved in ovarian cancer by interacting with other genes in the module of the PPI network (e.g., BCL2-FOS, BCL2-CDKN1A, FOS-CDKN1A, FOS-CD44, MMP3-MMP7 and MMP7-CD44). Overall, BCL2, FOS, CDKN1A, CD44, MMP3 and MMP7 may be correlated with ovarian cancer. PMID:27347159

  10. Genetic architecture of gene expression in ovine skeletal muscle

    Directory of Open Access Journals (Sweden)

    Kogelman Lisette JA

    2011-12-01

    Full Text Available Abstract Background In livestock populations the genetic contribution to muscling is intensively monitored in the progeny of industry sires and used as a tool in selective breeding programs. The genes and pathways conferring this genetic merit are largely undefined. Genetic variation within a population has potential, amongst other mechanisms, to alter gene expression via cis- or trans-acting mechanisms in a manner that impacts the functional activities of specific pathways that contribute to muscling traits. By integrating sire-based genetic merit information for a muscling trait with progeny-based gene expression data we directly tested the hypothesis that there is genetic structure in the gene expression program in ovine skeletal muscle. Results The genetic performance of six sires for a well defined muscling trait, longissimus lumborum muscle depth, was measured using extensive progeny testing and expressed as an Estimated Breeding Value by comparison with contemporary sires. Microarray gene expression data were obtained for longissimus lumborum samples taken from forty progeny of the six sires (4-8 progeny/sire. Initial unsupervised hierarchical clustering analysis revealed strong genetic architecture to the gene expression data, which also discriminated the sire-based Estimated Breeding Value for the trait. An integrated systems biology approach was then used to identify the major functional pathways contributing to the genetics of enhanced muscling by using both Estimated Breeding Value weighted gene co-expression network analysis and a differential gene co-expression network analysis. The modules of genes revealed by these analyses were enriched for a number of functional terms summarised as muscle sarcomere organisation and development, protein catabolism (proteosome, RNA processing, mitochondrial function and transcriptional regulation. Conclusions This study has revealed strong genetic structure in the gene expression program within

  11. Aberrant Gene Expression in Acute Myeloid Leukaemia

    DEFF Research Database (Denmark)

    Bagger, Frederik Otzen

    Summary Acute Myeloid Leukaemia (AML) is an aggressive cancer of the bone marrow, affecting formation of blood cells during haematopoiesis. This thesis presents investigation of AML using mRNA gene expression profiles (GEP) of samples extracted from the bone marrow of healthy and diseased subjects...

  12. The Low Noise Limit in Gene Expression.

    Directory of Open Access Journals (Sweden)

    Roy D Dar

    Full Text Available Protein noise measurements are increasingly used to elucidate biophysical parameters. Unfortunately noise analyses are often at odds with directly measured parameters. Here we show that these inconsistencies arise from two problematic analytical choices: (i the assumption that protein translation rate is invariant for different proteins of different abundances, which has inadvertently led to (ii the assumption that a large constitutive extrinsic noise sets the low noise limit in gene expression. While growing evidence suggests that transcriptional bursting may set the low noise limit, variability in translational bursting has been largely ignored. We show that genome-wide systematic variation in translational efficiency can-and in the case of E. coli does-control the low noise limit in gene expression. Therefore constitutive extrinsic noise is small and only plays a role in the absence of a systematic variation in translational efficiency. These results show the existence of two distinct expression noise patterns: (1 a global noise floor uniformly imposed on all genes by expression bursting; and (2 high noise distributed to only a select group of genes.

  13. Paradoxornis webbianus bulomachus Transcriptome or Gene expression [

    Lifescience Database Archive (English)

    Full Text Available Study Type Sample Organism Sequencing Platform Transcriptome Analysis Paradoxornis web...e Length Download SRR392516 SRS259594 Transcriptome Analysis Paradoxornis webbian...t/Resources DRASearch - DDBJ/DRA ENA Browser - EBI/ENA Paradoxornis webbianus bulomachus Transcriptome or Gene expression ...

  14. Global gene expression in Escherichia coli biofilms

    DEFF Research Database (Denmark)

    Schembri, Mark; Kjærgaard, K.; Klemm, Per

    2003-01-01

    antimicrobial treatments and host immune defence responses. Escherichia coli has been used as a model organism to study the mechanisms of growth within adhered communities. In this study, we use DNA microarray technology to examine the global gene expression profile of E. coli during sessile growth compared...

  15. Population-level control of gene expression

    Science.gov (United States)

    Nevozhay, Dmitry; Adams, Rhys; van Itallie, Elizabeth; Bennett, Matthew; Balazsi, Gabor

    2011-03-01

    Gene expression is the process that translates genetic information into proteins, that determine the way cells live, function and even die. It was demonstrated that cells with identical genomes exposed to the same environment can differ in their protein composition and therefore phenotypes. Protein levels can vary between cells due to the stochastic nature of intracellular biochemical events, indicating that the genotype-phenotype connection is not deterministic at the cellular level. We asked whether genomes could encode isogenic cell populations more reliably than single cells. To address this question, we built two gene circuits to control three cell population-level characteristics: gene expression mean, coefficient of variation and non-genetic memory of previous expression states. Indeed, we found that these population-level characteristics were more predictable than the gene expression of single cells in a well-controlled environment. This research was supported by the NIH Director's New Innovator Award 1DP2 OD006481-01 and Welch Foundation Grant C-1729.

  16. Cluster Analysis of Gene Expression Data

    CERN Document Server

    Domany, E

    2002-01-01

    The expression levels of many thousands of genes can be measured simultaneously by DNA microarrays (chips). This novel experimental tool has revolutionized research in molecular biology and generated considerable excitement. A typical experiment uses a few tens of such chips, each dedicated to a single sample - such as tissue extracted from a particular tumor. The results of such an experiment contain several hundred thousand numbers, that come in the form of a table, of several thousand rows (one for each gene) and 50 - 100 columns (one for each sample). We developed a clustering methodology to mine such data. In this review I provide a very basic introduction to the subject, aimed at a physics audience with no prior knowledge of either gene expression or clustering methods. I explain what genes are, what is gene expression and how it is measured by DNA chips. Next I explain what is meant by "clustering" and how we analyze the massive amounts of data from such experiments, and present results obtained from a...

  17. Gene Expression Commons: an open platform for absolute gene expression profiling.

    Directory of Open Access Journals (Sweden)

    Jun Seita

    Full Text Available Gene expression profiling using microarrays has been limited to comparisons of gene expression between small numbers of samples within individual experiments. However, the unknown and variable sensitivities of each probeset have rendered the absolute expression of any given gene nearly impossible to estimate. We have overcome this limitation by using a very large number (>10,000 of varied microarray data as a common reference, so that statistical attributes of each probeset, such as the dynamic range and threshold between low and high expression, can be reliably discovered through meta-analysis. This strategy is implemented in a web-based platform named "Gene Expression Commons" (https://gexc.stanford.edu/ which contains data of 39 distinct highly purified mouse hematopoietic stem/progenitor/differentiated cell populations covering almost the entire hematopoietic system. Since the Gene Expression Commons is designed as an open platform, investigators can explore the expression level of any gene, search by expression patterns of interest, submit their own microarray data, and design their own working models representing biological relationship among samples.

  18. Automatic Control of Gene Expression in Mammalian Cells.

    Science.gov (United States)

    Fracassi, Chiara; Postiglione, Lorena; Fiore, Gianfranco; di Bernardo, Diego

    2016-04-15

    Automatic control of gene expression in living cells is paramount importance to characterize both endogenous gene regulatory networks and synthetic circuits. In addition, such a technology can be used to maintain the expression of synthetic circuit components in an optimal range in order to ensure reliable performance. Here we present a microfluidics-based method to automatically control gene expression from the tetracycline-inducible promoter in mammalian cells in real time. Our approach is based on the negative-feedback control engineering paradigm. We validated our method in a monoclonal population of cells constitutively expressing a fluorescent reporter protein (d2EYFP) downstream of a minimal CMV promoter with seven tet-responsive operator motifs (CMV-TET). These cells also constitutively express the tetracycline transactivator protein (tTA). In cells grown in standard growth medium, tTA is able to bind the CMV-TET promoter, causing d2EYFP to be maximally expressed. Upon addition of tetracycline to the culture medium, tTA detaches from the CMV-TET promoter, thus preventing d2EYFP expression. We tested two different model-independent control algorithms (relay and proportional-integral (PI)) to force a monoclonal population of cells to express an intermediate level of d2EYFP equal to 50% of its maximum expression level for up to 3500 min. The control input is either tetracycline-rich or standard growth medium. We demonstrated that both the relay and PI controllers can regulate gene expression at the desired level, despite oscillations (dampened in the case of the PI controller) around the chosen set point. PMID:26414746

  19. Regulation of methane genes and genome expression

    Energy Technology Data Exchange (ETDEWEB)

    John N. Reeve

    2009-09-09

    At the start of this project, it was known that methanogens were Archaeabacteria (now Archaea) and were therefore predicted to have gene expression and regulatory systems different from Bacteria, but few of the molecular biology details were established. The goals were then to establish the structures and organizations of genes in methanogens, and to develop the genetic technologies needed to investigate and dissect methanogen gene expression and regulation in vivo. By cloning and sequencing, we established the gene and operon structures of all of the “methane” genes that encode the enzymes that catalyze methane biosynthesis from carbon dioxide and hydrogen. This work identified unique sequences in the methane gene that we designated mcrA, that encodes the largest subunit of methyl-coenzyme M reductase, that could be used to identify methanogen DNA and establish methanogen phylogenetic relationships. McrA sequences are now the accepted standard and used extensively as hybridization probes to identify and quantify methanogens in environmental research. With the methane genes in hand, we used northern blot and then later whole-genome microarray hybridization analyses to establish how growth phase and substrate availability regulated methane gene expression in Methanobacterium thermautotrophicus ΔH (now Methanothermobacter thermautotrophicus). Isoenzymes or pairs of functionally equivalent enzymes catalyze several steps in the hydrogen-dependent reduction of carbon dioxide to methane. We established that hydrogen availability determine which of these pairs of methane genes is expressed and therefore which of the alternative enzymes is employed to catalyze methane biosynthesis under different environmental conditions. As were unable to establish a reliable genetic system for M. thermautotrophicus, we developed in vitro transcription as an alternative system to investigate methanogen gene expression and regulation. This led to the discovery that an archaeal protein

  20. Comparative gene expression of intestinal metabolizing enzymes.

    Science.gov (United States)

    Shin, Ho-Chul; Kim, Hye-Ryoung; Cho, Hee-Jung; Yi, Hee; Cho, Soo-Min; Lee, Dong-Goo; Abd El-Aty, A M; Kim, Jin-Suk; Sun, Duxin; Amidon, Gordon L

    2009-11-01

    The purpose of this study was to compare the expression profiles of drug-metabolizing enzymes in the intestine of mouse, rat and human. Total RNA was isolated from the duodenum and the mRNA expression was measured using Affymetrix GeneChip oligonucleotide arrays. Detected genes from the intestine of mouse, rat and human were ca. 60% of 22690 sequences, 40% of 8739 and 47% of 12559, respectively. Total genes of metabolizing enzymes subjected in this study were 95, 33 and 68 genes in mouse, rat and human, respectively. Of phase I enzymes, the mouse exhibited abundant gene expressions for Cyp3a25, Cyp4v3, Cyp2d26, followed by Cyp2b20, Cyp2c65 and Cyp4f14, whereas, the rat showed higher expression profiles of Cyp3a9, Cyp2b19, Cyp4f1, Cyp17a1, Cyp2d18, Cyp27a1 and Cyp4f6. However, the highly expressed P450 enzymes were CYP3A4, CYP3A5, CYP4F3, CYP2C18, CYP2C9, CYP2D6, CYP3A7, CYP11B1 and CYP2B6 in the human. For phase II enzymes, glucuronosyltransferase Ugt1a6, glutathione S-transferases Gstp1, Gstm3 and Gsta2, sulfotransferase Sult1b1 and acyltransferase Dgat1 were highly expressed in the mouse. The rat revealed predominant expression of glucuronosyltransferases Ugt1a1 and Ugt1a7, sulfotransferase Sult1b1, acetyltransferase Dlat and acyltransferase Dgat1. On the other hand, in human, glucuronosyltransferases UGT2B15 and UGT2B17, glutathione S-transferases MGST3, GSTP1, GSTA2 and GSTM4, sulfotransferases ST1A3 and SULT1A2, acetyltransferases SAT1 and CRAT, and acyltransferase AGPAT2 were dominantly detected. Therefore, current data indicated substantial interspecies differences in the pattern of intestinal gene expression both for P450 enzymes and phase II drug-metabolizing enzymes. This genomic database is expected to improve our understanding of interspecies variations in estimating intestinal prehepatic clearance of oral drugs. PMID:19746353

  1. Systematic enrichment analysis of gene expression profiling studies identifies consensus pathways implicated in colorectal cancer development

    OpenAIRE

    Jesús Lascorz; Kari Hemminki; Asta Försti

    2011-01-01

    Background: A large number of gene expression profiling (GEP) studies on colorectal carcinogenesis have been performed but no reliable gene signature has been identified so far due to the lack of reproducibility in the reported genes. There is growing evidence that functionally related genes, rather than individual genes, contribute to the etiology of complex traits. We used, as a novel approach, pathway enrichment tools to define functionally related genes that are consistently up- or down-r...

  2. Outlier Analysis for Gene Expression Data

    Institute of Scientific and Technical Information of China (English)

    Chao Yan; Guo-Liang Chen; Yi-Fei Shen

    2004-01-01

    The rapid developments of technologies that generate arrays of gene data enable a global view of the transcription levels of hundreds of thousands of genes simultaneously. The outlier detection problem for gene data has its importance but together with the difficulty of high dimensionality. The sparsity of data in high dimensional space makes each point a relatively good outlier in the view of traditional distance-based definitions. Thus, finding outliers in high dimensional data is more complex. In this paper, sme basic outlier analysis algorithms are discussed and a new genetic algorithm is presented. This algorithm is to find best dimension projections based on a revised cell-based algorithm and to give explanations to solutions. It can solve the outlier detection problem for gene expression data and for other high dimensional data as well.

  3. Coevolution of gene expression among interacting proteins

    Energy Technology Data Exchange (ETDEWEB)

    Fraser, Hunter B.; Hirsh, Aaron E.; Wall, Dennis P.; Eisen,Michael B.

    2004-03-01

    Physically interacting proteins or parts of proteins are expected to evolve in a coordinated manner that preserves proper interactions. Such coevolution at the amino acid-sequence level is well documented and has been used to predict interacting proteins, domains, and amino acids. Interacting proteins are also often precisely coexpressed with one another, presumably to maintain proper stoichiometry among interacting components. Here, we show that the expression levels of physically interacting proteins coevolve. We estimate average expression levels of genes from four closely related fungi of the genus Saccharomyces using the codon adaptation index and show that expression levels of interacting proteins exhibit coordinated changes in these different species. We find that this coevolution of expression is a more powerful predictor of physical interaction than is coevolution of amino acid sequence. These results demonstrate previously uncharacterized coevolution of gene expression, adding a different dimension to the study of the coevolution of interacting proteins and underscoring the importance of maintaining coexpression of interacting proteins over evolutionary time. Our results also suggest that expression coevolution can be used for computational prediction of protein protein interactions.

  4. How should we measure proportionality on relative gene expression data?

    Science.gov (United States)

    Erb, Ionas; Notredame, Cedric

    2016-06-01

    Correlation is ubiquitously used in gene expression analysis although its validity as an objective criterion is often questionable. If no normalization reflecting the original mRNA counts in the cells is available, correlation between genes becomes spurious. Yet the need for normalization can be bypassed using a relative analysis approach called log-ratio analysis. This approach can be used to identify proportional gene pairs, i.e. a subset of pairs whose correlation can be inferred correctly from unnormalized data due to their vanishing log-ratio variance. To interpret the size of non-zero log-ratio variances, a proposal for a scaling with respect to the variance of one member of the gene pair was recently made by Lovell et al. Here we derive analytically how spurious proportionality is introduced when using a scaling. We base our analysis on a symmetric proportionality coefficient (briefly mentioned in Lovell et al.) that has a number of advantages over their statistic. We show in detail how the choice of reference needed for the scaling determines which gene pairs are identified as proportional. We demonstrate that using an unchanged gene as a reference has huge advantages in terms of sensitivity. We also explore the link between proportionality and partial correlation and derive expressions for a partial proportionality coefficient. A brief data-analysis part puts the discussed concepts into practice. PMID:26762323

  5. Identification of differently expressed genes in human colorectal adenocarcinoma

    Institute of Scientific and Technical Information of China (English)

    Yao Chen; Yi-Zeng Zhang; Zong-Guang Zhou; Gang Wang; Zeng-Ni Yi

    2006-01-01

    AIM: To investigate the differently expressed genes in human colorectal adenocarcinoma.METHODS: The integrated approach for gene expression profiling that couples suppression subtractive hybridization, high-throughput cDNA array, sequencing,bioinformatics analysis, and reverse transcriptase realtime quantitative polymerase chain reaction (PCR)was carried out. A set of cDNA clones including 1260SSH inserts amplified by PCR was arrayed using robotic printing. The cDNA arrays were hybridized with florescent-labeled probes prepared from RNA of human colorectal adenocarcinoma (HCRAC) and normal colorectal tissues.RESULTS: A total of 86 genes were identified, 16 unknown genes and 70 known genes. The transcription factor Sox9 influencing cell differentiation was downregulated. At the same time, Heat shock protein 10 KDis downregulated and Calmoulin is up-regulated.CONCLUSION: Downregulation of heat shock protein 10 KD lost its inhibition of Ras, and then attenuated the Ras GTPase signaling pathway, increased cell proliferation and inhibited cell apoptosis. Down-regulated transcription factor Sox9 influences cell differentiation and cell-specific gene expression. Down-regulated Sox9 also decreases its binding to calmodulin, accumulates calmodulin as receptor-activated kinase and phosphorylase kinase due to the activation of PhK.

  6. Gene expression regulation in roots under drought.

    Science.gov (United States)

    Janiak, Agnieszka; Kwaśniewski, Mirosław; Szarejko, Iwona

    2016-02-01

    Stress signalling and regulatory networks controlling expression of target genes are the basis of plant response to drought. Roots are the first organs exposed to water deficiency in the soil and are the place of drought sensing. Signalling cascades transfer chemical signals toward the shoot and initiate molecular responses that lead to the biochemical and morphological changes that allow plants to be protected against water loss and to tolerate stress conditions. Here, we present an overview of signalling network and gene expression regulation pathways that are actively induced in roots under drought stress. In particular, the role of several transcription factor (TF) families, including DREB, AP2/ERF, NAC, bZIP, MYC, CAMTA, Alfin-like and Q-type ZFP, in the regulation of root response to drought are highlighted. The information provided includes available data on mutual interactions between these TFs together with their regulation by plant hormones and other signalling molecules. The most significant downstream target genes and molecular processes that are controlled by the regulatory factors are given. These data are also coupled with information about the influence of the described regulatory networks on root traits and root development which may translate to enhanced drought tolerance. This is the first literature survey demonstrating the gene expression regulatory machinery that is induced by drought stress, presented from the perspective of roots. PMID:26663562

  7. Differentially expressed genes in pancreatic ductal adenocarcinomas identified through serial analysis of gene expression

    DEFF Research Database (Denmark)

    Hustinx, Steven R; Cao, Dengfeng; Maitra, Anirban;

    2004-01-01

    Serial analysis of gene expression (SAGE) is a powerful tool for the discovery of novel tumor markers. The publicly available online SAGE libraries of normal and neoplastic tissues (http://www.ncbi.nlm.nih.gov/SAGE/) have recently been expanded; in addition, a more complete annotation of the human...... genome and better biocomputational techniques have substantially improved the assignment of differentially expressed SAGE "tags" to human genes. These improvements have provided us with an opportunity to re-evaluate global gene expression in pancreatic cancer using existing SAGE libraries. SAGE libraries...... generated from six pancreatic cancers were compared to SAGE libraries generated from 11 non-neoplastic tissues. Compared to normal tissue libraries, we identified 453 SAGE tags as differentially expressed in pancreatic cancer, including 395 that mapped to known genes and 58 "uncharacterized" tags. Of the...

  8. Gene expression profiles in skeletal muscle after gene electrotransfer

    Directory of Open Access Journals (Sweden)

    Eriksen Jens

    2007-06-01

    Full Text Available Abstract Background Gene transfer by electroporation (DNA electrotransfer to muscle results in high level long term transgenic expression, showing great promise for treatment of e.g. protein deficiency syndromes. However little is known about the effects of DNA electrotransfer on muscle fibres. We have therefore investigated transcriptional changes through gene expression profile analyses, morphological changes by histological analysis, and physiological changes by force generation measurements. DNA electrotransfer was obtained using a combination of a short high voltage pulse (HV, 1000 V/cm, 100 μs followed by a long low voltage pulse (LV, 100 V/cm, 400 ms; a pulse combination optimised for efficient and safe gene transfer. Muscles were transfected with green fluorescent protein (GFP and excised at 4 hours, 48 hours or 3 weeks after treatment. Results Differentially expressed genes were investigated by microarray analysis, and descriptive statistics were performed to evaluate the effects of 1 electroporation, 2 DNA injection, and 3 time after treatment. The biological significance of the results was assessed by gene annotation and supervised cluster analysis. Generally, electroporation caused down-regulation of structural proteins e.g. sarcospan and catalytic enzymes. Injection of DNA induced down-regulation of intracellular transport proteins e.g. sentrin. The effects on muscle fibres were transient as the expression profiles 3 weeks after treatment were closely related with the control muscles. Most interestingly, no changes in the expression of proteins involved in inflammatory responses or muscle regeneration was detected, indicating limited muscle damage and regeneration. Histological analysis revealed structural changes with loss of cell integrity and striation pattern in some fibres after DNA+HV+LV treatment, while HV+LV pulses alone showed preservation of cell integrity. No difference in the force generation capacity was observed in

  9. Gene expression profiling in sinonasal adenocarcinoma

    Directory of Open Access Journals (Sweden)

    Sébille-Rivain Véronique

    2009-11-01

    Full Text Available Abstract Background Sinonasal adenocarcinomas are uncommon tumors which develop in the ethmoid sinus after exposure to wood dust. Although the etiology of these tumors is well defined, very little is known about their molecular basis and no diagnostic tool exists for their early detection in high-risk workers. Methods To identify genes involved in this disease, we performed gene expression profiling using cancer-dedicated microarrays, on nine matched samples of sinonasal adenocarcinomas and non-tumor sinusal tissue. Microarray results were validated by quantitative RT-PCR and immunohistochemistry on two additional sets of tumors. Results Among the genes with significant differential expression we selected LGALS4, ACS5, CLU, SRI and CCT5 for further exploration. The overexpression of LGALS4, ACS5, SRI, CCT5 and the downregulation of CLU were confirmed by quantitative RT-PCR. Immunohistochemistry was performed for LGALS4 (Galectin 4, ACS5 (Acyl-CoA synthetase and CLU (Clusterin proteins: LGALS4 was highly up-regulated, particularly in the most differentiated tumors, while CLU was lost in all tumors. The expression of ACS5, was more heterogeneous and no correlation was observed with the tumor type. Conclusion Within our microarray study in sinonasal adenocarcinoma we identified two proteins, LGALS4 and CLU, that were significantly differentially expressed in tumors compared to normal tissue. A further evaluation on a new set of tissues, including precancerous stages and low grade tumors, is necessary to evaluate the possibility of using them as diagnostic markers.

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

    Directory of Open Access Journals (Sweden)

    Leckie Christopher

    2011-03-01

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

  11. Motif-guided sparse decomposition of gene expression data for regulatory module identification

    Directory of Open Access Journals (Sweden)

    Hoffman Eric P

    2011-03-01

    Full Text Available Abstract Background Genes work coordinately as gene modules or gene networks. Various computational approaches have been proposed to find gene modules based on gene expression data; for example, gene clustering is a popular method for grouping genes with similar gene expression patterns. However, traditional gene clustering often yields unsatisfactory results for regulatory module identification because the resulting gene clusters are co-expressed but not necessarily co-regulated. Results We propose a novel approach, motif-guided sparse decomposition (mSD, to identify gene regulatory modules by integrating gene expression data and DNA sequence motif information. The mSD approach is implemented as a two-step algorithm comprising estimates of (1 transcription factor activity and (2 the strength of the predicted gene regulation event(s. Specifically, a motif-guided clustering method is first developed to estimate the transcription factor activity of a gene module; sparse component analysis is then applied to estimate the regulation strength, and so predict the target genes of the transcription factors. The mSD approach was first tested for its improved performance in finding regulatory modules using simulated and real yeast data, revealing functionally distinct gene modules enriched with biologically validated transcription factors. We then demonstrated the efficacy of the mSD approach on breast cancer cell line data and uncovered several important gene regulatory modules related to endocrine therapy of breast cancer. Conclusion We have developed a new integrated strategy, namely motif-guided sparse decomposition (mSD of gene expression data, for regulatory module identification. The mSD method features a novel motif-guided clustering method for transcription factor activity estimation by finding a balance between co-regulation and co-expression. The mSD method further utilizes a sparse decomposition method for regulation strength estimation. The

  12. Development of a synthetic gene network to modulate gene expression by mechanical forces.

    Science.gov (United States)

    Kis, Zoltán; Rodin, Tania; Zafar, Asma; Lai, Zhangxing; Freke, Grace; Fleck, Oliver; Del Rio Hernandez, Armando; Towhidi, Leila; Pedrigi, Ryan M; Homma, Takayuki; Krams, Rob

    2016-01-01

    The majority of (mammalian) cells in our body are sensitive to mechanical forces, but little work has been done to develop assays to monitor mechanosensor activity. Furthermore, it is currently impossible to use mechanosensor activity to drive gene expression. To address these needs, we developed the first mammalian mechanosensitive synthetic gene network to monitor endothelial cell shear stress levels and directly modulate expression of an atheroprotective transcription factor by shear stress. The technique is highly modular, easily scalable and allows graded control of gene expression by mechanical stimuli in hard-to-transfect mammalian cells. We call this new approach mechanosyngenetics. To insert the gene network into a high proportion of cells, a hybrid transfection procedure was developed that involves electroporation, plasmids replication in mammalian cells, mammalian antibiotic selection, a second electroporation and gene network activation. This procedure takes 1 week and yielded over 60% of cells with a functional gene network. To test gene network functionality, we developed a flow setup that exposes cells to linearly increasing shear stress along the length of the flow channel floor. Activation of the gene network varied logarithmically as a function of shear stress magnitude. PMID:27404994

  13. Querying Co-regulated Genes on Diverse Gene Expression Datasets Via Biclustering.

    Science.gov (United States)

    Deveci, Mehmet; Küçüktunç, Onur; Eren, Kemal; Bozdağ, Doruk; Kaya, Kamer; Çatalyürek, Ümit V

    2016-01-01

    Rapid development and increasing popularity of gene expression microarrays have resulted in a number of studies on the discovery of co-regulated genes. One important way of discovering such co-regulations is the query-based search since gene co-expressions may indicate a shared role in a biological process. Although there exist promising query-driven search methods adapting clustering, they fail to capture many genes that function in the same biological pathway because microarray datasets are fraught with spurious samples or samples of diverse origin, or the pathways might be regulated under only a subset of samples. On the other hand, a class of clustering algorithms known as biclustering algorithms which simultaneously cluster both the items and their features are useful while analyzing gene expression data, or any data in which items are related in only a subset of their samples. This means that genes need not be related in all samples to be clustered together. Because many genes only interact under specific circumstances, biclustering may recover the relationships that traditional clustering algorithms can easily miss. In this chapter, we briefly summarize the literature using biclustering for querying co-regulated genes. Then we present a novel biclustering approach and evaluate its performance by a thorough experimental analysis. PMID:26626937

  14. Multi-species microarrays reveal the effect of sequence divergence on gene expression profiles

    OpenAIRE

    Gilad, Yoav; Rifkin, Scott A.; Bertone, Paul; Gerstein, Mark; White, Kevin P

    2005-01-01

    Interspecies comparisons of gene expression levels will increase our understanding of the evolution of transcriptional mechanisms and help to identify targets of natural selection. This approach holds particular promise for apes, as many human-specific adaptations are thought to result from differences in gene expression rather than in coding sequence. To date, however, all studies directly comparing interspecies gene expression have been performed on single-species arrays, so that it has bee...

  15. FARO server: Meta-analysis of gene expression by matching gene expression signatures to a compendium of public gene expression data

    DEFF Research Database (Denmark)

    Manijak, Mieszko P.; Nielsen, Henrik Bjørn

    2011-01-01

    BACKGROUND: Although, systematic analysis of gene annotation is a powerful tool for interpreting gene expression data, it sometimes is blurred by incomplete gene annotation, missing expression response of key genes and secondary gene expression responses. These shortcomings may be partially...... circumvented by instead matching gene expression signatures to signatures of other experiments. FINDINGS: To facilitate this we present the Functional Association Response by Overlap (FARO) server, that match input signatures to a compendium of 242 gene expression signatures, extracted from more than 1700...... Arabidopsis microarray experiments. CONCLUSIONS: Hereby we present a publicly available tool for robust characterization of Arabidopsis gene expression experiments which can point to similar experimental factors in other experiments. The server is available at http://www.cbs.dtu.dk/services/faro/....

  16. FARO server: Meta-analysis of gene expression by matching gene expression signatures to a compendium of public gene expression data

    Directory of Open Access Journals (Sweden)

    Nielsen Henrik B

    2011-06-01

    Full Text Available Abstract Background Although, systematic analysis of gene annotation is a powerful tool for interpreting gene expression data, it sometimes is blurred by incomplete gene annotation, missing expression response of key genes and secondary gene expression responses. These shortcomings may be partially circumvented by instead matching gene expression signatures to signatures of other experiments. Findings To facilitate this we present the Functional Association Response by Overlap (FARO server, that match input signatures to a compendium of 242 gene expression signatures, extracted from more than 1700 Arabidopsis microarray experiments. Conclusions Hereby we present a publicly available tool for robust characterization of Arabidopsis gene expression experiments which can point to similar experimental factors in other experiments. The server is available at http://www.cbs.dtu.dk/services/faro/.

  17. Radiopharmaceuticals to monitor the expression of transferred genes in gene transfer therapy

    Energy Technology Data Exchange (ETDEWEB)

    Wiebe, L. I. [University of Alberta, Edmonton (Canada). Noujaim Institute for Pharmaceutical Oncology Research

    1997-10-01

    The development and application of radiopharmaceuticals has, in many instances, been based on the pharmacological properties of therapeutic agents. The molecular biology-biotechnology revolution has had an important impact on treatment of diseases, in part through the reduced toxicity of `biologicals`, in part because of their specificity for interaction at unique molecular sites and in part because of their selective delivery to the target site. Immunotherapeutic approaches include the use of monoclonal antibodies (MABs), MAB-fragments and chemotactic peptides. Such agents currently form the basis of both diagnostic and immunotherapeutic radiopharmaceuticals. More recently, gene transfer techniques have been advanced to the point that a new molecular approach, gene therapy, has become a reality. Gene therapy offers an opportunity to attack disease at its most fundamental level. The therapeutic mechanism is based on the expression of a specific gene or genes, the product of which will invoke immunological, receptor-based or enzyme-based therapeutic modalities. Several approaches to gene therapy of cancer have been envisioned, the most clinically-advanced concepts involving the introduction of genes that will encode for molecular targets nor normally found in healthy mammalian cells. A number of gene therapy clinical trials are based on the introduction of the Herpes simplex virus type-1 (HSV-1) gene that encodes for viral thymidine kinase (tk+). Once HSV-1 tk+ is expressed in the target (cancer) cell, therapy can be effected by the administration of a highly molecularly-targeted and systemically non-toxic antiviral drug such as ganciclovir. The development of radiodiagnostic imaging in gene therapy will be reviewed, using HSV-1 tk+ and radioiodinated IVFRU as a basis for development of the theme. Molecular targets that could be exploited in gene therapy, other than tk+, will be identified

  18. Radiopharmaceuticals to monitor the expression of transferred genes in gene transfer therapy

    International Nuclear Information System (INIS)

    The development and application of radiopharmaceuticals has, in many instances, been based on the pharmacological properties of therapeutic agents. The molecular biology-biotechnology revolution has had an important impact on treatment of diseases, in part through the reduced toxicity of 'biologicals', in part because of their specificity for interaction at unique molecular sites and in part because of their selective delivery to the target site. Immunotherapeutic approaches include the use of monoclonal antibodies (MABs), MAB-fragments and chemotactic peptides. Such agents currently form the basis of both diagnostic and immunotherapeutic radiopharmaceuticals. More recently, gene transfer techniques have been advanced to the point that a new molecular approach, gene therapy, has become a reality. Gene therapy offers an opportunity to attack disease at its most fundamental level. The therapeutic mechanism is based on the expression of a specific gene or genes, the product of which will invoke immunological, receptor-based or enzyme-based therapeutic modalities. Several approaches to gene therapy of cancer have been envisioned, the most clinically-advanced concepts involving the introduction of genes that will encode for molecular targets nor normally found in healthy mammalian cells. A number of gene therapy clinical trials are based on the introduction of the Herpes simplex virus type-1 (HSV-1) gene that encodes for viral thymidine kinase (tk+). Once HSV-1 tk+ is expressed in the target (cancer) cell, therapy can be effected by the administration of a highly molecularly-targeted and systemically non-toxic antiviral drug such as ganciclovir. The development of radiodiagnostic imaging in gene therapy will be reviewed, using HSV-1 tk+ and radioiodinated IVFRU as a basis for development of the theme. Molecular targets that could be exploited in gene therapy, other than tk+, will be identified

  19. Gene expression in Pseudomonas aeruginosa swarming motility

    Directory of Open Access Journals (Sweden)

    Déziel Eric

    2010-10-01

    Full Text Available Abstract Background The bacterium Pseudomonas aeruginosa is capable of three types of motilities: swimming, twitching and swarming. The latter is characterized by a fast and coordinated group movement over a semi-solid surface resulting from intercellular interactions and morphological differentiation. A striking feature of swarming motility is the complex fractal-like patterns displayed by migrating bacteria while they move away from their inoculation point. This type of group behaviour is still poorly understood and its characterization provides important information on bacterial structured communities such as biofilms. Using GeneChip® Affymetrix microarrays, we obtained the transcriptomic profiles of both bacterial populations located at the tip of migrating tendrils and swarm center of swarming colonies and compared these profiles to that of a bacterial control population grown on the same media but solidified to not allow swarming motility. Results Microarray raw data were corrected for background noise with the RMA algorithm and quantile normalized. Differentially expressed genes between the three conditions were selected using a threshold of 1.5 log2-fold, which gave a total of 378 selected genes (6.3% of the predicted open reading frames of strain PA14. Major shifts in gene expression patterns are observed in each growth conditions, highlighting the presence of distinct bacterial subpopulations within a swarming colony (tendril tips vs. swarm center. Unexpectedly, microarrays expression data reveal that a minority of genes are up-regulated in tendril tip populations. Among them, we found energy metabolism, ribosomal protein and transport of small molecules related genes. On the other hand, many well-known virulence factors genes were globally repressed in tendril tip cells. Swarm center cells are distinct and appear to be under oxidative and copper stress responses. Conclusions Results reported in this study show that, as opposed to

  20. Annotation of gene function in citrus using gene expression information and co-expression networks

    OpenAIRE

    Wong, Darren CJ; Sweetman, Crystal; Ford, Christopher M

    2014-01-01

    Background The genus Citrus encompasses major cultivated plants such as sweet orange, mandarin, lemon and grapefruit, among the world’s most economically important fruit crops. With increasing volumes of transcriptomics data available for these species, Gene Co-expression Network (GCN) analysis is a viable option for predicting gene function at a genome-wide scale. GCN analysis is based on a “guilt-by-association” principle whereby genes encoding proteins involved in similar and/or related bi...

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

    Directory of Open Access Journals (Sweden)

    Teng Shaolei

    2013-01-01

    Full Text Available Abstract 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.

  2. OryzaExpress: An Integrated Database of Gene Expression Networks and Omics Annotations in Rice

    OpenAIRE

    Hamada, Kazuki; Hongo, Kohei; Suwabe, Keita; Shimizu, Akifumi; Nagayama, Taishi; Abe, Reina; Kikuchi, Shunsuke; Yamamoto, Naoki; Fujii, Takaaki; Yokoyama, Koji; Tsuchida, Hiroko; Sano, Kazumi; Mochizuki, Takako; Oki, Nobuhiko; Horiuchi, Youko

    2010-01-01

    Similarity of gene expression profiles provides important clues for understanding the biological functions of genes, biological processes and metabolic pathways related to genes. A gene expression network (GEN) is an ideal choice to grasp such expression profile similarities among genes simultaneously. For GEN construction, the Pearson correlation coefficient (PCC) has been widely used as an index to evaluate the similarities of expression profiles for gene pairs. However, calculation of PCCs...

  3. DNA supercoiling and bacterial gene expression.

    Science.gov (United States)

    Dorman, Charles J

    2006-01-01

    DNA in bacterial cells is maintained in a negatively supercoiled state. This contributes to the organization of the bacterial nucleoid and also influences the global gene expression pattern in the cell through modulatory effects on transcription. Supercoiling arises as a result of changes to the linking number of the relaxed double-stranded DNA molecule and is set and reset by the action of DNA topoisomerases. This process is subject to a multitude of influences that are usually summarized as environmental stress. Responsiveness of linking number change to stress offers the promise of a mechanism for the wholesale adjustment of the transcription programme of the cell as the bacterium experiences different environments. Recent data from DNA microarray experiments support this proposition. The emerging picture is one of DNA supercoiling acting at or near the apex of a regulatory hierarchy where it collaborates with nucleoid-associated proteins and transcription factors to determine the gene expression profile of the cell. PMID:17338437

  4. Insights into SAGA function during gene expression

    Science.gov (United States)

    Rodríguez-Navarro, Susana

    2009-01-01

    Histone modifications are a crucial source of epigenetic control. SAGA (Spt–Ada–Gcn5 acetyltransferase) is a chromatin-modifying complex that contains two distinct enzymatic activities, Gcn5 and Ubp8, through which it acetylates and deubiquitinates histone residues, respectively, thereby enforcing a pattern of modifications that is decisive in regulating gene expression. Here, I discuss the latest contributions to understanding the roles of the SAGA complex, highlighting the characterization of the SAGA-deubiquitination module, and emphasizing the functions newly ascribed to SAGA during transcription elongation and messenger-RNA export. These findings suggest that a crosstalk exists between chromatin remodelling, transcription and messenger-RNA export, which could constitute a checkpoint for accurate gene expression. I focus particularly on the new components of human SAGA, which was recently discovered and confirms the conservation of the SAGA complex throughout evolution. PMID:19609321

  5. Statistical Approach to Gene Evolution

    OpenAIRE

    Chattopadhyay, Sujay; William A. Kanner; Chakrabarti, Jayprokas

    2001-01-01

    The evolution in coding DNA sequences brings new flexibility and freedom to the codon words, even as the underlying nucleotides get significantly ordered. These curious contra-rules of gene organisation are observed from the distribution of words and the second moments of the nucleotide letters. These statistical data give us the physics behind the classification of bacteria.

  6. Regulation of Gene Expression in Protozoa Parasites

    OpenAIRE

    Consuelo Gomez; Esther Ramirez, M.; Mercedes Calixto-Galvez; Olivia Medel; Rodríguez, Mario A

    2010-01-01

    Infections with protozoa parasites are associated with high burdens of morbidity and mortality across the developing world. Despite extensive efforts to control the transmission of these parasites, the spread of populations resistant to drugs and the lack of effective vaccines against them contribute to their persistence as major public health problems. Parasites should perform a strict control on the expression of genes involved in their pathogenicity, differentiation, immune evasion, or dru...

  7. Analysis of gene expression in rabbit muscle

    Directory of Open Access Journals (Sweden)

    Alena Gálová

    2014-02-01

    Full Text Available Increasing consumer knowledge of the link between diet and health has raised the demand for high quality food. Meat and meat products may be considered as irreplaceable in human nutrition. Breeding livestock to higher content of lean meat and the use of modern hybrids entails problems with the quality of meat. Analysing of livestock genomes could get us a great deal of important information, which may significantly affect the improvement process. Domestic animals are invaluable resources for study of the molecular architecture of complex traits. Although the mapping of quantitative trait loci (QTL responsible for economically important traits in domestic animals has achieved remarkable results in recent decades, not all of the genetic variation in the complex traits has been captured because of the low density of markers used in QTL mapping studies. The genome wide association study (GWAS, which utilizes high-density single-nucleotide polymorphism (SNP, provides a new way to tackle this issue. New technologies now allow producing microarrays containing thousands of hybridization probes on a single membrane or other solid support. We used microarray analysis to study gene expression in rabbit muscle during different developmental age stages. The outputs from GeneSpring GX sotware are presented in this work. After the evaluation of gene expression in rabbits, will be selected genes of interest in relation to meat quality parameters and will be further analyzed by the available methods of molecular biology and genetics.

  8. Tools and resources for analyzing gene expression changes in glaucomatous neurodegeneration

    OpenAIRE

    Nickells, Robert W; Pelzel, Heather R.

    2015-01-01

    Evaluating gene expression changes presents one of the most powerful interrogative approaches to study the molecular, biochemical, and cellular pathways associated with glaucomatous disease pathology. Technologies to study gene expression profiles in glaucoma are wide ranging. Qualitative techniques provide the power of localizing expression changes to individual cells, but are not robust to evaluate differences in expression changes. Alternatively, quantitative changes provide a high level o...

  9. Internet Resources for Gene Expression Analysis in Arabidopsis thaliana.

    Science.gov (United States)

    Hehl, Reinhard; Bülow, Lorenz

    2008-09-01

    The number of online databases and web-tools for gene expression analysis in Arabidopsis thaliana has increased tremendously during the last years. These resources permit the database-assisted identification of putative cis-regulatory DNA sequences, their binding proteins, and the determination of common cis-regulatory motifs in coregulated genes. DNA binding proteins may be predicted by the type of cis-regulatory motif. Further questions of combinatorial control based on the interaction of DNA binding proteins and the colocalization of cis-regulatory motifs can be addressed. The database-assisted spatial and temporal expression analysis of DNA binding proteins and their target genes may help to further refine experimental approaches. Signal transduction pathways upstream of regulated genes are not yet fully accessible in databases mainly because they need to be manually annotated. This review focuses on the use of the AthaMap and PathoPlant((R)) databases for gene expression regulation analysis and discusses similar and complementary online databases and web-tools. Online databases are helpful for the development of working hypothesis and for designing subsequent experiments. PMID:19506727

  10. Reduced expression of Autographa californica nucleopolyhedrovirus ORF34, an essential gene, enhances heterologous gene expression

    Energy Technology Data Exchange (ETDEWEB)

    Salem, Tamer Z. [Department of Entomology, Michigan State University, East Lansing, MI 48824 (United States); Department of Microbial Molecular Biology, AGERI, Agricultural Research Center, Giza 12619 (Egypt); Division of Biomedical Sciences, Zewail University, Zewail City of Science and Technology, Giza 12588 (Egypt); Zhang, Fengrui [Department of Entomology, Michigan State University, East Lansing, MI 48824 (United States); Thiem, Suzanne M., E-mail: smthiem@msu.edu [Department of Entomology, Michigan State University, East Lansing, MI 48824 (United States); Department of Microbiology and Molecular Genetics, Michigan State University, East Lansing, MI 48824 (United States)

    2013-01-20

    Autographa californica multiple nucleopolyhedrovirus ORF34 is part of a transcriptional unit that includes ORF32, encoding a viral fibroblast growth factor (FGF) and ORF33. We identified ORF34 as a candidate for deletion to improve protein expression in the baculovirus expression system based on enhanced reporter gene expression in an RNAi screen of virus genes. However, ORF34 was shown to be an essential gene. To explore ORF34 function, deletion (KO34) and rescue bacmids were constructed and characterized. Infection did not spread from primary KO34 transfected cells and supernatants from KO34 transfected cells could not infect fresh Sf21 cells whereas the supernatant from the rescue bacmids transfection could recover the infection. In addition, budded viruses were not observed in KO34 transfected cells by electron microscopy, nor were viral proteins detected from the transfection supernatants by western blots. These demonstrate that ORF34 is an essential gene with a possible role in infectious virus production.

  11. A gene co-expression network in whole blood of schizophrenia patients is independent of antipsychotic-use and enriched for brain-expressed genes

    DEFF Research Database (Denmark)

    de Jong, Simone; Boks, Marco P M; Fuller, Tova F; Strengman, Eric; Janson, Esther; de Kovel, Carolien G F; Ori, Anil P S; Vi, Nancy; Mulder, Flip; Blom, Jan Dirk; Glenthøj, Birte; Schubart, Chris D; Cahn, Wiepke; Kahn, René S; Horvath, Steve; Ophoff, Roel A

    2012-01-01

    schizophrenia patients and controls. We applied a systems biology approach to genome-wide expression data from whole blood of 92 medicated and 29 antipsychotic-free schizophrenia patients and 118 healthy controls. We show that gene expression profiling in whole blood can identify twelve large gene co......-expression modules associated with schizophrenia. Several of these disease related modules are likely to reflect expression changes due to antipsychotic medication. However, two of the disease modules could be replicated in an independent second data set involving antipsychotic-free patients and controls. One of......Despite large-scale genome-wide association studies (GWAS), the underlying genes for schizophrenia are largely unknown. Additional approaches are therefore required to identify the genetic background of this disorder. Here we report findings from a large gene expression study in peripheral blood of...

  12. Cholinergic regulation of VIP gene expression in human neuroblastoma cells

    DEFF Research Database (Denmark)

    Kristensen, Bo; Georg, Birgitte; Fahrenkrug, Jan

    Vasoactive intestinal polypeptide, muscarinic receptor, neuroblastoma cell, mRNA, gene expression, peptide processing......Vasoactive intestinal polypeptide, muscarinic receptor, neuroblastoma cell, mRNA, gene expression, peptide processing...

  13. The similarity of gene expression between human and mouse tissues

    OpenAIRE

    Dowell, Robin D.

    2011-01-01

    Meta-analysis of human and mouse microarray data reveals conservation of patterns of gene expression that will help to better characterize the evolution of gene expression. See research article: http://genomebiology.com/2010/11/12/R124

  14. The transcriptional regulation of regucalcin gene expression.

    Science.gov (United States)

    Yamaguchi, Masayoshi

    2011-01-01

    Regucalcin, which is discovered as a calcium-binding protein in 1978, has been shown to play a multifunctional role in many tissues and cell types; regucalcin has been proposed to play a pivotal role in keeping cell homeostasis and function for cell response. Regucalcin and its gene are identified in over 15 species consisting of regucalcin family. Comparison of the nucleotide sequences of regucalcin from vertebrate species is highly conserved in their coding region with throughout evolution. The regucalcin gene is localized on the chromosome X in rat and human. The organization of rat regucalcin gene consists of seven exons and six introns and several consensus regulatory elements exist upstream of the 5'-flanking region. AP-1, NF1-A1, RGPR-p117, β-catenin, and other factors have been found to be a transcription factor in the enhancement of regucalcin gene promoter activity. The transcription activity of regucalcin gene is enhanced through intracellular signaling factors that are mediated through the phosphorylation and dephosphorylation of nuclear protein in vitro. Regucalcin mRNA and its protein are markedly expressed in the liver and kidney cortex of rats. The expression of regucalcin mRNA in the liver and kidney cortex has been shown to stimulate by hormonal factors (including calcium, calcitonin, parathyroid hormone, insulin, estrogen, and dexamethasone) in vivo. Regucalcin mRNA expression is enhanced in the regenerating liver after partial hepatectomy of rats in vivo. The expression of regucalcin mRNA in the liver and kidney with pathophysiological state has been shown to suppress, suggesting an involvement of regucalcin in disease. Liver regucalcin expression is down-regulated in tumor cells, suggesting a suppressive role in the development of carcinogenesis. Liver regucalcin is markedly released into the serum of rats with chemically induced liver injury in vivo. Serum regucalcin has a potential sensitivity as a specific biochemical marker of chronic

  15. Up-regulation of SNCA gene expression: implications to synucleinopathies.

    Science.gov (United States)

    Tagliafierro, L; Chiba-Falek, O

    2016-07-01

    Synucleinopathies are a group of neurodegenerative diseases that share a common pathological lesion of intracellular protein inclusions largely composed by aggregates of alpha-synuclein protein. Accumulating evidence, including genome wide association studies, has implicated alpha-synuclein (SNCA) gene in the etiology of synucleinopathies. However, the precise variants within SNCA gene that contribute to the sporadic forms of Parkinson's disease (PD), dementia with Lewy bodies (DLB), multiple system atrophy (MSA), and other synucleinopathies and their molecular mechanisms of action remain elusive. It has been suggested that SNCA expression levels are critical for the development of these diseases. Here, we review several model systems that have been developed to advance the understanding of the role of SNCA expression levels in the etiology of synucleinopathies. We also describe different molecular mechanisms that regulate SNCA gene expression and discuss possible strategies for SNCA down-regulation as means for therapeutic approaches. Finally, we highlight some examples that underscore the relationships between the genetic association findings and the regulatory mechanisms of SNCA expression, which suggest that genetic variability in SNCA locus is directly responsible, at least in part, to the changes in gene expression and explain the reported associations of SNCA with synucleinopathies. Future studies utilizing induced pluripotent stem cells (iPSCs)-derived neuronal lines and genome editing by CRISPR/Cas9, will allow us to validate, characterize, and manipulate the effects of particular cis-genetic variants on SNCA expression. Moreover, this model system will enable us to compare different neuronal and glial lineages involved in synucleinopathies representing an attractive strategy to elucidate-common and specific-SNCA-genetic variants, regulatory mechanisms, and vulnerable expression levels underlying synucleinopathy spectrum disorders. This forthcoming

  16. Unsupervised Meta-Analysis on Diverse Gene Expression Datasets Allows Insight into Gene Function and Regulation

    Directory of Open Access Journals (Sweden)

    Julia C. Engelmann

    2008-01-01

    Full Text Available Over the past years, microarray databases have increased rapidly in size. While they offer a wealth of data, it remains challenging to integrate data arising from different studies. Here we propose an unsupervised approach of a large-scale meta-analysis on Arabidopsis thaliana whole genome expression datasets to gain additional insights into the function and regulation of genes. Applying kernel principal component analysis and hierarchical clustering, we found three major groups of experimental contrasts sharing a common biological trait. Genes associated to two of these clusters are known to play an important role in indole-3-acetic acid (IAA mediated plant growth and development or pathogen defense. Novel functions could be assigned to genes including a cluster of serine/threonine kinases that carry two uncharacterized domains (DUF26 in their receptor part implicated in host defense. With the approach shown here, hidden interrelations between genes regulated under different conditions can be unraveled.

  17. Digital gene expression analysis of the zebra finch genome

    Directory of Open Access Journals (Sweden)

    Burke Terry

    2010-04-01

    Full Text Available Abstract Background In order to understand patterns of adaptation and molecular evolution it is important to quantify both variation in gene expression and nucleotide sequence divergence. Gene expression profiling in non-model organisms has recently been facilitated by the advent of massively parallel sequencing technology. Here we investigate tissue specific gene expression patterns in the zebra finch (Taeniopygia guttata with special emphasis on the genes of the major histocompatibility complex (MHC. Results Almost 2 million 454-sequencing reads from cDNA of six different tissues were assembled and analysed. A total of 11,793 zebra finch transcripts were represented in this EST data, indicating a transcriptome coverage of about 65%. There was a positive correlation between the tissue specificity of gene expression and non-synonymous to synonymous nucleotide substitution ratio of genes, suggesting that genes with a specialised function are evolving at a higher rate (or with less constraint than genes with a more general function. In line with this, there was also a negative correlation between overall expression levels and expression specificity of contigs. We found evidence for expression of 10 different genes related to the MHC. MHC genes showed relatively tissue specific expression levels and were in general primarily expressed in spleen. Several MHC genes, including MHC class I also showed expression in brain. Furthermore, for all genes with highest levels of expression in spleen there was an overrepresentation of several gene ontology terms related to immune function. Conclusions Our study highlights the usefulness of next-generation sequence data for quantifying gene expression in the genome as a whole as well as in specific candidate genes. Overall, the data show predicted patterns of gene expression profiles and molecular evolution in the zebra finch genome. Expression of MHC genes in particular, corresponds well with expression

  18. Methodological Considerations For Gene Expression Profiling Of Human Brain

    OpenAIRE

    Atz, Mary; Walsh, David; Cartagena, Preston; Li, Jun; Evans, Simon; Choudary, Prabhakara; Overman, Kevin; Stein, Richard; Tomita, Hiro; Potkin, Steven; Myers, Rick; Watson, Stanley J.; Jones, E G; Akil, Huda; Bunney, William E.

    2007-01-01

    Gene expression profiles of postmortem brain tissue represent important resources for understanding neuropsychiatric illnesses. The impact(s) of quality covariables on the analysis and results of gene expression studies are important questions. This paper addressed critical variables which might affect gene expression in two brain regions. Four broad groups of quality indicators in gene expression profiling studies (clinical, tissue, RNA, and microarray quality) were identified. These quality...

  19. The gene expression fingerprint of human heart failure

    OpenAIRE

    Tan, Fen-Lai; Moravec, Christine S.; Li, Jianbo; Apperson-Hansen, Carolyn; McCarthy, Patrick M; Young, James B.; Bond, Meredith

    2002-01-01

    Multiple pathways are responsible for transducing mechanical and hormonal stimuli into changes in gene expression during heart failure. In this study our goals were (i) to develop a sound statistical method to establish a comprehensive cutoff point for identification of differentially expressed genes, (ii) to identify a gene expression fingerprint for heart failure, (iii) to attempt to distinguish different etiologies of heart failure by their gene expression fingerprint, and (iv) to identify...

  20. An anatomic gene expression atlas of the adult mouse brain

    OpenAIRE

    Ng, Lydia; Bernard, Amy; Lau, Chris; Overly, Caroline C.; Dong, Hong-Wei; Kuan, Chihchau; Pathak, Sayan; Sunkin, Susan M.; Dang, Chinh; Bohland, Jason W.; Bokil, Hemant; Mitra, Partha P.; Puelles, Luis; Hohmann, John; Anderson, David J.

    2009-01-01

    Studying gene expression provides a powerful means of understanding structure-function relationships in the nervous system. The availability of genome-scale in situ hybridization datasets enables new possibilities for understanding brain organization based on gene expression patterns. The Anatomic Gene Expression Atlas (AGEA) is a new relational atlas revealing the genetic architecture of the adult C57Bl/6J mouse brain based on spatial correlations across expression data for thousands of gene...

  1. Gene Expression Profiling of Xeroderma Pigmentosum

    Directory of Open Access Journals (Sweden)

    Bowden Nikola A

    2006-05-01

    Full Text Available Abstract Xeroderma pigmentosum (XP is a rare recessive disorder that is characterized by extreme sensitivity to UV light. UV light exposure results in the formation of DNA damage such as cyclobutane dimers and (6-4 photoproducts. Nucleotide excision repair (NER orchestrates the removal of cyclobutane dimers and (6-4 photoproducts as well as some forms of bulky chemical DNA adducts. The disease XP is comprised of 7 complementation groups (XP-A to XP-G, which represent functional deficiencies in seven different genes, all of which are believed to be involved in NER. The main clinical feature of XP is various forms of skin cancers; however, neurological degeneration is present in XPA, XPB, XPD and XPG complementation groups. The relationship between NER and other types of DNA repair processes is now becoming evident but the exact relationships between the different complementation groups remains to be precisely determined. Using gene expression analysis we have identified similarities and differences after UV light exposure between the complementation groups XP-A, XP-C, XP-D, XP-E, XP-F, XP-G and an unaffected control. The results reveal that there is a graded change in gene expression patterns between the mildest, most similar to the control response (XP-E and the severest form (XP-A of the disease, with the exception of XP-D. Distinct differences between the complementation groups with neurological symptoms (XP-A, XP-D and XP-G and without (XP-C, XP-E and XP-F were also identified. Therefore, this analysis has revealed distinct gene expression profiles for the XP complementation groups and the first step towards understanding the neurological symptoms of XP.

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

    Science.gov (United States)

    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

  3. Transcriptome-Wide Differential Gene Expression in Bicyclus anynana Butterflies: Female Vision-Related Genes Are More Plastic.

    Science.gov (United States)

    Macias-Muñoz, Aide; Smith, Gilbert; Monteiro, Antónia; Briscoe, Adriana D

    2016-01-01

    Vision is energetically costly to maintain. Consequently, over time many cave-adapted species downregulate the expression of vision genes or even lose their eyes and associated eye genes entirely. Alternatively, organisms that live in fluctuating environments, with different requirements for vision at different times, may evolve phenotypic plasticity for expression of vision genes. Here, we use a global transcriptomic and candidate gene approach to compare gene expression in the heads of a polyphenic butterfly. Bicyclus anynana have two seasonal forms that display sexual dimorphism and plasticity in eye morphology, and female-specific plasticity in opsin gene expression. Nonchoosy dry season females downregulate opsin expression, consistent with the high physiological cost of vision. To identify other genes associated with sexually dimorphic and seasonally plastic differences in vision, we analyzed RNA-sequencing data from whole head tissues. We identified two eye development genes (klarsicht and warts homologs) and an eye pigment biosynthesis gene (henna) differentially expressed between seasonal forms. By comparing sex-specific expression across seasonal forms, we found that klarsicht, warts, henna, and another eye development gene (domeless) were plastic in a female-specific manner. In a male-only analysis, white (w) was differentially expressed between seasonal forms. Reverse transcription polymerase chain reaction confirmed that warts and white are expressed in eyes only, whereas klarsicht, henna and domeless are expressed in both eyes and brain. We find that differential expression of eye development and eye pigment genes is associated with divergent eye phenotypes in B. anynana seasonal forms, and that there is a larger effect of season on female vision-related genes. PMID:26371082

  4. Studying the Complex Expression Dependences between Sets of Coexpressed Genes

    Directory of Open Access Journals (Sweden)

    Mario Huerta

    2014-01-01

    Full Text Available Organisms simplify the orchestration of gene expression by coregulating genes whose products function together in the cell. The use of clustering methods to obtain sets of coexpressed genes from expression arrays is very common; nevertheless there are no appropriate tools to study the expression networks among these sets of coexpressed genes. The aim of the developed tools is to allow studying the complex expression dependences that exist between sets of coexpressed genes. For this purpose, we start detecting the nonlinear expression relationships between pairs of genes, plus the coexpressed genes. Next, we form networks among sets of coexpressed genes that maintain nonlinear expression dependences between all of them. The expression relationship between the sets of coexpressed genes is defined by the expression relationship between the skeletons of these sets, where this skeleton represents the coexpressed genes with a well-defined nonlinear expression relationship with the skeleton of the other sets. As a result, we can study the nonlinear expression relationships between a target gene and other sets of coexpressed genes, or start the study from the skeleton of the sets, to study the complex relationships of activation and deactivation between the sets of coexpressed genes that carry out the different cellular processes present in the expression experiments.

  5. Mining gene expression data by interpreting principal components

    Directory of Open Access Journals (Sweden)

    Mortazavi Ali

    2006-04-01

    Full Text Available Abstract Background There are many methods for analyzing microarray data that group together genes having similar patterns of expression over all conditions tested. However, in many instances the biologically important goal is to identify relatively small sets of genes that share coherent expression across only some conditions, rather than all or most conditions as required in traditional clustering; e.g. genes that are highly up-regulated and/or down-regulated similarly across only a subset of conditions. Equally important is the need to learn which conditions are the decisive ones in forming such gene sets of interest, and how they relate to diverse conditional covariates, such as disease diagnosis or prognosis. Results We present a method for automatically identifying such candidate sets of biologically relevant genes using a combination of principal components analysis and information theoretic metrics. To enable easy use of our methods, we have developed a data analysis package that facilitates visualization and subsequent data mining of the independent sources of significant variation present in gene microarray expression datasets (or in any other similarly structured high-dimensional dataset. We applied these tools to two public datasets, and highlight sets of genes most affected by specific subsets of conditions (e.g. tissues, treatments, samples, etc.. Statistically significant associations for highlighted gene sets were shown via global analysis for Gene Ontology term enrichment. Together with covariate associations, the tool provides a basis for building testable hypotheses about the biological or experimental causes of observed variation. Conclusion We provide an unsupervised data mining technique for diverse microarray expression datasets that is distinct from major methods now in routine use. In test uses, this method, based on publicly available gene annotations, appears to identify numerous sets of biologically relevant genes. It

  6. Bi-clustering gene expression data under constraints

    OpenAIRE

    Le, Thanh; Fierro Gutiérrez, Ana Carolina Elisa; Guns, Tias; van Leeuwen, Matthijs; Nijssen, Siegfried; De Raedt, Luc; Marchal, Kathleen

    2013-01-01

    This paper presents a constraint-based approach to mining bi-clusters in gene expression data. Instead of designing an algorithm for each specific task, we propose to use constraint programming to turn the mining problem into a constraint satisfaction and/or optimisation problem. We demonstrate this promising approach on two cases. The first is to mine a single constant-row bi-cluster under noise constraints. The second is to mine a set of generic noisy constant-row bi-clusters under structu...

  7. Gene expression in developing watermelon fruit

    Directory of Open Access Journals (Sweden)

    Hernandez Alvaro

    2008-06-01

    Full Text Available Abstract Background Cultivated watermelon form large fruits that are highly variable in size, shape, color, and content, yet have extremely narrow genetic diversity. Whereas a plethora of genes involved in cell wall metabolism, ethylene biosynthesis, fruit softening, and secondary metabolism during fruit development and ripening have been identified in other plant species, little is known of the genes involved in these processes in watermelon. A microarray and quantitative Real-Time PCR-based study was conducted in watermelon [Citrullus lanatus (Thunb. Matsum. & Nakai var. lanatus] in order to elucidate the flow of events associated with fruit development and ripening in this species. RNA from three different maturation stages of watermelon fruits, as well as leaf, were collected from field grown plants during three consecutive years, and analyzed for gene expression using high-density photolithography microarrays and quantitative PCR. Results High-density photolithography arrays, composed of probes of 832 EST-unigenes from a subtracted, fruit development, cDNA library of watermelon were utilized to examine gene expression at three distinct time-points in watermelon fruit development. Analysis was performed with field-grown fruits over three consecutive growing seasons. Microarray analysis identified three hundred and thirty-five unique ESTs that are differentially regulated by at least two-fold in watermelon fruits during the early, ripening, or mature stage when compared to leaf. Of the 335 ESTs identified, 211 share significant homology with known gene products and 96 had no significant matches with any database accession. Of the modulated watermelon ESTs related to annotated genes, a significant number were found to be associated with or involved in the vascular system, carotenoid biosynthesis, transcriptional regulation, pathogen and stress response, and ethylene biosynthesis. Ethylene bioassays, performed with a closely related watermelon

  8. Gene Expression Profile Changes in Germinating Rice

    Institute of Scientific and Technical Information of China (English)

    Dongli He; Chao Han; Pingfang Yang

    2011-01-01

    Water absorption is a prerequisite for seed germination.During imbibition,water influx causes the resumption of many physiological and metabolic processes in growing seed.In order to obtain more complete knowledge about the mechanism of seed germination,two-dimensional gel electrophoresis was applied to investigate the protein profile changes of rice seed during the first 48 h of imbibition.Thirtynine differentially expressed proteins were identified,including 19 down-regulated and 20 up-regulated proteins.Storage proteins and some seed development- and desiccation-associated proteins were down regulated.The changed patterns of these proteins indicated extensive mobilization of seed reserves.By contrast,catabolism-associated proteins were up regulated upon imbibition.Semi-quantitative real time polymerase chain reaction analysis showed that most of the genes encoding the down- or upregulated proteins were also down or up regulated at mRNA level.The expression of these genes was largely consistent at mRNA and protein levels.In providing additional information concerning gene regulation in early plant life,this study will facilitate understanding of the molecular mechanisms of seed germination.

  9. Monoallelic expression of the human FOXP2 speech gene

    OpenAIRE

    Adegbola, Abidemi A.; Cox, Gerald F.; Bradshaw, Elizabeth M.; Hafler, David A.; Gimelbrant, Alexander; Chess, Andrew

    2014-01-01

    The recent descriptions of widespread random monoallelic expression (RMAE) of genes distributed throughout the autosomal genome indicate that there are more genes subject to RMAE on autosomes than the number of genes on the X chromosome where X-inactivation dictates RMAE of X-linked genes. Several of the autosomal genes that undergo RMAE have independently been implicated in human Mendelian disorders. Thus, parsing the relationship between allele-specific expression of these genes and disease...

  10. Novel redox nanomedicine improves gene expression of polyion complex vector

    OpenAIRE

    Kazuko Toh, Toru Yoshitomi, Yutaka Ikeda and Yukio Nagasaki

    2011-01-01

    Gene therapy has generated worldwide attention as a new medical technology. While non-viral gene vectors are promising candidates as gene carriers, they have several issues such as toxicity and low transfection efficiency. We have hypothesized that the generation of reactive oxygen species (ROS) affects gene expression in polyplex supported gene delivery systems. The effect of ROS on the gene expression of polyplex was evaluated using a nitroxide radical-containing nanoparticle (RNP) as an RO...

  11. Nuclear AXIN2 represses MYC gene expression

    Energy Technology Data Exchange (ETDEWEB)

    Rennoll, Sherri A.; Konsavage, Wesley M.; Yochum, Gregory S., E-mail: gsy3@psu.edu

    2014-01-03

    Highlights: •AXIN2 localizes to cytoplasmic and nuclear compartments in colorectal cancer cells. •Nuclear AXIN2 represses the activity of Wnt-responsive luciferase reporters. •β-Catenin bridges AXIN2 to TCF transcription factors. •AXIN2 binds the MYC promoter and represses MYC gene expression. -- Abstract: The β-catenin transcriptional coactivator is the key mediator of the canonical Wnt signaling pathway. In the absence of Wnt, β-catenin associates with a cytosolic and multi-protein destruction complex where it is phosphorylated and targeted for proteasomal degradation. In the presence of Wnt, the destruction complex is inactivated and β-catenin translocates into the nucleus. In the nucleus, β-catenin binds T-cell factor (TCF) transcription factors to activate expression of c-MYC (MYC) and Axis inhibition protein 2 (AXIN2). AXIN2 is a member of the destruction complex and, thus, serves in a negative feedback loop to control Wnt/β-catenin signaling. AXIN2 is also present in the nucleus, but its function within this compartment is unknown. Here, we demonstrate that AXIN2 localizes to the nuclei of epithelial cells within normal and colonic tumor tissues as well as colorectal cancer cell lines. In the nucleus, AXIN2 represses expression of Wnt/β-catenin-responsive luciferase reporters and forms a complex with β-catenin and TCF. We demonstrate that AXIN2 co-occupies β-catenin/TCF complexes at the MYC promoter region. When constitutively localized to the nucleus, AXIN2 alters the chromatin structure at the MYC promoter and directly represses MYC gene expression. These findings suggest that nuclear AXIN2 functions as a rheostat to control MYC expression in response to Wnt/β-catenin signaling.

  12. Nuclear AXIN2 represses MYC gene expression

    International Nuclear Information System (INIS)

    Highlights: •AXIN2 localizes to cytoplasmic and nuclear compartments in colorectal cancer cells. •Nuclear AXIN2 represses the activity of Wnt-responsive luciferase reporters. •β-Catenin bridges AXIN2 to TCF transcription factors. •AXIN2 binds the MYC promoter and represses MYC gene expression. -- Abstract: The β-catenin transcriptional coactivator is the key mediator of the canonical Wnt signaling pathway. In the absence of Wnt, β-catenin associates with a cytosolic and multi-protein destruction complex where it is phosphorylated and targeted for proteasomal degradation. In the presence of Wnt, the destruction complex is inactivated and β-catenin translocates into the nucleus. In the nucleus, β-catenin binds T-cell factor (TCF) transcription factors to activate expression of c-MYC (MYC) and Axis inhibition protein 2 (AXIN2). AXIN2 is a member of the destruction complex and, thus, serves in a negative feedback loop to control Wnt/β-catenin signaling. AXIN2 is also present in the nucleus, but its function within this compartment is unknown. Here, we demonstrate that AXIN2 localizes to the nuclei of epithelial cells within normal and colonic tumor tissues as well as colorectal cancer cell lines. In the nucleus, AXIN2 represses expression of Wnt/β-catenin-responsive luciferase reporters and forms a complex with β-catenin and TCF. We demonstrate that AXIN2 co-occupies β-catenin/TCF complexes at the MYC promoter region. When constitutively localized to the nucleus, AXIN2 alters the chromatin structure at the MYC promoter and directly represses MYC gene expression. These findings suggest that nuclear AXIN2 functions as a rheostat to control MYC expression in response to Wnt/β-catenin signaling

  13. Performance Analysis of Enhanced Clustering Algorithm for Gene Expression Data

    CERN Document Server

    Chandrasekhar, T; Elayaraja, E

    2011-01-01

    Microarrays are made it possible to simultaneously monitor the expression profiles of thousands of genes under various experimental conditions. It is used to identify the co-expressed genes in specific cells or tissues that are actively used to make proteins. This method is used to analysis the gene expression, an important task in bioinformatics research. Cluster analysis of gene expression data has proved to be a useful tool for identifying co-expressed genes, biologically relevant groupings of genes and samples. In this paper we applied K-Means with Automatic Generations of Merge Factor for ISODATA- AGMFI. Though AGMFI has been applied for clustering of Gene Expression Data, this proposed Enhanced Automatic Generations of Merge Factor for ISODATA- EAGMFI Algorithms overcome the drawbacks of AGMFI in terms of specifying the optimal number of clusters and initialization of good cluster centroids. Experimental results on Gene Expression Data show that the proposed EAGMFI algorithms could identify compact clus...

  14. Down-Regulation of Gene Expression by RNA-Induced Gene Silencing

    Science.gov (United States)

    Travella, Silvia; Keller, Beat

    Down-regulation of endogenous genes via post-transcriptional gene silencing (PTGS) is a key to the characterization of gene function in plants. Many RNA-based silencing mechanisms such as post-transcriptional gene silencing, co-suppression, quelling, and RNA interference (RNAi) have been discovered among species of different kingdoms (plants, fungi, and animals). One of the most interesting discoveries was RNAi, a sequence-specific gene-silencing mechanism initiated by the introduction of double-stranded RNA (dsRNA), homologous in sequence to the silenced gene, which triggers degradation of mRNA. Infection of plants with modified viruses can also induce RNA silencing and is referred to as virus-induced gene silencing (VIGS). In contrast to insertional mutagenesis, these emerging new reverse genetic approaches represent a powerful tool for exploring gene function and for manipulating gene expression experimentally in cereal species such as barley and wheat. We examined how RNAi and VIGS have been used to assess gene function in barley and wheat, including molecular mechanisms involved in the process and available methodological elements, such as vectors, inoculation procedures, and analysis of silenced phenotypes.

  15. Molecular mechanisms of curcumin action: gene expression.

    Science.gov (United States)

    Shishodia, Shishir

    2013-01-01

    Curcumin derived from the tropical plant Curcuma longa has a long history of use as a dietary agent, food preservative, and in traditional Asian medicine. It has been used for centuries to treat biliary disorders, anorexia, cough, diabetic wounds, hepatic disorders, rheumatism, and sinusitis. The preventive and therapeutic properties of curcumin are associated with its antioxidant, anti-inflammatory, and anticancer properties. Extensive research over several decades has attempted to identify the molecular mechanisms of curcumin action. Curcumin modulates numerous molecular targets by altering their gene expression, signaling pathways, or through direct interaction. Curcumin regulates the expression of inflammatory cytokines (e.g., TNF, IL-1), growth factors (e.g., VEGF, EGF, FGF), growth factor receptors (e.g., EGFR, HER-2, AR), enzymes (e.g., COX-2, LOX, MMP9, MAPK, mTOR, Akt), adhesion molecules (e.g., ELAM-1, ICAM-1, VCAM-1), apoptosis related proteins (e.g., Bcl-2, caspases, DR, Fas), and cell cycle proteins (e.g., cyclin D1). Curcumin modulates the activity of several transcription factors (e.g., NF-κB, AP-1, STAT) and their signaling pathways. Based on its ability to affect multiple targets, curcumin has the potential for the prevention and treatment of various diseases including cancers, arthritis, allergies, atherosclerosis, aging, neurodegenerative disease, hepatic disorders, obesity, diabetes, psoriasis, and autoimmune diseases. This review summarizes the molecular mechanisms of modulation of gene expression by curcumin. PMID:22996381

  16. Probing the endosperm gene expression landscape in Brassica napus

    Directory of Open Access Journals (Sweden)

    Huang Yi

    2009-06-01

    Full Text Available Abstract Background In species with exalbuminous seeds, the endosperm is eventually consumed and its space occupied by the embryo during seed development. However, the main constituent of the early developing seed is the liquid endosperm, and a significant portion of the carbon resources for the ensuing stages of seed development arrive at the embryo through the endosperm. In contrast to the extensive study of species with persistent endosperm, little is known about the global gene expression pattern in the endosperm of exalbuminous seed species such as crucifer oilseeds. Results We took a multiparallel approach that combines ESTs, protein profiling and microarray analyses to look into the gene expression landscape in the endosperm of the oilseed crop Brassica napus. An EST collection of over 30,000 entries allowed us to detect close to 10,000 unisequences expressed in the endosperm. A protein profile analysis of more than 800 proteins corroborated several signature pathways uncovered by abundant ESTs. Using microarray analyses, we identified genes that are differentially or highly expressed across all developmental stages. These complementary analyses provided insight on several prominent metabolic pathways in the endosperm. We also discovered that a transcription factor LEAFY COTYLEDON (LEC1 was highly expressed in the endosperm and that the regulatory cascade downstream of LEC1 operates in the endosperm. Conclusion The endosperm EST collection and the microarray dataset provide a basic genomic resource for dissecting metabolic and developmental events important for oilseed improvement. Our findings on the featured metabolic processes and the LEC1 regulatory cascade offer new angles for investigation on the integration of endosperm gene expression with embryo development and storage product deposition in seed development.

  17. The gene expression profiling of hepatocellular carcinoma by a network analysis approach shows a dominance of intrinsically disordered proteins (IDPs) between hub nodes.

    Science.gov (United States)

    Singh, Sakshi; Colonna, Giovanni; Di Bernardo, Giovanni; Bergantino, Francesca; Cammarota, Marcella; Castello, Giuseppe; Costantini, Susan

    2015-11-01

    We have analyzed the transcriptomic data from patients with hepatocellular carcinoma (HCC) after viral HCV infection at the various stages of the disease by means of a networking analysis using the publicly available E-MTAB-950 dataset. The data was compared with those obtained in our group from HepG2 cells, a cancer cell line that lacks the viral infection. By sequential pruning of data, and also taking into account the data from cells of healthy patients as blanks, we were able to obtain a distribution of hub genes for the various stages that characterize the disease and finally, we isolated a metabolic sub-net specific to HCC alone. The general picture is that the basic organization to energetically and metabolically sustain the cells in both the normal and diseased conditions is the same, but a complex cluster of sub-networks controlled by hub genes drives the HCC progression with high metabolic flexibility and plasticity. In particular, we have extracted a sub-net of genes strictly correlated to other hub genes of the network from HepG2 cells, but specific for the HCC and mainly devoted to: (i) control at chromatin levels of cell division; (ii) control of ergastoplasmatic stress through protein degradation and misfolding; (iii) control of the immune response also through an increase of mature T-cells in the thymus. This sub-net is characterized by 26 hub genes coding for intrinsically disordered proteins with a high ability to interact with numerous molecular partners. Moreover, we have also noted that periphery molecules, that is, with one or very few interactions (e.g., cytokines or post-translational enzymes), which do not have a central role in the clusters that make up the global metabolic network, essentially have roles as information transporters. The results evidence a strong presence of intrinsically disordered proteins with key roles as hubs in the sub-networks that characterize the various stages of the disease, conferring a structural plasticity to

  18. Predictive modelling of gene expression from transcriptional regulatory elements.

    Science.gov (United States)

    Budden, David M; Hurley, Daniel G; Crampin, Edmund J

    2015-07-01

    Predictive modelling of gene expression provides a powerful framework for exploring the regulatory logic underpinning transcriptional regulation. Recent studies have demonstrated the utility of such models in identifying dysregulation of gene and miRNA expression associated with abnormal patterns of transcription factor (TF) binding or nucleosomal histone modifications (HMs). Despite the growing popularity of such approaches, a comparative review of the various modelling algorithms and feature extraction methods is lacking. We define and compare three methods of quantifying pairwise gene-TF/HM interactions and discuss their suitability for integrating the heterogeneous chromatin immunoprecipitation (ChIP)-seq binding patterns exhibited by TFs and HMs. We then construct log-linear and ϵ-support vector regression models from various mouse embryonic stem cell (mESC) and human lymphoblastoid (GM12878) data sets, considering both ChIP-seq- and position weight matrix- (PWM)-derived in silico TF-binding. The two algorithms are evaluated both in terms of their modelling prediction accuracy and ability to identify the established regulatory roles of individual TFs and HMs. Our results demonstrate that TF-binding and HMs are highly predictive of gene expression as measured by mRNA transcript abundance, irrespective of algorithm or cell type selection and considering both ChIP-seq and PWM-derived TF-binding. As we encourage other researchers to explore and develop these results, our framework is implemented using open-source software and made available as a preconfigured bootable virtual environment. PMID:25231769

  19. Refining gene signatures: a Bayesian approach

    Directory of Open Access Journals (Sweden)

    Labbe Aurélie

    2009-12-01

    Full Text Available Abstract Background In high density arrays, the identification of relevant genes for disease classification is complicated by not only the curse of dimensionality but also the highly correlated nature of the array data. In this paper, we are interested in the question of how many and which genes should be selected for a disease class prediction. Our work consists of a Bayesian supervised statistical learning approach to refine gene signatures with a regularization which penalizes for the correlation between the variables selected. Results Our simulation results show that we can most often recover the correct subset of genes that predict the class as compared to other methods, even when accuracy and subset size remain the same. On real microarray datasets, we show that our approach can refine gene signatures to obtain either the same or better predictive performance than other existing methods with a smaller number of genes. Conclusions Our novel Bayesian approach includes a prior which penalizes highly correlated features in model selection and is able to extract key genes in the highly correlated context of microarray data. The methodology in the paper is described in the context of microarray data, but can be applied to any array data (such as micro RNA, for example as a first step towards predictive modeling of cancer pathways. A user-friendly software implementation of the method is available.

  20. Global expression differences and tissue specific expression differences in rice evolution result in two contrasting types of differentially expressed genes

    KAUST Repository

    Horiuchi, Youko

    2015-12-23

    Background Since the development of transcriptome analysis systems, many expression evolution studies characterized evolutionary forces acting on gene expression, without explicit discrimination between global expression differences and tissue specific expression differences. However, different types of gene expression alteration should have different effects on an organism, the evolutionary forces that act on them might be different, and different types of genes might show different types of differential expression between species. To confirm this, we studied differentially expressed (DE) genes among closely related groups that have extensive gene expression atlases, and clarified characteristics of different types of DE genes including the identification of regulating loci for differential expression using expression quantitative loci (eQTL) analysis data. Results We detected differentially expressed (DE) genes between rice subspecies in five homologous tissues that were verified using japonica and indica transcriptome atlases in public databases. Using the transcriptome atlases, we classified DE genes into two types, global DE genes and changed-tissues DE genes. Global type DE genes were not expressed in any tissues in the atlas of one subspecies, however changed-tissues type DE genes were expressed in both subspecies with different tissue specificity. For the five tissues in the two japonica-indica combinations, 4.6 ± 0.8 and 5.9 ± 1.5 % of highly expressed genes were global and changed-tissues DE genes, respectively. Changed-tissues DE genes varied in number between tissues, increasing linearly with the abundance of tissue specifically expressed genes in the tissue. Molecular evolution of global DE genes was rapid, unlike that of changed-tissues DE genes. Based on gene ontology, global and changed-tissues DE genes were different, having no common GO terms. Expression differences of most global DE genes were regulated by cis-eQTLs. Expression

  1. Use of bacterially expressed dsRNA to downregulate Entamoeba histolytica gene expression.

    Directory of Open Access Journals (Sweden)

    Carlos F Solis

    Full Text Available BACKGROUND: Modern RNA interference (RNAi methodologies using small interfering RNA (siRNA oligonucleotide duplexes or episomally synthesized hairpin RNA are valuable tools for the analysis of gene function in the protozoan parasite Entamoeba histolytica. However, these approaches still require time-consuming procedures including transfection and drug selection, or costly synthetic molecules. PRINCIPAL FINDINGS: Here we report an efficient and handy alternative for E. histolytica gene down-regulation mediated by bacterial double-stranded RNA (dsRNA targeting parasite genes. The Escherichia coli strain HT115 which is unable to degrade dsRNA, was genetically engineered to produce high quantities of long dsRNA segments targeting the genes that encode E. histolytica beta-tubulin and virulence factor KERP1. Trophozoites cultured in vitro were directly fed with dsRNA-expressing bacteria or soaked with purified dsRNA. Both dsRNA delivery methods resulted in significant reduction of protein expression. In vitro host cell-parasite assays showed that efficient downregulation of kerp1 gene expression mediated by bacterial dsRNA resulted in significant reduction of parasite adhesion and lytic capabilities, thus supporting a major role for KERP1 in the pathogenic process. Furthermore, treatment of trophozoites cultured in microtiter plates, with a repertoire of eighty-five distinct bacterial dsRNA segments targeting E. histolytica genes with unknown function, led to the identification of three genes potentially involved in the growth of the parasite. CONCLUSIONS: Our results showed that the use of bacterial dsRNA is a powerful method for the study of gene function in E. histolytica. This dsRNA delivery method is also technically suitable for the study of a large number of genes, thus opening interesting perspectives for the identification of novel drug and vaccine targets.

  2. Wavelet based approach for facial expression recognition

    Directory of Open Access Journals (Sweden)

    Zaenal Abidin

    2015-03-01

    Full Text Available Facial expression recognition is one of the most active fields of research. Many facial expression recognition methods have been developed and implemented. Neural networks (NNs have capability to undertake such pattern recognition tasks. The key factor of the use of NN is based on its characteristics. It is capable in conducting learning and generalizing, non-linear mapping, and parallel computation. Backpropagation neural networks (BPNNs are the approach methods that mostly used. In this study, BPNNs were used as classifier to categorize facial expression images into seven-class of expressions which are anger, disgust, fear, happiness, sadness, neutral and surprise. For the purpose of feature extraction tasks, three discrete wavelet transforms were used to decompose images, namely Haar wavelet, Daubechies (4 wavelet and Coiflet (1 wavelet. To analyze the proposed method, a facial expression recognition system was built. The proposed method was tested on static images from JAFFE database.

  3. Divergence in gene expression within and between two closely related flycatcher species.

    Science.gov (United States)

    Uebbing, Severin; Künstner, Axel; Mäkinen, Hannu; Backström, Niclas; Bolivar, Paulina; Burri, Reto; Dutoit, Ludovic; Mugal, Carina F; Nater, Alexander; Aken, Bronwen; Flicek, Paul; Martin, Fergal J; Searle, Stephen M J; Ellegren, Hans

    2016-05-01

    Relatively little is known about the character of gene expression evolution as species diverge. It is for instance unclear if gene expression generally evolves in a clock-like manner (by stabilizing selection or neutral evolution) or if there are frequent episodes of directional selection. To gain insights into the evolutionary divergence of gene expression, we sequenced and compared the transcriptomes of multiple organs from population samples of collared (Ficedula albicollis) and pied flycatchers (F. hypoleuca), two species which diverged less than one million years ago. Ordination analysis separated samples by organ rather than by species. Organs differed in their degrees of expression variance within species and expression divergence between species. Variance was negatively correlated with expression breadth and protein interactivity, suggesting that pleiotropic constraints reduce gene expression variance within species. Variance was correlated with between-species divergence, consistent with a pattern expected from stabilizing selection and neutral evolution. Using an expression PST approach, we identified genes differentially expressed between species and found 16 genes uniquely expressed in one of the species. For one of these, DPP7, uniquely expressed in collared flycatcher, the absence of expression in pied flycatcher could be associated with a ≈20-kb deletion including 11 of 13 exons. This study of a young vertebrate speciation model system expands our knowledge of how gene expression evolves as natural populations become reproductively isolated. PMID:26928872

  4. Stochastic gene expression with bursting and positive feedback

    Science.gov (United States)

    Platini, Thierry; Pendar, Hodjat; Kulkarni, Rahul

    2012-02-01

    Stochasticity (or noise) in the process of gene expression can play a critical role in cellular circuits that control switching between probabilistic cell-fate decisions in diverse organisms. Such circuits often include positive feedback loops as critical elements. In some cases (e.g. HIV-1 viral infections), switching between different cell fates occurs even in the absence of bistability in the underlying deterministic model. To characterize the role of noise in such systems, we analyze a simple gene expression circuit that includes contributions from both transcriptional and translational bursting and positive feedback effects. Using a combination of analytical approaches and stochastic simulations, we explore how the underlying parameters control the corresponding mean and variance in protein distributions.

  5. Gene expression profiling of cutaneous wound healing

    Directory of Open Access Journals (Sweden)

    Wang Ena

    2007-02-01

    Full Text Available Abstract Background Although the sequence of events leading to wound repair has been described at the cellular and, to a limited extent, at the protein level this process has yet to be fully elucidated. Genome wide transcriptional analysis tools promise to further define the global picture of this complex progression of events. Study Design This study was part of a placebo-controlled double-blind clinical trial in which basal cell carcinomas were treated topically with an immunomodifier – toll-like receptor 7 agonist: imiquimod. The fourteen patients with basal cell carcinoma in the placebo arm of the trial received placebo treatment consisting solely of vehicle cream. A skin punch biopsy was obtained immediately before treatment and at the end of the placebo treatment (after 2, 4 or 8 days. 17.5K cDNA microarrays were utilized to profile the biopsy material. Results Four gene signatures whose expression changed relative to baseline (before wound induction by the pre-treatment biopsy were identified. The largest group was comprised predominantly of inflammatory genes whose expression was increased throughout the study. Two additional signatures were observed which included preferentially pro-inflammatory genes in the early post-treatment biopsies (2 days after pre-treatment biopsies and repair and angiogenesis genes in the later (4 to 8 days biopsies. The fourth and smallest set of genes was down-regulated throughout the study. Early in wound healing the expression of markers of both M1 and M2 macrophages were increased, but later M2 markers predominated. Conclusion The initial response to a cutaneous wound induces powerful transcriptional activation of pro-inflammatory stimuli which may alert the host defense. Subsequently and in the absence of infection, inflammation subsides and it is replaced by angiogenesis and remodeling. Understanding this transition which may be driven by a change from a mixed macrophage population to predominately M2

  6. Gene Expression Control by Glucocorticoid Receptors during Innate Immune Responses

    Directory of Open Access Journals (Sweden)

    André M. Xavier

    2016-04-01

    Full Text Available Glucocorticoids (GCs are potent anti-inflammatory compounds that have been extensively used in clinical practice for several decades. GCs effects on inflammation are generally mediated through GC receptors (GRs. Signal transduction through these nuclear receptors leads to dramatic changes in gene expression programs in different cell types, typically due to GR binding to DNA or to transcription modulators. During the last decade the view of GCs as exclusive anti-inflammatory molecules has been challenged. GR negative interference in pro-inflammatory gene expression was a landmark in terms of molecular mechanisms that suppress immune activity. In fact, GR can induce varied inhibitory molecules, including a negative regulator of Toll-like receptors (TLRs pathway, or subject key transcription factors, such as NF-B and AP-1, to a repressor mechanism. In contrast, the expression of some acute-phase proteins (APPs and other players of innate immunity generally requires GR signaling. Consequently, GRs must operate context-dependent inhibitory, permissive or stimulatory effects on host defense signaling triggered by pathogens or tissue damage. This review aims to disclose how contradictory or comparable effects on inflammatory gene expression can depend on pharmacological approach (including selective glucocorticoid receptor modulators; SEGRMs, cell culture, animal treatment or transgenic strategies used as models. Although the current view of GR-signaling integrated many advances in the field, some answers to important questions remain elusive.

  7. Gene Expression Control by Glucocorticoid Receptors during Innate Immune Responses

    Science.gov (United States)

    Xavier, Andre Machado; Anunciato, Aparecida Kataryna Olimpio; Rosenstock, Tatiana Rosado; Glezer, Isaias

    2016-01-01

    Glucocorticoids (GCs) are potent anti-inflammatory compounds that have been extensively used in clinical practice for several decades. GC’s effects on inflammation are generally mediated through GC receptors (GRs). Signal transduction through these nuclear receptors leads to dramatic changes in gene expression programs in different cell types, typically due to GR binding to DNA or to transcription modulators. During the last decade, the view of GCs as exclusive anti-inflammatory molecules has been challenged. GR negative interference in pro-inflammatory gene expression was a landmark in terms of molecular mechanisms that suppress immune activity. In fact, GR can induce varied inhibitory molecules, including a negative regulator of Toll-like receptors pathway, or subject key transcription factors, such as NF-κB and AP-1, to a repressor mechanism. In contrast, the expression of some acute-phase proteins and other players of innate immunity generally requires GR signaling. Consequently, GRs must operate context-dependent inhibitory, permissive, or stimulatory effects on host defense signaling triggered by pathogens or tissue damage. This review aims to disclose how contradictory or comparable effects on inflammatory gene expression can depend on pharmacological approach (including selective GC receptor modulators; SEGRMs), cell culture, animal treatment, or transgenic strategies used as models. Although the current view of GR-signaling integrated many advances in the field, some answers to important questions remain elusive. PMID:27148162

  8. Network Completion for Static Gene Expression Data

    Directory of Open Access Journals (Sweden)

    Natsu Nakajima

    2014-01-01

    Full Text Available We tackle the problem of completing and inferring genetic networks under stationary conditions from static data, where network completion is to make the minimum amount of modifications to an initial network so that the completed network is most consistent with the expression data in which addition of edges and deletion of edges are basic modification operations. For this problem, we present a new method for network completion using dynamic programming and least-squares fitting. This method can find an optimal solution in polynomial time if the maximum indegree of the network is bounded by a constant. We evaluate the effectiveness of our method through computational experiments using synthetic data. Furthermore, we demonstrate that our proposed method can distinguish the differences between two types of genetic networks under stationary conditions from lung cancer and normal gene expression data.

  9. Quantitative analysis of cell-type specific gene expression in the green alga Volvox carteri

    Directory of Open Access Journals (Sweden)

    Hallmann Armin

    2006-12-01

    Full Text Available Abstract Background The multicellular alga Volvox carteri possesses only two cell types: mortal, motile somatic cells and potentially immortal, immotile reproductive cells. It is therefore an attractive model system for studying how cell-autonomous cytodifferentiation is programmed within a genome. Moreover, there are ongoing genome projects both in Volvox carteri and in the closely related unicellular alga Chlamydomonas reinhardtii. However, gene sequencing is only the beginning. To identify cell-type specific expression and to determine relative expression rates, we evaluate the potential of real-time RT-PCR for quantifying gene transcript levels. Results Here we analyze a diversified pool of 39 target genes by real-time RT-PCR for each cell type. This gene pool contains previously known genes with unknown localization of cellular expression, 28 novel genes which are described in this study for the first time, and a few known, cell-type specific genes as a control. The respective gene products are, for instance, part of photosynthesis, cellular regulation, stress response, or transport processes. We provide expression data for all these genes. Conclusion The results show that quantitative real-time RT-PCR is a favorable approach to analyze cell-type specific gene expression in Volvox, which can be extended to a much larger number of genes or to developmental or metabolic mutants. Our expression data also provide a basis for a detailed analysis of individual, previously unknown, cell-type specifically expressed genes.

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

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    Rasley Amy

    2006-06-01

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

  11. Ascorbic Acid and Gene Expression: Another Example of Regulation of Gene Expression by Small Molecules?

    OpenAIRE

    Belin, Sophie; Kaya, Ferdinand; Burtey, Stéphane; Fontes, Michel

    2010-01-01

    Ascorbic acid (vitamin C, AA) has long been considered a food supplement necessary for life and for preventing scurvy. However, it has been reported that other small molecules such as retinoic acid (vitamin A) and different forms of calciferol (vitamin D) are directly involved in regulating the expression of numerous genes. These molecules bind to receptors that are differentially expressed in the embryo and are therefore crucial signalling molecules in vertebrate development. The question is...

  12. Detection of gene expression pattern in the early stage after spinal cord injury by gene chip

    Institute of Scientific and Technical Information of China (English)

    刘成龙; 靳安民; 童斌辉

    2003-01-01

    Objective: To study the changes of the gene expression pattern of spinal cord tissues in the early stage after injury by DNA microarray (gene chip). Methods: The contusion model of rat spinal cord was established according to Allen's falling strike method and the gene expression patterns of normal and injured spinal cord tissues were studied by gene chip. Results: The expression of 45 genes was significantly changed in the early stage after spinal cord injury, in which 22 genes up-regulated and 23 genes down-regulated. Conclusions: The expression of some genes changes significantly in the early stage after spinal cord injury, which indicates the complexity of secondary spinal cord injury.

  13. Dynamic Gene Expression in the Human Cerebral Cortex Distinguishes Children from Adults

    OpenAIRE

    Sterner, Kirstin N.; Weckle, Amy; Chugani, Harry T.; Tarca, Adi L.; Sherwood, Chet C.; Hof, Patrick R; Kuzawa, Christopher W.; Boddy, Amy M.; Abbas, Asad; Raaum, Ryan L.; Grégoire, Lucie; Lipovich, Leonard; Grossman, Lawrence I; Uddin, Monica; Goodman, Morris

    2012-01-01

    In comparison with other primate species, humans have an extended juvenile period during which the brain is more plastic. In the current study we sought to examine gene expression in the cerebral cortex during development in the context of this adaptive plasticity. We introduce an approach designed to discriminate genes with variable as opposed to uniform patterns of gene expression and found that greater inter-individual variance is observed among children than among adults. For the 337 tran...

  14. MDR1 gene expression in primary colorectal carcinomas.

    OpenAIRE

    Pirker, R; Wallner, J.; Gsur, A; Götzl, M.; Zöchbauer, S; Scheithauer, W.; Depisch, D

    1993-01-01

    The expression of the MDR1 gene, a multidrug resistance gene, was prospectively determined in 113 primary colorectal carcinoma specimens and correlated with clinical data including survival durations of the patients. MDR1 RNA was detected in 65% of the carcinomas. No expression of the MDR2 gene was seen, MDR1 gene expression was independent of age and sex of the patients, size and histologic grading of the tumour, lymph node involvement and distant metastasis. Kaplan-Meier analysis revealed t...

  15. Discovery of time-delayed gene regulatory networks based on temporal gene expression profiling

    Directory of Open Access Journals (Sweden)

    Guo Zheng

    2006-01-01

    Full Text Available Abstract Background It is one of the ultimate goals for modern biological research to fully elucidate the intricate interplays and the regulations of the molecular determinants that propel and characterize the progression of versatile life phenomena, to name a few, cell cycling, developmental biology, aging, and the progressive and recurrent pathogenesis of complex diseases. The vast amount of large-scale and genome-wide time-resolved data is becoming increasing available, which provides the golden opportunity to unravel the challenging reverse-engineering problem of time-delayed gene regulatory networks. Results In particular, this methodological paper aims to reconstruct regulatory networks from temporal gene expression data by using delayed correlations between genes, i.e., pairwise overlaps of expression levels shifted in time relative each other. We have thus developed a novel model-free computational toolbox termed TdGRN (Time-delayed Gene Regulatory Network to address the underlying regulations of genes that can span any unit(s of time intervals. This bioinformatics toolbox has provided a unified approach to uncovering time trends of gene regulations through decision analysis of the newly designed time-delayed gene expression matrix. We have applied the proposed method to yeast cell cycling and human HeLa cell cycling and have discovered most of the underlying time-delayed regulations that are supported by multiple lines of experimental evidence and that are remarkably consistent with the current knowledge on phase characteristics for the cell cyclings. Conclusion We established a usable and powerful model-free approach to dissecting high-order dynamic trends of gene-gene interactions. We have carefully validated the proposed algorithm by applying it to two publicly available cell cycling datasets. In addition to uncovering the time trends of gene regulations for cell cycling, this unified approach can also be used to study the complex

  16. Regulation of gene expression by hypoxia.

    Science.gov (United States)

    Millhorn, D E; Czyzyk-Krzeska, M; Bayliss, D A; Lawson, E E

    1993-12-01

    The present study was undertaken to determine if gene expression for tyrosine hydroxylase (TH), the rate limiting enzyme in the biosynthesis of catecholamines, is regulated in the carotid body, sympathetic ganglia and adrenal medulla by hypoxia. We found that a reduction in oxygen tension from 21% to 10% caused a substantial increase (200% at 1 hour and 500% at 6 hours exposure) in the concentration of TH mRNA in carotid body type I cells but not in either the sympathetic ganglia or adrenal gland. In addition, we found that hypercapnia, another natural stimulus of carotid body activity, failed to enhance TH mRNA in type I cells. Removal of the sensory and sympathetic innervation of the carotid body failed to prevent the induction of TH mRNA by hypoxia in type I cells. Our results show that TH gene expression is regulated by hypoxia in the carotid body but not in other peripheral catecholamine synthesizing tissue and that the regulatory mechanism is intrinsic to type I cells. PMID:7909954

  17. Unsupervised meta-analysis on diverse gene expression datasets allows insight into gene function and regulation

    OpenAIRE

    Engelmann, Julia C; Roland Schwarz; Steffen Blenk; Torben Friedrich; Seibel, Philipp N.; Thomas Dandekar; Tobias Müller

    2008-01-01

    Over the past years, microarray databases have increased rapidly in size. While they offer a wealth of data, it remains challenging to integrate data arising from different studies. Here we propose an unsupervised approach of a large-scale meta-analysis on Arabidopsis thaliana whole genome expression datasets to gain additional insights into the function and regulation of genes. Applying kernel principal component analysis and hierarchical clustering, we found three major groups of experiment...

  18. Real-time feedback control of gene expression

    OpenAIRE

    Uhlendorf, Jannis

    2013-01-01

    Gene expression is fundamental for the functioning of cellular processes and is tightly regulated. Inducible promoters allow one to perturb gene expression by changing the expression level of a protein from its physiological level. This is a common tool to decipher the functioning of biological processes: the expression level of a gene is changed and one observes how the perturbed cell behaves differently from an unperturbed cell. A shortcoming of inducible promoters is the difficulty to appl...

  19. Transcript length mediates developmental timing of gene expression across Drosophila

    OpenAIRE

    Artieri, Carlo G.; Fraser, Hunter B.

    2013-01-01

    The time required to transcribe genes with long primary transcripts may limit their ability to be expressed in cells with short mitotic cycles, a phenomenon termed intron delay. As such short cycles are a hallmark of the earliest stages of insect development, we used Drosophila developmental timecourse expression data to test whether intron delay affects gene expression genome-wide, and to determine its consequences for the evolution of gene structure. We find that long zygotically expressed,...

  20. Peripheral blood gene expression profiles in COPD subjects

    OpenAIRE

    2011-01-01

    To identify non-invasive gene expression markers for chronic obstructive pulmonary disease (COPD), we performed genome-wide expression profiling of peripheral blood samples from 12 subjects with significant airflow obstruction and an equal number of non-obstructed controls. RNA was isolated from Peripheral Blood Mononuclear Cells (PBMCs) and gene expression was assessed using Affymetrix U133 Plus 2.0 arrays. Tests for gene expression changes that discriminate between COPD cases (FEV1< 70% pre...

  1. Biclustering for the comprehensive search of correlated gene expression patterns using clustered seed expansion

    OpenAIRE

    Yun, Taegyun; Yi, Gwan-Su

    2013-01-01

    Background In a functional analysis of gene expression data, biclustering method can give crucial information by showing correlated gene expression patterns under a subset of conditions. However, conventional biclustering algorithms still have some limitations to show comprehensive and stable outputs. Results We propose a novel biclustering approach called “BIclustering by Correlated and Large number of Individual Clustered seeds (BICLIC)” to find comprehensive sets of correlated expression p...

  2. Seed-Based Biclustering of Gene Expression Data

    OpenAIRE

    Jiyuan An; Alan Wee-Chung Liew; Colleen C Nelson

    2012-01-01

    BACKGROUND: Accumulated biological research outcomes show that biological functions do not depend on individual genes, but on complex gene networks. Microarray data are widely used to cluster genes according to their expression levels across experimental conditions. However, functionally related genes generally do not show coherent expression across all conditions since any given cellular process is active only under a subset of conditions. Biclustering finds gene clusters that have similar e...

  3. Tools and resources for analyzing gene expression changes in glaucomatous neurodegeneration.

    Science.gov (United States)

    Nickells, Robert W; Pelzel, Heather R

    2015-12-01

    Evaluating gene expression changes presents one of the most powerful interrogative approaches to study the molecular, biochemical, and cellular pathways associated with glaucomatous disease pathology. Technologies to study gene expression profiles in glaucoma are wide ranging. Qualitative techniques provide the power of localizing expression changes to individual cells, but are not robust to evaluate differences in expression changes. Alternatively, quantitative changes provide a high level of stringency to quantify changes in gene expression. Additionally, advances in high throughput analysis and bioinformatics have dramatically improved the number of individual genes that can be evaluated in a single experiment, while dramatically reducing amounts of input tissue/starting material. Together, gene expression profiling and proteomics have yielded new insights on the roles of neuroinflammation, the complement cascade, and metabolic shutdown as important players in the pathology of the optic nerve head and retina in this disease. PMID:25999234

  4. Positive selection on gene expression in the human brain

    DEFF Research Database (Denmark)

    Khaitovich, Philipp; Tang, Kun; Franz, Henriette;

    2006-01-01

    Recent work has shown that the expression levels of genes transcribed in the brains of humans and chimpanzees have changed less than those of genes transcribed in other tissues [1] . However, when gene expression changes are mapped onto the evolutionary lineage in which they occurred, the brain...... shows more changes than other tissues in the human lineage compared to the chimpanzee lineage [1] , [2] and [3] . There are two possible explanations for this: either positive selection drove more gene expression changes to fixation in the human brain than in the chimpanzee brain, or genes expressed in...... the brain experienced less purifying selection in humans than in chimpanzees, i.e. gene expression in the human brain is functionally less constrained. The first scenario would be supported if genes that changed their expression in the brain in the human lineage showed more selective sweeps than other...

  5. Global gene expression analysis of the zoonotic parasite Trichinella spiralis revealed novel genes in host parasite interaction.

    Directory of Open Access Journals (Sweden)

    Xiaolei Liu

    Full Text Available BACKGROUND: Trichinellosis is a typical food-borne zoonotic disease which is epidemic worldwide and the nematode Trichinella spiralis is the main pathogen. The life cycle of T. spiralis contains three developmental stages, i.e. adult worms, new borne larva (new borne L1 larva and muscular larva (infective L1 larva. Stage-specific gene expression in the parasites has been investigated with various immunological and cDNA cloning approaches, whereas the genome-wide transcriptome and expression features of the parasite have been largely unknown. The availability of the genome sequence information of T. spiralis has made it possible to deeply dissect parasite biology in association with global gene expression and pathogenesis. METHODOLOGY AND PRINCIPAL FINDINGS: In this study, we analyzed the global gene expression patterns in the three developmental stages of T. spiralis using digital gene expression (DGE analysis. Almost 15 million sequence tags were generated with the Illumina RNA-seq technology, producing expression data for more than 9,000 genes, covering 65% of the genome. The transcriptome analysis revealed thousands of differentially expressed genes within the genome, and importantly, a panel of genes encoding functional proteins associated with parasite invasion and immuno-modulation were identified. More than 45% of the genes were found to be transcribed from both strands, indicating the importance of RNA-mediated gene regulation in the development of the parasite. Further, based on gene ontological analysis, over 3000 genes were functionally categorized and biological pathways in the three life cycle stage were elucidated. CONCLUSIONS AND SIGNIFICANCE: The global transcriptome of T. spiralis in three developmental stages has been profiled, and most gene activity in the genome was found to be developmentally regulated. Many metabolic and biological pathways have been revealed. The findings of the differential expression of several protein

  6. Expression profiles for six zebrafish genes during gonadal sex differentiation

    DEFF Research Database (Denmark)

    Jørgensen, Anne; Morthorst, Jane E.; Andersen, Ole;

    2008-01-01

    the precise timing of expression of six genes previously suggested to be associated with sex differentiation in zebrafish. The current study investigates the expression of all six genes in the same individual fish with extensive sampling dates during sex determination and -differentiation. RESULTS: In...... investigated on cDNA from the same fish allowing comparison of the high and low expressers of genes that are expected to be highest expressed in either males or females. There were 78% high or low expressers of all three "male" genes (ar, sox9a and dmrt1) in the investigated period and 81% were high or low...

  7. A Resampling Based Clustering Algorithm for Replicated Gene Expression Data.

    Science.gov (United States)

    Li, Han; Li, Chun; Hu, Jie; Fan, Xiaodan

    2015-01-01

    In gene expression data analysis, clustering is a fruitful exploratory technique to reveal the underlying molecular mechanism by identifying groups of co-expressed genes. To reduce the noise, usually multiple experimental replicates are performed. An integrative analysis of the full replicate data, instead of reducing the data to the mean profile, carries the promise of yielding more precise and robust clusters. In this paper, we propose a novel resampling based clustering algorithm for genes with replicated expression measurements. Assuming those replicates are exchangeable, we formulate the problem in the bootstrap framework, and aim to infer the consensus clustering based on the bootstrap samples of replicates. In our approach, we adopt the mixed effect model to accommodate the heterogeneous variances and implement a quasi-MCMC algorithm to conduct statistical inference. Experiments demonstrate that by taking advantage of the full replicate data, our algorithm produces more reliable clusters and has robust performance in diverse scenarios, especially when the data is subject to multiple sources of variance. PMID:26671802

  8. Functional analysis of prognostic gene expression network genes in metastatic breast cancer models.

    Directory of Open Access Journals (Sweden)

    Thomas R Geiger

    Full Text Available Identification of conserved co-expression networks is a useful tool for clustering groups of genes enriched for common molecular or cellular functions [1]. The relative importance of genes within networks can frequently be inferred by the degree of connectivity, with those displaying high connectivity being significantly more likely to be associated with specific molecular functions [2]. Previously we utilized cross-species network analysis to identify two network modules that were significantly associated with distant metastasis free survival in breast cancer. Here, we validate one of the highly connected genes as a metastasis associated gene. Tpx2, the most highly connected gene within a proliferation network specifically prognostic for estrogen receptor positive (ER+ breast cancers, enhances metastatic disease, but in a tumor autonomous, proliferation-independent manner. Histologic analysis suggests instead that variation of TPX2 levels within disseminated tumor cells may influence the transition between dormant to actively proliferating cells in the secondary site. These results support the co-expression network approach for identification of new metastasis-associated genes to provide new information regarding the etiology of breast cancer progression and metastatic disease.

  9. Signal Transduction Pathways that Regulate CAB Gene Expression

    Energy Technology Data Exchange (ETDEWEB)

    Chory, Joanne

    2006-01-16

    The process of chloroplast differentiation, involves the coordinate regulation of many nuclear and chloroplast genes. The cues for the initiation of this developmental program are both extrinsic (e.g., light) and intrinsic (cell-type and plastid signals). During this project period, we utilized a molecular genetic approach to select for Arabidopsis mutants that did not respond properly to environmental light conditions, as well as mutants that were unable to perceive plastid damage. These latter mutants, called gun mutants, define two retrograde signaling pathways that regulate nuclear gene expression in response to chloroplasts. A major finding was to identify a signal from chloroplasts that regulates nuclear gene transcription. This signal is the build-up of Mg-Protoporphyrin IX, a key intermediate of the chlorophyll biosynthetic pathway. The signaling pathways downstream of this signal are currently being studied. Completion of this project has provided an increased understanding of the input signals and retrograde signaling pathways that control nuclear gene expression in response to the functional state of chloroplasts. These studies should ultimately influence our abilities to manipulate plant growth and development, and will aid in the understanding of the developmental control of photosynthesis.

  10. Signal Transduction Pathways that Regulate CAB Gene Expression

    Energy Technology Data Exchange (ETDEWEB)

    Chory, Joanne

    2004-12-31

    The process of chloroplast differentiation, involves the coordinate regulation of many nuclear and chloroplast genes. The cues for the initiation of this developmental program are both extrinsic (e.g., light) and intrinsic (cell-type and plastid signals). During this project period, we utilized a molecular genetic approach to select for Arabidopsis mutants that did not respond properly to environmental light conditions, as well as mutants that were unable to perceive plastid damage. These latter mutants, called gun mutants, define two retrograde signaling pathways that regulate nuclear gene expression in response to chloroplasts. A major finding was to identify a signal from chloroplasts that regulates nuclear gene transcription. This signal is the build-up of Mg-Protoporphyrin IX, a key intermediate of the chlorophyll biosynthetic pathway. The signaling pathways downstream of this signal are currently being studied. Completion of this project has provided an increased understanding of the input signals and retrograde signaling pathways that control nuclear gene expression in response to the functional state of chloroplasts. These studies should ultimately influence our abilities to manipulate plant growth and development, and will aid in the understanding of the developmental control of photosynthesis.

  11. Using interpolation to estimate system uncertainty in gene expression experiments.

    Directory of Open Access Journals (Sweden)

    Lee J Falin

    Full Text Available The widespread use of high-throughput experimental assays designed to measure the entire complement of a cell's genes or gene products has led to vast stores of data that are extremely plentiful in terms of the number of items they can measure in a single sample, yet often sparse in the number of samples per experiment due to their high cost. This often leads to datasets where the number of treatment levels or time points sampled is limited, or where there are very small numbers of technical and/or biological replicates. Here we introduce a novel algorithm to quantify the uncertainty in the unmeasured intervals between biological measurements taken across a set of quantitative treatments. The algorithm provides a probabilistic distribution of possible gene expression values within unmeasured intervals, based on a plausible biological constraint. We show how quantification of this uncertainty can be used to guide researchers in further data collection by identifying which samples would likely add the most information to the system under study. Although the context for developing the algorithm was gene expression measurements taken over a time series, the approach can be readily applied to any set of quantitative systems biology measurements taken following quantitative (i.e. non-categorical treatments. In principle, the method could also be applied to combinations of treatments, in which case it could greatly simplify the task of exploring the large combinatorial space of future possible measurements.

  12. Pol II-expressed shRNA knocks down Sod2 gene expression and causes phenotypes of the gene knockout in mice.

    Directory of Open Access Journals (Sweden)

    2006-01-01

    Full Text Available RNA interference (RNAi has been used increasingly for reverse genetics in invertebrates and mammalian cells, and has the potential to become an alternative to gene knockout technology in mammals. Thus far, only RNA polymerase III (Pol III-expressed short hairpin RNA (shRNA has been used to make shRNA-expressing transgenic mice. However, widespread knockdown and induction of phenotypes of gene knockout in postnatal mice have not been demonstrated. Previous studies have shown that Pol II synthesizes micro RNAs (miRNAs-the endogenous shRNAs that carry out gene silencing function. To achieve efficient gene knockdown in mammals and to generate phenotypes of gene knockout, we designed a construct in which a Pol II (ubiquitin C promoter drove the expression of an shRNA with a structure that mimics human miRNA miR-30a. Two transgenic lines showed widespread and sustained shRNA expression, and efficient knockdown of the target gene Sod2. These mice were viable but with phenotypes of SOD2 deficiency. Bigenic heterozygous mice generated by crossing these two lines showed nearly undetectable target gene expression and phenotypes consistent with the target gene knockout, including slow growth, fatty liver, dilated cardiomyopathy, and premature death. This approach opens the door of RNAi to a wide array of well-established Pol II transgenic strategies and offers a technically simpler, cheaper, and quicker alternative to gene knockout by homologous recombination for reverse genetics in mice and other mammalian species.

  13. GECKO: a complete large-scale gene expression analysis platform

    Directory of Open Access Journals (Sweden)

    Heuer Michael

    2004-12-01

    Full Text Available Abstract Background Gecko (Gene Expression: Computation and Knowledge Organization is a complete, high-capacity centralized gene expression analysis system, developed in response to the needs of a distributed user community. Results Based on a client-server architecture, with a centralized repository of typically many tens of thousands of Affymetrix scans, Gecko includes automatic processing pipelines for uploading data from remote sites, a data base, a computational engine implementing ~ 50 different analysis tools, and a client application. Among available analysis tools are clustering methods, principal component analysis, supervised classification including feature selection and cross-validation, multi-factorial ANOVA, statistical contrast calculations, and various post-processing tools for extracting data at given error rates or significance levels. On account of its open architecture, Gecko also allows for the integration of new algorithms. The Gecko framework is very general: non-Affymetrix and non-gene expression data can be analyzed as well. A unique feature of the Gecko architecture is the concept of the Analysis Tree (actually, a directed acyclic graph, in which all successive results in ongoing analyses are saved. This approach has proven invaluable in allowing a large (~ 100 users and distributed community to share results, and to repeatedly return over a span of years to older and potentially very complex analyses of gene expression data. Conclusions The Gecko system is being made publicly available as free software http://sourceforge.net/projects/geckoe. In totality or in parts, the Gecko framework should prove useful to users and system developers with a broad range of analysis needs.

  14. Monoallelic expression of the human FOXP2 speech gene.

    Science.gov (United States)

    Adegbola, Abidemi A; Cox, Gerald F; Bradshaw, Elizabeth M; Hafler, David A; Gimelbrant, Alexander; Chess, Andrew

    2015-06-01

    The recent descriptions of widespread random monoallelic expression (RMAE) of genes distributed throughout the autosomal genome indicate that there are more genes subject to RMAE on autosomes than the number of genes on the X chromosome where X-inactivation dictates RMAE of X-linked genes. Several of the autosomal genes that undergo RMAE have independently been implicated in human Mendelian disorders. Thus, parsing the relationship between allele-specific expression of these genes and disease is of interest. Mutations in the human forkhead box P2 gene, FOXP2, cause developmental verbal dyspraxia with profound speech and language deficits. Here, we show that the human FOXP2 gene undergoes RMAE. Studying an individual with developmental verbal dyspraxia, we identify a deletion 3 Mb away from the FOXP2 gene, which impacts FOXP2 gene expression in cis. Together these data suggest the intriguing possibility that RMAE impacts the haploinsufficiency phenotypes observed for FOXP2 mutations. PMID:25422445

  15. An Expression Refinement Process Ensures Singular Odorant Receptor Gene Choice.

    Science.gov (United States)

    Abdus-Saboor, Ishmail; Al Nufal, Mohammed J; Agha, Maha V; Ruinart de Brimont, Marion; Fleischmann, Alexander; Shykind, Benjamin M

    2016-04-25

    Odorant receptor (OR) gene choice in mammals is a paradigmatic example of monogenic and monoallelic transcriptional selection, in which each olfactory sensory neuron (OSN) chooses to express one OR allele from over 1,000 encoded in the genome [1-3]. This process, critical for generation of the circuit from nose to brain [4-6], is thought to occur in two steps: a slow initial phase that randomly activates a single OR allele, followed by a rapid feedback that halts subsequent expression [7-14]. Inherent in this model is a finite failure rate wherein multiple OR alleles may be activated prior to feedback suppression [15, 16]. Confronted with more than one receptor, the neuron would need to activate a refinement mechanism to eliminate multigenic OR expression and resolve unique neuronal identity [16], critical to the generation of the circuit from nose to olfactory bulb. Here we used a genetic approach in mice to reveal a new facet of OR regulation that corrects adventitious activation of multiple OR alleles, restoring monogenic OR expression and unique neuronal identity. Using the tetM71tg model system, in which the M71 OR is expressed in >95% of mature OSNs and potently suppresses the expression of the endogenous OR repertoire [10], we provide clear evidence of a post-selection refinement (PSR) process that winnows down the number of ORs. We further demonstrate that PSR efficiency is linked to OR expression level, suggesting an underlying competitive process and shedding light on OR gene switching and the fundamental mechanism of singular OR choice. PMID:27040780

  16. A chain reaction approach to modelling gene pathways.

    Science.gov (United States)

    Cheng, Gary C; Chen, Dung-Tsa; Chen, James J; Soong, Seng-Jaw; Lamartiniere, Coral; Barnes, Stephen

    2012-08-01

    BACKGROUND: Of great interest in cancer prevention is how nutrient components affect gene pathways associated with the physiological events of puberty. Nutrient-gene interactions may cause changes in breast or prostate cells and, therefore, may result in cancer risk later in life. Analysis of gene pathways can lead to insights about nutrient-gene interactions and the development of more effective prevention approaches to reduce cancer risk. To date, researchers have relied heavily upon experimental assays (such as microarray analysis, etc.) to identify genes and their associated pathways that are affected by nutrient and diets. However, the vast number of genes and combinations of gene pathways, coupled with the expense of the experimental analyses, has delayed the progress of gene-pathway research. The development of an analytical approach based on available test data could greatly benefit the evaluation of gene pathways, and thus advance the study of nutrient-gene interactions in cancer prevention. In the present study, we have proposed a chain reaction model to simulate gene pathways, in which the gene expression changes through the pathway are represented by the species undergoing a set of chemical reactions. We have also developed a numerical tool to solve for the species changes due to the chain reactions over time. Through this approach we can examine the impact of nutrient-containing diets on the gene pathway; moreover, transformation of genes over time with a nutrient treatment can be observed numerically, which is very difficult to achieve experimentally. We apply this approach to microarray analysis data from an experiment which involved the effects of three polyphenols (nutrient treatments), epigallo-catechin-3-O-gallate (EGCG), genistein, and resveratrol, in a study of nutrient-gene interaction in the estrogen synthesis pathway during puberty. RESULTS: In this preliminary study, the estrogen synthesis pathway was simulated by a chain reaction model. By

  17. Analysis of promoter regions of co-expressed genes identified by microarray analysis

    Directory of Open Access Journals (Sweden)

    Höglund Mattias

    2006-08-01

    Full Text Available Abstract Background The use of global gene expression profiling to identify sets of genes with similar expression patterns is rapidly becoming a widespread approach for understanding biological processes. A logical and systematic approach to study co-expressed genes is to analyze their promoter sequences to identify transcription factors that may be involved in establishing specific profiles and that may be experimentally investigated. Results We introduce promoter clustering i.e. grouping of promoters with respect to their high scoring motif content, and show that this approach greatly enhances the identification of common and significant transcription factor binding sites (TFBS in co-expressed genes. We apply this method to two different dataset, one consisting of micro array data from 108 leukemias (AMLs and a second from a time series experiment, and show that biologically relevant promoter patterns may be obtained using phylogenetic foot-printing methodology. In addition, we also found that 15% of the analyzed promoter regions contained transcription factors start sites for additional genes transcribed in the opposite direction. Conclusion Promoter clustering based on global promoter features greatly improve the identification of shared TFBS in co-expressed genes. We believe that the outlined approach may be a useful first step to identify transcription factors that contribute to specific features of gene expression profiles.

  18. Inferring developmental stage composition from gene expression in human malaria.

    Directory of Open Access Journals (Sweden)

    Regina Joice

    Full Text Available In the current era of malaria eradication, reducing transmission is critical. Assessment of transmissibility requires tools that can accurately identify the various developmental stages of the malaria parasite, particularly those required for transmission (sexual stages. Here, we present a method for estimating relative amounts of Plasmodium falciparum asexual and sexual stages from gene expression measurements. These are modeled using constrained linear regression to characterize stage-specific expression profiles within mixed-stage populations. The resulting profiles were analyzed functionally by gene set enrichment analysis (GSEA, confirming differentially active pathways such as increased mitochondrial activity and lipid metabolism during sexual development. We validated model predictions both from microarrays and from quantitative RT-PCR (qRT-PCR measurements, based on the expression of a small set of key transcriptional markers. This sufficient marker set was identified by backward selection from the whole genome as available from expression arrays, targeting one sentinel marker per stage. The model as learned can be applied to any new microarray or qRT-PCR transcriptional measurement. We illustrate its use in vitro in inferring changes in stage distribution following stress and drug treatment and in vivo in identifying immature and mature sexual stage carriers within patient cohorts. We believe this approach will be a valuable resource for staging lab and field samples alike and will have wide applicability in epidemiological studies of malaria transmission.

  19. Modulation of R-gene expression across environments.

    Science.gov (United States)

    MacQueen, Alice; Bergelson, Joy

    2016-03-01

    Some environments are more conducive to pathogen growth than others, and, as a consequence, plants might be expected to invest more in resistance when pathogen growth is favored. Resistance (R-) genes in Arabidopsis thaliana have unusually extensive variation in basal expression when comparing the same R-gene among accessions collected from different environments. R-gene expression variation was characterized to explore whether R-gene expression is up-regulated in environments favoring pathogen proliferation and down-regulated when risks of infection are low; down-regulation would follow if costs of R-gene expression negatively impact plant fitness in the absence of disease. Quantitative reverse transcription-PCR was used to quantify the expression of 13 R-gene loci in plants grown in eight environmental conditions for each of 12 A. thaliana accessions, and large effects of the environment on R-gene expression were found. Surprisingly, almost every change in the environment--be it a change in biotic or abiotic conditions--led to an increase in R-gene expression, a response that was distinct from the average transcriptome response and from that of other stress response genes. These changes in expression are functional in that environmental change prior to infection affected levels of specific disease resistance to isolates of Pseudomonas syringae. In addition, there are strong latitudinal clines in basal R-gene expression and clines in R-gene expression plasticity correlated with drought and high temperatures. These results suggest that variation in R-gene expression across environments may be shaped by natural selection to reduce fitness costs of R-gene expression in permissive or predictable environments. PMID:26983577

  20. Selection of housekeeping genes for gene expression studies in human reticulocytes using real-time PCR

    OpenAIRE

    Thein Swee; Jiang Jie; Best Steve; Silver Nicholas

    2006-01-01

    Abstract Background Control genes, which are often referred to as housekeeping genes, are frequently used to normalise mRNA levels between different samples. However, the expression level of these genes may vary among tissues or cells and may change under certain circumstances. Thus, the selection of housekeeping genes is critical for gene expression studies. To address this issue, 7 candidate housekeeping genes including several commonly used ones were investigated in isolated human reticulo...

  1. Gene expression profiling of intestinal regeneration in the sea cucumber

    Directory of Open Access Journals (Sweden)

    Méndez-Merced Ana T

    2009-06-01

    Full Text Available Abstract Background Among deuterostomes, the regenerative potential is maximally expressed in echinoderms, animals that can quickly replace most injured organs. In particular, sea cucumbers are excellent models for studying organ regeneration since they regenerate their digestive tract after evisceration. However, echinoderms have been sidelined in modern regeneration studies partially because of the lack of genome-wide profiling approaches afforded by modern genomic tools. For the last decade, our laboratory has been using the sea cucumber Holothuria glaberrima to dissect the cellular and molecular events that allow for such amazing regenerative processes. We have already established an EST database obtained from cDNA libraries of normal and regenerating intestine at two different regeneration stages. This database now has over 7000 sequences. Results In the present work we used a custom-made microchip from Agilent with 60-mer probes for these ESTs, to determine the gene expression profile during intestinal regeneration. Here we compared the expression profile of animals at three different intestinal regeneration stages (3-, 7- and 14-days post evisceration against the profile from normal (uneviscerated intestines. The number of differentially expressed probes ranged from 70% at p actins, and developmental genes, such as Wnt and Hox genes, show interesting expression profiles during regeneration. Conclusion Our findings set the base for future studies into the molecular basis of intestinal regeneration. Moreover, it advances the use of echinoderms in regenerative biology, animals that because of their amazing properties and their key evolutionary position, might provide important clues to the genetic basis of regenerative processes.

  2. Preferential DNA repair in expressed genes.

    Science.gov (United States)

    Hanawalt, P C

    1987-01-01

    Potentially deleterious alterations to DNA occur nonrandomly within the mammalian genome. These alterations include the adducts produced by many chemical carcinogens, but not the UV-induced cyclobutane pyrimidine dimer, which may be an exception. Recent studies in our laboratory have shown that the excision repair of pyrimidine dimers and certain other lesions is nonrandom in the mammalian genome, exhibiting a distinct preference for actively transcribed DNA sequences. An important consequence of this fact is that mutagenesis and carcinogenesis may be determined in part by the activities of the relevant genes. Repair may also be processive, and a model is proposed in which excision repair is coupled to transcription at the nuclear matrix. Similar but freely diffusing repair complexes may account for the lower overall repair efficiencies in the silent domains of the genome. Risk assessment in relation to chemical carcinogenesis requires assays that determine effective levels of DNA damage for producing malignancy. The existence of nonrandom repair in the genome casts into doubt the reliability of overall indicators of DNA binding and lesion repair for such determinations. Furthermore, some apparent differences between the intragenomic repair heterogeneity in rodent cells and that in human cells mandate a reevaluation of rodent test systems for human risk assessment. Tissue-specific and cell-specific differences in the coordinate regulation of gene expression and DNA repair may account for corresponding differences in the carcinogenic response. Images FIGURE 1. FIGURE 1. PMID:3447906

  3. A model for gene deregulation detection using expression data.

    Science.gov (United States)

    Picchetti, Thomas; Chiquet, Julien; Elati, Mohamed; Neuvial, Pierre; Nicolle, Rémy; Birmelé, Etienne

    2015-01-01

    In tumoral cells, gene regulation mechanisms are severely altered. Genes that do not react normally to their regulators' activity can provide explanations for the tumoral behavior, and be characteristic of cancer subtypes. We thus propose a statistical methodology to identify the misregulated genes given a reference network and gene expression data. PMID:26679516

  4. Biclustering of gene expression data by non-smooth non-negative matrix factorization

    Directory of Open Access Journals (Sweden)

    Carazo Jose M

    2006-02-01

    Full Text Available Abstract Background The extended use of microarray technologies has enabled the generation and accumulation of gene expression datasets that contain expression levels of thousands of genes across tens or hundreds of different experimental conditions. One of the major challenges in the analysis of such datasets is to discover local structures composed by sets of genes that show coherent expression patterns across subsets of experimental conditions. These patterns may provide clues about the main biological processes associated to different physiological states. Results In this work we present a methodology able to cluster genes and conditions highly related in sub-portions of the data. Our approach is based on a new data mining technique, Non-smooth Non-Negative Matrix Factorization (nsNMF, able to identify localized patterns in large datasets. We assessed the potential of this methodology analyzing several synthetic datasets as well as two large and heterogeneous sets of gene expression profiles. In all cases the method was able to identify localized features related to sets of genes that show consistent expression patterns across subsets of experimental conditions. The uncovered structures showed a clear biological meaning in terms of relationships among functional annotations of genes and the phenotypes or physiological states of the associated conditions. Conclusion The proposed approach can be a useful tool to analyze large and heterogeneous gene expression datasets. The method is able to identify complex relationships among genes and conditions that are difficult to identify by standard clustering algorithms.

  5. Gene therapy approaches for spinal cord injury

    Science.gov (United States)

    Bright, Corinne

    As the biomedical engineering field expands, combination technologies are demonstrating enormous potential for treating human disease. In particular, intersections between the rapidly developing fields of gene therapy and tissue engineering hold promise to achieve tissue regeneration. Nonviral gene therapy uses plasmid DNA to deliver therapeutic proteins in vivo for extended periods of time. Tissue engineering employs biomedical materials, such as polymers, to support the regrowth of injured tissue. In this thesis, a combination strategy to deliver genes and drugs in a polymeric scaffold was applied to a spinal cord injury model. In order to develop a platform technology to treat spinal cord injury, several nonviral gene delivery systems and polymeric scaffolds were evaluated in vitro and in vivo. Nonviral vector trafficking was evaluated in primary neuronal culture to develop an understanding of the barriers to gene transfer in neurons and their supporting glia. Although the most efficient gene carrier in vitro differed from the optimal gene carrier in vivo, confocal and electron microscopy of these nonviral vectors provided insights into the interaction of these vectors with the nucleus. A novel pathway for delivering nanoparticles into the nuclei of neurons and Schwann cells via vesicle trafficking was observed in this study. Reporter gene expression levels were evaluated after direct and remote delivery to the spinal cord, and the optimal nonviral vector, dose, and delivery strategy were applied to deliver the gene encoding the basic fibroblast growth factor (bFGF) to the spinal cord. An injectable and biocompatible gel, composed of the amphiphillic polymer poly(ethylene glycol)-poly(epsilon-caprolactone)-poly(ethylene glycol) (PEG-PCL-PEG) was evaluated as a drug and gene delivery system in vitro, and combined with the optimized nonviral gene delivery system to treat spinal cord injury. Plasmid DNA encoding the bFGF gene and the therapeutic NEP1--40 peptide

  6. Expression profiling identifies genes involved in emphysema severity

    Directory of Open Access Journals (Sweden)

    Bowman Rayleen V

    2009-09-01

    Full Text Available Abstract Chronic obstructive pulmonary disease (COPD is a major public health problem. The aim of this study was to identify genes involved in emphysema severity in COPD patients. Gene expression profiling was performed on total RNA extracted from non-tumor lung tissue from 30 smokers with emphysema. Class comparison analysis based on gas transfer measurement was performed to identify differentially expressed genes. Genes were then selected for technical validation by quantitative reverse transcriptase-PCR (qRT-PCR if also represented on microarray platforms used in previously published emphysema studies. Genes technically validated advanced to tests of biological replication by qRT-PCR using an independent test set of 62 lung samples. Class comparison identified 98 differentially expressed genes (p p Gene expression profiling of lung from emphysema patients identified seven candidate genes associated with emphysema severity including COL6A3, SERPINF1, ZNHIT6, NEDD4, CDKN2A, NRN1 and GSTM3.

  7. A powerful method for detecting differentially expressed genes from GeneChip arrays that does not require replicates

    Directory of Open Access Journals (Sweden)

    Hein Anne-Mette K

    2006-07-01

    Full Text Available Abstract Background Studies of differential expression that use Affymetrix GeneChip arrays are often carried out with a limited number of replicates. Reasons for this include financial considerations and limits on the available amount of RNA for sample preparation. In addition, failed hybridizations are not uncommon leading to a further reduction in the number of replicates available for analysis. Most existing methods for studying differential expression rely on the availability of replicates and the demand for alternative methods that require few or no replicates is high. Results We describe a statistical procedure for performing differential expression analysis without replicates. The procedure relies on a Bayesian integrated approach (BGX to the analysis of Affymetrix GeneChips. The BGX method estimates a posterior distribution of expression for each gene and condition, from a simultaneous consideration of the available probe intensities representing the gene in a condition. Importantly, posterior distributions of expression are obtained regardless of the number of replicates available. We exploit these posterior distributions to create ranked gene lists that take into account the estimated expression difference as well as its associated uncertainty. We estimate the proportion of non-differentially expressed genes empirically, allowing an informed choice of cut-off for the ranked gene list, adapting an approach proposed by Efron. We assess the performance of the method, and compare it to those of other methods, on publicly available spike-in data sets, as well as in a proper biological setting. Conclusion The method presented is a powerful tool for extracting information on differential expression from GeneChip expression studies with limited or no replicates.

  8. Precise regulation of gene expression dynamics favors complex promoter architectures.

    Directory of Open Access Journals (Sweden)

    Dirk Müller

    2009-01-01

    Full Text Available Promoters process signals through recruitment of transcription factors and RNA polymerase, and dynamic changes in promoter activity constitute a major noise source in gene expression. However, it is barely understood how complex promoter architectures determine key features of promoter dynamics. Here, we employ prototypical promoters of yeast ribosomal protein genes as well as simplified versions thereof to analyze the relations among promoter design, complexity, and function. These promoters combine the action of a general regulatory factor with that of specific transcription factors, a common motif of many eukaryotic promoters. By comprehensively analyzing stationary and dynamic promoter properties, this model-based approach enables us to pinpoint the structural characteristics underlying the observed behavior. Functional tradeoffs impose constraints on the promoter architecture of ribosomal protein genes. We find that a stable scaffold in the natural design results in low transcriptional noise and strong co-regulation of target genes in the presence of gene silencing. This configuration also exhibits superior shut-off properties, and it can serve as a tunable switch in living cells. Model validation with independent experimental data suggests that the models are sufficiently realistic. When combined, our results offer a mechanistic explanation for why specific factors are associated with low protein noise in vivo. Many of these findings hold for a broad range of model parameters and likely apply to other eukaryotic promoters of similar structure.

  9. Automated discovery of functional generality of human gene expression programs.

    Directory of Open Access Journals (Sweden)

    Georg K Gerber

    2007-08-01

    Full Text Available An important research problem in computational biology is the identification of expression programs, sets of co-expressed genes orchestrating normal or pathological processes, and the characterization of the functional breadth of these programs. The use of human expression data compendia for discovery of such programs presents several challenges including cellular inhomogeneity within samples, genetic and environmental variation across samples, uncertainty in the numbers of programs and sample populations, and temporal behavior. We developed GeneProgram, a new unsupervised computational framework based on Hierarchical Dirichlet Processes that addresses each of the above challenges. GeneProgram uses expression data to simultaneously organize tissues into groups and genes into overlapping programs with consistent temporal behavior, to produce maps of expression programs, which are sorted by generality scores that exploit the automatically learned groupings. Using synthetic and real gene expression data, we showed that GeneProgram outperformed several popular expression analysis methods. We applied GeneProgram to a compendium of 62 short time-series gene expression datasets exploring the responses of human cells to infectious agents and immune-modulating molecules. GeneProgram produced a map of 104 expression programs, a substantial number of which were significantly enriched for genes involved in key signaling pathways and/or bound by NF-kappaB transcription factors in genome-wide experiments. Further, GeneProgram discovered expression programs that appear to implicate surprising signaling pathways or receptor types in the response to infection, including Wnt signaling and neurotransmitter receptors. We believe the discovered map of expression programs involved in the response to infection will be useful for guiding future biological experiments; genes from programs with low generality scores might serve as new drug targets that exhibit minimal

  10. Selective expression of rat pancreatic genes during embryonic development.

    OpenAIRE

    Han, J H; Rall, L; Rutter, W J

    1986-01-01

    We present the developmental profiles of the mRNAs of 10 selectively expressed pancreatic exocrine genes and of insulin. The mRNA profiles fall into three related classes, but each profile is in some respect unique. The data on gene expression suggest there are four developmental states of the exocrine pancreas: early morphogenesis and low-level gene expression (the protodifferentiated state), the embryonic differentiated state, a modulated state in neonatal animals, and the adult differentia...

  11. Serial Analysis of Gene Expression: Applications in Human Studies

    OpenAIRE

    Renu Tuteja; Narendra Tuteja

    2004-01-01

    Serial analysis of gene expression (SAGE) is a powerful tool, which provides quantitative and comprehensive expression profile of genes in a given cell population. It works by isolating short fragments of genetic information from the expressed genes that are present in the cell being studied. These short sequences, called SAGE tags, are linked together for efficient sequencing. The frequency of each SAGE tag in the cloned multimers directly reflects the transcript abundance. Therefore, SAGE r...

  12. Regulated system for heterologous gene expression in Penicillium chrysogenum.

    OpenAIRE

    Graessle, S.; de Haas, H.; Friedlin, E; Kürnsteiner, H; Stöffler, G; Redl, B

    1997-01-01

    A system for regulated heterologous gene expression in the filamentous fungus Penicillium chrysogenum was established. This is the first heterologous expression system to be developed for this organism. Expression of a recombinant fungal xylanase gene (xylp) and the cDNA for the human tear lipocalin (LCNI) was achieved by placing the encoding sequences under the control of the repressible acid phosphatase gene (phoA) promoter of P. chrysogenum. Secreted recombinant proteins were detected in t...

  13. Identifying genes associated with quantitative traits in pigs: integrating quantitative and molecular approaches for meat quality

    Directory of Open Access Journals (Sweden)

    Karl Schellander

    2010-01-01

    Full Text Available Two major strategies are used to identify genes that are involved in complex traits, genome scanning and candidate gene approaches. While a quantitative trait locus (QTL strategy relies on a scan of the entire genome combined with phenotypic measurements, a candidate gene approach tries to identify genes based on their possible role in the physiology of the traits. Both strategies are based on the integration between quantitative and molecular approaches. Over the last decade, enormous effort has been applied to identify and localize QTL involved in most of the economically important traits in pigs and a number of candidate genes were suggested and further validated according to a concordant position to the detected QTL and related functions. However, lacking of information in regards to identified genes within the identified QTL, and false-positive QTL are major constraints that limit the successful of this approach. Additional approaches, including a gene expression analysis of the divergence of phenotype of interest was integrated into a candidate gene analysis, in which a putative candidate gene is the one that could be statistically detected from the genes controlling large components of inheritable gene expression variation. Furthermore, a remarkable progress of molecular approaches by newly developed technique, a study of an interaction between genes and a holistic study of biological regulation, system biology, is underway. These continuations will assist the researchers to identify direct candidate gene for quantitative traits in animal breeding.

  14. Gene expression prediction by soft integration and the elastic net-best performance of the DREAM3 gene expression challenge.

    Directory of Open Access Journals (Sweden)

    Mika Gustafsson

    Full Text Available BACKGROUND: To predict gene expressions is an important endeavour within computational systems biology. It can both be a way to explore how drugs affect the system, as well as providing a framework for finding which genes are interrelated in a certain process. A practical problem, however, is how to assess and discriminate among the various algorithms which have been developed for this purpose. Therefore, the DREAM project invited the year 2008 to a challenge for predicting gene expression values, and here we present the algorithm with best performance. METHODOLOGY/PRINCIPAL FINDINGS: We develop an algorithm by exploring various regression schemes with different model selection procedures. It turns out that the most effective scheme is based on least squares, with a penalty term of a recently developed form called the "elastic net". Key components in the algorithm are the integration of expression data from other experimental conditions than those presented for the challenge and the utilization of transcription factor binding data for guiding the inference process towards known interactions. Of importance is also a cross-validation procedure where each form of external data is used only to the extent it increases the expected performance. CONCLUSIONS/SIGNIFICANCE: Our algorithm proves both the possibility to extract information from large-scale expression data concerning prediction of gene levels, as well as the benefits of integrating different data sources for improving the inference. We believe the former is an important message to those still hesitating on the possibilities for computational approaches, while the latter is part of an important way forward for the future development of the field of computational systems biology.

  15. Differential gene co-expression networks via Bayesian biclustering models

    OpenAIRE

    Gao, Chuan; Zhao, Shiwen; McDowell, Ian C.; Brown, Christopher D.; Barbara E Engelhardt

    2014-01-01

    Identifying latent structure in large data matrices is essential for exploring biological processes. Here, we consider recovering gene co-expression networks from gene expression data, where each network encodes relationships between genes that are locally co-regulated by shared biological mechanisms. To do this, we develop a Bayesian statistical model for biclustering to infer subsets of co-regulated genes whose covariation may be observed in only a subset of the samples. Our biclustering me...

  16. Biclustering of Linear Patterns In Gene Expression Data

    OpenAIRE

    Gao, Qinghui; Ho, Christine; Jia, Yingmin; Li, Jingyi Jessica; Huang, Haiyan

    2012-01-01

    Identifying a bicluster, or submatrix of a gene expression dataset wherein the genes express similar behavior over the columns, is useful for discovering novel functional gene interactions. In this article, we introduce a new algorithm for finding biClusters with Linear Patterns (CLiP). Instead of solely maximizing Pearson correlation, we introduce a fitness function that also considers the correlation of complementary genes and conditions. This eliminates the need for a priori determination ...

  17. Differential Expression of Salinity Resistance Gene on Cotton

    Institute of Scientific and Technical Information of China (English)

    YE Wu-wei; YU Shu-xun

    2008-01-01

    @@ Salinity resistance and differential gene expression associated with salinity in cotton germplasm were studied,because of the large scale area of salinity in China,and its significant negative effects on the cotton production.The salinityresisted genes and their differential expression were studied under the stress of NaCI on cotton.There were found,under the NaCI stress,1644 genes differentially expressed from the salinity-sensitive cotton and only 817 genes differentially expressed from the salinityresisted cotton.

  18. Expression of protein-coding genes embedded in ribosomal DNA

    DEFF Research Database (Denmark)

    Johansen, Steinar D; Haugen, Peik; Nielsen, Henrik

    2007-01-01

    encode reverse transcriptase-like genes, and group I introns and archaeal introns that encode homing endonuclease genes (HEGs). Although rDNA-embedded protein genes are widespread in nuclei, organelles and bacteria, there is surprisingly little information available on how these genes are expressed....... Exceptions include a handful of HEGs from group I introns. Recent studies have revealed unusual and essential roles of group I and group I-like ribozymes in the endogenous expression of HEGs. Here we discuss general aspects of rDNA-embedded protein genes and focus on HEG expression from group I introns in...

  19. Genome-wide age-related changes in DNA methylation and gene expression in human PBMCs.

    Science.gov (United States)

    Steegenga, Wilma T; Boekschoten, Mark V; Lute, Carolien; Hooiveld, Guido J; de Groot, Philip J; Morris, Tiffany J; Teschendorff, Andrew E; Butcher, Lee M; Beck, Stephan; Müller, Michael

    2014-06-01

    Aging is a progressive process that results in the accumulation of intra- and extracellular alterations that in turn contribute to a reduction in health. Age-related changes in DNA methylation have been reported before and may be responsible for aging-induced changes in gene expression, although a causal relationship has yet to be shown. Using genome-wide assays, we analyzed age-induced changes in DNA methylation and their effect on gene expression with and without transient induction with the synthetic transcription modulating agent WY14,643. To demonstrate feasibility of the approach, we isolated peripheral blood mononucleated cells (PBMCs) from five young and five old healthy male volunteers and cultured them with or without WY14,643. Infinium 450K BeadChip and Affymetrix Human Gene 1.1 ST expression array analysis revealed significant differential methylation of at least 5 % (ΔYO > 5 %) at 10,625 CpG sites between young and old subjects, but only a subset of the associated genes were also differentially expressed. Age-related differential methylation of previously reported epigenetic biomarkers of aging including ELOVL2, FHL2, PENK, and KLF14 was confirmed in our study, but these genes did not display an age-related change in gene expression in PBMCs. Bioinformatic analysis revealed that differentially methylated genes that lack an age-related expression change predominantly represent genes involved in carcinogenesis and developmental processes, and expression of most of these genes were silenced in PBMCs. No changes in DNA methylation were found in genes displaying transiently induced changes in gene expression. In conclusion, aging-induced differential methylation often targets developmental genes and occurs mostly without change in gene expression. PMID:24789080

  20. An integrative genomic approach reveals coordinated expression of intronic miR-335, miR-342, and miR-561 with deregulated host genes in multiple myeloma

    Directory of Open Access Journals (Sweden)

    Agnelli Luca

    2008-08-01

    Full Text Available Abstract Background The role of microRNAs (miRNAs in multiple myeloma (MM has yet to be fully elucidated. To identify miRNAs that are potentially deregulated in MM, we investigated those mapping within transcription units, based on evidence that intronic miRNAs are frequently coexpressed with their host genes. To this end, we monitored host transcript expression values in a panel of 20 human MM cell lines (HMCLs and focused on transcripts whose expression varied significantly across the dataset. Methods miRNA expression was quantified by Quantitative Real-Time PCR. Gene expression and genome profiling data were generated on Affymetrix oligonucleotide microarrays. Significant Analysis of Microarrays algorithm was used to investigate differentially expressed transcripts. Conventional statistics were used to test correlations for significance. Public libraries were queried to predict putative miRNA targets. Results We identified transcripts specific to six miRNA host genes (CCPG1, GULP1, EVL, TACSTD1, MEST, and TNIK whose average changes in expression varied at least 2-fold from the mean of the examined dataset. We evaluated the expression levels of the corresponding intronic miRNAs and identified a significant correlation between the expression levels of MEST, EVL, and GULP1 and those of the corresponding miRNAs miR-335, miR-342-3p, and miR-561, respectively. Genome-wide profiling of the 20 HMCLs indicated that the increased expression of the three host genes and their corresponding intronic miRNAs was not correlated with local copy number variations. Notably, miRNAs and their host genes were overexpressed in a fraction of primary tumors with respect to normal plasma cells; however, this finding was not correlated with known molecular myeloma groups. The predicted putative miRNA targets and the transcriptional profiles associated with the primary tumors suggest that MEST/miR-335 and EVL/miR-342-3p may play a role in plasma cell homing and

  1. Gene expression in epithelial cells in response to pneumovirus infection

    Directory of Open Access Journals (Sweden)

    Rosenberg Helene F

    2001-05-01

    Full Text Available Abstract Respiratory syncytial virus (RSV and pneumonia virus of mice (PVM are viruses of the family Paramyxoviridae, subfamily pneumovirus, which cause clinically important respiratory infections in humans and rodents, respectively. The respiratory epithelial target cells respond to viral infection with specific alterations in gene expression, including production of chemoattractant cytokines, adhesion molecules, elements that are related to the apoptosis response, and others that remain incompletely understood. Here we review our current understanding of these mucosal responses and discuss several genomic approaches, including differential display reverse transcription-polymerase chain reaction (PCR and gene array strategies, that will permit us to unravel the nature of these responses in a more complete and systematic manner.

  2. Strategies used for genetically modifying bacterial genome: ite-directed mutagenesis, gene inactivation, and gene over-expression*

    Science.gov (United States)

    Xu, Jian-zhong; Zhang, Wei-guo

    2016-01-01

    With the availability of the whole genome sequence of Escherichia coli or Corynebacterium glutamicum, strategies for directed DNA manipulation have developed rapidly. DNA manipulation plays an important role in understanding the function of genes and in constructing novel engineering bacteria according to requirement. DNA manipulation involves modifying the autologous genes and expressing the heterogenous genes. Two alternative approaches, using electroporation linear DNA or recombinant suicide plasmid, allow a wide variety of DNA manipulation. However, the over-expression of the desired gene is generally executed via plasmid-mediation. The current review summarizes the common strategies used for genetically modifying E. coli and C. glutamicum genomes, and discusses the technical problem of multi-layered DNA manipulation. Strategies for gene over-expression via integrating into genome are proposed. This review is intended to be an accessible introduction to DNA manipulation within the bacterial genome for novices and a source of the latest experimental information for experienced investigators. PMID:26834010

  3. Strategies used for genetically modifying bacterial genome: site-directed mutagenesis, gene inactivation, and gene over-expression.

    Science.gov (United States)

    Xu, Jian-zhong; Zhang, Wei-guo

    2016-02-01

    With the availability of the whole genome sequence of Escherichia coli or Corynebacterium glutamicum, strategies for directed DNA manipulation have developed rapidly. DNA manipulation plays an important role in understanding the function of genes and in constructing novel engineering bacteria according to requirement. DNA manipulation involves modifying the autologous genes and expressing the heterogenous genes. Two alternative approaches, using electroporation linear DNA or recombinant suicide plasmid, allow a wide variety of DNA manipulation. However, the over-expression of the desired gene is generally executed via plasmid-mediation. The current review summarizes the common strategies used for genetically modifying E. coli and C. glutamicum genomes, and discusses the technical problem of multi-layered DNA manipulation. Strategies for gene over-expression via integrating into genome are proposed. This review is intended to be an accessible introduction to DNA manipulation within the bacterial genome for novices and a source of the latest experimental information for experienced investigators. PMID:26834010

  4. A Combinatorial Approach to Detecting Gene-Gene and Gene-Environment Interactions in Family Studies

    OpenAIRE

    Lou, Xiang-Yang; Chen, Guo-Bo; Yan, Lei; Ma, Jennie Z.; Mangold, Jamie E.; Zhu, Jun; Elston, Robert C.; Li, Ming D.

    2008-01-01

    Widespread multifactor interactions present a significant challenge in determining risk factors of complex diseases. Several combinatorial approaches, such as the multifactor dimensionality reduction (MDR) method, have emerged as a promising tool for better detecting gene-gene (G × G) and gene-environment (G × E) interactions. We recently developed a general combinatorial approach, namely the generalized multifactor dimensionality reduction (GMDR) method, which can entertain both qualitative ...

  5. A Novel Approach to Functional Analysis of the Ribulose Bisphosphate Carboxylase Small Subunit Gene by Agrobacterium-Mediated Gene Silencing

    Institute of Scientific and Technical Information of China (English)

    Xiao-Fu Zhou; Peng-Da Ma; Ren-Hou Wang; Bo Liu; Xing-Zhi Wang

    2006-01-01

    A novel approach to virus-induced post-transcriptional gene silencing for studying the function of the ribulose bisphosphate carboxylase small subunlt (rbcS) gene was established and optimized using potato virus X vector and Nicotiana benthamiana as experimental material. The analysis of silencing phenomena,transcriptional level, protein expression, and pigment measurement showed that the expression of the rbcS endogenous gene was inactivated by the expression of a 500-bp homologous cDNA fragment carried in the virus vector.

  6. Identification of transcription-factor genes expressed in the Arabidopsis female gametophyte

    Directory of Open Access Journals (Sweden)

    Kang Il-Ho

    2010-06-01

    study have not been reported previously as being expressed in the female gametophyte. Therefore, they might represent novel regulators and provide entry points for reverse genetic and molecular approaches to uncover the gene regulatory networks underlying female gametophyte development.

  7. Expressed genes in regenerating rat liver after partial hepatectomy

    Institute of Scientific and Technical Information of China (English)

    Cun-Shuan Xu; Salman Rahrnan; Jing-Bo Zhang; Cui-Fang Chang; Jin-Yun Yuan; Wen-Qiang Li; Hong-Peng Han; Ke-Jin Yang; Li-Feng Zhao; Yu-Chang Li; Hui-Yong Zhang

    2005-01-01

    AIM: To reveal the liver regeneration (LR) and its controlas well as the occurrence of liver disease and to study the gene expression profiles of 551 genes after partial hepatectomy (PH) in regenerating rat livers.METHODS: Five hundred and fifty-one expressed sequence tags screened by suppression subtractive hybridization were made into an in-house cDNA microarray, and the expressive genes and their expressive profiles in regenerating rat livers were analyzed by microarray and bioinformatics. RESULTS: Three hundred of the analyzed 551 genes were up- or downregulated more than twofolds at one or more time points during LR. Most of the genes were up- or downregulated 2-5 folds, but the highest reached 90 folds of the control. One hundred and thirty-nine of themshowed upregulation, 135 displayed downregulation, and up or down expression of 26 genes revealed a dependence on regenerating livers. The genes expressedin 24-h regenerating livers were much more than those in the others. Cluster analysis and generalization analysis showed that there were at least six distinct temporal patterns of gene expression in the regenerating livers, that is, genes were expressed in the immediate early phase, early phase, intermediate phase, early-late phase, late phase, terminal phase. CONCLUSION: In LR, the number of down-regulated genes was almost similar to that of the upregulated genes; the successively altered genes were more than the rapidly transient genes. The temporal patterns of gene expression were similar 2 and 4 h, 12 and 16 h, 48 and 96 h, 72 and 144 h after PH. Microarray combined with suppressive subtractive hybridization can effectively identify the genes related to LR.

  8. Noise in gene expression is coupled to growth rate

    OpenAIRE

    Keren, Leeat; van Dijk, David; Weingarten-Gabbay, Shira; Davidi, Dan; Jona, Ghil; Weinberger, Adina; Milo, Ron; Segal, Eran

    2015-01-01

    Genetically identical cells exposed to the same environment display variability in gene expression (noise), with important consequences for the fidelity of cellular regulation and biological function. Although population average gene expression is tightly coupled to growth rate, the effects of changes in environmental conditions on expression variability are not known. Here, we measure the single-cell expression distributions of approximately 900 Saccharomyces cerevisiae promoters across four...

  9. Expression of UGA-Containing Mycoplasma Genes in Bacillus subtilis

    OpenAIRE

    Kannan, T. R.; Baseman, Joel B.

    2000-01-01

    We used Bacillus subtilis to express UGA-containing Mycoplasma genes encoding the P30 adhesin (one UGA) of Mycoplasma pneumoniae and methionine sulfoxide reductase (two UGAs) of Mycoplasma genitalium. Due to natural UGA suppression, these Mycoplasma genes were expressed as full-length protein products, but at relatively low efficiency, in recombinant wild-type Bacillus. The B. subtilis-expressed Mycoplasma proteins appeared as single bands and not as multiple bands compared to expression in r...

  10. Multiscale Embedded Gene Co-expression Network Analysis

    OpenAIRE

    Song, Won-Min; Zhang, Bin

    2015-01-01

    Gene co-expression network analysis has been shown effective in identifying functional co-expressed gene modules associated with complex human diseases. However, existing techniques to construct co-expression networks require some critical prior information such as predefined number of clusters, numerical thresholds for defining co-expression/interaction, or do not naturally reproduce the hallmarks of complex systems such as the scale-free degree distribution of small-worldness. Previously, a...

  11. Conserved co-expression for candidate disease gene prioritization

    Directory of Open Access Journals (Sweden)

    Huynen Martijn A

    2008-04-01

    Full Text Available Abstract Background Genes that are co-expressed tend to be involved in the same biological process. However, co-expression is not a very reliable predictor of functional links between genes. The evolutionary conservation of co-expression between species can be used to predict protein function more reliably than co-expression in a single species. Here we examine whether co-expression across multiple species is also a better prioritizer of disease genes than is co-expression between human genes alone. Results We use co-expression data from yeast (S. cerevisiae, nematode worm (C. elegans, fruit fly (D. melanogaster, mouse and human and find that the use of evolutionary conservation can indeed improve the predictive value of co-expression. The effect that genes causing the same disease have higher co-expression than do other genes from their associated disease loci, is significantly enhanced when co-expression data are combined across evolutionarily distant species. We also find that performance can vary significantly depending on the co-expression datasets used, and just using more data does not necessarily lead to better prioritization. Instead, we find that dataset quality is more important than quantity, and using a consistent microarray platform per species leads to better performance than using more inclusive datasets pooled from various platforms. Conclusion We find that evolutionarily conserved gene co-expression prioritizes disease candidate genes better than human gene co-expression alone, and provide the integrated data as a new resource for disease gene prioritization tools.

  12. Binary gene expression patterning of the molt cycle: the case of chitin metabolism.

    Science.gov (United States)

    Abehsera, Shai; Glazer, Lilah; Tynyakov, Jenny; Plaschkes, Inbar; Chalifa-Caspi, Vered; Khalaila, Isam; Aflalo, Eliahu D; Sagi, Amir

    2014-01-01

    In crustaceans, like all arthropods, growth is accompanied by a molting cycle. This cycle comprises major physiological events in which mineralized chitinous structures are built and degraded. These events are in turn governed by genes whose patterns of expression are presumably linked to the molting cycle. To study these genes we performed next generation sequencing and constructed a molt-related transcriptomic library from two exoskeletal-forming tissues of the crayfish Cherax quadricarinatus, namely the gastrolith and the mandible cuticle-forming epithelium. To simplify the study of such a complex process as molting, a novel approach, binary patterning of gene expression, was employed. This approach revealed that key genes involved in the synthesis and breakdown of chitin exhibit a molt-related pattern in the gastrolith-forming epithelium. On the other hand, the same genes in the mandible cuticle-forming epithelium showed a molt-independent pattern of expression. Genes related to the metabolism of glucosamine-6-phosphate, a chitin precursor synthesized from simple sugars, showed a molt-related pattern of expression in both tissues. The binary patterning approach unfolds typical patterns of gene expression during the molt cycle of a crustacean. The use of such a simplifying integrative tool for assessing gene patterning seems appropriate for the study of complex biological processes. PMID:25919476

  13. Binary Gene Expression Patterning of the Molt Cycle: The Case of Chitin Metabolism

    Science.gov (United States)

    Abehsera, Shai; Glazer, Lilah; Tynyakov, Jenny; Plaschkes, Inbar; Chalifa-Caspi, Vered; Khalaila, Isam; Aflalo, Eliahu D.; Sagi, Amir

    2015-01-01

    In crustaceans, like all arthropods, growth is accompanied by a molting cycle. This cycle comprises major physiological events in which mineralized chitinous structures are built and degraded. These events are in turn governed by genes whose patterns of expression are presumably linked to the molting cycle. To study these genes we performed next generation sequencing and constructed a molt-related transcriptomic library from two exoskeletal-forming tissues of the crayfish Cherax quadricarinatus, namely the gastrolith and the mandible cuticle-forming epithelium. To simplify the study of such a complex process as molting, a novel approach, binary patterning of gene expression, was employed. This approach revealed that key genes involved in the synthesis and breakdown of chitin exhibit a molt-related pattern in the gastrolith-forming epithelium. On the other hand, the same genes in the mandible cuticle-forming epithelium showed a molt-independent pattern of expression. Genes related to the metabolism of glucosamine-6-phosphate, a chitin precursor synthesized from simple sugars, showed a molt-related pattern of expression in both tissues. The binary patterning approach unfolds typical patterns of gene expression during the molt cycle of a crustacean. The use of such a simplifying integrative tool for assessing gene patterning seems appropriate for the study of complex biological processes. PMID:25919476

  14. Binary gene expression patterning of the molt cycle: the case of chitin metabolism.

    Directory of Open Access Journals (Sweden)

    Shai Abehsera

    Full Text Available In crustaceans, like all arthropods, growth is accompanied by a molting cycle. This cycle comprises major physiological events in which mineralized chitinous structures are built and degraded. These events are in turn governed by genes whose patterns of expression are presumably linked to the molting cycle. To study these genes we performed next generation sequencing and constructed a molt-related transcriptomic library from two exoskeletal-forming tissues of the crayfish Cherax quadricarinatus, namely the gastrolith and the mandible cuticle-forming epithelium. To simplify the study of such a complex process as molting, a novel approach, binary patterning of gene expression, was employed. This approach revealed that key genes involved in the synthesis and breakdown of chitin exhibit a molt-related pattern in the gastrolith-forming epithelium. On the other hand, the same genes in the mandible cuticle-forming epithelium showed a molt-independent pattern of expression. Genes related to the metabolism of glucosamine-6-phosphate, a chitin precursor synthesized from simple sugars, showed a molt-related pattern of expression in both tissues. The binary patterning approach unfolds typical patterns of gene expression during the molt cycle of a crustacean. The use of such a simplifying integrative tool for assessing gene patterning seems appropriate for the study of complex biological processes.

  15. Structure and ovarian expression of the oxytocin gene in sheep.

    Science.gov (United States)

    Ivell, R; Hunt, N; Abend, N; Brackman, B; Nollmeyer, D; Lamsa, J C; McCracken, J A

    1990-01-01

    In sheep, the oxytocin gene is highly up-regulated in the ovarian corpus luteum as well as in the hypothalamus. This expression is already elevated on Day 2 of the oestrous cycle, representing 1% of all transcripts in this tissue, and it declines thereafter to low levels after Day 6 of the cycle. In order to study the mechanisms involved in luteal oxytocin gene expression, we have cloned and sequenced the oxytocin gene from the sheep. This gene is closely homologous to other known mammalian oxytocin genes, especially the bovine one, and comparison of the gene promoter regions highlights several blocks of putative control elements. PMID:2095591

  16. Shrinkage Approach for Gene Expression Data Analysis

    Czech Academy of Sciences Publication Activity Database

    Haman, Jiří; Valenta, Zdeněk

    2013-01-01

    Roč. 9, č. 3 (2013), s. 2-8. ISSN 1801-5603 Grant ostatní: UK(CZ) SVV-2013-266517 Institutional support: RVO:67985807 Keywords : microarray technology * high dimensional data * mean squared error * James-Stein shrinkage estimator * mutual information Subject RIV: IN - Informatics, Computer Science http://www.ejbi.org/img/ejbi/2013/3/Haman_en.pdf

  17. Global gene expression analysis for evaluation and design of biomaterials

    Directory of Open Access Journals (Sweden)

    Nobutaka Hanagata, Taro Takemura and Takashi Minowa

    2010-01-01

    Full Text Available Comprehensive gene expression analysis using DNA microarrays has become a widespread technique in molecular biological research. In the biomaterials field, it is used to evaluate the biocompatibility or cellular toxicity of metals, polymers and ceramics. Studies in this field have extracted differentially expressed genes in the context of differences in cellular responses among multiple materials. Based on these genes, the effects of materials on cells at the molecular level have been examined. Expression data ranging from several to tens of thousands of genes can be obtained from DNA microarrays. For this reason, several tens or hundreds of differentially expressed genes are often present in different materials. In this review, we outline the principles of DNA microarrays, and provide an introduction to methods of extracting information which is useful for evaluating and designing biomaterials from comprehensive gene expression data.

  18. Mutants of Agrobacterium tumefaciens with elevated vir gene expression

    International Nuclear Information System (INIS)

    Expression of Agrobacterium tumefaciens virulence (vir) genes requires virA, virG, and a plant-derived inducing compound such as acetosyringone. To identify the critical functional domains of virA and virG, a mutational approach was used. Agrobacterium A136 harboring plasmid pGP159, which contains virA, virG, and a reporter virB:lacZ gene fusion, was mutagenized with UV light or nitrosoguanidine. Survivors that formed blue colonies on a plate containing 5-bromo-4-chloro-3-indolyl beta-D-galactoside were isolated and analyzed. Quantification of beta-galactosidase activity in liquid assays identified nine mutant strains. By plasmid reconstruction and other procedures, all mutations mapped to the virA locus. These mutations caused an 11- to 560-fold increase in the vegetative level of virB:lacZ reporter gene expression. DNA sequence analysis showed that the mutations are located in four regions of VirA: transmembrane domain one, the active site, a glycine-rich region with homology to ATP-binding sites, and a region at the C terminus that has homology to the N terminus of VirG

  19. Statistical Inference and Reverse Engineering of Gene Regulatory Networks from Observational Expression Data

    OpenAIRE

    Emmert-Streib, Frank; Glazko, Galina V.; Altay, Gökmen; Matos Simoes, Ricardo de

    2012-01-01

    In this paper, we present a systematic and conceptual overview of methods for inferring gene regulatory networks from observational gene expression data. Further, we discuss two classic approaches to infer causal structures and compare them with contemporary methods by providing a conceptual categorization thereof. We complement the above by surveying global and local evaluation measures for assessing the performance of inference algorithms.

  20. Simpler Evaluation of Predictions and Signature Stability for Gene Expression Data

    Directory of Open Access Journals (Sweden)

    Yvonne E. Pittelkow

    2009-01-01

    Full Text Available Scientific advances are raising expectations that patient-tailored treatment will soon be available. The development of resulting clinical approaches needs to be based on well-designed experimental and observational procedures that provide data to which proper biostatistical analyses are applied. Gene expression microarray and related technology are rapidly evolving. It is providing extremely large gene expression profiles containing many thousands of measurements. Choosing a subset from these gene expression measurements to include in a gene expression signature is one of the many challenges needing to be met. Choice of this signature depends on many factors, including the selection of patients in the training set. So the reliability and reproducibility of the resultant prognostic gene signature needs to be evaluated, in such a way as to be relevant to the clinical setting. A relatively straightforward approach is based on cross validation, with separate selection of genes at each iteration to avoid selection bias. Within this approach we developed two different methods, one based on forward selection, the other on genes that were statistically significant in all training blocks of data. We demonstrate our approach to gene signature evaluation with a well-known breast cancer data set.

  1. Gene Expression Pattern of Signal Transduction in Chronic Myeloid Leukemia

    Institute of Scientific and Technical Information of China (English)

    LI Huiyu; JIE Shenghua; GUO Tiannan; HUANG Shi'ang

    2006-01-01

    To explore the transcriptional gene expression profiles of signaling pathway in Chronic myeloid leukemia (CML), a series of cDNA microarray chips were tested. The results showed that differentially expressed genes related to singal transduction in CML were screened out and the genes involved in Phosphoinositide 3-kinases (PI3K), Ras-MAPK (mitogen-activated protein kinase) and other signaling pathway genes simultaneously. The results also showed that most of these genes were up-expression genes , which suggested that signal transduction be overactivated in CML. Further analysis of these differentially expressed signal transduction genes will be helpful to understand the molecular mechanism of CML and find new targets of treatment.

  2. Identification of imprinted genes subject to parent-of-origin specific expression in Arabidopsis thaliana seeds

    LENUS (Irish Health Repository)

    McKeown, Peter C

    2011-08-12

    confirmed via allele-specific transcript analysis across a range of different accessions. Differentially methylated regions were identified adjacent to ATCDC48 and PDE120, which may represent candidate imprinting control regions. Finally, we demonstrate that expression levels of these three genes in vegetative tissues are MET1-dependent, while their uniparental maternal expression in the seed is not dependent on MET1. Conclusions Using a cDNA-AFLP transcriptome profiling approach, we have identified three genes, ATCDC48, PDE120 and MS5-like which represent novel maternally expressed imprinted genes in the Arabidopsis thaliana seed. The extent of overlap between our cDNA-AFLP screen for maternally expressed imprinted genes, and other screens for imprinted and endosperm-expressed genes is discussed.

  3. Identification of imprinted genes subject to parent-of-origin specific expression in Arabidopsis thaliana seeds

    Directory of Open Access Journals (Sweden)

    Wennblom Trevor J

    2011-08-01

    seeds was confirmed via allele-specific transcript analysis across a range of different accessions. Differentially methylated regions were identified adjacent to ATCDC48 and PDE120, which may represent candidate imprinting control regions. Finally, we demonstrate that expression levels of these three genes in vegetative tissues are MET1-dependent, while their uniparental maternal expression in the seed is not dependent on MET1. Conclusions Using a cDNA-AFLP transcriptome profiling approach, we have identified three genes, ATCDC48, PDE120 and MS5-like which represent novel maternally expressed imprinted genes in the Arabidopsis thaliana seed. The extent of overlap between our cDNA-AFLP screen for maternally expressed imprinted genes, and other screens for imprinted and endosperm-expressed genes is discussed.

  4. Dynamic covariation between gene expression and proteome characteristics

    Directory of Open Access Journals (Sweden)

    Lehtinen Tommi O

    2005-08-01

    Full Text Available Abstract Background Cells react to changing intra- and extracellular signals by dynamically modulating complex biochemical networks. Cellular responses to extracellular signals lead to changes in gene and protein expression. Since the majority of genes encode proteins, we investigated possible correlations between protein parameters and gene expression patterns to identify proteome-wide characteristics indicative of trends common to expressed proteins. Results Numerous bioinformatics methods were used to filter and merge information regarding gene and protein annotations. A new statistical time point-oriented analysis was developed for the study of dynamic correlations in large time series data. The method was applied to investigate microarray datasets for different cell types, organisms and processes, including human B and T cell stimulation, Drosophila melanogaster life span, and Saccharomyces cerevisiae cell cycle. Conclusion We show that the properties of proteins synthesized correlate dynamically with the gene expression profile, indicating that not only is the actual identity and function of expressed proteins important for cellular responses but that several physicochemical and other protein properties correlate with gene expression as well. Gene expression correlates strongly with amino acid composition, composition- and sequence-derived variables, functional, structural, localization and gene ontology parameters. Thus, our results suggest that a dynamic relationship exists between proteome properties and gene expression in many biological systems, and therefore this relationship is fundamental to understanding cellular mechanisms in health and disease.

  5. Benzoic Acid-Inducible Gene Expression in Mycobacteria.

    Directory of Open Access Journals (Sweden)

    Marte S Dragset

    Full Text Available Conditional expression is a powerful tool to investigate the role of bacterial genes. Here, we adapt the Pseudomonas putida-derived positively regulated XylS/Pm expression system to control inducible gene expression in Mycobacterium smegmatis and Mycobacterium tuberculosis, the causative agent of human tuberculosis. By making simple changes to a Gram-negative broad-host-range XylS/Pm-regulated gene expression vector, we prove that it is possible to adapt this well-studied expression system to non-Gram-negative species. With the benzoic acid-derived inducer m-toluate, we achieve a robust, time- and dose-dependent reversible induction of Pm-mediated expression in mycobacteria, with low background expression levels. XylS/Pm is thus an important addition to existing mycobacterial expression tools, especially when low basal expression is of particular importance.

  6. The Arabidopsis Root Transcriptome by Serial Analysis of Gene Expression. Gene Identification Using the Genome Sequence1

    Science.gov (United States)

    Fizames, Cécile; Muños, Stéphane; Cazettes, Céline; Nacry, Philippe; Boucherez, Jossia; Gaymard, Frédéric; Piquemal, David; Delorme, Valérie; Commes, Thérèse; Doumas, Patrick; Cooke, Richard; Marti, Jacques; Sentenac, Hervé; Gojon, Alain

    2004-01-01

    Large-scale identification of genes expressed in roots of the model plant Arabidopsis was performed by serial analysis of gene expression (SAGE), on a total of 144,083 sequenced tags, representing at least 15,964 different mRNAs. For tag to gene assignment, we developed a computational approach based on 26,620 genes annotated from the complete sequence of the genome. The procedure selected warrants the identification of the genes corresponding to the majority of the tags found experimentally, with a high level of reliability, and provides a reference database for SAGE studies in Arabidopsis. This new resource allowed us to characterize the expression of more than 3,000 genes, for which there is no expressed sequence tag (EST) or cDNA in the databases. Moreover, 85% of the tags were specific for one gene. To illustrate this advantage of SAGE for functional genomics, we show that our data allow an unambiguous analysis of most of the individual genes belonging to 12 different ion transporter multigene families. These results indicate that, compared with EST-based tag to gene assignment, the use of the annotated genome sequence greatly improves gene identification in SAGE studies. However, more than 6,000 different tags remained with no gene match, suggesting that a significant proportion of transcripts present in the roots originate from yet unknown or wrongly annotated genes. The root transcriptome characterized in this study markedly differs from those obtained in other organs, and provides a unique resource for investigating the functional specificities of the root system. As an example of the use of SAGE for transcript profiling in Arabidopsis, we report here the identification of 270 genes differentially expressed between roots of plants grown either with NO3- or NH4NO3 as N source. PMID:14730065

  7. Gene therapy in glaucoma-3: Therapeutic approaches

    Directory of Open Access Journals (Sweden)

    Mohamed Abdel-Monem Soliman Mahdy

    2010-01-01

    Recently, several promising genetic therapeutic approaches had been investigated. Some are either used to stop apoptosis and halt further glaucomatous damage, wound healing modulating effect or long lasting intraocular pressure lowering effects than the conventional commercially available antiglaucoma medications. Method of Literature Search The literature was searched on the Medline database using the PubMed interface. The key words for search were glaucoma, gene therapy, and genetic diagnosis of glaucoma.

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

    Directory of Open Access Journals (Sweden)

    Sadhukhan Provash

    2004-06-01

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

  9. Robust assignment of cancer subtypes from expression data using a uni-variate gene expression average as classifier

    International Nuclear Information System (INIS)

    Genome wide gene expression data is a rich source for the identification of gene signatures suitable for clinical purposes and a number of statistical algorithms have been described for both identification and evaluation of such signatures. Some employed algorithms are fairly complex and hence sensitive to over-fitting whereas others are more simple and straight forward. Here we present a new type of simple algorithm based on ROC analysis and the use of metagenes that we believe will be a good complement to existing algorithms. The basis for the proposed approach is the use of metagenes, instead of collections of individual genes, and a feature selection using AUC values obtained by ROC analysis. Each gene in a data set is assigned an AUC value relative to the tumor class under investigation and the genes are ranked according to these values. Metagenes are then formed by calculating the mean expression level for an increasing number of ranked genes, and the metagene expression value that optimally discriminates tumor classes in the training set is used for classification of new samples. The performance of the metagene is then evaluated using LOOCV and balanced accuracies. We show that the simple uni-variate gene expression average algorithm performs as well as several alternative algorithms such as discriminant analysis and the more complex approaches such as SVM and neural networks. The R package rocc is freely available at http://cran.r-project.org/web/packages/rocc/index.html

  10. Gene length and expression level shape genomic novelties

    OpenAIRE

    Grishkevich, Vladislav; YANAI, Itai

    2014-01-01

    Gene duplication and alternative splicing are important mechanisms in the production of genomic novelties. Previous work has shown that a gene’s family size and the number of splice variants it produces are inversely related, although the underlying reason is not well understood. Here, we report that gene length and expression level together explain this relationship. We found that gene lengths correlate with both gene duplication and alternative splicing: Longer genes are less likely to prod...

  11. Clinicopathologic and gene expression parameters predict liver cancer prognosis

    International Nuclear Information System (INIS)

    The prognosis of hepatocellular carcinoma (HCC) varies following surgical resection and the large variation remains largely unexplained. Studies have revealed the ability of clinicopathologic parameters and gene expression to predict HCC prognosis. However, there has been little systematic effort to compare the performance of these two types of predictors or combine them in a comprehensive model. Tumor and adjacent non-tumor liver tissues were collected from 272 ethnic Chinese HCC patients who received curative surgery. We combined clinicopathologic parameters and gene expression data (from both tissue types) in predicting HCC prognosis. Cross-validation and independent studies were employed to assess prediction. HCC prognosis was significantly associated with six clinicopathologic parameters, which can partition the patients into good- and poor-prognosis groups. Within each group, gene expression data further divide patients into distinct prognostic subgroups. Our predictive genes significantly overlap with previously published gene sets predictive of prognosis. Moreover, the predictive genes were enriched for genes that underwent normal-to-tumor gene network transformation. Previously documented liver eSNPs underlying the HCC predictive gene signatures were enriched for SNPs that associated with HCC prognosis, providing support that these genes are involved in key processes of tumorigenesis. When applied individually, clinicopathologic parameters and gene expression offered similar predictive power for HCC prognosis. In contrast, a combination of the two types of data dramatically improved the power to predict HCC prognosis. Our results also provided a framework for understanding the impact of gene expression on the processes of tumorigenesis and clinical outcome

  12. Gene expression profiling of differentially expressed genes in bull testicle between different scrotal circumference using DDRT

    International Nuclear Information System (INIS)

    To identify tissue-specific expression gene in testicle of differential scrotal circumference bulls and analyze the function of the specific gene on the development of the bull's scrotum in this study. The DDRT-PCR and Reverse Northern Blot Analysis were used to identify tissue-specific expression genes in bulls with differential scrotal circumference. The experiment was designed sixty 6-month-old crossbreeds (Charolais with indigenous Fuzhou female). These were raised under the same age, cross generation, raising condition and management. When the feeding was over after 6 months, the scrotal circumferences of bulls were measured. Four bulls were selected and classified into two groups, and the difference of scrotal circumference is significant between the two groups (P < 0.01). A group was consisted of two bulls with larger scrotal circumference 26±2.5cm. The control group was two crossbreed bulls with smaller scrotal circumference 17±2.2 cm. When the scrotal circumferences were measured, the bulls were castrated by surgical operations. A piece of tissue (2 by 2 by 2 cm) was removed from the deeper area of the testis and stored in liquid nitrogen. A small section (0.5 by 0.5 by 0.5 cm) was used for total RNA extraction by using the TRIZOL reagent kit (GIBCO/BRL, Bethesda, MA, USA). The RNA was prepared for DDRT-PCR experiments and quantitative real-time PCR. The results were shown that six genes corresponded to genes of known or inferred function; either the bovine gene or the likely human orthologue and three genes or ESTs were unknown. Bos taurus similar to galactosidase, beta 1-like; Bos taurus similar to Kinesin heavy chain isoform 5C; Bos taurus similar to ankyrin repeat domain protein 15 isoform and Bos taurus ebd-P2 pseudogene were founded both highly expressed in bulls which had bigger scrotal circumference by qRT-PCR. Their functions may be involved with sperm maturation in the epididymis, sperm protection and preventing the ascent of microorganisms

  13. Identification and validation of suitable endogenous reference genes for gene expression studies in human peripheral blood

    Directory of Open Access Journals (Sweden)

    Turner Renee J

    2009-08-01

    Full Text Available Abstract Background Gene expression studies require appropriate normalization methods. One such method uses stably expressed reference genes. Since suitable reference genes appear to be unique for each tissue, we have identified an optimal set of the most stably expressed genes in human blood that can be used for normalization. Methods Whole-genome Affymetrix Human 2.0 Plus arrays were examined from 526 samples of males and females ages 2 to 78, including control subjects and patients with Tourette syndrome, stroke, migraine, muscular dystrophy, and autism. The top 100 most stably expressed genes with a broad range of expression levels were identified. To validate the best candidate genes, we performed quantitative RT-PCR on a subset of 10 genes (TRAP1, DECR1, FPGS, FARP1, MAPRE2, PEX16, GINS2, CRY2, CSNK1G2 and A4GALT, 4 commonly employed reference genes (GAPDH, ACTB, B2M and HMBS and PPIB, previously reported to be stably expressed in blood. Expression stability and ranking analysis were performed using GeNorm and NormFinder algorithms. Results Reference genes were ranked based on their expression stability and the minimum number of genes needed for nomalization as calculated using GeNorm showed that the fewest, most stably expressed genes needed for acurate normalization in RNA expression studies of human whole blood is a combination of TRAP1, FPGS, DECR1 and PPIB. We confirmed the ranking of the best candidate control genes by using an alternative algorithm (NormFinder. Conclusion The reference genes identified in this study are stably expressed in whole blood of humans of both genders with multiple disease conditions and ages 2 to 78. Importantly, they also have different functions within cells and thus should be expressed independently of each other. These genes should be useful as normalization genes for microarray and RT-PCR whole blood studies of human physiology, metabolism and disease.

  14. Learning Gene Regulatory Networks Computationally from Gene Expression Data Using Weighted Consensus

    KAUST Repository

    Fujii, Chisato

    2015-04-16

    Gene regulatory networks analyze the relationships between genes allowing us to un- derstand the gene regulatory interactions in systems biology. Gene expression data from the microarray experiments is used to obtain the gene regulatory networks. How- ever, the microarray data is discrete, noisy and non-linear which makes learning the networks a challenging problem and existing gene network inference methods do not give consistent results. Current state-of-the-art study uses the average-ranking-based consensus method to combine and average the ranked predictions from individual methods. However each individual method has an equal contribution to the consen- sus prediction. We have developed a linear programming-based consensus approach which uses learned weights from linear programming among individual methods such that the methods have di↵erent weights depending on their performance. Our result reveals that assigning di↵erent weights to individual methods rather than giving them equal weights improves the performance of the consensus. The linear programming- based consensus method is evaluated and it had the best performance on in silico and Saccharomyces cerevisiae networks, and the second best on the Escherichia coli network outperformed by Inferelator Pipeline method which gives inconsistent results across a wide range of microarray data sets.

  15. Artificial transcription factor-mediated regulation of gene expression.

    Science.gov (United States)

    van Tol, Niels; van der Zaal, Bert J

    2014-08-01

    The transcriptional regulation of endogenous genes with artificial transcription factors (TFs) can offer new tools for plant biotechnology. Three systems are available for mediating site-specific DNA recognition of artificial TFs: those based on zinc fingers, TALEs, and on the CRISPR/Cas9 technology. Artificial TFs require an effector domain that controls the frequency of transcription initiation at endogenous target genes. These effector domains can be transcriptional activators or repressors, but can also have enzymatic activities involved in chromatin remodeling or epigenetic regulation. Artificial TFs are able to regulate gene expression in trans, thus allowing them to evoke dominant mutant phenotypes. Large scale changes in transcriptional activity are induced when the DNA binding domain is deliberately designed to have lower binding specificity. This technique, known as genome interrogation, is a powerful tool for generating novel mutant phenotypes. Genome interrogation has clear mechanistic and practical advantages over activation tagging, which is the technique most closely resembling it. Most notably, genome interrogation can lead to the discovery of mutant phenotypes that are unlikely to be found when using more conventional single gene-based approaches. PMID:25017160

  16. Assembly and Expression of Shark Ig Genes.

    Science.gov (United States)

    Hsu, Ellen

    2016-05-01

    Sharks are modern descendants of the earliest vertebrates possessing Ig superfamily receptor-based adaptive immunity. They respond to immunogen with Abs that, upon boosting, appear more rapidly and show affinity maturation. Specific Abs and immunological memory imply that Ab diversification and clonal selection exist in cartilaginous fish. Shark Ag receptors are generated through V(D)J recombination, and because it is a mechanism known to generate autoreactive receptors, this implies that shark lymphocytes undergo selection. In the mouse, the ∼2.8-Mb IgH and IgL loci require long-range, differential activation of component parts for V(D)J recombination, allelic exclusion, and receptor editing. These processes, including class switching, evolved with and appear inseparable from the complex locus organization. In contrast, shark Igs are encoded by 100-200 autonomously rearranging miniloci. This review describes how the shark primary Ab repertoire is generated in the absence of structural features considered essential in mammalian Ig gene assembly and expression. PMID:27183649

  17. Local gene expression in nerve endings.

    Science.gov (United States)

    Crispino, Marianna; Chun, Jong Tai; Cefaliello, Carolina; Perrone Capano, Carla; Giuditta, Antonio

    2014-03-01

    At the Nobel lecture for physiology in 1906, Ramón y Cajal famously stated that "the nerve elements possess reciprocal relationships in contiguity but not in continuity," summing up the neuron doctrine. Sixty years later, by the time the central dogma of molecular biology formulated the axis of genetic information flow from DNA to mRNA, and then to protein, it became obvious that neurons with extensive ramifications and long axons inevitably incur an innate problem: how can the effect of gene expression be extended from the nucleus to the remote and specific sites of the cell periphery? The most straightforward solution would be to deliver soma-produced proteins to the target sites. The influential discovery of axoplasmic flow has supported this scheme of protein supply. Alternatively, mRNAs can be dispatched instead of protein, and translated locally at the strategic target sites. Over the past decades, such a local system of protein synthesis has been demonstrated in dendrites, axons, and presynaptic terminals. Moreover, the local protein synthesis in neurons might even involve intercellular trafficking of molecules. The innovative concept of glia-neuron unit suggests that the local protein synthesis in the axonal and presynaptic domain of mature neurons is sustained by a local supply of RNAs synthesized in the surrounding glial cells and transferred to these domains. Here, we have reviewed some of the evidence indicating the presence of a local system of protein synthesis in axon terminals, and have examined its regulation in various model systems. PMID:23853157

  18. Mining Gene Expression Profiles: An Integrated Implementation of Kernel Principal Component Analysis and Singular Value Decomposition

    Institute of Scientific and Technical Information of China (English)

    Ferran Reverter; Esteban Vegas; Pedro Sánchez

    2010-01-01

    The detection of genes that show similar profiles under different experimental conditions is often an initial step in inferring the biological significance of such genes.Visualization tools are used to identify genes with similar profiles in microarray studies.Given the large number of genes recorded in microarray experiments,gene expression data are generally displayed on a low dimensional plot,based on linear methods.However,microarray data show nonlinearity,due to high-order terms of interaction between genes,so alternative approaches,such as kernel methods,may be more appropriate.We introduce a technique that combines kernel principal component analysis(KPCA)and Biplot to visualize gene expression profiles.Our approach relies on the singular value decomposition of the input matrix and incorporates an additional step that involves KPCA.The main properties of our method are the extraction of nonlinear features and the preservation of the input variables(genes)in the output display.We apply this algorithm to colon tumor,leukemia and lymphoma datasets.Our approach reveals the underlying structure of the gene expression profiles and provides a more intuitive understanding of the gene and sample association.

  19. Comparison of Larval and Adult Drosophila Astrocytes Reveals Stage-Specific Gene Expression Profiles

    OpenAIRE

    Huang, Yanmei; Ng, Fanny S.; Jackson, F. Rob

    2015-01-01

    The analysis of adult astrocyte glial cells has revealed a remarkable heterogeneity with regard to morphology, molecular signature, and physiology. A key question in glial biology is how such heterogeneity arises during brain development. One approach to this question is to identify genes with differential astrocyte expression during development; certain genes expressed later in neural development may contribute to astrocyte differentiation. We have utilized the Drosophila model and Translati...

  20. Application of simulated annealing to the biclustering of gene expression data

    OpenAIRE

    Bolshakova, Nadia; Cunningham, Padraig

    2006-01-01

    In a gene expression data matrix, a bicluster is a submatrix of genes and conditions that exhibits a high correlation of expression activity across both rows and columns. The problem of locating the most significant bicluster has been shown to be NP-complete. Heuristic approaches such as Cheng and Church?s greedy node deletion algorithm have been previously employed. It is to be expected that stochastic search techniques such as evolutionary algorithms or simulated anneal...

  1. Global analysis of nutrient control of gene expression in Saccharomyces cerevisiae during growth and starvation

    OpenAIRE

    Wu, Jian; Zhang, Nianshu; Hayes, Andrew; Panoutsopoulou, Kalliope; Oliver, Stephen G.

    2004-01-01

    Global gene expression in yeast was examined in five different nutrient-limited steady states and in their corresponding starvation-induced stationary phases. The use of chemostats, with their ability to generate defined and reproducible physiological conditions, permitted the exclusion of the confounding variables that frequently complicate transcriptome analyses. This approach allowed us to dissect out effects on gene expression that are specific to particular physiological states. Thus, we...

  2. Integrated Weighted Gene Co-expression Network Analysis with an Application to Chronic Fatigue Syndrome

    OpenAIRE

    Rajeevan Mangalathu S; Suarez Charlyn J; Whistler Toni; Papp Jeanette C; Sobel Eric M; Presson Angela P; Vernon Suzanne D; Horvath Steve

    2008-01-01

    Abstract Background Systems biologic approaches such as Weighted Gene Co-expression Network Analysis (WGCNA) can effectively integrate gene expression and trait data to identify pathways and candidate biomarkers. Here we show that the additional inclusion of genetic marker data allows one to characterize network relationships as causal or reactive in a chronic fatigue syndrome (CFS) data set. Results We combine WGCNA with genetic marker data to identify a disease-related pathway and its causa...

  3. Isolation of Specific Neurons from C. elegans Larvae for Gene Expression Profiling

    OpenAIRE

    W Clay Spencer; Rebecca McWhirter; Tyne Miller; Pnina Strasbourger; Owen Thompson; Hillier, LaDeana W.; Waterston, Robert H.; Miller, David M.

    2014-01-01

    Background The simple and well-described structure of the C. elegans nervous system offers an unprecedented opportunity to identify the genetic programs that define the connectivity and function of individual neurons and their circuits. A correspondingly precise gene expression map of C. elegans neurons would facilitate the application of genetic methods toward this goal. Here we describe a powerful new approach, SeqCeL (RNA-Seq of C. elegans cells) for producing gene expression profiles of s...

  4. Ranking differentially expressed genes from Affymetrix gene expression data: methods with reproducibility, sensitivity, and specificity

    Directory of Open Access Journals (Sweden)

    Shimizu Kentaro

    2009-04-01

    Full Text Available Abstract Background To identify differentially expressed genes (DEGs from microarray data, users of the Affymetrix GeneChip system need to select both a preprocessing algorithm to obtain expression-level measurements and a way of ranking genes to obtain the most plausible candidates. We recently recommended suitable combinations of a preprocessing algorithm and gene ranking method that can be used to identify DEGs with a higher level of sensitivity and specificity. However, in addition to these recommendations, researchers also want to know which combinations enhance reproducibility. Results We compared eight conventional methods for ranking genes: weighted average difference (WAD, average difference (AD, fold change (FC, rank products (RP, moderated t statistic (modT, significance analysis of microarrays (samT, shrinkage t statistic (shrinkT, and intensity-based moderated t statistic (ibmT with six preprocessing algorithms (PLIER, VSN, FARMS, multi-mgMOS (mmgMOS, MBEI, and GCRMA. A total of 36 real experimental datasets was evaluated on the basis of the area under the receiver operating characteristic curve (AUC as a measure for both sensitivity and specificity. We found that the RP method performed well for VSN-, FARMS-, MBEI-, and GCRMA-preprocessed data, and the WAD method performed well for mmgMOS-preprocessed data. Our analysis of the MicroArray Quality Control (MAQC project's datasets showed that the FC-based gene ranking methods (WAD, AD, FC, and RP had a higher level of reproducibility: The percentages of overlapping genes (POGs across different sites for the FC-based methods were higher overall than those for the t-statistic-based methods (modT, samT, shrinkT, and ibmT. In particular, POG values for WAD were the highest overall among the FC-based methods irrespective of the choice of preprocessing algorithm. Conclusion Our results demonstrate that to increase sensitivity, specificity, and reproducibility in microarray analyses, we need

  5. Microdissection of the gene expression codes driving nephrogenesis.

    Science.gov (United States)

    Potter, S Steven; Brunskill, Eric W; Patterson, Larry T

    2010-01-01

    The kidney represents an excellent model system for learning the principles of organogenesis. It is intermediate in complexity, and employs many commonly used developmental processes. As such, kidney development has been the subject of intensive study, using a variety of techniques, including in situ hybridization, organ culture and gene targeting, revealing many critical genes and pathways. Nevertheless, proper organogenesis requires precise patterns of cell type specific differential gene expression, involving very large numbers of genes. This review is focused on the use of global profiling technologies to create an atlas of gene expression codes driving development of different mammalian kidney compartments. Such an atlas allows one to select a gene of interest, and to determine its expression level in each element of the developing kidney, or to select a structure of interest, such as the renal vesicle, and to examine its complete gene expression state. Novel component specific molecular markers are identified, and the changing waves of gene expression that drive nephrogenesis are defined. As the tools continue to improve for the purification of specific cell types and expression profiling of even individual cells it is possible to predict an atlas of gene expression during kidney development that extends to single cell resolution. PMID:21220959

  6. Congruence of tissue expression profiles from Gene Expression Atlas, SAGEmap and TissueInfo databases

    Directory of Open Access Journals (Sweden)

    Wolfe Kenneth H

    2003-07-01

    Full Text Available Abstract Background Extracting biological knowledge from large amounts of gene expression information deposited in public databases is a major challenge of the postgenomic era. Additional insights may be derived by data integration and cross-platform comparisons of expression profiles. However, database meta-analysis is complicated by differences in experimental technologies, data post-processing, database formats, and inconsistent gene and sample annotation. Results We have analysed expression profiles from three public databases: Gene Expression Atlas, SAGEmap and TissueInfo. These are repositories of oligonucleotide microarray, Serial Analysis of Gene Expression and Expressed Sequence Tag human gene expression data respectively. We devised a method, Preferential Expression Measure, to identify genes that are significantly over- or under-expressed in any given tissue. We examined intra- and inter-database consistency of Preferential Expression Measures. There was good correlation between replicate experiments of oligonucleotide microarray data, but there was less coherence in expression profiles as measured by Serial Analysis of Gene Expression and Expressed Sequence Tag counts. We investigated inter-database correlations for six tissue categories, for which data were present in the three databases. Significant positive correlations were found for brain, prostate and vascular endothelium but not for ovary, kidney, and pancreas. Conclusion We show that data from Gene Expression Atlas, SAGEmap and TissueInfo can be integrated using the UniGene gene index, and that expression profiles correlate relatively well when large numbers of tags are available or when tissue cellular composition is simple. Finally, in the case of brain, we demonstrate that when PEM values show good correlation, predictions of tissue-specific expression based on integrated data are very accurate.

  7. Expression and mapping of anthocyanin biosynthesis genes in carrot

    Science.gov (United States)

    Anthocyanin gene expression has been extensively studied in leaves, fruits and flowers of numerous plants. Little, however, is known about anthocyanin accumulation in roots, or in carrots or other Apiaceae. We quantified expression of six anthocyanin biosynthetic genes (phenylalanine ammonia-lyase (...

  8. Using differential gene expression to study Entamoeba histolytica pathogenesis

    OpenAIRE

    Gilchrist, Carol A.; Petri, William A.

    2009-01-01

    The release of the Entamoeba histolytica genome has facilitated the development of techniques to survey rapidly and to relate gene expression with biology. The association and potential contribution of differential gene expression to the life cycle and the virulence of this protozoan parasite of humans are reviewed here.

  9. Meta-analysis of differentially expressed genes in ankylosing spondylitis.

    Science.gov (United States)

    Lee, Y H; Song, G G

    2015-01-01

    The purpose of this study was to identify differentially expressed (DE) genes and biological processes associated with changes in gene expression in ankylosing spondylitis (AS). We performed a meta-analysis using the integrative meta-analysis of expression data program on publicly available microarray AS Gene Expression Omnibus (GEO) datasets. We performed Gene Ontology (GO) enrichment analyses and pathway analysis using the Kyoto Encyclopedia of Genes and Genomes. Four GEO datasets, including 31 patients with AS and 39 controls, were available for the meta-analysis. We identified 65 genes across the studies that were consistently DE in patients with AS vs controls (23 upregulated and 42 downregulated). The upregulated gene with the largest effect size (ES; -1.2628, P = 0.020951) was integral membrane protein 2A (ITM2A), which is expressed by CD4+ T cells and plays a role in activation of T cells. The downregulated gene with the largest ES (1.2299, P = 0.040075) was mitochondrial ribosomal protein S11 (MRPS11). The most significant GO enrichment was in the respiratory electron transport chain category (P = 1.67 x 10-9). Therefore, our meta-analysis identified genes that were consistently DE as well as biological pathways associated with gene expression changes in AS. PMID:26125709

  10. ANALYSES ON DIFFERENTIALLY EXPRESSED GENES ASSOCIATED WITH HUMAN BREAST CANCER

    Institute of Scientific and Technical Information of China (English)

    MENG Xu-li; DING Xiao-wen; XU Xiao-hong

    2006-01-01

    Objective: To investigate the molecular etiology of breast cancer by way of studying the differential expression and initial function of the related genes in the occurrence and development of breast cancer. Methods: Two hundred and eighty-eight human tumor related genes were chosen for preparation of the oligochips probe. mRNA was extracted from 16 breast cancer tissues and the corresponding normal breast tissues, and cDNA probe was prepared through reverse-transcription and hybridized with the gene chip. A laser focused fluorescent scanner was used to scan the chip. The different gene expressions were thereafter automatically compared and analyzed between the two sample groups. Cy3/Cy5>3.5 meant significant up-regulation. Cy3/Cy5<0.25 meant significant down-regulation. Results: The comparison between the breast cancer tissues and their corresponding normal tissues showed that 84 genes had differential expression in the Chip. Among the differently expressed genes, there were 4 genes with significant down-regulation and 6 with significant up-regulation. Compared with normal breast tissues, differentially expressed genes did partially exist in the breast cancer tissues. Conclusion: Changes in multi-gene expression regulations take place during the occurrence and development of breast cancer; and the research on related genes can help understanding the mechanism of tumor occurrence.

  11. More attention should be paid on the interpretation of gene expression data

    Institute of Scientific and Technical Information of China (English)

    Eric Verna

    2012-01-01

    Molecular profiling of gene expression is important for determining signatures in cancer progression and diagnosis.For this purpose,polymerase chain reactionbased techniques are preferentially used as a feasible and sensitive approach.Nevertheless,when relative quantitative analyses are performed on gene expression,the interpretation of mathematical equations must be carefully done.This letter to the editor is focused on recently published gene expression data in World Journal of Gastroenterology by Ozmen et al demonstrating increased levels of LYVE-1,VEGFR-3 and CD44 genes in gastric cancer samples compared to nonneoplastic gastric tissues.However,there are major concerns about misinterpretation of the gene expression data obtained with the 2-△△ct relative quantitative method.In the study,2-△△Ct values calculated for many samples were smaller than 1 (2-△△ct < 1) which indicate decreased levels of LYVE-1,VEGFR-3 and CD44 gene expression in the gastric cancer tissues.This unfortunate mistake is an important example showing how a simple error in the interpretation of relative-quantitative gene expression data may result in misleading scientific conclusions.In this letter,a brief explanation of the 2-△△ct method is given.In addition,the importance of technical quality and interpretation in gene expression studies is discussed.

  12. MALDI-TOF mass spectrometry for quantitative gene expression analysis of acid responses in Staphylococcus aureus.

    Science.gov (United States)

    Rode, Tone Mari; Berget, Ingunn; Langsrud, Solveig; Møretrø, Trond; Holck, Askild

    2009-07-01

    Microorganisms are constantly exposed to new and altered growth conditions, and respond by changing gene expression patterns. Several methods for studying gene expression exist. During the last decade, the analysis of microarrays has been one of the most common approaches applied for large scale gene expression studies. A relatively new method for gene expression analysis is MassARRAY, which combines real competitive-PCR and MALDI-TOF (matrix-assisted laser desorption/ionization time-of-flight) mass spectrometry. In contrast to microarray methods, MassARRAY technology is suitable for analysing a larger number of samples, though for a smaller set of genes. In this study we compare the results from MassARRAY with microarrays on gene expression responses of Staphylococcus aureus exposed to acid stress at pH 4.5. RNA isolated from the same stress experiments was analysed using both the MassARRAY and the microarray methods. The MassARRAY and microarray methods showed good correlation. Both MassARRAY and microarray estimated somewhat lower fold changes compared with quantitative real-time PCR (qRT-PCR). The results confirmed the up-regulation of the urease genes in acidic environments, and also indicated the importance of metal ion regulation. This study shows that the MassARRAY technology is suitable for gene expression analysis in prokaryotes, and has advantages when a set of genes is being analysed for an organism exposed to many different environmental conditions. PMID:19445975

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

    Science.gov (United States)

    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. Gene expression of the mismatch repair gene MSH2 in primary colorectal cancer

    DEFF Research Database (Denmark)

    Jensen, Lars Henrik; Kuramochi, Hidekazu; Crüger, Dorthe Gylling; Lindebjerg, Jan; Kolvraa, Steen; Danenberg, Peter; Danenberg, Kathleen; Jakobsen, Anders

    2011-01-01

    marker for the level of MMR and a potential molecular marker with clinical relevance. The aim was to investigate the gene expression of MSH2 in primary operable colorectal cancer in correlation with MSI, protein expression, and promoter hypermethylation. In a cohort of 210 patients, the primary tumor and...... promoter was only detected in 14 samples and only at a low level with no correlation to gene expression. MSH2 gene expression was not a prognostic factor for overall survival in univariate or multivariate analysis. The gene expression of MSH2 is a potential quantitative marker ready for further clinical...

  15. Gene Expression Measurement Module (GEMM) - a fully automated, miniaturized instrument for measuring gene expression in space

    Science.gov (United States)

    Karouia, Fathi; Ricco, Antonio; Pohorille, Andrew; Peyvan, Kianoosh

    2012-07-01

    The capability to measure gene expression on board spacecrafts opens the doors to a large number of experiments on the influence of space environment on biological systems that will profoundly impact our ability to conduct safe and effective space travel, and might also shed light on terrestrial physiology or biological function and human disease and aging processes. Measurements of gene expression will help us to understand adaptation of terrestrial life to conditions beyond the planet of origin, identify deleterious effects of the space environment on a wide range of organisms from microbes to humans, develop effective countermeasures against these effects, determine metabolic basis of microbial pathogenicity and drug resistance, test our ability to sustain and grow in space organisms that can be used for life support and in situ resource utilization during long-duration space exploration, and monitor both the spacecraft environment and crew health. These and other applications hold significant potential for discoveries in space biology, biotechnology and medicine. Accordingly, supported by funding from the NASA Astrobiology Science and Technology Instrument Development Program, we are developing a fully automated, miniaturized, integrated fluidic system for small spacecraft capable of in-situ measuring microbial expression of thousands of genes from multiple samples. The instrument will be capable of (1) lysing bacterial cell walls, (2) extracting and purifying RNA released from cells, (3) hybridizing it on a microarray and (4) providing electrochemical readout, all in a microfluidics cartridge. The prototype under development is suitable for deployment on nanosatellite platforms developed by the NASA Small Spacecraft Office. The first target application is to cultivate and measure gene expression of the photosynthetic bacterium Synechococcus elongatus, i.e. a cyanobacterium known to exhibit remarkable metabolic diversity and resilience to adverse conditions

  16. Expression profile of genes associated with mastitis in dairy cattle

    OpenAIRE

    Fonseca, Isabela; Silva, Priscila Vendramini; Lange, Carla Christine; Guimarães, Marta F. M.; Weller, Mayara Morena Del Cambre Amaral; Sousa, Katiene Régia Silva; Lopes, Paulo Sávio; Guimarães, José Domingos; Simone E.F. Guimarães

    2009-01-01

    In order to characterize the expression of genes associated with immune response mechanisms to mastitis, we quantified the relative expression of the IL-2, IL-4, IL-6, IL-8, IL-10, IFN-γ and TNF- α genes in milk cells of healthy cows and cows with clinical mastitis. Total RNA was extracted from milk cells of six Black and White Holstein (BW) cows and six Gyr cows, including three animals with and three without mastitis per breed. Gene expression was analyzed by real-time PCR. IL-10 gene expre...

  17. Use of eukaryotic expression technology in the functional analysis of cloned genes

    International Nuclear Information System (INIS)

    The purpose of this chapter is to describe ways in which eukaryotic expression technology can be used to identify and to analyze the function of cloned eukaryotic genes. The assumption is made that the clone of interest has been sequenced and an open reading frame has been identified. Although expression of genomic sequences will be briefly discussed, in general it is assumed that the sequence of interest is a cDNA. This chapter is divided into three sections. The first section describes several possible strategies for maximizing heterologous gene expression in the cells of higher eukaryotes. The second section deals with potential assays for gene expression based on function, and the third section describes some immunological approaches. Overall, the focus is on the use of techniques which yield information not obtainable from heterologous gene expression in bacteria or yeast

  18. Decoupling Linear and Nonlinear Associations of Gene Expression

    KAUST Repository

    Itakura, Alan

    2013-05-01

    The FANTOM consortium has generated a large gene expression dataset of different cell lines and tissue cultures using the single-molecule sequencing technology of HeliscopeCAGE. This provides a unique opportunity to investigate novel associations between gene expression over time and different cell types. Here, we create a MatLab wrapper for a powerful and computationally intensive set of statistics known as Maximal Information Coefficient, and then calculate this statistic for a large, comprehensive dataset containing gene expression of a variety of differentiating tissues. We then distinguish between linear and nonlinear associations, and then create gene association networks. Following this analysis, we are then able to identify clusters of linear gene associations that then associate nonlinearly with other clusters of linearity, providing insight to much more complex connections between gene expression patterns than previously anticipated.

  19. Gene expression profiling of placentas affected by pre-eclampsia

    DEFF Research Database (Denmark)

    Hoegh, Anne Mette; Borup, Rehannah; Nielsen, Finn Cilius;

    2010-01-01

    expression from pooled samples was analysed by microarrays. Verification of the expression of selected genes was performed using real-time PCR. A surprisingly low number of genes (21 out of 15,000) were identified as differentially expressed. Among these were genes not previously associated with pre......-eclampsia as bradykinin B1 receptor and a 14-3-3 protein, but also genes that have already been connected with pre-eclampsia, for example, inhibin beta A subunit and leptin. A low number of genes were repeatedly identified as differentially expressed, because they may represent the endpoint of a cascade of......Several studies point to the placenta as the primary cause of pre-eclampsia. Our objective was to identify placental genes that may contribute to the development of pre-eclampsia. RNA was purified from tissue biopsies from eleven pre-eclamptic placentas and eighteen normal controls. Messenger RNA...

  20. Imaging gene expression in real-time using aptamers

    Energy Technology Data Exchange (ETDEWEB)

    Shin, Ilchung [Iowa State Univ., Ames, IA (United States)

    2012-01-01

    Signal transduction pathways are usually activated by external stimuli and are transient. The downstream changes such as transcription of the activated genes are also transient. Real-time detection of promoter activity is useful for understanding changes in gene expression, especially during cell differentiation and in development. A simple and reliable method for viewing gene expression in real time is not yet available. Reporter proteins such as fluorescent proteins and luciferase allow for non-invasive detection of the products of gene expression in living cells. However, current reporter systems do not provide for real-time imaging of promoter activity in living cells. This is because of the long time period after transcription required for fluorescent protein synthesis and maturation. We have developed an RNA reporter system for imaging in real-time to detect changes in promoter activity as they occur. The RNA reporter uses strings of RNA aptamers that constitute IMAGEtags (Intracellular MultiAptamer GEnetic tags), which can be expressed from a promoter of choice. The tobramycin, neomycin and PDC RNA aptamers have been utilized for this system and expressed in yeast from the GAL1 promoter. The IMAGEtag RNA kinetics were quantified by RT-qPCR. In yeast precultured in raffinose containing media the GAL1 promoter responded faster than in yeast precultured in glucose containing media. IMAGEtag RNA has relatively short half-life (5.5 min) in yeast. For imaging, the yeast cells are incubated with their ligands that are labeled with fluorescent dyes. To increase signal to noise, ligands have been separately conjugated with the FRET (Förster resonance energy transfer) pairs, Cy3 and Cy5. With these constructs, the transcribed aptamers can be imaged after activation of the promoter by galactose. FRET was confirmed with three different approaches, which were sensitized emission, acceptor photobleaching and donor lifetime by FLIM (fluorescence lifetime imaging

  1. Imaging gene expression in real-time using aptamers

    Energy Technology Data Exchange (ETDEWEB)

    Shin, Il Chung [Iowa State Univ., Ames, IA (United States)

    2011-01-01

    Signal transduction pathways are usually activated by external stimuli and are transient. The downstream changes such as transcription of the activated genes are also transient. Real-time detection of promoter activity is useful for understanding changes in gene expression, especially during cell differentiation and in development. A simple and reliable method for viewing gene expression in real time is not yet available. Reporter proteins such as fluorescent proteins and luciferase allow for non-invasive detection of the products of gene expression in living cells. However, current reporter systems do not provide for real-time imaging of promoter activity in living cells. This is because of the long time period after transcription required for fluorescent protein synthesis and maturation. We have developed an RNA reporter system for imaging in real-time to detect changes in promoter activity as they occur. The RNA reporter uses strings of RNA aptamers that constitute IMAGEtags (Intracellular MultiAptamer GEnetic tags), which can be expressed from a promoter of choice. The tobramycin, neomycin and PDC RNA aptamers have been utilized for this system and expressed in yeast from the GAL1 promoter. The IMAGEtag RNA kinetics were quantified by RT-qPCR. In yeast precultured in raffinose containing media the GAL1 promoter responded faster than in yeast precultured in glucose containing media. IMAGEtag RNA has relatively short half-life (5.5 min) in yeast. For imaging, the yeast cells are incubated with their ligands that are labeled with fluorescent dyes. To increase signal to noise, ligands have been separately conjugated with the FRET (Förster resonance energy transfer) pairs, Cy3 and Cy5. With these constructs, the transcribed aptamers can be imaged after activation of the promoter by galactose. FRET was confirmed with three different approaches, which were sensitized emission, acceptor photobleaching and donor lifetime by FLIM (fluorescence lifetime imaging

  2. Genetic analysis of DNA methylation and gene expression levels in whole blood of healthy human subjects

    Directory of Open Access Journals (Sweden)

    van Eijk Kristel R

    2012-11-01

    Full Text Available Abstract Background The predominant model for regulation of gene expression through DNA methylation is an inverse association in which increased methylation results in decreased gene expression levels. However, recent studies suggest that the relationship between genetic variation, DNA methylation and expression is more complex. Results Systems genetic approaches for examining relationships between gene expression and methylation array data were used to find both negative and positive associations between these levels. A weighted correlation network analysis revealed that i both transcriptome and methylome are organized in modules, ii co-expression modules are generally not preserved in the methylation data and vice-versa, and iii highly significant correlations exist between co-expression and co-methylation modules, suggesting the existence of factors that affect expression and methylation of different modules (i.e., trans effects at the level of modules. We observed that methylation probes associated with expression in cis were more likely to be located outside CpG islands, whereas specificity for CpG island shores was present when methylation, associated with expression, was under local genetic control. A structural equation model based analysis found strong support in particular for a traditional causal model in which gene expression is regulated by genetic variation via DNA methylation instead of gene expression affecting DNA methylation levels. Conclusions Our results provide new insights into the complex mechanisms between genetic markers, epigenetic mechanisms and gene expression. We find strong support for the classical model of genetic variants regulating methylation, which in turn regulates gene expression. Moreover we show that, although the methylation and expression modules differ, they are highly correlated.

  3. Integration of biological networks and gene expression data using Cytoscape

    DEFF Research Database (Denmark)

    Cline, M.S.; Smoot, M.; Cerami, E.;

    2007-01-01

    interaction network obtained for genes of interest. Five major steps are described: (i) obtaining a gene or protein network, (ii) displaying the network using layout algorithms, (iii) integrating with gene expression and other functional attributes, (iv) identifying putative complexes and functional modules...

  4. Dimensionality of Data Matrices with Applications to Gene Expression Profiles

    Science.gov (United States)

    Feng, Xingdong

    2009-01-01

    Probe-level microarray data are usually stored in matrices. Take a given probe set (gene), for example, each row of the matrix corresponds to an array, and each column corresponds to a probe. Often, people summarize each array by the gene expression level. Is one number sufficient to summarize a whole probe set for a specific gene in an array?…

  5. Gene expression profiling in adipose tissue from growing broiler chickens

    Science.gov (United States)

    Hausman, Gary J; Barb, C Rick; Fairchild, Brian D; Gamble, John; Lee-Rutherford, Laura

    2014-01-01

    In this study, total RNA was collected from abdominal adipose tissue samples obtained from ten broiler chickens at 3, 4, 5, and 6 weeks of age and prepared for gene microarray analysis with Affymetrix GeneChip Chicken Genome Arrays (Affymetrix) and quantitative real-time PCR analysis. Studies of global gene expression in chicken adipose tissue were initiated since such studies in many animal species show that adipose tissue expresses and secretes many factors that can influence growth and physiology. Microarray results indicated 333 differentially expressed adipose tissue genes between 3 and 6 wk, 265 differentially expressed genes between 4 and 6 wk and 42 differentially expressed genes between 3 and 4 wk. Enrichment scores of Gene Ontology Biological Process categories indicated strong age upregulation of genes involved in the immune system response. In addition to microarray analysis, quantitative real-time PCR analysis was used to confirm the influence of age on the expression of adipose tissue CC chemokine ligands (CCL), toll-like receptor (TLR)-2, lipopolysaccharide-induced TNF factor (LITAF), chemokine (C-C motif) receptor 8 (CCR8), and several other genes. Between 3 and 6 wk of age CCL5, CCL1, and CCR8 expression increased (P = 0.0001) with age. Furthermore, TLR2, CCL19, and LITAF expression increased between 4 and 6 wk of age (P = 0.001). This is the first demonstration of age related changes in CCL, LITAF, and TLR2 gene expression in chicken adipose tissue. Future studies are needed to elucidate the role of these adipose tissue genes in growth and the immune system. PMID:26317054

  6. Discovering Coherent Biclusters from Gene Expression Data Using Zero-Suppressed Binary Decision Diagrams

    OpenAIRE

    Yoon, Sungroh; Nardini, Christine; Benini, Luca; De Micheli, Giovanni

    2005-01-01

    The biclustering method can be a very useful analysis tool when some genes have multiple functions and experimental conditions are diverse in gene expression measurement. This is because the biclustering approach, in contrast to the conventional clustering techniques, focuses on finding a subset of the genes and a subset of the experimental conditions that together exhibit coherent behavior. However, the biclustering problem is inherently intractable, and it is often computationally costly to...

  7. Regulated expression of foreign genes in vivo after germline transfer.

    OpenAIRE

    Passman, R S; Fishman, G I

    1994-01-01

    Tight transcriptional control of foreign genes introduced into the germline of transgenic mice would be of great experimental value in studies of gene function. To develop a system in which the spatial and temporal expression of candidate genes implicated in cardiac development or function could be tightly controlled in vivo, we have generated transgenic mice expressing a tetracycline-controlled transactivator (tTA) under the control of a rat alpha myosin heavy chain promoter (MHC alpha-tTA m...

  8. Expression of intestinal transporter genes in beagle dogs

    OpenAIRE

    Cho, Soo-Min; Park, Sung-Won; Kim, Na-Hyun; Park, Jin-A; YI, HEE; CHO, Hee-Jung; PARK, KI-HWAN; HWANG, INGYUN; Shin, Ho-Chul

    2012-01-01

    This study was performed to produce a transcriptional database of the intestinal transporters of beagle dogs. Total RNA was isolated from the duodenum and the expression of various mRNAs was measured using GeneChip® oligonucleotide arrays. A total of 124 transporter genes were detected. Genes for fatty acid, peptide, amino acid and glucose and multidrug resistance/multidrug resistance-associated protein (MDR/MRP) transport were expressed at relatively higher levels than the other transporter ...

  9. Inducible gene expression system by 3-hydroxypropionic acid

    OpenAIRE

    Zhou, Shengfang; Ainala, Satish Kumar; Seol, Eunhee; Nguyen, Trinh Thi; Park, Sunghoon

    2015-01-01

    Background 3-Hydroxypropionic acid (3-HP) is an important platform chemical that boasts a variety of industrial applications. Gene expression systems inducible by 3-HP, if available, are of great utility for optimization of the pathways of 3-HP production and excretion. Results Here we report the presence of unique inducible gene expression systems in Pseudomonas denitrificans and other microorganisms. In P. denitrificans, transcription of three genes (hpdH, mmsA and hbdH-4) involved in 3-HP ...

  10. Pancreatic expression of human insulin gene in transgenic mice.

    OpenAIRE

    Bucchini, D; Ripoche, M A; Stinnakre, M G; Desbois, P; Lorès, P; Monthioux, E; Absil, J; Lepesant, J A; Pictet, R; Jami, J

    1986-01-01

    We have investigated the possibility of obtaining integration and expression of a native human gene in transgenic mice. An 11-kilobase (kb) human chromosomal DNA fragment including the insulin gene (1430 base pairs) was microinjected into fertilized mouse eggs. This fragment was present in the genomic DNA of several developing animals. One transgenic mouse and its progeny were analyzed for expression of the foreign gene. Synthesis and release of human insulin was revealed by detection of the ...

  11. An Effective Tri-Clustering Algorithm Combining Expression Data with Gene Regulation Information

    Directory of Open Access Journals (Sweden)

    Ao Li

    2009-04-01

    Full Text Available Motivation: Bi-clustering algorithms aim to identify sets of genes sharing similar expression patterns across a subset of conditions. However direct interpretation or prediction of gene regulatory mechanisms may be difficult as only gene expression data is used. Information about gene regulators may also be available, most commonly about which transcription factors may bind to the promoter region and thus control the expression level of a gene. Thus a method to integrate gene expression and gene regulation information is desirable for clustering and analyzing. Methods: By incorporating gene regulatory information with gene expression data, we define regulated expression values (REV as indicators of how a gene is regulated by a specific factor. Existing bi-clustering methods are extended to a three dimensional data space by developing a heuristic TRI-Clustering algorithm. An additional approach named Automatic Boundary Searching algorithm (ABS is introduced to automatically determine the boundary threshold. Results: Results based on incorporating ChIP-chip data representing transcription factor-gene interactions show that the algorithms are efficient and robust for detecting tri-clusters. Detailed analysis of the tri-cluster extracted from yeast sporulation REV data shows genes in this cluster exhibited significant differences during the middle and late stages. The implicated regulatory network was then reconstructed for further study of defined regulatory mechanisms. Topological and statistical analysis of this network demonstrated evidence of significant changes of TF activities during the different stages of yeast sporulation, and suggests this approach might be a general way to study regulatory networks undergoing transformations.

  12. Elucidating gene function and function evolution through comparison of co-expression networks in plants

    Directory of Open Access Journals (Sweden)

    Marek Mutwil

    2014-08-01

    Full Text Available The analysis of gene expression data has shown that transcriptionally coordinated (co-expressed genes are often functionally related, enabling scientists to use expression data in gene function prediction. This Focused Review discusses our original paper (Large-scale co-expression approach to dissect secondary cell wall formation across plant species, Frontiers in Plant Science 2:23. In this paper we applied cross-species analysis to co-expression networks of genes involved in cellulose biosynthesis. We show that the co-expression networks from different species are highly similar, indicating that whole biological pathways are conserved across species. This finding has two important implications. First, the analysis can transfer gene function annotation from well-studied plants, such as Arabidopsis, to other, uncharacterized plant species. As the analysis finds genes that have similar sequence and similar expression pattern across different organisms, functionally equivalent genes can be identified. Second, since co-expression analyses are often noisy, a comparative analysis should have higher performance, as parts of co-expression networks that are conserved are more likely to be functionally relevant. In this Focused Review, we outline the comparative analysis done in the original paper and comment on the recent advances and approaches that allow comparative analyses of co-function networks. We hypothesize that, in comparison to simple co-expression analysis, comparative analysis would yield more accurate gene function predictions. Finally, by combining comparative analysis with genomic information of green plants, we propose a possible composition of cellulose biosynthesis machinery during earlier stages of plant evolution.

  13. Performance Analysis of Enhanced Clustering Algorithm for Gene Expression Data

    Directory of Open Access Journals (Sweden)

    T. Chandrasekhar

    2011-11-01

    Full Text Available Microarrays are made it possible to simultaneously monitor the expression profiles of thousands of genes under various experimental conditions. It is used to identify the co-expressed genes in specific cells or tissues that are actively used to make proteins. This method is used to analysis the gene expression, an important task in bioinformatics research. Cluster analysis of gene expression data has proved to be a useful tool for identifying co-expressed genes, biologically relevant groupings of genes and samples. In this paper we applied K-Means with Automatic Generations of Merge Factor for ISODATA- AGMFI. Though AGMFI has been applied for clustering of Gene Expression Data, this proposed Enhanced Automatic Generations of Merge Factor for ISODATA- EAGMFI Algorithms overcome the drawbacks of AGMFI in terms of specifying the optimal number of clusters and initialization of good cluster centroids. Experimental results on Gene Expression Data show that the proposed EAGMFI algorithms could identify compact clusters with perform well in terms of the Silhouette Coefficients cluster measure.

  14. Sequential construction of a model for modular gene expression control, applied to spatial patterning of the Drosophila gene hunchback.

    Science.gov (United States)

    Spirov, Alexander V; Myasnikova, Ekaterina M; Holloway, David M

    2016-04-01

    Gene network simulations are increasingly used to quantify mutual gene regulation in biological tissues. These are generally based on linear interactions between single-entity regulatory and target genes. Biological genes, by contrast, commonly have multiple, partially independent, cis-regulatory modules (CRMs) for regulator binding, and can produce variant transcription and translation products. We present a modeling framework to address some of the gene regulatory dynamics implied by this biological complexity. Spatial patterning of the hunchback (hb) gene in Drosophila development involves control by three CRMs producing two distinct mRNA transcripts. We use this example to develop a differential equations model for transcription which takes into account the cis-regulatory architecture of the gene. Potential regulatory interactions are screened by a genetic algorithms (GAs) approach and compared to biological expression data. PMID:27122317

  15. GEE: An Informatics Tool for Gene Expression Data Explore

    OpenAIRE

    Lee, Soo Youn; Park, Chan Hee; Yoon, Jun Hee; Yun, Sunmin; Kim, Ju Han

    2016-01-01

    Objectives Major public high-throughput functional genomic data repositories, including the Gene Expression Omnibus (GEO) and ArrayExpress have rapidly expanded. As a result, a large number of diverse high-throughput functional genomic data retrieval systems have been developed. However, high-throughput functional genomic data retrieval remains challenging. Methods We developed Gene Expression data Explore (GEE), the first powerful, flexible web and mobile search application for searching who...

  16. Gene Expression Profiling in the Brains of Human Cocaine Abusers

    OpenAIRE

    Bannon, Michael J.; Kapatos, Gregory; ALBERTSON, DAWN N.

    2005-01-01

    Chronic cocaine abuse induces long-term neurochemical, structural and behavioural changes thought to result from altered gene expression within the nucleus accumbens and other brain regions playing a critical role in addiction. Recent methodological advances now allow the profiling of gene expression in human postmortem brain. In this article, we review studies in which we have used Affymetrix oligonucleotide microarrays to identify transcripts that are differentially expressed in the nucleus...

  17. Assessment of Normal Variability in Peripheral Blood Gene Expression

    OpenAIRE

    Catherine Campbell; Vernon, Suzanne D; Karem, Kevin L.; Rosane Nisenbaum; Unger, Elizabeth R

    2002-01-01

    Peripheral blood is representative of many systemic processes and is an ideal sample for expression profiling of diseases that have no known or accessible lesion. Peripheral blood is a complex mixture of cell types and some differences in peripheral blood gene expression may reflect the timing of sample collection rather than an underlying disease process. For this reason, it is important to assess study design factors that may cause variability in gene expression not related to what is being...

  18. Biclustering of the Gene Expression Data by Coevolution Cuckoo Search

    OpenAIRE

    Lu Yin; Yongguo Liu

    2015-01-01

    Biclustering has a potential to discover the local expression patterns analyzing the gene expression data which provide clues about biological processes. However, since it is proven that the biclustering problem is NP-hard, it is necessary to seek more effective algorithm. Cuckoo Search (CS) models the brood parasitism behavior of cuckoo to solve the optimization problem and outperforms the other existing algorithms. In this paper, we introduce a new algorithm for biclustering gene expression...

  19. Laminin Mediates Tissue-specific Gene Expression in Mammary Epithelia

    OpenAIRE

    Streuli, Charles H

    2011-01-01

    Tissue-specific gene expression in mammary epithelium is dependent on the extracellular matrix as well as hormones. There is good evidence that the basement membrane provides signals for regulating beta-casein expression, and that integrins are involved in this process. Here, we demonstrate that in the presence of lactogenic hormones, laminin can direct expression of the beta-casein gene. Mouse mammary epithelial cells plated on gels of native laminin or laminin-entactin undergo functional di...

  20. An atlas of gene expression and gene co-regulation in the human retina.

    Science.gov (United States)

    Pinelli, Michele; Carissimo, Annamaria; Cutillo, Luisa; Lai, Ching-Hung; Mutarelli, Margherita; Moretti, Maria Nicoletta; Singh, Marwah Veer; Karali, Marianthi; Carrella, Diego; Pizzo, Mariateresa; Russo, Francesco; Ferrari, Stefano; Ponzin, Diego; Angelini, Claudia; Banfi, Sandro; di Bernardo, Diego

    2016-07-01

    The human retina is a specialized tissue involved in light stimulus transduction. Despite its unique biology, an accurate reference transcriptome is still missing. Here, we performed gene expression analysis (RNA-seq) of 50 retinal samples from non-visually impaired post-mortem donors. We identified novel transcripts with high confidence (Observed Transcriptome (ObsT)) and quantified the expression level of known transcripts (Reference Transcriptome (RefT)). The ObsT included 77 623 transcripts (23 960 genes) covering 137 Mb (35 Mb new transcribed genome). Most of the transcripts (92%) were multi-exonic: 81% with known isoforms, 16% with new isoforms and 3% belonging to new genes. The RefT included 13 792 genes across 94 521 known transcripts. Mitochondrial genes were among the most highly expressed, accounting for about 10% of the reads. Of all the protein-coding genes in Gencode, 65% are expressed in the retina. We exploited inter-individual variability in gene expression to infer a gene co-expression network and to identify genes specifically expressed in photoreceptor cells. We experimentally validated the photoreceptors localization of three genes in human retina that had not been previously reported. RNA-seq data and the gene co-expression network are available online (http://retina.tigem.it). PMID:27235414

  1. Prevalence of gene expression additivity in genetically stable wheat allohexaploids.

    Science.gov (United States)

    Chelaifa, Houda; Chagué, Véronique; Chalabi, Smahane; Mestiri, Imen; Arnaud, Dominique; Deffains, Denise; Lu, Yunhai; Belcram, Harry; Huteau, Virginie; Chiquet, Julien; Coriton, Olivier; Just, Jérémy; Jahier, Joseph; Chalhoub, Boulos

    2013-02-01

    The reprogramming of gene expression appears as the major trend in synthetic and natural allopolyploids where expression of an important proportion of genes was shown to deviate from that of the parents or the average of the parents. In this study, we analyzed gene expression changes in previously reported, highly stable synthetic wheat allohexaploids that combine the D genome of Aegilops tauschii and the AB genome extracted from the natural hexaploid wheat Triticum aestivum. A comprehensive genome-wide analysis of transcriptional changes using the Affymetrix GeneChip Wheat Genome Array was conducted. Prevalence of gene expression additivity was observed where expression does not deviate from the average of the parents for 99.3% of 34,820 expressed transcripts. Moreover, nearly similar expression was observed (for 99.5% of genes) when comparing these synthetic and natural wheat allohexaploids. Such near-complete additivity has never been reported for other allopolyploids and, more interestingly, for other synthetic wheat allohexaploids that differ from the ones studied here by having the natural tetraploid Triticum turgidum as the AB genome progenitor. Our study gave insights into the dynamics of additive gene expression in the highly stable wheat allohexaploids. PMID:23278496

  2. Toxicogenomic Analysis Suggests Chemical-Induced Sexual Dimorphism in the Expression of Metabolic Genes in Zebrafish Liver

    OpenAIRE

    Xun Zhang; Choong Yong Ung; Siew Hong Lam; Jing Ma; Yu Zong Chen; Louxin Zhang; Zhiyuan Gong; Baowen Li

    2012-01-01

    Differential gene expression in two sexes is widespread throughout the animal kingdom, giving rise to sex-dimorphic gene activities and sex-dependent adaptability to environmental cues, diets, growth and development as well as susceptibility to diseases. Here, we present a study using a toxicogenomic approach to investigate metabolic genes that show sex-dimorphic expression in the zebrafish liver triggered by several chemicals. Our analysis revealed that, besides the known genes for xenobioti...

  3. Using PCR to Target Misconceptions about Gene Expression

    Directory of Open Access Journals (Sweden)

    Leslie K. Wright

    2013-02-01

    Full Text Available We present a PCR-based laboratory exercise that can be used with first- or second-year biology students to help overcome common misconceptions about gene expression. Biology students typically do not have a clear understanding of the difference between genes (DNA and gene expression (mRNA/protein and often believe that genes exist in an organism or cell only when they are expressed. This laboratory exercise allows students to carry out a PCR-based experiment designed to challenge their misunderstanding of the difference between genes and gene expression. Students first transform E. coli with an inducible GFP gene containing plasmid and observe induced and un-induced colonies. The following exercise creates cognitive dissonance when actual PCR results contradict their initial (incorrect predictions of the presence of the GFP gene in transformed cells. Field testing of this laboratory exercise resulted in learning gains on both knowledge and application questions on concepts related to genes and gene expression.

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

    Indian Academy of Sciences (India)

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

    2014-06-01

    In the present study, the human liposarcoma cell line SW872 was used to identify global changes in gene expression profiles occurring during adipogenesis. We further explored some of the genes expressed during the late phase of adipocyte differentiation. These genes may play a major role in promoting excessive proliferation and accumulation of lipid droplets, which contribute to the development of obesity. By using microarray-based technology, we examined differential gene expression in early differentiated adipocytes and late differentiated adipocytes. Validated genes exhibited a ≥ 10-fold increase in the late phase of adipocyte differentiation by polymerase chain reaction (RT-PCR). Compared with undifferentiated preadipocytes, we found that 763 genes were increased in early differentiated adipocytes, and 667 genes were increased in later differentiated adipocytes. Furthermore, 21 genes were found being expressed 10-fold higher in the late phase of adipocyte differentiation. The results were in accordance with the RT-PCR test, which validated 11 genes, namely, CIDEC, PID1, LYRM1, ADD1, PPAR2, ANGPTL4, ADIPOQ, ACOX1, FIP1L1, MAP3K2 and PEX14. Most of these genes were found being expressed in the later phase of adipocyte differentiation involved in obesity-related diseases. The findings may help to better understand the mechanism of obesity and related diseases.

  5. Differential expression of olfactory genes in the southern house mosquito and insights into unique odorant receptor gene isoforms

    OpenAIRE

    Walter S Leal; Choo, Young-Moo; Xu, Pingxi; da Silva, Cherre S. B.; Ueira-Vieira, Carlos

    2013-01-01

    Mosquitoes use their acute sense of smell to locate hosts, oviposition sites, and repellents. Here, we investigated by next generation sequencing the key molecular components of the olfactory system of the southern house mosquito—a vector of West Nile virus. We studied differential expression of genes in antennae—the main olfactory organ—and nonolfactory tissues. Additionally, we prospected for unknown genes with transcripts enriched in antennae. Our approach, which was validated by quantitat...

  6. Seed-based biclustering of gene expression data.

    Directory of Open Access Journals (Sweden)

    Jiyuan An

    Full Text Available BACKGROUND: Accumulated biological research outcomes show that biological functions do not depend on individual genes, but on complex gene networks. Microarray data are widely used to cluster genes according to their expression levels across experimental conditions. However, functionally related genes generally do not show coherent expression across all conditions since any given cellular process is active only under a subset of conditions. Biclustering finds gene clusters that have similar expression levels across a subset of conditions. This paper proposes a seed-based algorithm that identifies coherent genes in an exhaustive, but efficient manner. METHODS: In order to find the biclusters in a gene expression dataset, we exhaustively select combinations of genes and conditions as seeds to create candidate bicluster tables. The tables have two columns (a a gene set, and (b the conditions on which the gene set have dissimilar expression levels to the seed. First, the genes with less than the maximum number of dissimilar conditions are identified and a table of these genes is created. Second, the rows that have the same dissimilar conditions are grouped together. Third, the table is sorted in ascending order based on the number of dissimilar conditions. Finally, beginning with the first row of the table, a test is run repeatedly to determine whether the cardinality of the gene set in the row is greater than the minimum threshold number of genes in a bicluster. If so, a bicluster is outputted and the corresponding row is removed from the table. Repeating this process, all biclusters in the table are systematically identified until the table becomes empty. CONCLUSIONS: This paper presents a novel biclustering algorithm for the identification of additive biclusters. Since it involves exhaustively testing combinations of genes and conditions, the additive biclusters can be found more readily.

  7. Web-based interrogation of gene expression signatures using EXALT

    Directory of Open Access Journals (Sweden)

    Yu Jian

    2009-12-01

    Full Text Available Abstract Background Widespread use of high-throughput techniques such as microarrays to monitor gene expression levels has resulted in an explosive growth of data sets in public domains. Integration and exploration of these complex and heterogeneous data have become a major challenge. Results The EXALT (EXpression signature AnaLysis Tool online program enables meta-analysis of gene expression profiles derived from publically accessible sources. Searches can be executed online against two large databases currently containing more than 28,000 gene expression signatures derived from GEO (Gene Expression Omnibus and published expression profiles of human cancer. Comparisons among gene expression signatures can be performed with homology analysis and co-expression analysis. Results can be visualized instantly in a plot or a heat map. Three typical use cases are illustrated. Conclusions The EXALT online program is uniquely suited for discovering relationships among transcriptional profiles and searching gene expression patterns derived from diverse physiological and pathological settings. The EXALT online program is freely available for non-commercial users from http://seq.mc.vanderbilt.edu/exalt/.

  8. Pre-gastrula expression of zebrafish extraembryonic genes

    Directory of Open Access Journals (Sweden)

    Lempicki Richard A

    2010-04-01

    Full Text Available Abstract Background Many species form extraembryonic tissues during embryogenesis, such as the placenta of humans and other viviparous mammals. Extraembryonic tissues have various roles in protecting, nourishing and patterning embryos. Prior to gastrulation in zebrafish, the yolk syncytial layer - an extraembryonic nuclear syncytium - produces signals that induce mesoderm and endoderm formation. Mesoderm and endoderm precursor cells are situated in the embryonic margin, an external ring of cells along the embryo-yolk interface. The yolk syncytial layer initially forms below the margin, in a domain called the external yolk syncytial layer (E-YSL. Results We hypothesize that key components of the yolk syncytial layer's mesoderm and endoderm inducing activity are expressed as mRNAs in the E-YSL. To identify genes expressed in the E-YSL, we used microarrays to compare the transcription profiles of intact pre-gastrula embryos with pre-gastrula embryonic cells that we had separated from the yolk and yolk syncytial layer. This identified a cohort of genes with enriched expression in intact embryos. Here we describe our whole mount in situ hybridization analysis of sixty-eight of them. This includes ten genes with E-YSL expression (camsap1l1, gata3, znf503, hnf1ba, slc26a1, slc40a1, gata6, gpr137bb, otop1 and cebpa, four genes with expression in the enveloping layer (EVL, a superficial epithelium that protects the embryo (zgc:136817, zgc:152778, slc14a2 and elovl6l, three EVL genes whose expression is transiently confined to the animal pole (elovl6l, zgc:136359 and clica, and six genes with transient maternal expression (mtf1, wu:fj59f04, mospd2, rftn2, arrdc1a and pho. We also assessed the requirement of Nodal signaling for the expression of selected genes in the E-YSL, EVL and margin. Margin expression was Nodal dependent for all genes we tested, including the concentrated margin expression of an EVL gene: zgc:110712. All other instances of EVL and E

  9. Agrobacterium-mediated transient gene expression and silencing: a rapid tool for functional gene assay in potato.

    Directory of Open Access Journals (Sweden)

    Pudota B Bhaskar

    Full Text Available Potato is the third most important food crop worldwide. However, genetic and genomic research of potato has lagged behind other major crops due to the autopolyploidy and highly heterozygous nature associated with the potato genome. Reliable and technically undemanding techniques are not available for functional gene assays in potato. Here we report the development of a transient gene expression and silencing system in potato. Gene expression or RNAi-based gene silencing constructs were delivered into potato leaf cells using Agrobacterium-mediated infiltration. Agroinfiltration of various gene constructs consistently resulted in potato cell transformation and spread of the transgenic cells around infiltration zones. The efficiency of agroinfiltration was affected by potato genotypes, concentration of Agrobacterium, and plant growth conditions. We demonstrated that the agroinfiltration-based transient gene expression can be used to detect potato proteins in sub-cellular compartments in living cells. We established a double agroinfiltration procedure that allows to test whether a specific gene is associated with potato late blight resistance pathway mediated by the resistance gene RB. This procedure provides a powerful approach for high throughput functional assay for a large number of candidate genes in potato late blight resistance.

  10. Gene Body Methylation can alter Gene Expression and is a Therapeutic Target in Cancer

    Science.gov (United States)

    Yang, Xiaojing; Han, Han; De Carvalho, Daniel D.; Lay, Fides D.; Jones, Peter A.; Liang, Gangning

    2014-01-01

    SUMMARY DNA methylation in promoters is well known to silence genes and is the presumed therapeutic target of methylation inhibitors. Gene body methylation is positively correlated with expression yet its function is unknown. We show that 5-aza-2'-deoxycytidine treatment not only reactivates genes but decreases the over-expression of genes, many of which are involved in metabolic processes regulated by c-MYC. Down-regulation is caused by DNA demethylation of the gene bodies and restoration of high levels of expression requires remethylation by DNMT3B. Gene body methylation may therefore be an unexpected therapeutic target for DNA methylation inhibitors, resulting in the normalization of gene over-expression induced during carcinogenesis. Our results provide direct evidence for a causal relationship between gene body methylation and transcription. PMID:25263941

  11. Gene expression module-based chemical function similarity search

    OpenAIRE

    Li, Yun; Hao, Pei; Zheng, Siyuan; Tu, Kang; Fan, Haiwei; Zhu, Ruixin; Ding, Guohui; Dong, Changzheng; Wang, Chuan; Li, Xuan; Thiesen, H.-J.; Chen, Y. Eugene; Jiang, HuaLiang; Liu, Lei; Li, Yixue

    2008-01-01

    Investigation of biological processes using selective chemical interventions is generally applied in biomedical research and drug discovery. Many studies of this kind make use of gene expression experiments to explore cellular responses to chemical interventions. Recently, some research groups constructed libraries of chemical related expression profiles, and introduced similarity comparison into chemical induced transcriptome analysis. Resembling sequence similarity alignment, expression pat...

  12. Meta-Analysis of Differential Connectivity in Gene Co-Expression Networks in Multiple Sclerosis.

    Science.gov (United States)

    Creanza, Teresa Maria; Liguori, Maria; Liuni, Sabino; Nuzziello, Nicoletta; Ancona, Nicola

    2016-01-01

    Differential gene expression analyses to investigate multiple sclerosis (MS) molecular pathogenesis cannot detect genes harboring genetic and/or epigenetic modifications that change the gene functions without affecting their expression. Differential co-expression network approaches may capture changes in functional interactions resulting from these alterations. We re-analyzed 595 mRNA arrays from publicly available datasets by studying changes in gene co-expression networks in MS and in response to interferon (IFN)-β treatment. Interestingly, MS networks show a reduced connectivity relative to the healthy condition, and the treatment activates the transcription of genes and increases their connectivity in MS patients. Importantly, the analysis of changes in gene connectivity in MS patients provides new evidence of association for genes already implicated in MS by single-nucleotide polymorphism studies and that do not show differential expression. This is the case of amiloride-sensitive cation channel 1 neuronal (ACCN1) that shows a reduced number of interacting partners in MS networks, and it is known for its role in synaptic transmission and central nervous system (CNS) development. Furthermore, our study confirms a deregulation of the vitamin D system: among the transcription factors that potentially regulate the deregulated genes, we find TCF3 and SP1 that are both involved in vitamin D3-induced p27Kip1 expression. Unveiling differential network properties allows us to gain systems-level insights into disease mechanisms and may suggest putative targets for the treatment. PMID:27314336

  13. Meta-Analysis of Differential Connectivity in Gene Co-Expression Networks in Multiple Sclerosis

    Directory of Open Access Journals (Sweden)

    Teresa Maria Creanza

    2016-06-01

    Full Text Available Differential gene expression analyses to investigate multiple sclerosis (MS molecular pathogenesis cannot detect genes harboring genetic and/or epigenetic modifications that change the gene functions without affecting their expression. Differential co-expression network approaches may capture changes in functional interactions resulting from these alterations. We re-analyzed 595 mRNA arrays from publicly available datasets by studying changes in gene co-expression networks in MS and in response to interferon (IFN-β treatment. Interestingly, MS networks show a reduced connectivity relative to the healthy condition, and the treatment activates the transcription of genes and increases their connectivity in MS patients. Importantly, the analysis of changes in gene connectivity in MS patients provides new evidence of association for genes already implicated in MS by single-nucleotide polymorphism studies and that do not show differential expression. This is the case of amiloride-sensitive cation channel 1 neuronal (ACCN1 that shows a reduced number of interacting partners in MS networks, and it is known for its role in synaptic transmission and central nervous system (CNS development. Furthermore, our study confirms a deregulation of the vitamin D system: among the transcription factors that potentially regulate the deregulated genes, we find TCF3 and SP1 that are both involved in vitamin D3-induced p27Kip1 expression. Unveiling differential network properties allows us to gain systems-level insights into disease mechanisms and may suggest putative targets for the treatment.

  14. BICLUSTERING GENE EXPRESSION DATASET USING ENHANCED BARYCENTER CROSSING MINIMIZATION

    Directory of Open Access Journals (Sweden)

    Tamer Mohamed

    2013-01-01

    Full Text Available There are two main categories of bi-clustering approaches graph-based bi-clustering, and non-graph based bi-clustering. In graph-based bi-clustering algorithm the input dataset is converted into bigraph such as bipartite graph, and apply some heuristic local searching techniques to minimize the number of crossings between edges in the Bigraph such as BaryCenter (BC used in SPHier algorithm. The main problem of graph-based bi-clustering algorithm is to extract the best bi-clusters, and this leads to the ordering of gene expression dataset before we apply biclustering algorithm. In bipartite graph this is achieved through minimizing the number of crossings in bipartite graph. As we minimize the number of crossings in the bipartite graph, the gene expression dataset becomes more ordered, and this enhances the results of biclustering algorithm. The main goal of our proposed algorithm is the enhancement of graph-based biclustering algorithm by enhancing BaryCenter crossing minimization heuristics of bipartite graph. In the proposed algorithm we add the rank of each node to the rank of its neighbors, and using the position of each node in the calculations to give a new rank to each node, and using this rank for reordering the nodes of each layer.

  15. A gene expression atlas of early craniofacial development.

    Science.gov (United States)

    Brunskill, Eric W; Potter, Andrew S; Distasio, Andrew; Dexheimer, Phillip; Plassard, Andrew; Aronow, Bruce J; Potter, S Steven

    2014-07-15

    We present a gene expression atlas of early mouse craniofacial development. Laser capture microdissection (LCM) was used to isolate cells from the principal critical microregions, whose development, differentiation and signaling interactions are responsible for the construction of the mammalian face. At E8.5, as migrating neural crest cells begin to exit the neural fold/epidermal ectoderm boundary, we examined the cranial mesenchyme, composed of mixed neural crest and paraxial mesoderm cells, as well as cells from adjacent neuroepithelium. At E9.5 cells from the cranial mesenchyme, overlying olfactory placode/epidermal ectoderm, and underlying neuroepithelium, as well as the emerging mandibular and maxillary arches were sampled. At E10.5, as the facial prominences form, cells from the medial and lateral prominences, the olfactory pit, multiple discrete regions of underlying neuroepithelium, the mandibular and maxillary arches, including both their mesenchymal and ectodermal components, as well as Rathke's pouch, were similarly sampled and profiled using both microarray and RNA-seq technologies. Further, we performed single cell studies to better define the gene expression states of the early E8.5 pioneer neural crest cells and paraxial mesoderm. Taken together, and analyzable by a variety of biological network approaches, these data provide a complementing and cross validating resource capable of fueling discovery of novel compartment specific markers and signatures whose combinatorial interactions of transcription factors and growth factors/receptors are responsible for providing the master genetic blueprint for craniofacial development. PMID:24780627

  16. Building an atlas of gene expression driving kidney development: pushing the limits of resolution.

    Science.gov (United States)

    Potter, S Steven; Brunskill, Eric W

    2014-04-01

    Changing gene expression patterns is the essential driver of developmental processes. Growth factors, micro-RNAs, long intergenic noncoding RNAs, and epigenetic marks, such as DNA methylation and histone modifications, all work by impacting gene expression. The key features of developing cells, including their ability to communicate with others, are defined primarily by their gene-expression profiles. It is therefore clear that a gene-expression atlas of the developing kidney can provide a useful tool for the developmental nephrology research community. Toward this end, the GenitoUrinary Development Molecular Anatomy Project (GUDMAP) consortium has worked to create an atlas of the changing gene-expression patterns that drive kidney development. In this article, the global gene-expression profiling strategies of GUDMAP are reviewed. The initial work used laser-capture microdissection to purify multiple compartments of the developing kidney, including cap mesenchyme, renal vesicle, S-shaped bodies, proximal tubules, and more, which were then gene-expression profiled using microarrays. Resolution of the atlas was then improved by using transgenic mice with specific cell types labeled with green fluorescent protein (GFP), allowing their purification and profiling. In addition, RNA-Seq replaced microarrays. Currently, the atlas is being pushed to the single-cell resolution using microfluidic approaches that allow high-throughput RNA-Seq analysis of hundreds of individual cells. Results can identify novel types of cells and define interesting heterogeneities present within cell populations. PMID:23996451

  17. IL-4 dependent alternatively-activated macrophages have a distinctive in vivo gene expression phenotype

    Directory of Open Access Journals (Sweden)

    Guiliano David

    2002-07-01

    Full Text Available Abstract Background "Alternatively-activated" macrophages are found in Th2-mediated inflammatory settings such as nematode infection and allergic pulmonary inflammation. Due in part to a lack of markers, these cells have not been well characterized in vivo and their function remains unknown. Results We have used murine macrophages elicited by nematode infection (NeMφ as a source of in vivo derived alternatively activated macrophages. Using three distinct yet complementary molecular approaches we have established a gene expression profile of alternatively activated macrophages and identified macrophage genes that are regulated in vivo by IL-4. First, genes abundantly expressed were identified by an expressed sequence tag strategy. Second, an array of 1176 known mouse genes was screened for differential expression between NeMφ from wild type or IL-4 deficient mice. Third, a subtractive library was screened to identify novel IL-4 dependent macrophage genes. Differential expression was confirmed by real time RT-PCR analysis. Conclusions Our data demonstrate that alternatively activated macrophages generated in vivo have a gene expression profile distinct from any macrophage population described to date. Several of the genes we identified, including those most abundantly expressed, have not previously been associated with macrophages and thus this study provides unique new information regarding the phenotype of macrophages found in Th2-mediated, chronic inflammatory settings. Our data also provide additional in vivo evidence for parallels between the inflammatory processes involved in nematode infection and allergy.

  18. Noise in gene expression is coupled to growth rate.

    Science.gov (United States)

    Keren, Leeat; van Dijk, David; Weingarten-Gabbay, Shira; Davidi, Dan; Jona, Ghil; Weinberger, Adina; Milo, Ron; Segal, Eran

    2015-12-01

    Genetically identical cells exposed to the same environment display variability in gene expression (noise), with important consequences for the fidelity of cellular regulation and biological function. Although population average gene expression is tightly coupled to growth rate, the effects of changes in environmental conditions on expression variability are not known. Here, we measure the single-cell expression distributions of approximately 900 Saccharomyces cerevisiae promoters across four environmental conditions using flow cytometry, and find that gene expression noise is tightly coupled to the environment and is generally higher at lower growth rates. Nutrient-poor conditions, which support lower growth rates, display elevated levels of noise for most promoters, regardless of their specific expression values. We present a simple model of noise in expression that results from having an asynchronous population, with cells at different cell-cycle stages, and with different partitioning of the cells between the stages at different growth rates. This model predicts non-monotonic global changes in noise at different growth rates as well as overall higher variability in expression for cell-cycle-regulated genes in all conditions. The consistency between this model and our data, as well as with noise measurements of cells growing in a chemostat at well-defined growth rates, suggests that cell-cycle heterogeneity is a major contributor to gene expression noise. Finally, we identify gene and promoter features that play a role in gene expression noise across conditions. Our results show the existence of growth-related global changes in gene expression noise and suggest their potential phenotypic implications. PMID:26355006

  19. Gene Expression Prediction by Soft Integration and the Elastic Net—Best Performance of the DREAM3 Gene Expression Challenge

    OpenAIRE

    Mika Gustafsson; Michael Hörnquist

    2010-01-01

    Background: To predict gene expressions is an important endeavour within computational systems biology. It can both be a way to explore how drugs affect the system, as well as providing a framework for finding which genes are interrelated in a certain process. A practical problem, however, is how to assess and discriminate among the various algorithms which have been developed for this purpose. Therefore, the DREAM project invited the year 2008 to a challenge for predicting gene expression va...

  20. Coex-Rank: An approach incorporating co-expression information for combined analysis of microarray data

    OpenAIRE

    Cai, Jinlu; Keen, Henry L.; Sigmund, Curt D.; Casavant, Thomas L.

    2012-01-01

    Microarrays have been widely used to study differential gene expression at the genomic level. They can also provide genome-wide co-expression information. Biologically related datasets from independent studies are publicly available, which requires robust combined approaches for integration and validation. Previously, meta-analysis has been adopted to solve this problem.

  1. Selection and validation of reference genes for quantitative gene expression studies in Erythroxylum coca

    OpenAIRE

    Teresa Docimo; Schmidt, Gregor W; Katrin Luck; Sven K Delaney; John C D'Auria

    2013-01-01

    Real-time quantitative PCR is a powerful technique for the investigation of comparative gene expression, but its accuracy and reliability depend on the reference genes used as internal standards. Only genes that show a high level of expression stability are suitable for use as reference genes, and these must be identified on a case-by-case basis. Erythroxylum coca produces and accumulates high amounts of the pharmacologically active tropane alkaloid cocaine (especially in the leaves), and is ...

  2. Flies selected for longevity retain a young gene expression profile

    DEFF Research Database (Denmark)

    Sarup, Pernille Merete; Sørensen, Peter; Loeschcke, Volker

    2011-01-01

      We investigated correlated responses in the transcriptomes of longevity-selected lines of Drosophila melanogaster to identify pathways that affect life span in metazoan systems. We evaluated the gene expression profile in young, middle-aged, and old male flies, finding that 530 genes were...... differentially expressed between selected and control flies when measured at the same chronological age. The longevity-selected flies consistently showed expression profiles more similar to control flies one age class younger than control flies of the same age. This finding is in accordance with a younger gene...... expression profile in longevity-selected lines. Among the genes down-regulated in longevity-selected lines, we found a clear over-representation of genes involved in immune functions, supporting the hypothesis of a life-shortening effect of an overactive immune system, known as inflammaging. We judged the...

  3. Identifying differential expression in multiple SAGE libraries: an overdispersed log-linear model approach

    OpenAIRE

    Kepler Thomas B; Tomfohr John K; Lu Jun

    2005-01-01

    Abstract Background In testing for differential gene expression involving multiple serial analysis of gene expression (SAGE) libraries, it is critical to account for both between and within library variation. Several methods have been proposed, including the t test, tw test, and an overdispersed logistic regression approach. The merits of these tests, however, have not been fully evaluated. Questions still remain on whether further improvements can be made. Results In this article, we introdu...

  4. Gene expression profiles of Nitrosomonas europaea, an obligate chemolitotroph

    Energy Technology Data Exchange (ETDEWEB)

    Daniel J. Arp

    2005-05-25

    Nitrosomonas europaea is an aerobic lithoautotrophic bacterium that uses ammonia (NH3) as its energy source. As a nitrifier, it is an important participant in the nitrogen cycle, which can also influence the carbon cycle. The focus of this work was to explore the genetic structure and mechanisms underlying the lithoautotrophic growth style of N. europaea. Whole genome gene expression: The gene expression profile of cells in exponential growth and during starvation was analyzed using microarrays. During growth, 98% of the genes increased in expression at least two fold compared to starvation conditions. In growing cells, approximately 30% of the genes were expressed eight fold higher, Approximately 10% were expressed more than 15 fold higher. Approximately 3% (91 genes) were expressed to more than 20 fold of their levels in starved cells. Carbon fixation gene expression: N. europaea fixes carbon via the Calvin-Benson-Bassham (CBB) cycle via a type I ribulose bisphosphate carboxylase/oxygenase (RubisCO). This study showed that transcription of cbb genes was up-regulated when the carbon source was limited, while amo, hao and other energy harvesting related genes were down-regulated. Iron related gene expression: Because N. europaea has a relatively high content of hemes, sufficient Fe must be available in the medium for it to grow. The genome revealed that approximately 5% of the coding genes in N. europaea are dedicated to Fe transport and assimilation. Nonetheless, with the exception of citrate biosynthesis genes, N. europaea lacks genes for siderophore production. The Fe requirements for growth and the expression of the putative membrane siderophore receptors were determined. The N. europaea genome has over 100 putative genes ({approx}5% of the coding genes) related to Fe uptake and its siderophore receptors could be grouped phylogenetically in four clusters. Fe related genes, such as a number of TonB-dependent Fe-siderophore receptors for ferrichrome and

  5. Gene expression profiles of Nitrosomonas europaea, an obligate chemolitotroph

    Energy Technology Data Exchange (ETDEWEB)

    Daniel J Arp

    2005-06-15

    Nitrosomonas europaea is an aerobic lithoautotrophic bacterium that uses ammonia (NH3) as its energy source. As a nitrifier, it is an important participant in the nitrogen cycle, which can also influence the carbon cycle. The focus of this work was to explore the genetic structure and mechanisms underlying the lithoautotrophic growth style of N. europaea. Whole genome gene expression. The gene expression profile of cells in exponential growth and during starvation was analyzed using microarrays. During growth, 98% of the genes increased in expression at least two fold compared to starvation conditions. In growing cells, approximately 30% of the genes were expressed eight fold higher, Approximately 10% were expressed more than 15 fold higher. Approximately 3% (91 genes) were expressed to more than 20 fold of their levels in starved cells. Carbon fixation gene expression. N. europaea fixes carbon via the Calvin-Benson-Bassham (CBB) cycle via a type I ribulose bisphosphate carboxylase/oxygenase (RubisCO). This study showed that transcription of cbb genes was up-regulated when the carbon source was limited, while amo, hao and other energy harvesting related genes were down-regulated. Iron related gene expression. Because N. europaea has a relatively high content of hemes, sufficient Fe must be available in the medium for it to grow. The genome revealed that approximately 5% of the coding genes in N. europaea are dedicated to Fe transport and assimilation. Nonetheless, with the exception of citrate biosynthesis genes, N. europaea lacks genes for siderophore production. The Fe requirements for growth and the expression of the putative membrane siderophore receptors were determined. The N. europaea genome has over 100 putative genes ({approx}5% of the coding genes) related to Fe uptake and its siderophore receptors could be grouped phylogenetically in four clusters. Fe related genes, such as a number of TonB-dependent Fe-siderophore receptors for ferrichrome and

  6. Computational gene expression profiling under salt stress reveals patterns of co-expression.

    Science.gov (United States)

    Sanchita; Sharma, Ashok

    2016-03-01

    Plants respond differently to environmental conditions. Among various abiotic stresses, salt stress is a condition where excess salt in soil causes inhibition of plant growth. To understand the response of plants to the stress conditions, identification of the responsible genes is required. Clustering is a data mining technique used to group the genes with similar expression. The genes of a cluster show similar expression and function. We applied clustering algorithms on gene expression data of Solanum tuberosum showing differential expression in Capsicum annuum under salt stress. The clusters, which were common in multiple algorithms were taken further for analysis. Principal component analysis (PCA) further validated the findings of other cluster algorithms by visualizing their clusters in three-dimensional space. Functional annotation results revealed that most of the genes were involved in stress related responses. Our findings suggest that these algorithms may be helpful in the prediction of the function of co-expressed genes. PMID:26981411

  7. Empirical validation of the S-Score algorithm in the analysis of gene expression data

    Directory of Open Access Journals (Sweden)

    Archer Kellie J

    2006-03-01

    Full Text Available Abstract Background Current methods of analyzing Affymetrix GeneChip® microarray data require the estimation of probe set expression summaries, followed by application of statistical tests to determine which genes are differentially expressed. The S-Score algorithm described by Zhang and colleagues is an alternative method that allows tests of hypotheses directly from probe level data. It is based on an error model in which the detected signal is proportional to the probe pair signal for highly expressed genes, but approaches a background level (rather than 0 for genes with low levels of expression. This model is used to calculate relative change in probe pair intensities that converts probe signals into multiple measurements with equalized errors, which are summed over a probe set to form the S-Score. Assuming no expression differences between chips, the S-Score follows a standard normal distribution, allowing direct tests of hypotheses to be made. Using spike-in and dilution datasets, we validated the S-Score method against comparisons of gene expression utilizing the more recently developed methods RMA, dChip, and MAS5. Results The S-score showed excellent sensitivity and specificity in detecting low-level gene expression changes. Rank ordering of S-Score values more accurately reflected known fold-change values compared to other algorithms. Conclusion The S-score method, utilizing probe level data directly, offers significant advantages over comparisons using only probe set expression summaries.

  8. Expression of homeobox genes in the mouse olfactory epithelium.

    Science.gov (United States)

    Parrilla, Marta; Chang, Isabelle; Degl'Innocenti, Andrea; Omura, Masayo

    2016-10-01

    Homeobox genes constitute a large family of genes widely studied because of their role in the establishment of the body pattern. However, they are also involved in many other events during development and adulthood. The main olfactory epithelium (MOE) is an excellent model to study neurogenesis in the adult nervous system. Analyses of homeobox genes during development show that some of these genes are involved in the formation and establishment of cell diversity in the MOE. Moreover, the mechanisms of expression of odorant receptors (ORs) constitute one of the biggest enigmas in the field. Analyses of OR promoters revealed the presence of homeodomain binding sites in their sequences. Here we characterize the expression patterns of a set of 49 homeobox genes in the MOE with in situ hybridization. We found that seven of them (Dlx3, Dlx5, Dlx6, Msx1, Meis1, Isl1, and Pitx1) are zonally expressed. The homeobox gene Emx1 is expressed in three guanylate cyclase(+) populations, two located in the MOE and the third one in an olfactory subsystem known as Grüneberg ganglion located at the entrance of the nasal cavity. The homeobox gene Tshz1 is expressed in a unique patchy pattern across the MOE. Our findings provide new insights to guide functional studies that aim to understand the complexity of transcription factor expression and gene regulation in the MOE. J. Comp. Neurol. 524:2713-2739, 2016. © 2016 Wiley Periodicals, Inc. PMID:27243442

  9. Detecting microRNA activity from gene expression data.

    LENUS (Irish Health Repository)

    Madden, Stephen F

    2010-01-01

    BACKGROUND: MicroRNAs (miRNAs) are non-coding RNAs that regulate gene expression by binding to the messenger RNA (mRNA) of protein coding genes. They control gene expression by either inhibiting translation or inducing mRNA degradation. A number of computational techniques have been developed to identify the targets of miRNAs. In this study we used predicted miRNA-gene interactions to analyse mRNA gene expression microarray data to predict miRNAs associated with particular diseases or conditions. RESULTS: Here we combine correspondence analysis, between group analysis and co-inertia analysis (CIA) to determine which miRNAs are associated with differences in gene expression levels in microarray data sets. Using a database of miRNA target predictions from TargetScan, TargetScanS, PicTar4way PicTar5way, and miRanda and combining these data with gene expression levels from sets of microarrays, this method produces a ranked list of miRNAs associated with a specified split in samples. We applied this to three different microarray datasets, a papillary thyroid carcinoma dataset, an in-house dataset of lipopolysaccharide treated mouse macrophages, and a multi-tissue dataset. In each case we were able to identified miRNAs of biological importance. CONCLUSIONS: We describe a technique to integrate gene expression data and miRNA target predictions from multiple sources.

  10. Detecting microRNA activity from gene expression data

    LENUS (Irish Health Repository)

    Madden, Stephen F

    2010-05-18

    Abstract Background MicroRNAs (miRNAs) are non-coding RNAs that regulate gene expression by binding to the messenger RNA (mRNA) of protein coding genes. They control gene expression by either inhibiting translation or inducing mRNA degradation. A number of computational techniques have been developed to identify the targets of miRNAs. In this study we used predicted miRNA-gene interactions to analyse mRNA gene expression microarray data to predict miRNAs associated with particular diseases or conditions. Results Here we combine correspondence analysis, between group analysis and co-inertia analysis (CIA) to determine which miRNAs are associated with differences in gene expression levels in microarray data sets. Using a database of miRNA target predictions from TargetScan, TargetScanS, PicTar4way PicTar5way, and miRanda and combining these data with gene expression levels from sets of microarrays, this method produces a ranked list of miRNAs associated with a specified split in samples. We applied this to three different microarray datasets, a papillary thyroid carcinoma dataset, an in-house dataset of lipopolysaccharide treated mouse macrophages, and a multi-tissue dataset. In each case we were able to identified miRNAs of biological importance. Conclusions We describe a technique to integrate gene expression data and miRNA target predictions from multiple sources.

  11. An Interactive Database of Cocaine-Responsive Gene Expression

    Directory of Open Access Journals (Sweden)

    Willard M. Freeman

    2002-01-01

    Full Text Available The postgenomic era of large-scale gene expression studies is inundating drug abuse researchers and many other scientists with findings related to gene expression. This information is distributed across many different journals, and requires laborious literature searches. Here, we present an interactive database that combines existing information related to cocaine-mediated changes in gene expression in an easy-to-use format. The database is limited to statistically significant changes in mRNA or protein expression after cocaine administration. The Flash-based program is integrated into a Web page, and organizes changes in gene expression based on neuroanatomical region, general function, and gene name. Accompanying each gene is a description of the gene, links to the original publications, and a link to the appropriate OMIM (Online Mendelian Inheritance in Man entry. The nature of this review allows for timely modifications and rapid inclusion of new publications, and should help researchers build second-generation hypotheses on the role of gene expression changes in the physiology and behavior of cocaine abuse. Furthermore, this method of organizing large volumes of scientific information can easily be adapted to assist researchers in fields outside of drug abuse.

  12. Design and Implementation of Visual Dynamic Display Software of Gene Expression Based on GTK

    Institute of Scientific and Technical Information of China (English)

    JIANG Wei; MENG Fanjiang; LI Yong; YU Xiao

    2009-01-01

    The paper presented an implement method for a dynamic gene expression display software based on the GTK. This method established the dynamic presentation system of gene expression which according to gene expression data from gene chip hybridize at different time, adopted a linearity combination model and Pearson correlation coefficient algorithm. The system described the gene expression changes in graphic form, the gene expression changes with time and the changes in characteristics of the gene expression, also the changes in relations of the gene expression and regulation relationships among genes. The system also provided an integrated platform for analysis on gene chips data, especially for the research on the network of gene regulation.

  13. A Marfan syndrome gene expression phenotype in cultured skin fibroblasts

    Directory of Open Access Journals (Sweden)

    Emond Mary

    2007-09-01

    Full Text Available Abstract Background Marfan syndrome (MFS is a heritable connective tissue disorder caused by mutations in the fibrillin-1 gene. This syndrome constitutes a significant identifiable subtype of aortic aneurysmal disease, accounting for over 5% of ascending and thoracic aortic aneurysms. Results We used spotted membrane DNA macroarrays to identify genes whose altered expression levels may contribute to the phenotype of the disease. Our analysis of 4132 genes identified a subset with significant expression differences between skin fibroblast cultures from unaffected controls versus cultures from affected individuals with known fibrillin-1 mutations. Subsequently, 10 genes were chosen for validation by quantitative RT-PCR. Conclusion Differential expression of many of the validated genes was associated with MFS samples when an additional group of unaffected and MFS affected subjects were analyzed (p-value -6 under the null hypothesis that expression levels in cultured fibroblasts are unaffected by MFS status. An unexpected observation was the range of individual gene expression. In unaffected control subjects, expression ranges exceeding 10 fold were seen in many of the genes selected for qRT-PCR validation. The variation in expression in the MFS affected subjects was even greater.

  14. Integrated analysis of DNA methylation profiles and gene expression profiles to identify genes associated with pilocytic astrocytomas

    OpenAIRE

    Zhou, Ruigang; MAN, YIGANG

    2016-01-01

    The present study performed an integral analysis of the gene expression and DNA methylation profile of pilocytic astrocytomas (PAs). Weighted gene co-expression network analysis (WGCNA) was also performed to examine and identify the genes correlated to PAs, to identify candidate therapeutic targets for the treatment of PAs. The DNA methylation profile and gene expression profile were downloaded from the Gene Expression Omnibus database. Following screening of the differentially expressed gene...

  15. Novel redox nanomedicine improves gene expression of polyion complex vector

    Directory of Open Access Journals (Sweden)

    Kazuko Toh, Toru Yoshitomi, Yutaka Ikeda and Yukio Nagasaki

    2011-01-01

    Full Text Available Gene therapy has generated worldwide attention as a new medical technology. While non-viral gene vectors are promising candidates as gene carriers, they have several issues such as toxicity and low transfection efficiency. We have hypothesized that the generation of reactive oxygen species (ROS affects gene expression in polyplex supported gene delivery systems. The effect of ROS on the gene expression of polyplex was evaluated using a nitroxide radical-containing nanoparticle (RNP as an ROS scavenger. When polyethyleneimine (PEI/pGL3 or PEI alone was added to the HeLa cells, ROS levels increased significantly. In contrast, when (PEI/pGL3 or PEI was added with RNP, the ROS levels were suppressed. The luciferase expression was increased by the treatment with RNP in a dose-dependent manner and the cellular uptake of pDNA was also increased. Inflammatory cytokines play an important role in ROS generation in vivo. In particular, tumor necrosis factor (TNF-α caused intracellular ROS generation in HeLa cells and decreased gene expression. RNP treatment suppressed ROS production even in the presence of TNF-α and increased gene expression. This anti-inflammatory property of RNP suggests that it may be used as an effective adjuvant for non-viral gene delivery systems.

  16. Novel redox nanomedicine improves gene expression of polyion complex vector

    International Nuclear Information System (INIS)

    Gene therapy has generated worldwide attention as a new medical technology. While non-viral gene vectors are promising candidates as gene carriers, they have several issues such as toxicity and low transfection efficiency. We have hypothesized that the generation of reactive oxygen species (ROS) affects gene expression in polyplex supported gene delivery systems. The effect of ROS on the gene expression of polyplex was evaluated using a nitroxide radical-containing nanoparticle (RNP) as an ROS scavenger. When polyethyleneimine (PEI)/pGL3 or PEI alone was added to the HeLa cells, ROS levels increased significantly. In contrast, when (PEI)/pGL3 or PEI was added with RNP, the ROS levels were suppressed. The luciferase expression was increased by the treatment with RNP in a dose-dependent manner and the cellular uptake of pDNA was also increased. Inflammatory cytokines play an important role in ROS generation in vivo. In particular, tumor necrosis factor (TNF)-α caused intracellular ROS generation in HeLa cells and decreased gene expression. RNP treatment suppressed ROS production even in the presence of TNF-α and increased gene expression. This anti-inflammatory property of RNP suggests that it may be used as an effective adjuvant for non-viral gene delivery systems.

  17. Novel redox nanomedicine improves gene expression of polyion complex vector

    Science.gov (United States)

    Toh, Kazuko; Yoshitomi, Toru; Ikeda, Yutaka; Nagasaki, Yukio

    2011-12-01

    Gene therapy has generated worldwide attention as a new medical technology. While non-viral gene vectors are promising candidates as gene carriers, they have several issues such as toxicity and low transfection efficiency. We have hypothesized that the generation of reactive oxygen species (ROS) affects gene expression in polyplex supported gene delivery systems. The effect of ROS on the gene expression of polyplex was evaluated using a nitroxide radical-containing nanoparticle (RNP) as an ROS scavenger. When polyethyleneimine (PEI)/pGL3 or PEI alone was added to the HeLa cells, ROS levels increased significantly. In contrast, when (PEI)/pGL3 or PEI was added with RNP, the ROS levels were suppressed. The luciferase expression was increased by the treatment with RNP in a dose-dependent manner and the cellular uptake of pDNA was also increased. Inflammatory cytokines play an important role in ROS generation in vivo. In particular, tumor necrosis factor (TNF)-α caused intracellular ROS generation in HeLa cells and decreased gene expression. RNP treatment suppressed ROS production even in the presence of TNF-α and increased gene expression. This anti-inflammatory property of RNP suggests that it may be used as an effective adjuvant for non-viral gene delivery systems.

  18. Gene expression profiling reveals multiple toxicity endpoints induced by hepatotoxicants

    Energy Technology Data Exchange (ETDEWEB)

    Huang Qihong; Jin Xidong; Gaillard, Elias T.; Knight, Brian L.; Pack, Franklin D.; Stoltz, James H.; Jayadev, Supriya; Blanchard, Kerry T

    2004-05-18

    Microarray technology continues to gain increased acceptance in the drug development process, particularly at the stage of toxicology and safety assessment. In the current study, microarrays were used to investigate gene expression changes associated with hepatotoxicity, the most commonly reported clinical liability with pharmaceutical agents. Acetaminophen, methotrexate, methapyrilene, furan and phenytoin were used as benchmark compounds capable of inducing specific but different types of hepatotoxicity. The goal of the work was to define gene expression profiles capable of distinguishing the different subtypes of hepatotoxicity. Sprague-Dawley rats were orally dosed with acetaminophen (single dose, 4500 mg/kg for 6, 24 and 72 h), methotrexate (1 mg/kg per day for 1, 7 and 14 days), methapyrilene (100 mg/kg per day for 3 and 7 days), furan (40 mg/kg per day for 1, 3, 7 and 14 days) or phenytoin (300 mg/kg per day for 14 days). Hepatic gene expression was assessed using toxicology-specific gene arrays containing 684 target genes or expressed sequence tags (ESTs). Principal component analysis (PCA) of gene expression data was able to provide a clear distinction of each compound, suggesting that gene expression data can be used to discern different hepatotoxic agents and toxicity endpoints. Gene expression data were applied to the multiplicity-adjusted permutation test and significantly changed genes were categorized and correlated to hepatotoxic endpoints. Repression of enzymes involved in lipid oxidation (acyl-CoA dehydrogenase, medium chain, enoyl CoA hydratase, very long-chain acyl-CoA synthetase) were associated with microvesicular lipidosis. Likewise, subsets of genes associated with hepatotocellular necrosis, inflammation, hepatitis, bile duct hyperplasia and fibrosis have been identified. The current study illustrates that expression profiling can be used to: (1) distinguish different hepatotoxic endpoints; (2) predict the development of toxic endpoints; and

  19. Gene expression profiling reveals multiple toxicity endpoints induced by hepatotoxicants

    International Nuclear Information System (INIS)

    Microarray technology continues to gain increased acceptance in the drug development process, particularly at the stage of toxicology and safety assessment. In the current study, microarrays were used to investigate gene expression changes associated with hepatotoxicity, the most commonly reported clinical liability with pharmaceutical agents. Acetaminophen, methotrexate, methapyrilene, furan and phenytoin were used as benchmark compounds capable of inducing specific but different types of hepatotoxicity. The goal of the work was to define gene expression profiles capable of distinguishing the different subtypes of hepatotoxicity. Sprague-Dawley rats were orally dosed with acetaminophen (single dose, 4500 mg/kg for 6, 24 and 72 h), methotrexate (1 mg/kg per day for 1, 7 and 14 days), methapyrilene (100 mg/kg per day for 3 and 7 days), furan (40 mg/kg per day for 1, 3, 7 and 14 days) or phenytoin (300 mg/kg per day for 14 days). Hepatic gene expression was assessed using toxicology-specific gene arrays containing 684 target genes or expressed sequence tags (ESTs). Principal component analysis (PCA) of gene expression data was able to provide a clear distinction of each compound, suggesting that gene expression data can be used to discern different hepatotoxic agents and toxicity endpoints. Gene expression data were applied to the multiplicity-adjusted permutation test and significantly changed genes were categorized and correlated to hepatotoxic endpoints. Repression of enzymes involved in lipid oxidation (acyl-CoA dehydrogenase, medium chain, enoyl CoA hydratase, very long-chain acyl-CoA synthetase) were associated with microvesicular lipidosis. Likewise, subsets of genes associated with hepatotocellular necrosis, inflammation, hepatitis, bile duct hyperplasia and fibrosis have been identified. The current study illustrates that expression profiling can be used to: (1) distinguish different hepatotoxic endpoints; (2) predict the development of toxic endpoints; and

  20. Dopamine receptor-mediated regulation of neuronal "clock" gene expression.

    Science.gov (United States)

    Imbesi, M; Yildiz, S; Dirim Arslan, A; Sharma, R; Manev, H; Uz, T

    2009-01-23

    Using a transgenic mice model (i.e. "clock" knockouts), clock transcription factors have been suggested as critical regulators of dopaminergic behaviors induced by drugs of abuse. Moreover, it has been shown that systemic administration of psychostimulants, such as cocaine and methamphetamine regulates the striatal expression of clock genes. However, it is not known whether dopamine receptors mediate these regulatory effects of psychostimulants at the cellular level. Primary striatal neurons in culture express dopamine receptors as well as clock genes and have been successfully used in studying dopamine receptor functioning. Therefore, we investigated the role of dopamine receptors on neuronal clock gene expression in this model using specific receptor agonists. We found an inhibitory effect on the expression of mClock and mPer1 genes with the D2-class (i.e. D2/D3) receptor agonist quinpirole. We also found a generalized stimulatory effect on the expression of clock genes mPer1, mClock, mNPAS2 (neuronal PAS domain protein 2), and mBmal1 with the D1-class (i.e. D1) receptor agonist SKF38393. Further, we tested whether systemic administration of dopamine receptor agonists causes similar changes in striatal clock gene expression in vivo. We found quinpirole-induced alterations in mPER1 protein levels in the mouse striatum (i.e. rhythm shift). Collectively, our results indicate that the dopamine receptor system may mediate psychostimulant-induced changes in clock gene expression. Using striatal neurons in culture as a model, further research is needed to better understand how dopamine signaling modulates the expression dynamics of clock genes (i.e. intracellular signaling pathways) and thereby influences neuronal gene expression, neuronal transmission, and brain functioning. PMID:19017537

  1. Gene Expression Profiling Predicts Survival in Conventional Renal Cell Carcinoma.

    Directory of Open Access Journals (Sweden)

    2005-12-01

    Full Text Available BACKGROUND: Conventional renal cell carcinoma (cRCC accounts for most of the deaths due to kidney cancer. Tumor stage, grade, and patient performance status are used currently to predict survival after surgery. Our goal was to identify gene expression features, using comprehensive gene expression profiling, that correlate with survival. METHODS AND FINDINGS: Gene expression profiles were determined in 177 primary cRCCs using DNA microarrays. Unsupervised hierarchical clustering analysis segregated cRCC into five gene expression subgroups. Expression subgroup was correlated with survival in long-term follow-up and was independent of grade, stage, and performance status. The tumors were then divided evenly into training and test sets that were balanced for grade, stage, performance status, and length of follow-up. A semisupervised learning algorithm (supervised principal components analysis was applied to identify transcripts whose expression was associated with survival in the training set, and the performance of this gene expression-based survival predictor was assessed using the test set. With this method, we identified 259 genes that accurately predicted disease-specific survival among patients in the independent validation group (p < 0.001. In multivariate analysis, the gene expression predictor was a strong predictor of survival independent of tumor stage, grade, and performance status (p < 0.001. CONCLUSIONS: cRCC displays molecular heterogeneity and can be separated into gene expression subgroups that correlate with survival after surgery. We have identified a set of 259 genes that predict survival after surgery independent of clinical prognostic factors.

  2. The Iterative Signature Algorithm for the analysis of large scale gene expression data

    CERN Document Server

    Bergmann, S R; Barkai, N; Bergmann, Sven; Ihmels, Jan; Barkai, Naama

    2003-01-01

    We present a new approach for the analysis of genome-wide expression data. Our method is designed to overcome the limitations of traditional techniques, when applied to large-scale data. Rather than alloting each gene to a single cluster, we assign both genes and conditions to context-dependent and potentially overlapping transcription modules. We provide a rigorous definition of a transcription module as the object to be retrieved from the expression data. An efficient algorithm, that searches for the modules encoded in the data by iteratively refining sets of genes and conditions until they match this definition, is established. Each iteration involves a linear map, induced by the normalized expression matrix, followed by the application of a threshold function. We argue that our method is in fact a generalization of Singular Value Decomposition, which corresponds to the special case where no threshold is applied. We show analytically that for noisy expression data our approach leads to better classificatio...

  3. Quantitative assessment of gene expression network module-validation methods.

    Science.gov (United States)

    Li, Bing; Zhang, Yingying; Yu, Yanan; Wang, Pengqian; Wang, Yongcheng; Wang, Zhong; Wang, Yongyan

    2015-01-01

    Validation of pluripotent modules in diverse networks holds enormous potential for systems biology and network pharmacology. An arising challenge is how to assess the accuracy of discovering all potential modules from multi-omic networks and validating their architectural characteristics based on innovative computational methods beyond function enrichment and biological validation. To display the framework progress in this domain, we systematically divided the existing Computational Validation Approaches based on Modular Architecture (CVAMA) into topology-based approaches (TBA) and statistics-based approaches (SBA). We compared the available module validation methods based on 11 gene expression datasets, and partially consistent results in the form of homogeneous models were obtained with each individual approach, whereas discrepant contradictory results were found between TBA and SBA. The TBA of the Zsummary value had a higher Validation Success Ratio (VSR) (51%) and a higher Fluctuation Ratio (FR) (80.92%), whereas the SBA of the approximately unbiased (AU) p-value had a lower VSR (12.3%) and a lower FR (45.84%). The Gray area simulated study revealed a consistent result for these two models and indicated a lower Variation Ratio (VR) (8.10%) of TBA at 6 simulated levels. Despite facing many novel challenges and evidence limitations, CVAMA may offer novel insights into modular networks. PMID:26470848

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

    Directory of Open Access Journals (Sweden)

    Hu Xiaohua

    2011-07-01

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

  5. Characterization of MTAP Gene Expression in Breast Cancer Patients and Cell Lines

    Science.gov (United States)

    de Oliveira, Sarah Franco Vieira; Ganzinelli, Monica; Chilà, Rosaria; Serino, Leandro; Maciel, Marcos Euzébio; Urban, Cícero de Andrade; de Lima, Rubens Silveira; Cavalli, Iglenir João; Generali, Daniele; Broggini, Massimo

    2016-01-01

    MTAP is a ubiquitously expressed gene important for adenine and methionine salvage. The gene is located at 9p21, a chromosome region often deleted in breast carcinomas, similar to CDKN2A, a recognized tumor suppressor gene. Several research groups have shown that MTAP acts as a tumor suppressor, and some therapeutic approaches were proposed based on a tumors´ MTAP status. We analyzed MTAP and CDKN2A gene (RT-qPCR) and protein (western-blotting) expression in seven breast cancer cell lines and evaluated their promoter methylation patterns to better characterize the contribution of these genes to breast cancer. Cytotoxicity assays with inhibitors of de novo adenine synthesis (5-FU, AZA and MTX) after MTAP gene knockdown showed an increased sensitivity, mainly to 5-FU. MTAP expression was also evaluated in two groups of samples from breast cancer patients, fresh tumors and paired normal breast tissue, and from formalin-fixed paraffin embedded (FFPE) core breast cancer samples diagnosed as Luminal-A tumors and triple negative breast tumors (TNBC). The difference of MTAP expression between fresh tumors and normal tissues was not statistically significant. However, MTAP expression was significantly higher in Luminal-A breast tumors than in TNBC, suggesting the lack of expression in more aggressive breast tumors and the possibility of using the new approaches based on MTAP status in TNBC. PMID:26751376

  6. Characterization of MTAP Gene Expression in Breast Cancer Patients and Cell Lines.

    Directory of Open Access Journals (Sweden)

    Sarah Franco Vieira de Oliveira

    Full Text Available MTAP is a ubiquitously expressed gene important for adenine and methionine salvage. The gene is located at 9p21, a chromosome region often deleted in breast carcinomas, similar to CDKN2A, a recognized tumor suppressor gene. Several research groups have shown that MTAP acts as a tumor suppressor, and some therapeutic approaches were proposed based on a tumors´ MTAP status. We analyzed MTAP and CDKN2A gene (RT-qPCR and protein (western-blotting expression in seven breast cancer cell lines and evaluated their promoter methylation patterns to better characterize the contribution of these genes to breast cancer. Cytotoxicity assays with inhibitors of de novo adenine synthesis (5-FU, AZA and MTX after MTAP gene knockdown showed an increased sensitivity, mainly to 5-FU. MTAP expression was also evaluated in two groups of samples from breast cancer patients, fresh tumors and paired normal breast tissue, and from formalin-fixed paraffin embedded (FFPE core breast cancer samples diagnosed as Luminal-A tumors and triple negative breast tumors (TNBC. The difference of MTAP expression between fresh tumors and normal tissues was not statistically significant. However, MTAP expression was significantly higher in Luminal-A breast tumors than in TNBC, suggesting the lack of expression in more aggressive breast tumors and the possibility of using the new approaches based on MTAP status in TNBC.

  7. In plants, expression breadth and expression level distinctly and non-linearly correlate with gene structure

    Directory of Open Access Journals (Sweden)

    Yang Hangxing

    2009-11-01

    Full Text Available Abstract Background Compactness of highly/broadly expressed genes in human has been explained as selection for efficiency, regional mutation biases or genomic design. However, highly expressed genes in flowering plants were shown to be less compact than lowly expressed ones. On the other hand, opposite facts have also been documented that pollen-expressed Arabidopsis genes tend to contain shorter introns and highly expressed moss genes are compact. This issue is important because it provides a chance to compare the selectionism and the neutralism views about genome evolution. Furthermore, this issue also helps to understand the fates of introns, from the angle of gene expression. Results In this study, I used expression data covering more tissues and employ new analytical methods to reexamine the correlations between gene expression and gene structure for two flowering plants, Arabidopsis thaliana and Oryza sativa. It is shown that, different aspects of expression pattern correlate with different parts of gene sequences in distinct ways. In detail, expression level is significantly negatively correlated with gene size, especially the size of non-coding regions, whereas expression breadth correlates with non-coding structural parameters positively and with coding region parameters negatively. Furthermore, the relationships between expression level and structural parameters seem to be non-linear, with the extremes of structural parameters possibly scale as power-laws or logrithmic functions of expression levels. Conclusion In plants, highly expressed genes are compact, especially in the non-coding regions. Broadly expressed genes tend to contain longer non-coding sequences, which may be necessary for complex regulations. In combination with previous studies about other plants and about animals, some common scenarios about the correlation between gene expression and gene structure begin to emerge. Based on the functional relationships between

  8. Gene expression profiling of canine osteosarcoma reveals genes associated with short and long survival times

    Directory of Open Access Journals (Sweden)

    Rao Nagesha AS

    2009-09-01

    Full Text Available Abstract Background Gene expression profiling of spontaneous tumors in the dog offers a unique translational opportunity to identify prognostic biomarkers and signaling pathways that are common to both canine and human. Osteosarcoma (OS accounts for approximately 80% of all malignant bone tumors in the dog. Canine OS are highly comparable with their human counterpart with respect to histology, high metastatic rate and poor long-term survival. This study investigates the prognostic gene profile among thirty-two primary canine OS using canine specific cDNA microarrays representing 20,313 genes to identify genes and cellular signaling pathways associated with survival. This, the first report of its kind in dogs with OS, also demonstrates the advantages of cross-species comparison with human OS. Results The 32 tumors were classified into two prognostic groups based on survival time (ST. They were defined as short survivors (dogs with poor prognosis: surviving fewer than 6 months and long survivors (dogs with better prognosis: surviving 6 months or longer. Fifty-one transcripts were found to be differentially expressed, with common upregulation of these genes in the short survivors. The overexpressed genes in short survivors are associated with possible roles in proliferation, drug resistance or metastasis. Several deregulated pathways identified in the present study, including Wnt signaling, Integrin signaling and Chemokine/cytokine signaling are comparable to the pathway analysis conducted on human OS gene profiles, emphasizing the value of the dog as an excellent model for humans. Conclusion A molecular-based method for discrimination of outcome for short and long survivors is useful for future prognostic stratification at initial diagnosis, where genes and pathways associated with cell cycle/proliferation, drug resistance and metastasis could be potential targets for diagnosis and therapy. The similarities between human and canine OS makes the

  9. A novel method to identify pathways associated with renal cell carcinoma based on a gene co-expression network.

    Science.gov (United States)

    Ruan, Xiyun; Li, Hongyun; Liu, Bo; Chen, Jie; Zhang, Shibao; Sun, Zeqiang; Liu, Shuangqing; Sun, Fahai; Liu, Qingyong

    2015-08-01

    The aim of the present study was to develop a novel method for identifying pathways associated with renal cell carcinoma (RCC) based on a gene co-expression network. A framework was established where a co-expression network was derived from the database as well as various co-expression approaches. First, the backbone of the network based on differentially expressed (DE) genes between RCC patients and normal controls was constructed by the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) database. The differentially co-expressed links were detected by Pearson's correlation, the empirical Bayesian (EB) approach and Weighted Gene Co-expression Network Analysis (WGCNA). The co-expressed gene pairs were merged by a rank-based algorithm. We obtained 842; 371; 2,883 and 1,595 co-expressed gene pairs from the co-expression networks of the STRING database, Pearson's correlation EB method and WGCNA, respectively. Two hundred and eighty-one differentially co-expressed (DC) gene pairs were obtained from the merged network using this novel method. Pathway enrichment analysis based on the Kyoto Encyclopedia of Genes and Genomes (KEGG) database and the network enrichment analysis (NEA) method were performed to verify feasibility of the merged method. Results of the KEGG and NEA pathway analyses showed that the network was associated with RCC. The suggested method was computationally efficient to identify pathways associated with RCC and has been identified as a useful complement to traditional co-expression analysis. PMID:26058425

  10. Spatial gene expression quantification in changing morphologies

    NARCIS (Netherlands)

    D. Botman

    2016-01-01

    In systems biology, an organisms’ behavior is explained from the interactions among individual components such as genes and proteins. With few exceptions, interactions among genes and proteins are not measured directly and are therefore inferred from the observed output of a biological system. A net

  11. An Algorithm for the Stochastic Simulation of Gene Expression and Heterogeneous Population Dynamics

    CERN Document Server

    Charlebois, Daniel A; Fraser, Dawn; Kaern, Mads

    2011-01-01

    We present an algorithm for the stochastic simulation of gene expression and heterogeneous population dynamics. The algorithm combines an exact method to simulate molecular-level fluctuations in single cells and a constant-number Monte Carlo method to simulate time-dependent statistical characteristics of growing cell populations. To benchmark performance, we compare simulation results with steadystate and time-dependent analytical solutions for several scenarios, including steadystate and time-dependent gene expression, and the effects on population heterogeneity of cell growth, division, and DNA replication. This comparison demonstrates that the algorithm provides an efficient and accurate approach to simulate how complex biological features influence gene expression. We also use the algorithm to model gene expression dynamics within "bet-hedging" cell populations during their adaption to environmental stress. These simulations indicate that the algorithm provides a framework suitable for simulating and ana...

  12. Extracting gene expression profiles common to colon and pancreatic adenocarcinoma using simultaneous nonnegative matrix factorization.

    Science.gov (United States)

    Badea, Liviu

    2008-01-01

    In this paper we introduce a clustering algorithm capable of simultaneously factorizing two distinct gene expression datasets with the aim of uncovering gene regulatory programs that are common to the two phenotypes. The siNMF algorithm simultaneously searches for two factorizations that share the same gene expression profiles. The two key ingredients of this algorithm are the nonnegativity constraint and the offset variables, which together ensure the sparseness of the factorizations. While cancer is a very heterogeneous disease, there is overwhelming recent evidence that the differences between cancer subtypes implicate entire pathways and biological processes involving large numbers of genes, rather than changes in single genes. We have applied our simultaneous factorization algorithm looking for gene expression profiles that are common between the more homogeneous pancreatic ductal adenocarcinoma (PDAC) and the more heterogeneous colon adenocarcinoma. The fact that the PDAC signature is active in a large fraction of colon adeocarcinoma suggests that the oncogenic mechanisms involved may be similar to those in PDAC, at least in this subset of colon samples. There are many approaches to uncovering common mechanisms involved in different phenotypes, but most are based on comparing gene lists. The approach presented in this paper additionally takes gene expression data into account and can thus be more sensitive. PMID:18229692

  13. Expression profile of genes associated with mastitis in dairy cattle

    OpenAIRE

    Isabela Fonseca; Priscila Vendramini Silva; Carla Christine Lange; Guimarães, Marta F. M.; Mayara Morena Del Cambre Amaral Weller; Katiene Régia Silva Sousa; Paulo de Sávio Lopes; José Domingos Guimarães; Simone E.F. Guimarães

    2009-01-01

    In order to characterize the expression of genes associated with immune response mechanisms to mastitis, we quantified the relative expression of the IL-2, IL-4, IL-6, IL-8, IL-10, IFN-γ and TNF-α genes in milk cells of healthy cows and cows with clinical mastitis. Total RNA was extracted from milk cells of six Black and White Holstein (BW) cows and six Gyr cows, including three animals with and three without mastitis per breed. Gene expression was analyzed by real-time PCR. IL-10 g...

  14. A longitudinal study of gene expression in healthy individuals

    Directory of Open Access Journals (Sweden)

    Tessier Michel

    2009-06-01

    Full Text Available Abstract Background The use of gene expression in venous blood either as a pharmacodynamic marker in clinical trials of drugs or as a diagnostic test requires knowledge of the variability in expression over time in healthy volunteers. Here we defined a normal range of gene expression over 6 months in the blood of four cohorts of healthy men and women who were stratified by age (22–55 years and > 55 years and gender. Methods Eleven immunomodulatory genes likely to play important roles in inflammatory conditions such as rheumatoid arthritis and infection in addition to four genes typically used as reference genes were examined by quantitative reverse transcription-polymerase chain reaction (qRT-PCR, as well as the full genome as represented by Affymetrix HG U133 Plus 2.0 microarrays. Results Gene expression levels as assessed by qRT-PCR and microarray were relatively stable over time with ~2% of genes as measured by microarray showing intra-subject differences over time periods longer than one month. Fifteen genes varied by gender. The eleven genes examined by qRT-PCR remained within a limited dynamic range for all individuals. Specifically, for the seven most stably expressed genes (CXCL1, HMOX1, IL1RN, IL1B, IL6R, PTGS2, and TNF, 95% of all samples profiled fell within 1.5–2.5 Ct, the equivalent of a 4- to 6-fold dynamic range. Two subjects who experienced severe adverse events of cancer and anemia, had microarray gene expression profiles that were distinct from normal while subjects who experienced an infection had only slightly elevated levels of inflammatory markers. Conclusion This study defines the range and variability of gene expression in healthy men and women over a six-month period. These parameters can be used to estimate the number of subjects needed to observe significant differences from normal gene expression in clinical studies. A set of genes that varied by gender was also identified as were a set of genes with elevated

  15. Reference genes for gene expression studies in wheat flag leaves grown under different farming conditions

    Directory of Open Access Journals (Sweden)

    Cordeiro Raposo Fernando

    2011-09-01

    Full Text Available Abstract Background Internal control genes with highly uniform expression throughout the experimental conditions are required for accurate gene expression analysis as no universal reference genes exists. In this study, the expression stability of 24 candidate genes from Triticum aestivum cv. Cubus flag leaves grown under organic and conventional farming systems was evaluated in two locations in order to select suitable genes that can be used for normalization of real-time quantitative reverse-transcription PCR (RT-qPCR reactions. The genes were selected among the most common used reference genes as well as genes encoding proteins involved in several metabolic pathways. Findings Individual genes displayed different expression rates across all samples assayed. Applying geNorm, a set of three potential reference genes were suitable for normalization of RT-qPCR reactions in winter wheat flag leaves cv. Cubus: TaFNRII (ferredoxin-NADP(H oxidoreductase; AJ457980.1, ACT2 (actin 2; TC234027, and rrn26 (a putative homologue to RNA 26S gene; AL827977.1. In addition of these three genes that were also top-ranked by NormFinder, two extra genes: CYP18-2 (Cyclophilin A, AY456122.1 and TaWIN1 (14-3-3 like protein, AB042193 were most consistently stably expressed. Furthermore, we showed that TaFNRII, ACT2, and CYP18-2 are suitable for gene expression normalization in other two winter wheat varieties (Tommi and Centenaire grown under three treatments (organic, conventional and no nitrogen and a different environment than the one tested with cv. Cubus. Conclusions This study provides a new set of reference genes which should improve the accuracy of gene expression analyses when using wheat flag leaves as those related to the improvement of nitrogen use efficiency for cereal production.

  16. Gene gymnastics: Synthetic biology for baculovirus expression vector system engineering.

    Science.gov (United States)

    Vijayachandran, Lakshmi S; Thimiri Govinda Raj, Deepak B; Edelweiss, Evelina; Gupta, Kapil; Maier, Josef; Gordeliy, Valentin; Fitzgerald, Daniel J; Berger, Imre

    2013-01-01

    Most essential activities in eukaryotic cells are catalyzed by large multiprotein assemblies containing up to ten or more interlocking subunits. The vast majority of these protein complexes are not easily accessible for high resolution studies aimed at unlocking their mechanisms, due to their low cellular abundance and high heterogeneity. Recombinant overproduction can resolve this bottleneck and baculovirus expression vector systems (BEVS) have emerged as particularly powerful tools for the provision of eukaryotic multiprotein complexes in high quality and quantity. Recently, synthetic biology approaches have begun to make their mark in improving existing BEVS reagents by de novo design of streamlined transfer plasmids and by engineering the baculovirus genome. Here we present OmniBac, comprising new custom designed reagents that further facilitate the integration of heterologous genes into the baculovirus genome for multiprotein expression. Based on comparative genome analysis and data mining, we herein present a blueprint to custom design and engineer the entire baculovirus genome for optimized production properties using a bottom-up synthetic biology approach. PMID:23328086

  17. Prediction of Tumor Outcome Based on Gene Expression Data

    Institute of Scientific and Technical Information of China (English)

    Liu Juan; Hitoshi Iba

    2004-01-01

    Gene expression microarray data can be used to classify tumor types. We proposed a new procedure to classify human tumor samples based on microarray gene expressions by using a hybrid supervised learning method called MOEA+WV (Multi-Objective Evolutionary Algorithm+Weighted Voting). MOEA is used to search for a relatively few subsets of informative genes from the high-dimensional gene space, and WV is used as a classification tool. This new method has been applied to predicate the subtypes of lymphoma and outcomes of medulloblastoma. The results are relatively accurate and meaningful compared to those from other methods.

  18. Differential gene expression between visceral and subcutaneous fat depots.

    Science.gov (United States)

    Atzmon, G; Yang, X M; Muzumdar, R; Ma, X H; Gabriely, I; Barzilai, N

    2002-01-01

    Abdominal obesity has been linked to the development of insulin resistance and Type 2 diabetes mellitus (DM2). By surgical removal of visceral fat (VF) in a variety of rodent models, we prevented insulin resistance and glucose intolerance, establishing a cause-effect relationship between VF and the metabolic syndrome. To characterize the biological differences between visceral and peripheral fat depots, we obtained perirenal visceral (VF) and subcutaneous (SC) fat from 5 young rats. We extracted mRNA from the fat tissue and performed gene array hybridization using Affymetrix technology with a platform containing 9 000 genes. Out of the 1 660 genes that were expressed in fat tissue, 297 (17.9 %) genes show a two-fold or higher difference in their expression between the two tissues. We present the 20 genes whose expression is higher in VF fat (by 3 - 7 fold) and the 20 genes whose expression is higher in SC fat (by 3 - 150 fold), many of which are predominantly involved in glucose homeostasis, insulin action, and lipid metabolism. We confirmed the findings of gene array expression and quantified the changes in expression in VF of genes involved in insulin resistance (PPARgamma leptin) and its syndrome (angiotensinogen and plasminogen activating inhibitor-1, PAI-1) by real-time PCR (qRT-PCR) technology. Finally, we demonstrated increased expression of resistin in VF by around 12-fold and adiponectin by around 4-fold, peptides that were not part of the gene expression platform. These results indicate that visceral fat and subcutaneous fat are biologically distinct. PMID:12660871

  19. Influence of mitochondria on gene expression in a citrus cybrid.

    Science.gov (United States)

    Bassene, Jean-Baptiste; Froelicher, Yann; Navarro, Luis; Ollitrault, Patrick; Ancillo, Gema

    2011-06-01

    The production of cybrids, combining nucleus of a species with alien cytoplasmic organelles, is a valuable method used for improvement of various crops. Several citrus cybrids have been created by somatic hybridization. These genotypes are interesting models to analyze the impact of cytoplasmic genome change on nuclear genome expression. Herein, we report genome-wide gene expression analysis in leaves of a citrus cybrid between C. reticulata cv 'Willowleaf mandarin' and C. limon cv 'Eureka lemon' compared with its lemon parent, using a Citrus 20K cDNA microarray. Molecular analysis showed that this cybrid possesses nuclear and chloroplast genomes of Eureka lemon plus mitochondria from Willowleaf mandarin and, therefore, can be considered as a lemon bearing foreign mitochondria. Mandarin mitochondria influenced the expression of a large set of lemon nuclear genes causing an over-expression of 480 of them and repression of 39 genes. Quantitative real-time RT-PCR further confirmed the credibility of microarray data. Genes over-expressed in cybrid leaves are predominantly attributed to the functional category "cellular protein metabolism" whereas in the down-regulated none functional category was enriched. Overall, mitochondria replacement affected different nuclear genes including particularly genes predicted to be involved in mitochondrial retrograde signaling. Mitochondria regulate all cell structures even chloroplast status. These results suggest that nuclear gene expression is modulated with respect to new information received from the foreign organelle, with the final objective to suit specific needs to ensure better cell physiological balance. PMID:21308470

  20. Global Gene Expression Analysis for the Assessment of Nanobiomaterials.

    Science.gov (United States)

    Hanagata, Nobutaka

    2015-01-01

    Using global gene expression analysis, the effects of biomaterials and nanomaterials can be analyzed at the genetic level. Even though information obtained from global gene expression analysis can be useful for the evaluation and design of biomaterials and nanomaterials, its use for these purposes is not widespread. This is due to the difficulties involved in data analysis. Because the expression data of about 20,000 genes can be obtained at once with global gene expression analysis, the data must be analyzed using bioinformatics. A method of bioinformatic analysis called gene ontology can estimate the kinds of changes on cell functions caused by genes whose expression level is changed by biomaterials and nanomaterials. Also, by applying a statistical analysis technique called hierarchical clustering to global gene expression data between a variety of biomaterials, the effects of the properties of materials on cell functions can be estimated. In this chapter, these theories of analysis and examples of applications to nanomaterials and biomaterials are described. Furthermore, global microRNA analysis, a method that has gained attention in recent years, and its application to nanomaterials are introduced. PMID:26201278

  1. [Expression of bioinformatically identified genes in skin of psoriasis patients].

    Science.gov (United States)

    2013-10-01

    Gene expression analysis for EPHA2 (EPH receptor A2), EPHB2 (EPH receptor B2), S100A9 (S100 calcium binding protein A9), PBEF(nicotinamide phosphoribosyltransferase), LILRB2 (leukocyte immunoglobulin-like receptor, subfamily B (with TM and ITIM domains), member 2), PLAUR (plasminogen activator, urokinase receptor), LTB (lymphotoxin beta (TNF superfamily, member 3)), WNT5A (wingless-type MMTV integration site family, member 5A) has been conducted using real-time polymerase chain reaction in specimens affected by psoriasis versus visually intact skin in 18 patients. It was revealed that the expression of the nine examined genes was upregulated in the affected by psoriasis compared to visually intact skin specimens. The highest expression was observed for S100A9, S100AS, PBEF, WNT5A2, and EPHB2 genes. S100A9 and S100A8 gene expression in the affected by psoriasis skin was 100-fold higher versus visually intact skin while PBEF, WNT5A, and EPHB2 gene expression was upregulated more than five-fold. We suggested that the high expression of these genes might be associated with the state of the pathological process in psoriasis. Moreover, the transcriptional activity of these genes might serve a molecular indicator of the efficacy of treatment in psoriasis. PMID:25508677

  2. Identification and characterization of a novel gene differentially expressed in zebrafish cross-subfamily cloned embryos

    Directory of Open Access Journals (Sweden)

    Wang Ya-Ping

    2008-03-01

    Full Text Available Abstract Background Cross-species nuclear transfer has been shown to be a potent approach to retain the genetic viability of a certain species near extinction. However, most embryos produced by cross-species nuclear transfer were compromised because that they were unable to develop to later stages. Gene expression analysis of cross-species cloned embryos will yield new insights into the regulatory mechanisms involved in cross-species nuclear transfer and embryonic development. Results A novel gene, K31, was identified as an up-regulated gene in fish cross-subfamily cloned embryos using SSH approach and RACE method. K31 complete cDNA sequence is 1106 base pairs (bp in length, with a 342 bp open reading frame (ORF encoding a putative protein of 113 amino acids (aa. Comparative analysis revealed no homologous known gene in zebrafish and other species database. K31 protein contains a putative transmembrane helix and five putative phosphorylation sites but without a signal peptide. Expression pattern analysis by real time RT-PCR and whole-mount in situ hybridization (WISH shows that it has the characteristics of constitutively expressed gene. Sub-cellular localization assay shows that K31 protein can not penetrate the nuclei. Interestingly, over-expression of K31 gene can cause lethality in the epithelioma papulosum cyprinid (EPC cells in cell culture, which gave hint to the inefficient reprogramming events occurred in cloned embryos. Conclusion Taken together, our findings indicated that K31 gene is a novel gene differentially expressed in fish cross-subfamily cloned embryos and over-expression of K31 gene can cause lethality of cultured fish cells. To our knowledge, this is the first report on the determination of novel genes involved in nucleo-cytoplasmic interaction of fish cross-subfamily cloned embryos.

  3. A biphasic pattern of gene expression during mouse retina development

    Directory of Open Access Journals (Sweden)

    Soares Marcelo

    2006-10-01

    Full Text Available Abstract Background Between embryonic day 12 and postnatal day 21, six major neuronal and one glia cell type are generated from multipotential progenitors in a characteristic sequence during mouse retina development. We investigated expression patterns of retina transcripts during the major embryonic and postnatal developmental stages to provide a systematic view of normal mouse retina development, Results A tissue-specific cDNA microarray was generated using a set of sequence non-redundant EST clones collected from mouse retina. Eleven stages of mouse retina, from embryonic day 12.5 (El2.5 to postnatal day 21 (PN21, were collected for RNA isolation. Non-amplified RNAs were labeled for microarray experiments and three sets of data were analyzed for significance, hierarchical relationships, and functional clustering. Six individual gene expression clusters were identified based on expression patterns of transcripts through retina development. Two developmental phases were clearly divided with postnatal day 5 (PN5 as a separate cluster. Among 4,180 transcripts that changed significantly during development, approximately 2/3 of the genes were expressed at high levels up until PN5 and then declined whereas the other 1/3 of the genes increased expression from PN5 and remained at the higher levels until at least PN21. Less than 1% of the genes observed showed a peak of expression between the two phases. Among the later increased population, only about 40% genes are correlated with rod photoreceptors, indicating that multiple cell types contributed to gene expression in this phase. Within the same functional classes, however, different gene populations were expressed in distinct developmental phases. A correlation coefficient analysis of gene expression during retina development between previous SAGE studies and this study was also carried out. Conclusion This study provides a complementary genome-wide view of common gene dynamics and a broad molecular

  4. GeneSigDB—A Curated Database of Gene Expression Signatures

    OpenAIRE

    Culhane, Aedín C.; Schwarzl, Thomas; Sultana, Razvan; Picard, Shaita C.; Lu, Tim H.; Franklin, Katherine R.; French, Simon J.; Papenhausen, Gerald; Correll, Mick; Picard, Kermshlise; Quackenbush, John

    2009-01-01

    The primary objective of most gene expression studies is the identification of one or more gene signatures; lists of genes whose transcriptional levels are uniquely associated with a specific biological phenotype. Whilst thousands of experimentally derived gene signatures are published, their potential value to the community is limited by their computational inaccessibility. Gene signatures are embedded in published article figures, tables or in supplementary materials, and are frequently pre...

  5. Gene expression profiles of mouse spermatogenesis during recovery from irradiation

    DEFF Research Database (Denmark)

    Shah, Fozia J; Tanaka, Masami; Nielsen, John E;

    2009-01-01

    cellular changes that happen during recovery from irradiation by means of histology. We have earlier generated gene expression profiles during induction of spermatogenesis in mouse postnatal developing testes and found a correlation between profiles and the expressing cell types. The aim of the present...... work was to utilize the link between expression profile and cell types to follow the cellular changes that occur during post-irradiation recovery of spermatogenesis in order to describe recovery by means of gene expression. METHODS: Adult mouse testes were subjected to irradiation with 1 Gy or a...

  6. Expression of a Carrot Antifreeze Protein Gene in Escherichia coli

    Institute of Scientific and Technical Information of China (English)

    Ma Xinyu; Shen Xin; Lu Cunfu

    2003-01-01

    The recombinant expression vectorpET43. lb-AFP, which contains full encoding region of a carrot 36 kD antifreeze protein (AFP) gene was constructed. The recombinant was transformed into expression host carrying T7 RNA polymerase gene (DE3 lysogen) and induced by 1 mmol. L-1 IPTG (isopropyl-β-D-thiogalactoside) to express 110 kD polypeptide of AFP fusion protein.The analysis of product solubility revealed that pET43. 1b-AFP was predominately soluble, and the expressed amount reached the maximum after the IPTG treatment for 3 h.

  7. THE GENE EXPRESSION PROFILE OF HIGHLY METASTATIC HUMAN OVARIAN CANCER CELL LINE BY GENE CHIP

    Institute of Scientific and Technical Information of China (English)

    吕桂泉; 许沈华; 牟瀚舟; 朱赤红; 羊正炎; 高永良; 楼洪坤; 刘祥麟; 杨文; 程勇

    2001-01-01

    To study the gene expression of high metastatic human ovarian carcinoma cell line (HO-8910PM) and to screen for novel metastasis- associated genes by cDNA microarray. Methods: The cDNA was retro-transcribed from equal quantity mRNA derived from tissues of highly metastatic ovarian carcinoma cell line and normal ovarian, and was labeled with Cy5 and Cy3 fluorescence as probes. The mixed probes were hybridized with BioDoor 4096 double dot human whole gene chip. The chip was scanned by scanArray 3000 laser scanner. The acquired image was analyzed by ImaGene 3.0 software. Results: By applying the cDNA microarray we found: A total of 323 genes whose expression level were 3 times higher or lower in HO-8910PM cell than normal ovarian epithelium cell were screened out, with 71 higher and 252 lower respectively. Among these 10 were new genes. 67 genes showed expression difference bigger than 6 times between HO-8910PM cell and normal ovarian epithelium cell, among these genes 12 were higher, 55 lower, and two new genes were found. Conclusion: cDNA microarray technique is effective in screening the differentially expressed genes between human ovarian cancer cell line (HO-8910PM) and normal ovarian epithelium cell. Using the cDNA microarray to analyze of human ovarian cancer cell line gene expression profile difference will help the gene diagnosis, treatment and protection.

  8. Gene expression profile differences in gastric cancer, pericancerous epithelium and normal gastric mucosa by gene chip

    Institute of Scientific and Technical Information of China (English)

    Chuan-Ding Yu; Shen-Hua Xu; Hang-Zhou Mou; Zhi-Ming Jiang; Chi-Hong Zhu; Xiang-Lin Liu

    2005-01-01

    AIM: To study the difference of gene expression in gastric cancer (T), pericancerous epithelium (P) and normal tissue of gastric mucosa (C), and to screen an associated novel gene in early gastric carcinogenesis by oligonudeotide microarray.METHODS: U133A (Affymetrix, Santa Clara, CA) gene chip was used to detect the gene expression profile difference in T, P and C, respectively. Bioinformatics was used to analyze the detected results.RESULTS: When gastric cancer was compared with normal gastric mucosa, 766 genes were found, with a difference of more than four times in expression levels. Of the 766 genes,530 were up-regulated (Signal Log Ratio [SLR]>2), and 236 were down-regulated (SLR<-2). When pericancerous epithelium was compared with normal gastric mucosa, 64genes were found, with a difference of more than four times in expression levels. Of the 64 genes, 50 were up-regulated (SLR>2), and 14 were down-regulated (SLR<-2). Compared with normal gastric mucosa, a total of 143 genes with a difference in expression levels (more than four times, either in cancer or in pericancerous epithelium) were found in gastric cancer (T) and pericancerous epithelium (P). Of the 143 genes, 108 were up-regulated (SLR>2), and 35were down-regulated (SLR<-2).CONCLUSION: To apply a gene chip could find 143 genes associated with the genes of gastric cancer in pericancerous epithelium, although there were no pathological changes in the tissue slices. More interesting, six genes of pericancerous epithelium were up-regulated in comparison with genes of gastric cancer and three genes were down-regulated in comparison with genes of gastric cancer. It is suggested that these genes may be related to the carcinogenesis and development of early gastric cancer.

  9. Patterns of homoeologous gene expression shown by RNA sequencing in hexaploid bread wheat.

    KAUST Repository

    Leach, Lindsey J

    2014-04-11

    BACKGROUND: Bread wheat (Triticum aestivum) has a large, complex and hexaploid genome consisting of A, B and D homoeologous chromosome sets. Therefore each wheat gene potentially exists as a trio of A, B and D homoeoloci, each of which may contribute differentially to wheat phenotypes. We describe a novel approach