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Sample records for robust gene expression

  1. Robust, synergistic regulation of human gene expression using TALE activators.

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    Maeder, Morgan L; Linder, Samantha J; Reyon, Deepak; Angstman, James F; Fu, Yanfang; Sander, Jeffry D; Joung, J Keith

    2013-03-01

    Artificial activators designed using transcription activator-like effector (TALE) technology have broad utility, but previous studies suggest that these monomeric proteins often exhibit low activities. Here we demonstrate that TALE activators can robustly function individually or in synergistic combinations to increase expression of endogenous human genes over wide dynamic ranges. These findings will encourage applications of TALE activators for research and therapy, and guide design of monomeric TALE-based fusion proteins.

  2. Evolution of robustness to noise and mutation in gene expression dynamics.

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    Kunihiko Kaneko

    Full Text Available Phenotype of biological systems needs to be robust against mutation in order to sustain themselves between generations. On the other hand, phenotype of an individual also needs to be robust against fluctuations of both internal and external origins that are encountered during growth and development. Is there a relationship between these two types of robustness, one during a single generation and the other during evolution? Could stochasticity in gene expression have any relevance to the evolution of these types of robustness? Robustness can be defined by the sharpness of the distribution of phenotype; the variance of phenotype distribution due to genetic variation gives a measure of 'genetic robustness', while that of isogenic individuals gives a measure of 'developmental robustness'. Through simulations of a simple stochastic gene expression network that undergoes mutation and selection, we show that in order for the network to acquire both types of robustness, the phenotypic variance induced by mutations must be smaller than that observed in an isogenic population. As the latter originates from noise in gene expression, this signifies that the genetic robustness evolves only when the noise strength in gene expression is larger than some threshold. In such a case, the two variances decrease throughout the evolutionary time course, indicating increase in robustness. The results reveal how noise that cells encounter during growth and development shapes networks' robustness to stochasticity in gene expression, which in turn shapes networks' robustness to mutation. The necessary condition for evolution of robustness, as well as the relationship between genetic and developmental robustness, is derived quantitatively through the variance of phenotypic fluctuations, which are directly measurable experimentally.

  3. Evolution of robustness to noise and mutation in gene expression dynamics.

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    Kaneko, Kunihiko

    2007-05-09

    Phenotype of biological systems needs to be robust against mutation in order to sustain themselves between generations. On the other hand, phenotype of an individual also needs to be robust against fluctuations of both internal and external origins that are encountered during growth and development. Is there a relationship between these two types of robustness, one during a single generation and the other during evolution? Could stochasticity in gene expression have any relevance to the evolution of these types of robustness? Robustness can be defined by the sharpness of the distribution of phenotype; the variance of phenotype distribution due to genetic variation gives a measure of 'genetic robustness', while that of isogenic individuals gives a measure of 'developmental robustness'. Through simulations of a simple stochastic gene expression network that undergoes mutation and selection, we show that in order for the network to acquire both types of robustness, the phenotypic variance induced by mutations must be smaller than that observed in an isogenic population. As the latter originates from noise in gene expression, this signifies that the genetic robustness evolves only when the noise strength in gene expression is larger than some threshold. In such a case, the two variances decrease throughout the evolutionary time course, indicating increase in robustness. The results reveal how noise that cells encounter during growth and development shapes networks' robustness to stochasticity in gene expression, which in turn shapes networks' robustness to mutation. The necessary condition for evolution of robustness, as well as the relationship between genetic and developmental robustness, is derived quantitatively through the variance of phenotypic fluctuations, which are directly measurable experimentally.

  4. Robust modeling of differential gene expression data using normal/independent distributions: a Bayesian approach.

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    Mojtaba Ganjali

    Full Text Available In this paper, the problem of identifying differentially expressed genes under different conditions using gene expression microarray data, in the presence of outliers, is discussed. For this purpose, the robust modeling of gene expression data using some powerful distributions known as normal/independent distributions is considered. These distributions include the Student's t and normal distributions which have been used previously, but also include extensions such as the slash, the contaminated normal and the Laplace distributions. The purpose of this paper is to identify differentially expressed genes by considering these distributional assumptions instead of the normal distribution. A Bayesian approach using the Markov Chain Monte Carlo method is adopted for parameter estimation. Two publicly available gene expression data sets are analyzed using the proposed approach. The use of the robust models for detecting differentially expressed genes is investigated. This investigation shows that the choice of model for differentiating gene expression data is very important. This is due to the small number of replicates for each gene and the existence of outlying data. Comparison of the performance of these models is made using different statistical criteria and the ROC curve. The method is illustrated using some simulation studies. We demonstrate the flexibility of these robust models in identifying differentially expressed genes.

  5. Proportionality between variances in gene expression induced by noise and mutation: consequence of evolutionary robustness

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    Kaneko Kunihiko

    2011-01-01

    Full Text Available Abstract Background Characterization of robustness and plasticity of phenotypes is a basic issue in evolutionary and developmental biology. The robustness and plasticity are concerned with changeability of a biological system against external perturbations. The perturbations are either genetic, i.e., due to mutations in genes in the population, or epigenetic, i.e., due to noise during development or environmental variations. Thus, the variances of phenotypes due to genetic and epigenetic perturbations provide quantitative measures for such changeability during evolution and development, respectively. Results Using numerical models simulating the evolutionary changes in the gene regulation network required to achieve a particular expression pattern, we first confirmed that gene expression dynamics robust to mutation evolved in the presence of a sufficient level of transcriptional noise. Under such conditions, the two types of variances in the gene expression levels, i.e. those due to mutations to the gene regulation network and those due to noise in gene expression dynamics were found to be proportional over a number of genes. The fraction of such genes with a common proportionality coefficient increased with an increase in the robustness of the evolved network. This proportionality was generally confirmed, also under the presence of environmental fluctuations and sexual recombination in diploids, and was explained from an evolutionary robustness hypothesis, in which an evolved robust system suppresses the so-called error catastrophe - the destabilization of the single-peaked distribution in gene expression levels. Experimental evidences for the proportionality of the variances over genes are also discussed. Conclusions The proportionality between the genetic and epigenetic variances of phenotypes implies the correlation between the robustness (or plasticity against genetic changes and against noise in development, and also suggests that

  6. ROBUST HYPERPARAMETER ESTIMATION PROTECTS AGAINST HYPERVARIABLE GENES AND IMPROVES POWER TO DETECT DIFFERENTIAL EXPRESSION

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    Phipson, Belinda; Lee, Stanley; Majewski, Ian J.; Alexander, Warren S.; Smyth, Gordon K.

    2017-01-01

    One of the most common analysis tasks in genomic research is to identify genes that are differentially expressed (DE) between experimental conditions. Empirical Bayes (EB) statistical tests using moderated genewise variances have been very effective for this purpose, especially when the number of biological replicate samples is small. The EB procedures can however be heavily influenced by a small number of genes with very large or very small variances. This article improves the differential expression tests by robustifying the hyperparameter estimation procedure. The robust procedure has the effect of decreasing the informativeness of the prior distribution for outlier genes while increasing its informativeness for other genes. This effect has the double benefit of reducing the chance that hypervariable genes will be spuriously identified as DE while increasing statistical power for the main body of genes. The robust EB algorithm is fast and numerically stable. The procedure allows exact small-sample null distributions for the test statistics and reduces exactly to the original EB procedure when no outlier genes are present. Simulations show that the robustified tests have similar performance to the original tests in the absence of outlier genes but have greater power and robustness when outliers are present. The article includes case studies for which the robust method correctly identifies and downweights genes associated with hidden covariates and detects more genes likely to be scientifically relevant to the experimental conditions. The new procedure is implemented in the limma software package freely available from the Bioconductor repository.

  7. Massive-scale gene co-expression network construction and robustness testing using random matrix theory.

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    Gibson, Scott M; Ficklin, Stephen P; Isaacson, Sven; Luo, Feng; Feltus, Frank A; Smith, Melissa C

    2013-01-01

    The study of gene relationships and their effect on biological function and phenotype is a focal point in systems biology. Gene co-expression networks built using microarray expression profiles are one technique for discovering and interpreting gene relationships. A knowledge-independent thresholding technique, such as Random Matrix Theory (RMT), is useful for identifying meaningful relationships. Highly connected genes in the thresholded network are then grouped into modules that provide insight into their collective functionality. While it has been shown that co-expression networks are biologically relevant, it has not been determined to what extent any given network is functionally robust given perturbations in the input sample set. For such a test, hundreds of networks are needed and hence a tool to rapidly construct these networks. To examine functional robustness of networks with varying input, we enhanced an existing RMT implementation for improved scalability and tested functional robustness of human (Homo sapiens), rice (Oryza sativa) and budding yeast (Saccharomyces cerevisiae). We demonstrate dramatic decrease in network construction time and computational requirements and show that despite some variation in global properties between networks, functional similarity remains high. Moreover, the biological function captured by co-expression networks thresholded by RMT is highly robust.

  8. Massive-scale gene co-expression network construction and robustness testing using random matrix theory.

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    Scott M Gibson

    Full Text Available The study of gene relationships and their effect on biological function and phenotype is a focal point in systems biology. Gene co-expression networks built using microarray expression profiles are one technique for discovering and interpreting gene relationships. A knowledge-independent thresholding technique, such as Random Matrix Theory (RMT, is useful for identifying meaningful relationships. Highly connected genes in the thresholded network are then grouped into modules that provide insight into their collective functionality. While it has been shown that co-expression networks are biologically relevant, it has not been determined to what extent any given network is functionally robust given perturbations in the input sample set. For such a test, hundreds of networks are needed and hence a tool to rapidly construct these networks. To examine functional robustness of networks with varying input, we enhanced an existing RMT implementation for improved scalability and tested functional robustness of human (Homo sapiens, rice (Oryza sativa and budding yeast (Saccharomyces cerevisiae. We demonstrate dramatic decrease in network construction time and computational requirements and show that despite some variation in global properties between networks, functional similarity remains high. Moreover, the biological function captured by co-expression networks thresholded by RMT is highly robust.

  9. Robust Yet Fragile: Expression Noise, Protein Misfolding, and Gene Dosage in the Evolution of Genomes.

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    Pires, J Chris; Conant, Gavin C

    2016-11-23

    The complex manner in which organisms respond to changes in their gene dosage has long fascinated geneticists. Oddly, although the existence of dominance implies that dosage reductions often have mild phenotypes, extra copies of whole chromosomes (aneuploidy) are generally strongly deleterious. Even more paradoxically, an extra copy of the genome is better tolerated than is aneuploidy. We review the resolution of this paradox, highlighting the roles of biochemistry, protein aggregation, and disruption of cellular microstructure in that explanation. Returning to life's curious combination of robustness and sensitivity to dosage changes, we argue that understanding how biological robustness evolved makes these observations less inexplicable. We propose that noise in gene expression and evolutionary strategies for its suppression play a role in generating dosage phenotypes. Finally, we outline an unappreciated mechanism for the preservation of duplicate genes, namely preservation to limit expression noise, arguing that it is particularly relevant in polyploid organisms.

  10. The impact of gene expression variation on the robustness and evolvability of a developmental gene regulatory network.

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    David A Garfield

    2013-10-01

    Full Text Available Regulatory interactions buffer development against genetic and environmental perturbations, but adaptation requires phenotypes to change. We investigated the relationship between robustness and evolvability within the gene regulatory network underlying development of the larval skeleton in the sea urchin Strongylocentrotus purpuratus. We find extensive variation in gene expression in this network throughout development in a natural population, some of which has a heritable genetic basis. Switch-like regulatory interactions predominate during early development, buffer expression variation, and may promote the accumulation of cryptic genetic variation affecting early stages. Regulatory interactions during later development are typically more sensitive (linear, allowing variation in expression to affect downstream target genes. Variation in skeletal morphology is associated primarily with expression variation of a few, primarily structural, genes at terminal positions within the network. These results indicate that the position and properties of gene interactions within a network can have important evolutionary consequences independent of their immediate regulatory role.

  11. Robust detection of hierarchical communities from Escherichia coli gene expression data.

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    Santiago Treviño

    Full Text Available Determining the functional structure of biological networks is a central goal of systems biology. One approach is to analyze gene expression data to infer a network of gene interactions on the basis of their correlated responses to environmental and genetic perturbations. The inferred network can then be analyzed to identify functional communities. However, commonly used algorithms can yield unreliable results due to experimental noise, algorithmic stochasticity, and the influence of arbitrarily chosen parameter values. Furthermore, the results obtained typically provide only a simplistic view of the network partitioned into disjoint communities and provide no information of the relationship between communities. Here, we present methods to robustly detect co-regulated and functionally enriched gene communities and demonstrate their application and validity for Escherichia coli gene expression data. Applying a recently developed community detection algorithm to the network of interactions identified with the context likelihood of relatedness (CLR method, we show that a hierarchy of network communities can be identified. These communities significantly enrich for gene ontology (GO terms, consistent with them representing biologically meaningful groups. Further, analysis of the most significantly enriched communities identified several candidate new regulatory interactions. The robustness of our methods is demonstrated by showing that a core set of functional communities is reliably found when artificial noise, modeling experimental noise, is added to the data. We find that noise mainly acts conservatively, increasing the relatedness required for a network link to be reliably assigned and decreasing the size of the core communities, rather than causing association of genes into new communities.

  12. Indirect two-sided relative ranking: a robust similarity measure for gene expression data

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    Licamele Louis

    2010-03-01

    Full Text Available Abstract Background There is a large amount of gene expression data that exists in the public domain. This data has been generated under a variety of experimental conditions. Unfortunately, these experimental variations have generally prevented researchers from accurately comparing and combining this wealth of data, which still hides many novel insights. Results In this paper we present a new method, which we refer to as indirect two-sided relative ranking, for comparing gene expression profiles that is robust to variations in experimental conditions. This method extends the current best approach, which is based on comparing the correlations of the up and down regulated genes, by introducing a comparison based on the correlations in rankings across the entire database. Because our method is robust to experimental variations, it allows a greater variety of gene expression data to be combined, which, as we show, leads to richer scientific discoveries. Conclusions We demonstrate the benefit of our proposed indirect method on several datasets. We first evaluate the ability of the indirect method to retrieve compounds with similar therapeutic effects across known experimental barriers, namely vehicle and batch effects, on two independent datasets (one private and one public. We show that our indirect method is able to significantly improve upon the previous state-of-the-art method with a substantial improvement in recall at rank 10 of 97.03% and 49.44%, on each dataset, respectively. Next, we demonstrate that our indirect method results in improved accuracy for classification in several additional datasets. These datasets demonstrate the use of our indirect method for classifying cancer subtypes, predicting drug sensitivity/resistance, and classifying (related cell types. Even in the absence of a known (i.e., labeled experimental barrier, the improvement of the indirect method in each of these datasets is statistically significant.

  13. The human desmin promoter drives robust gene expression for skeletal muscle stem cell-mediated gene therapy.

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    Jonuschies, Jacqueline; Antoniou, Michael; Waddington, Simon; Boldrin, Luisa; Muntoni, Francesco; Thrasher, Adrian; Morgan, Jennifer

    2014-01-01

    Lentiviral vectors (LVs) represent suitable candidates to mediate gene therapy for muscular dystrophies as they infect dividing and non-dividing cells and integrate their genetic material into the host genome, thereby theoretically mediating longterm expression. We evaluated the ability of LVs where a GFP reporter gene was under the control of five different promoters, to transduce and mediate expression in myogenic and non-myogenic cells in vitro and in skeletal muscle fibres and stem (satellite) cells in vivo. We further analysed lentivirally-transduced satellite cell-derived myoblasts following their transplantation into dystrophic, immunodeficient mouse muscles. The spleen focus-forming virus promoter mediated the highest gene expression in all cell types; the CBX3-HNRPA2B1 ubiquitously-acting chromatin opening element (UCOE) promoter was also active in all cells, whereas the human desmin promoter in isolation or fused with UCOE had lower activity in non-muscle cells. Surprisingly, the human skeletal muscle actin promoter was also active in immune cells. The human desmin promoter mediated robust, persistent reporter gene expression in myogenic cells in vitro, and satellite cells and muscle fibres in vivo. The human desmin promoter combined with UCOE did not significantly increase transgene expression. Therefore, our data indicate that the desmin promoter is suitable for the development of therapeutic purposes.

  14. Poinsettia protoplasts - a simple, robust and efficient system for transient gene expression studies

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    Pitzschke Andrea

    2012-05-01

    Full Text Available Abstract Background Transient gene expression systems are indispensable tools in molecular biology. Yet, their routine application is limited to few plant species often requiring substantial equipment and facilities. High chloroplast and chlorophyll content may further impede downstream applications of transformed cells from green plant tissue. Results Here, we describe a fast and simple technique for the high-yield isolation and efficient transformation (>70% of mesophyll-derived protoplasts from red leaves of the perennial plant Poinsettia (Euphorbia pulccherrima. In this method no particular growth facilities or expensive equipments are needed. Poinsettia protoplasts display an astonishing robustness and can be employed in a variety of commonly-used downstream applications, such as subcellular localisation (multi-colour fluorescence or promoter activity studies. Due to low abundance of chloroplasts or chromoplasts, problems encountered in other mesophyll-derived protoplast systems (particularly autofluorescence are alleviated. Furthermore, the transgene expression is detectable within 90 minutes of transformation and lasts for several days. Conclusions The simplicity of the isolation and transformation procedure renders Poinsettia protoplasts an attractive system for transient gene expression experiments, including multi-colour fluorescence, subcellular localisation and promoter activity studies. In addition, they offer hitherto unknown possibilities for anthocyan research and industrial applications.

  15. Robust TLR4-induced gene expression patterns are not an accurate indicator of human immunity

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    2010-01-01

    Background Activation of Toll-like receptors (TLRs) is widely accepted as an essential event for defence against infection. Many TLRs utilize a common signalling pathway that relies on activation of the kinase IRAK4 and the transcription factor NFκB for the rapid expression of immunity genes. Methods 21 K DNA microarray technology was used to evaluate LPS-induced (TLR4) gene responses in blood monocytes from a child with an IRAK4-deficiency. In vitro responsiveness to LPS was confirmed by real-time PCR and ELISA and compared to the clinical predisposition of the child and IRAK4-deficient mice to Gram negative infection. Results We demonstrated that the vast majority of LPS-responsive genes in IRAK4-deficient monocytes were greatly suppressed, an observation that is consistent with the described role for IRAK4 as an essential component of TLR4 signalling. The severely impaired response to LPS, however, is inconsistent with a remarkably low incidence of Gram negative infections observed in this child and other children with IRAK4-deficiency. This unpredicted clinical phenotype was validated by demonstrating that IRAK4-deficient mice had a similar resistance to infection with Gram negative S. typhimurium as wildtype mice. A number of immunity genes, such as chemokines, were expressed at normal levels in human IRAK4-deficient monocytes, indicating that particular IRAK4-independent elements within the repertoire of TLR4-induced responses are expressed. Conclusions Sufficient defence to Gram negative immunity does not require IRAK4 or a robust, 'classic' inflammatory and immune response. PMID:20105294

  16. A robust dual reporter system to visualize and quantify gene expression mediated by transcription activator-like effectors

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    Uhde-Stone Claudia

    2012-08-01

    Full Text Available Abstract Background Transcription activator-like effectors (TALEs are a class of naturally occurring transcription effectors that recognize specific DNA sequences and modulate gene expression. The modularity of TALEs DNA binding domain enables sequence-specific perturbation and offers broad applications in genetic and epigenetic studies. Although the efficient construction of TALEs has been established, robust functional tools to assess their functions remain lacking. Results We established a dual reporter system that was specifically designed for real-time monitoring and quantifying gene expression mediated by TALEs. We validated both sensitivity and specificity of this dual-reporter system in mammalian cells, and demonstrated that this dual reporter system is robust and potentially amenable to high throughput (HTP applications. Conclusion We have designed, constructed and validated a novel dual reporter system for assessing TALE mediated gene regulations. This system offers a robust and easy-to- use tool for real-time monitoring and quantifying gene expression in mammalian cells.

  17. Automated optogenetic feedback control for precise and robust regulation of gene expression and cell growth

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    Milias-Argeitis, Andreas; Rullan, Marc; Aoki, Stephanie K.; Buchmann, Peter; Khammash, Mustafa

    2016-01-01

    Dynamic control of gene expression can have far-reaching implications for biotechnological applications and biological discovery. Thanks to the advantages of light, optogenetics has emerged as an ideal technology for this task. Current state-of-the-art methods for optical expression control fail to combine precision with repeatability and cannot withstand changing operating culture conditions. Here, we present a novel fully automatic experimental platform for the robust and precise long-term optogenetic regulation of protein production in liquid Escherichia coli cultures. Using a computer-controlled light-responsive two-component system, we accurately track prescribed dynamic green fluorescent protein expression profiles through the application of feedback control, and show that the system adapts to global perturbations such as nutrient and temperature changes. We demonstrate the efficacy and potential utility of our approach by placing a key metabolic enzyme under optogenetic control, thus enabling dynamic regulation of the culture growth rate with potential applications in bacterial physiology studies and biotechnology. PMID:27562138

  18. Gene Expression Noise Enhances Robust Organization of the Early Mammalian Blastocyst

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    Wang, Qixuan; Du, Huijing; Peng, Tao; Chiang, Michael; Cinquin, Olivier; Cho, Ken

    2017-01-01

    A critical event in mammalian embryo development is construction of an inner cell mass surrounded by a trophoectoderm (a shell of cells that later form extraembryonic structures). We utilize multi-scale, stochastic modeling to investigate the design principles responsible for robust establishment of these structures. This investigation makes three predictions, each supported by our quantitative imaging. First, stochasticity in the expression of critical genes promotes cell plasticity and has a critical role in accurately organizing the developing mouse blastocyst. Second, asymmetry in the levels of noise variation (expression fluctuation) of Cdx2 and Oct4 provides a means to gain the benefits of noise-mediated plasticity while ameliorating the potentially detrimental effects of stochasticity. Finally, by controlling the timing and pace of cell fate specification, the embryo temporally modulates plasticity and creates a time window during which each cell can continually read its environment and adjusts its fate. These results suggest noise has a crucial role in maintaining cellular plasticity and organizing the blastocyst. PMID:28114387

  19. A Hybrid One-Way ANOVA Approach for the Robust and Efficient Estimation of Differential Gene Expression with Multiple Patterns.

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    Mohammad Manir Hossain Mollah

    Full Text Available Identifying genes that are differentially expressed (DE between two or more conditions with multiple patterns of expression is one of the primary objectives of gene expression data analysis. Several statistical approaches, including one-way analysis of variance (ANOVA, are used to identify DE genes. However, most of these methods provide misleading results for two or more conditions with multiple patterns of expression in the presence of outlying genes. In this paper, an attempt is made to develop a hybrid one-way ANOVA approach that unifies the robustness and efficiency of estimation using the minimum β-divergence method to overcome some problems that arise in the existing robust methods for both small- and large-sample cases with multiple patterns of expression.The proposed method relies on a β-weight function, which produces values between 0 and 1. The β-weight function with β = 0.2 is used as a measure of outlier detection. It assigns smaller weights (≥ 0 to outlying expressions and larger weights (≤ 1 to typical expressions. The distribution of the β-weights is used to calculate the cut-off point, which is compared to the observed β-weight of an expression to determine whether that gene expression is an outlier. This weight function plays a key role in unifying the robustness and efficiency of estimation in one-way ANOVA.Analyses of simulated gene expression profiles revealed that all eight methods (ANOVA, SAM, LIMMA, EBarrays, eLNN, KW, robust BetaEB and proposed perform almost identically for m = 2 conditions in the absence of outliers. However, the robust BetaEB method and the proposed method exhibited considerably better performance than the other six methods in the presence of outliers. In this case, the BetaEB method exhibited slightly better performance than the proposed method for the small-sample cases, but the the proposed method exhibited much better performance than the BetaEB method for both the small- and large

  20. GOexpress: an R/Bioconductor package for the identification and visualisation of robust gene ontology signatures through supervised learning of gene expression data.

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    Rue-Albrecht, Kévin; McGettigan, Paul A; Hernández, Belinda; Nalpas, Nicolas C; Magee, David A; Parnell, Andrew C; Gordon, Stephen V; MacHugh, David E

    2016-03-11

    Identification of gene expression profiles that differentiate experimental groups is critical for discovery and analysis of key molecular pathways and also for selection of robust diagnostic or prognostic biomarkers. While integration of differential expression statistics has been used to refine gene set enrichment analyses, such approaches are typically limited to single gene lists resulting from simple two-group comparisons or time-series analyses. In contrast, functional class scoring and machine learning approaches provide powerful alternative methods to leverage molecular measurements for pathway analyses, and to compare continuous and multi-level categorical factors. We introduce GOexpress, a software package for scoring and summarising the capacity of gene ontology features to simultaneously classify samples from multiple experimental groups. GOexpress integrates normalised gene expression data (e.g., from microarray and RNA-seq experiments) and phenotypic information of individual samples with gene ontology annotations to derive a ranking of genes and gene ontology terms using a supervised learning approach. The default random forest algorithm allows interactions between all experimental factors, and competitive scoring of expressed genes to evaluate their relative importance in classifying predefined groups of samples. GOexpress enables rapid identification and visualisation of ontology-related gene panels that robustly classify groups of samples and supports both categorical (e.g., infection status, treatment) and continuous (e.g., time-series, drug concentrations) experimental factors. The use of standard Bioconductor extension packages and publicly available gene ontology annotations facilitates straightforward integration of GOexpress within existing computational biology pipelines.

  1. Robust and regulatory expression of defensin A gene driven by vitellogenin promoter in transgenic Anopheles stephensi

    Institute of Scientific and Technical Information of China (English)

    CHEN XiaoGuang; ZHANG YaJing; ZHENG XueLi; WANG ChunMei

    2007-01-01

    The use of genetically modified mosquitoes to reduce or replace field populations is a new strategy to control mosquito-borne diseases. The precondition of the implementation of this strategy is the ability to manipulate the genome of mosquitoes and to induce specific expression of the effector molecules driven by a suitable promoter. The objective of this study is to evaluate the expression of defensin A gene of Anopheles sinensis under the control of a vitellogenin promoter in transgenic Anopheles stephensi. The regulatory region of Anopheles gambiae vitellogenin was cloned and subcloned into transfer vector pSLFa consisting of an expression cassette with defensin A coding sequence. Then, the expression cassette was transferred into transformation vector pBac[3xP3-DsRedafm] using Asc I digestion. The recombinant plasmid DNA of pBac[3xP3DsRed-AgVgT2-DefA] and helper plasmid DNA of phsp-pBac were micro-injected into embryos of An. stephensi. The positive transgenic mosquitoes were screened by observing specific red fluorescence in the eyes of G1 larvae. Southern blot analysis showed that a single-copy transgene integrated into the genome of An. stephensi. RT-PCR analysis showed that the defensin A gene expressed specifically in fat bodies of female mosquitoes after a blood meal. Interestingly, the mRNA of defensin A is more stable compared with that of the endogenous vitellogenin gene. After multiple blood meals, the expression of defensin A appeared as a reducible and non-cycling type, a crucial feature for its anti-pathogen effect. From data above, we concluded that the regulatory function of the Vg promoter and the expression of defensin A gene were relatively conserved in different species of anopheles mosquitoes. These molecules could be used as candidates in the development of genetically modified mosquitoes.

  2. Robust control of the seasonal expression of the Arabidopsis FLC gene in a fluctuating environment.

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    Aikawa, Shinichiro; Kobayashi, Masaki J; Satake, Akiko; Shimizu, Kentaro K; Kudoh, Hiroshi

    2010-06-22

    Plants flower in particular seasons even in natural, fluctuating environments. The molecular basis of temperature-dependent flowering-time regulation has been extensively studied, but little is known about how gene expression is controlled in natural environments. Without a memory of past temperatures, it would be difficult for plants to detect seasons in natural, noisy environments because temperature changes occurring within a few weeks are often inconsistent with seasonal trends. Our 2-y census of the expression of a temperature-dependent flowering-time gene, AhgFLC, in a natural population of perennial Arabidopsis halleri revealed that the regulatory system of this flowering-time gene extracts seasonal cues as if it memorizes temperatures over the past 6 wk. Time-series analysis revealed that as much as 83% of the variation in the AhgFLC expression is explained solely by the temperature for the previous 6 wk, but not by the temperatures over shorter or longer periods. The accuracy of our model in predicting the gene expression pattern under contrasting temperature regimes in the transplant experiments indicates that such modeling incorporating the molecular bases of flowering-time regulation will contribute to predicting plant responses to future climate changes.

  3. A robust prognostic gene expression signature for early stage lung adenocarcinoma

    DEFF Research Database (Denmark)

    Krzystanek, Marcin; Moldvay, Judit; Szüts, David;

    2016-01-01

    Stage I lung adenocarcinoma is usually not treated with adjuvant chemotherapy; however, around half of these patients do not survive 5 years. Therefore, a reliable prognostic biomarker for early stage patients would be critical to identify those most likely to benefit from early additional treatm...... not given adjuvant therapy. Seven genes consistently obtained statistical significance in Cox regression for overall survival. The combined signature has a weighted mean hazard ratio of 3.2 in all cohorts and 3.0 (C.I. 1.3-7.4, p ...... treatments. Several studies have searched for gene expression prognostic biomarkers for lung adenocarcinoma, but these have not yielded a widely accepted prognosticator. We analyzed gene expression from seven published lung adenocarcinoma cohorts for which we included only stage I and II patients who were...

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

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    Ryden Tobias

    2010-10-01

    Full Text Available Abstract Background 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. Results 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. Conclusions 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.

  5. Characterization of stem cells and cancer cells on the basis of gene expression profile stability, plasticity, and robustness: dynamical systems theory of gene expressions under cell-cell interaction explains mutational robustness of differentiated cells and suggests how cancer cells emerge.

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    Kaneko, Kunihiko

    2011-06-01

    Here I present and discuss a model that, among other things, appears able to describe the dynamics of cancer cell origin from the perspective of stable and unstable gene expression profiles. In identifying such aberrant gene expression profiles as lying outside the normal stable states attracted through development and normal cell differentiation, the hypothesis explains why cancer cells accumulate mutations, to which they are not robust, and why these mutations create a new stable state far from the normal gene expression profile space. Such cells are in strong contrast with normal cell types that appeared as an attractor state in the gene expression dynamical system under cell-cell interaction and achieved robustness to noise through evolution, which in turn also conferred robustness to mutation. In complex gene regulation networks, other aberrant cellular states lacking such high robustness are expected to remain, which would correspond to cancer cells.

  6. A Hybrid One-Way ANOVA Approach for the Robust and Efficient Estimation of Differential Gene Expression with Multiple Patterns

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    Mohammad Manir Hossain Mollah; Rahman Jamal; Norfilza Mohd Mokhtar; Roslan Harun; Md. Nurul Haque Mollah

    2015-01-01

    Background Identifying genes that are differentially expressed (DE) between two or more conditions with multiple patterns of expression is one of the primary objectives of gene expression data analysis. Several statistical approaches, including one-way analysis of variance (ANOVA), are used to identify DE genes. However, most of these methods provide misleading results for two or more conditions with multiple patterns of expression in the presence of outlying genes. In this paper, an attempt ...

  7. A simple metric of promoter architecture robustly predicts expression breadth of human genes suggesting that most transcription factors are positive regulators.

    Science.gov (United States)

    Hurst, Laurence D; Sachenkova, Oxana; Daub, Carsten; Forrest, Alistair R R; Huminiecki, Lukasz

    2014-07-31

    Conventional wisdom holds that, owing to the dominance of features such as chromatin level control, the expression of a gene cannot be readily predicted from knowledge of promoter architecture. This is reflected, for example, in a weak or absent correlation between promoter divergence and expression divergence between paralogs. However, an inability to predict may reflect an inability to accurately measure or employment of the wrong parameters. Here we address this issue through integration of two exceptional resources: ENCODE data on transcription factor binding and the FANTOM5 high-resolution expression atlas. Consistent with the notion that in eukaryotes most transcription factors are activating, the number of transcription factors binding a promoter is a strong predictor of expression breadth. In addition, evolutionarily young duplicates have fewer transcription factor binders and narrower expression. Nonetheless, we find several binders and cooperative sets that are disproportionately associated with broad expression, indicating that models more complex than simple correlations should hold more predictive power. Indeed, a machine learning approach improves fit to the data compared with a simple correlation. Machine learning could at best moderately predict tissue of expression of tissue specific genes. We find robust evidence that some expression parameters and paralog expression divergence are strongly predictable with knowledge of transcription factor binding repertoire. While some cooperative complexes can be identified, consistent with the notion that most eukaryotic transcription factors are activating, a simple predictor, the number of binding transcription factors found on a promoter, is a robust predictor of expression breadth.

  8. Stroke-associated pattern of gene expression previously identified by machine-learning is diagnostically robust in an independent patient population.

    Science.gov (United States)

    O'Connell, Grant C; Chantler, Paul D; Barr, Taura L

    2017-12-01

    Our group recently employed genome-wide transcriptional profiling in tandem with machine-learning based analysis to identify a ten-gene pattern of differential expression in peripheral blood which may have utility for detection of stroke. The objective of this study was to assess the diagnostic capacity and temporal stability of this stroke-associated transcriptional signature in an independent patient population. Publicly available whole blood microarray data generated from 23 ischemic stroke patients at 3, 5, and 24 h post-symptom onset, as well from 23 cardiovascular disease controls, were obtained via the National Center for Biotechnology Information Gene Expression Omnibus. Expression levels of the ten candidate genes (ANTXR2, STK3, PDK4, CD163, MAL, GRAP, ID3, CTSZ, KIF1B, and PLXDC2) were extracted, compared between groups, and evaluated for their discriminatory ability at each time point. We observed a largely identical pattern of differential expression between stroke patients and controls across the ten candidate genes as reported in our prior work. Furthermore, the coordinate expression levels of the ten candidate genes were able to discriminate between stroke patients and controls with levels of sensitivity and specificity upwards of 90% across all three time points. These findings confirm the diagnostic robustness of the previously identified pattern of differential expression in an independent patient population, and further suggest that it is temporally stable over the first 24 h of stroke pathology.

  9. Multicistronic lentiviral vectors containing the FMDV 2A cleavage factor demonstrate robust expression of encoded genes at limiting MOI

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    Margison Geoffrey P

    2006-03-01

    Full Text Available Abstract Background A number of gene therapy applications would benefit from vectors capable of expressing multiple genes. In this study we explored the feasibility and efficiency of expressing two or three transgenes in HIV-1 based lentiviral vector. Bicistronic and tricistronic self-inactivating lentiviral vectors were constructed employing the internal ribosomal entry site (IRES sequence of encephalomyocarditis virus (EMCV and/or foot-and-mouth disease virus (FMDV cleavage factor 2A. We employed enhanced green fluorescent protein (eGFP, O6-methylguanine-DNA-methyltransferase (MGMT, and homeobox transcription factor HOXB4 as model genes and their expression was detected by appropriate methods including fluorescence microscopy, flow cytometry, immunocytochemistry, biochemical assay, and western blotting. Results All the multigene vectors produced high titer virus and were able to simultaneously express two or three transgenes in transduced cells. However, the level of expression of individual transgenes varied depending on: the transgene itself; its position within the construct; the total number of transgenes expressed; the strategy used for multigene expression and the average copy number of pro-viral insertions. Notably, at limiting MOI, the expression of eGFP in a bicistronic vector based on 2A was ~4 times greater than that of an IRES based vector. Conclusion The small and efficient 2A sequence can be used alone or in combination with an IRES for the construction of multicistronic lentiviral vectors which can express encoded transgenes at functionally relevant levels in cells containing an average of one pro-viral insert.

  10. (Im)Perfect robustness and adaptation of metabolic networks subject to metabolic and gene-expression regulation: marrying control engineering with metabolic control analysis.

    Science.gov (United States)

    He, Fei; Fromion, Vincent; Westerhoff, Hans V

    2013-11-21

    Metabolic control analysis (MCA) and supply-demand theory have led to appreciable understanding of the systems properties of metabolic networks that are subject exclusively to metabolic regulation. Supply-demand theory has not yet considered gene-expression regulation explicitly whilst a variant of MCA, i.e. Hierarchical Control Analysis (HCA), has done so. Existing analyses based on control engineering approaches have not been very explicit about whether metabolic or gene-expression regulation would be involved, but designed different ways in which regulation could be organized, with the potential of causing adaptation to be perfect. This study integrates control engineering and classical MCA augmented with supply-demand theory and HCA. Because gene-expression regulation involves time integration, it is identified as a natural instantiation of the 'integral control' (or near integral control) known in control engineering. This study then focuses on robustness against and adaptation to perturbations of process activities in the network, which could result from environmental perturbations, mutations or slow noise. It is shown however that this type of 'integral control' should rarely be expected to lead to the 'perfect adaptation': although the gene-expression regulation increases the robustness of important metabolite concentrations, it rarely makes them infinitely robust. For perfect adaptation to occur, the protein degradation reactions should be zero order in the concentration of the protein, which may be rare biologically for cells growing steadily. A proposed new framework integrating the methodologies of control engineering and metabolic and hierarchical control analysis, improves the understanding of biological systems that are regulated both metabolically and by gene expression. In particular, the new approach enables one to address the issue whether the intracellular biochemical networks that have been and are being identified by genomics and systems

  11. A robust approach to identifying tissue-specific gene expression regulatory variants using personalized human induced pluripotent stem cells.

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    Je-Hyuk Lee

    2009-11-01

    Full Text Available Normal variation in gene expression due to regulatory polymorphisms is often masked by biological and experimental noise. In addition, some regulatory polymorphisms may become apparent only in specific tissues. We derived human induced pluripotent stem (iPS cells from adult skin primary fibroblasts and attempted to detect tissue-specific cis-regulatory variants using in vitro cell differentiation. We used padlock probes and high-throughput sequencing for digital RNA allelotyping and measured allele-specific gene expression in primary fibroblasts, lymphoblastoid cells, iPS cells, and their differentiated derivatives. We show that allele-specific expression is both cell type and genotype-dependent, but the majority of detectable allele-specific expression loci remains consistent despite large changes in the cell type or the experimental condition following iPS reprogramming, except on the X-chromosome. We show that our approach to mapping cis-regulatory variants reduces in vitro experimental noise and reveals additional tissue-specific variants using skin-derived human iPS cells.

  12. Development of a robust protocol for gene expression analysis using formalin-fixed, paraffin-embedded liver transplant biopsy specimens.

    Science.gov (United States)

    Thompson, Emily; Burt, Alastair D; Barker, Catriona E; Kirby, John A; Brain, John G

    2013-09-01

    Liver transplant biopsies are routinely archived following formalin fixation and paraffin embedding and may provide an additional source of diagnostic information following transcriptomic biomarker analysis. This study was designed to compare gene transcription between resting and stressed biliary cells in culture, these cells after fixation and embedding and archival liver transplant biopsy tissue. The transcription of p21/WAF1 and transforming growth factor (TGF)-β1 showed similar changes in the fresh and embedded liver cells. However, the expression of TGF-β2 was markedly different between the fresh and embedded samples, suggesting that fixation can produce sequence-specific artefacts. Sufficient quantities of pure RNA were recovered from all the liver transplant biopsies to allow complementary DNA production. Measurement of the transcription of all three genes showed variability between the cases. Although the results for individual transcripts should be interpreted with care, these data do suggest the feasibility of performing a larger biomarker discovery studies using archival tissue.

  13. Erythroid-Specific Expression of LIN28A Is Sufficient for Robust Gamma-Globin Gene and Protein Expression in Adult Erythroblasts.

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    Y Terry Lee

    Full Text Available Increasing fetal hemoglobin (HbF levels in adult humans remains an active area in hematologic research. Here we explored erythroid-specific LIN28A expression for its effect in regulating gamma-globin gene expression and HbF levels in cultured adult erythroblasts. For this purpose, lentiviral transduction vectors were produced with LIN28A expression driven by erythroid-specific gene promoter regions of the human KLF1 or SPTA1 genes. Transgene expression of LIN28A with a linked puromycin resistance marker was restricted to the erythroid lineage as demonstrated by selective survival of erythroid colonies (greater than 95% of all colonies. Erythroblast LIN28A over-expression (LIN28A-OE did not significantly affect proliferation or inhibit differentiation. Greater than 70% suppression of total let-7 microRNA levels was confirmed in LIN28A-OE cells. Increases in gamma-globin mRNA and protein expression with HbF levels reaching 30-40% were achieved. These data suggest that erythroblast targeting of LIN28A expression is sufficient for increasing fetal hemoglobin expression in adult human erythroblasts.

  14. Erythroid-Specific Expression of LIN28A Is Sufficient for Robust Gamma-Globin Gene and Protein Expression in Adult Erythroblasts.

    Science.gov (United States)

    Lee, Y Terry; de Vasconcellos, Jaira F; Byrnes, Colleen; Kaushal, Megha; Rabel, Antoinette; Tumburu, Laxminath; Allwardt, Joshua M; Miller, Jeffery L

    2015-01-01

    Increasing fetal hemoglobin (HbF) levels in adult humans remains an active area in hematologic research. Here we explored erythroid-specific LIN28A expression for its effect in regulating gamma-globin gene expression and HbF levels in cultured adult erythroblasts. For this purpose, lentiviral transduction vectors were produced with LIN28A expression driven by erythroid-specific gene promoter regions of the human KLF1 or SPTA1 genes. Transgene expression of LIN28A with a linked puromycin resistance marker was restricted to the erythroid lineage as demonstrated by selective survival of erythroid colonies (greater than 95% of all colonies). Erythroblast LIN28A over-expression (LIN28A-OE) did not significantly affect proliferation or inhibit differentiation. Greater than 70% suppression of total let-7 microRNA levels was confirmed in LIN28A-OE cells. Increases in gamma-globin mRNA and protein expression with HbF levels reaching 30-40% were achieved. These data suggest that erythroblast targeting of LIN28A expression is sufficient for increasing fetal hemoglobin expression in adult human erythroblasts.

  15. Robust facial expression recognition via compressive sensing.

    Science.gov (United States)

    Zhang, Shiqing; Zhao, Xiaoming; Lei, Bicheng

    2012-01-01

    Recently, compressive sensing (CS) has attracted increasing attention in the areas of signal processing, computer vision and pattern recognition. In this paper, a new method based on the CS theory is presented for robust facial expression recognition. The CS theory is used to construct a sparse representation classifier (SRC). The effectiveness and robustness of the SRC method is investigated on clean and occluded facial expression images. Three typical facial features, i.e., the raw pixels, Gabor wavelets representation and local binary patterns (LBP), are extracted to evaluate the performance of the SRC method. Compared with the nearest neighbor (NN), linear support vector machines (SVM) and the nearest subspace (NS), experimental results on the popular Cohn-Kanade facial expression database demonstrate that the SRC method obtains better performance and stronger robustness to corruption and occlusion on robust facial expression recognition tasks.

  16. Robust multi-tissue gene panel for cancer detection

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    Talantov Dmitri

    2010-06-01

    Full Text Available Abstract Background We have identified a set of genes whose relative mRNA expression levels in various solid tumors can be used to robustly distinguish cancer from matching normal tissue. Our current feature set consists of 113 gene probes for 104 unique genes, originally identified as differentially expressed in solid primary tumors in microarray data on Affymetrix HG-U133A platform in five tissue types: breast, colon, lung, prostate and ovary. For each dataset, we first identified a set of genes significantly differentially expressed in tumor vs. normal tissue at p-value = 0.05 using an experimentally derived error model. Our common cancer gene panel is the intersection of these sets of significantly dysregulated genes and can distinguish tumors from normal tissue on all these five tissue types. Methods Frozen tumor specimens were obtained from two commercial vendors Clinomics (Pittsfield, MA and Asterand (Detroit, MI. Biotinylated targets were prepared using published methods (Affymetrix, CA and hybridized to Affymetrix U133A GeneChips (Affymetrix, CA. Expression values for each gene were calculated using Affymetrix GeneChip analysis software MAS 5.0. We then used a software package called Genes@Work for differential expression discovery, and SVM light linear kernel for building classification models. Results We validate the predictability of this gene list on several publicly available data sets generated on the same platform. Of note, when analysing the lung cancer data set of Spira et al, using an SVM linear kernel classifier, our gene panel had 94.7% leave-one-out accuracy compared to 87.8% using the gene panel in the original paper. In addition, we performed high-throughput validation on the Dana Farber Cancer Institute GCOD database and several GEO datasets. Conclusions Our result showed the potential for this panel as a robust classification tool for multiple tumor types on the Affymetrix platform, as well as other whole genome arrays

  17. Mutational robustness of gene regulatory networks.

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    Aalt D J van Dijk

    Full Text Available Mutational robustness of gene regulatory networks refers to their ability to generate constant biological output upon mutations that change network structure. Such networks contain regulatory interactions (transcription factor-target gene interactions but often also protein-protein interactions between transcription factors. Using computational modeling, we study factors that influence robustness and we infer several network properties governing it. These include the type of mutation, i.e. whether a regulatory interaction or a protein-protein interaction is mutated, and in the case of mutation of a regulatory interaction, the sign of the interaction (activating vs. repressive. In addition, we analyze the effect of combinations of mutations and we compare networks containing monomeric with those containing dimeric transcription factors. Our results are consistent with available data on biological networks, for example based on evolutionary conservation of network features. As a novel and remarkable property, we predict that networks are more robust against mutations in monomer than in dimer transcription factors, a prediction for which analysis of conservation of DNA binding residues in monomeric vs. dimeric transcription factors provides indirect evidence.

  18. Combining multiple hypothesis testing and affinity propagation clustering leads to accurate, robust and sample size independent classification on gene expression data

    Directory of Open Access Journals (Sweden)

    Sakellariou Argiris

    2012-10-01

    Full Text Available Abstract Background A feature selection method in microarray gene expression data should be independent of platform, disease and dataset size. Our hypothesis is that among the statistically significant ranked genes in a gene list, there should be clusters of genes that share similar biological functions related to the investigated disease. Thus, instead of keeping N top ranked genes, it would be more appropriate to define and keep a number of gene cluster exemplars. Results We propose a hybrid FS method (mAP-KL, which combines multiple hypothesis testing and affinity propagation (AP-clustering algorithm along with the Krzanowski & Lai cluster quality index, to select a small yet informative subset of genes. We applied mAP-KL on real microarray data, as well as on simulated data, and compared its performance against 13 other feature selection approaches. Across a variety of diseases and number of samples, mAP-KL presents competitive classification results, particularly in neuromuscular diseases, where its overall AUC score was 0.91. Furthermore, mAP-KL generates concise yet biologically relevant and informative N-gene expression signatures, which can serve as a valuable tool for diagnostic and prognostic purposes, as well as a source of potential disease biomarkers in a broad range of diseases. Conclusions mAP-KL is a data-driven and classifier-independent hybrid feature selection method, which applies to any disease classification problem based on microarray data, regardless of the available samples. Combining multiple hypothesis testing and AP leads to subsets of genes, which classify unknown samples from both, small and large patient cohorts with high accuracy.

  19. No tradeoff between versatility and robustness in gene circuit motifs

    Science.gov (United States)

    Payne, Joshua L.

    2016-05-01

    Circuit motifs are small directed subgraphs that appear in real-world networks significantly more often than in randomized networks. In the Boolean model of gene circuits, most motifs are realized by multiple circuit genotypes. Each of a motif's constituent circuit genotypes may have one or more functions, which are embodied in the expression patterns the circuit forms in response to specific initial conditions. Recent enumeration of a space of nearly 17 million three-gene circuit genotypes revealed that all circuit motifs have more than one function, with the number of functions per motif ranging from 12 to nearly 30,000. This indicates that some motifs are more functionally versatile than others. However, the individual circuit genotypes that constitute each motif are less robust to mutation if they have many functions, hinting that functionally versatile motifs may be less robust to mutation than motifs with few functions. Here, I explore the relationship between versatility and robustness in circuit motifs, demonstrating that functionally versatile motifs are robust to mutation despite the inherent tradeoff between versatility and robustness at the level of an individual circuit genotype.

  20. A Bregman-proximal point algorithm for robust non-negative matrix factorization with possible missing values and outliers - application to gene expression analysis.

    Science.gov (United States)

    Chrétien, Stéphane; Guyeux, Christophe; Conesa, Bastien; Delage-Mouroux, Régis; Jouvenot, Michèle; Huetz, Philippe; Descôtes, Françoise

    2016-08-31

    Non-Negative Matrix factorization has become an essential tool for feature extraction in a wide spectrum of applications. In the present work, our objective is to extend the applicability of the method to the case of missing and/or corrupted data due to outliers. An essential property for missing data imputation and detection of outliers is that the uncorrupted data matrix is low rank, i.e. has only a small number of degrees of freedom. We devise a new version of the Bregman proximal idea which preserves nonnegativity and mix it with the Augmented Lagrangian approach for simultaneous reconstruction of the features of interest and detection of the outliers using a sparsity promoting ℓ 1 penality. An application to the analysis of gene expression data of patients with bladder cancer is finally proposed.

  1. Correcting for intra-experiment variation in Illumina BeadChip data is necessary to generate robust gene-expression profiles

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    van Hemert Jano I

    2010-02-01

    Full Text Available Abstract Background Microarray technology is a popular means of producing whole genome transcriptional profiles, however high cost and scarcity of mRNA has led many studies to be conducted based on the analysis of single samples. We exploit the design of the Illumina platform, specifically multiple arrays on each chip, to evaluate intra-experiment technical variation using repeated hybridisations of universal human reference RNA (UHRR and duplicate hybridisations of primary breast tumour samples from a clinical study. Results A clear batch-specific bias was detected in the measured expressions of both the UHRR and clinical samples. This bias was found to persist following standard microarray normalisation techniques. However, when mean-centering or empirical Bayes batch-correction methods (ComBat were applied to the data, inter-batch variation in the UHRR and clinical samples were greatly reduced. Correlation between replicate UHRR samples improved by two orders of magnitude following batch-correction using ComBat (ranging from 0.9833-0.9991 to 0.9997-0.9999 and increased the consistency of the gene-lists from the duplicate clinical samples, from 11.6% in quantile normalised data to 66.4% in batch-corrected data. The use of UHRR as an inter-batch calibrator provided a small additional benefit when used in conjunction with ComBat, further increasing the agreement between the two gene-lists, up to 74.1%. Conclusion In the interests of practicalities and cost, these results suggest that single samples can generate reliable data, but only after careful compensation for technical bias in the experiment. We recommend that investigators appreciate the propensity for such variation in the design stages of a microarray experiment and that the use of suitable correction methods become routine during the statistical analysis of the data.

  2. Robustness under functional constraint: the genetic network for temporal expression in Drosophila neurogenesis.

    Directory of Open Access Journals (Sweden)

    Akihiko Nakajima

    2010-04-01

    Full Text Available Precise temporal coordination of gene expression is crucial for many developmental processes. One central question in developmental biology is how such coordinated expression patterns are robustly controlled. During embryonic development of the Drosophila central nervous system, neural stem cells called neuroblasts express a group of genes in a definite order, which leads to the diversity of cell types. We produced all possible regulatory networks of these genes and examined their expression dynamics numerically. From the analysis, we identified requisite regulations and predicted an unknown factor to reproduce known expression profiles caused by loss-of-function or overexpression of the genes in vivo, as well as in the wild type. Following this, we evaluated the stability of the actual Drosophila network for sequential expression. This network shows the highest robustness against parameter variations and gene expression fluctuations among the possible networks that reproduce the expression profiles. We propose a regulatory module composed of three types of regulations that is responsible for precise sequential expression. This study suggests that the Drosophila network for sequential expression has evolved to generate the robust temporal expression for neuronal specification.

  3. 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...

  4. Effect of Duplicate Genes on Mouse Genetic Robustness: An Update

    Directory of Open Access Journals (Sweden)

    Zhixi Su

    2014-01-01

    Full Text Available In contrast to S. cerevisiae and C. elegans, analyses based on the current knockout (KO mouse phenotypes led to the conclusion that duplicate genes had almost no role in mouse genetic robustness. It has been suggested that the bias of mouse KO database toward ancient duplicates may possibly cause this knockout duplicate puzzle, that is, a very similar proportion of essential genes (PE between duplicate genes and singletons. In this paper, we conducted an extensive and careful analysis for the mouse KO phenotype data and corroborated a strong effect of duplicate genes on mouse genetics robustness. Moreover, the effect of duplicate genes on mouse genetic robustness is duplication-age dependent, which holds after ruling out the potential confounding effect from coding-sequence conservation, protein-protein connectivity, functional bias, or the bias of duplicates generated by whole genome duplication (WGD. Our findings suggest that two factors, the sampling bias toward ancient duplicates and very ancient duplicates with a proportion of essential genes higher than that of singletons, have caused the mouse knockout duplicate puzzle; meanwhile, the effect of genetic buffering may be correlated with sequence conservation as well as protein-protein interactivity.

  5. Gene set analysis for longitudinal gene expression data

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    Piepho Hans-Peter

    2011-07-01

    Full Text Available Abstract Background Gene set analysis (GSA has become a successful tool to interpret gene expression profiles in terms of biological functions, molecular pathways, or genomic locations. GSA performs statistical tests for independent microarray samples at the level of gene sets rather than individual genes. Nowadays, an increasing number of microarray studies are conducted to explore the dynamic changes of gene expression in a variety of species and biological scenarios. In these longitudinal studies, gene expression is repeatedly measured over time such that a GSA needs to take into account the within-gene correlations in addition to possible between-gene correlations. Results We provide a robust nonparametric approach to compare the expressions of longitudinally measured sets of genes under multiple treatments or experimental conditions. The limiting distributions of our statistics are derived when the number of genes goes to infinity while the number of replications can be small. When the number of genes in a gene set is small, we recommend permutation tests based on our nonparametric test statistics to achieve reliable type I error and better power while incorporating unknown correlations between and within-genes. Simulation results demonstrate that the proposed method has a greater power than other methods for various data distributions and heteroscedastic correlation structures. This method was used for an IL-2 stimulation study and significantly altered gene sets were identified. Conclusions The simulation study and the real data application showed that the proposed gene set analysis provides a promising tool for longitudinal microarray analysis. R scripts for simulating longitudinal data and calculating the nonparametric statistics are posted on the North Dakota INBRE website http://ndinbre.org/programs/bioinformatics.php. Raw microarray data is available in Gene Expression Omnibus (National Center for Biotechnology Information with

  6. A Unifying Mathematical Framework for Genetic Robustness, Environmental Robustness, Network Robustness and their Trade-offs on Phenotype Robustness in Biological Networks. Part III: Synthetic Gene Networks in Synthetic Biology

    Science.gov (United States)

    Chen, Bor-Sen; Lin, Ying-Po

    2013-01-01

    Robust stabilization and environmental disturbance attenuation are ubiquitous systematic properties that are observed in biological systems at many different levels. The underlying principles for robust stabilization and environmental disturbance attenuation are universal to both complex biological systems and sophisticated engineering systems. In many biological networks, network robustness should be large enough to confer: intrinsic robustness for tolerating intrinsic parameter fluctuations; genetic robustness for buffering genetic variations; and environmental robustness for resisting environmental disturbances. Network robustness is needed so phenotype stability of biological network can be maintained, guaranteeing phenotype robustness. Synthetic biology is foreseen to have important applications in biotechnology and medicine; it is expected to contribute significantly to a better understanding of functioning of complex biological systems. This paper presents a unifying mathematical framework for investigating the principles of both robust stabilization and environmental disturbance attenuation for synthetic gene networks in synthetic biology. Further, from the unifying mathematical framework, we found that the phenotype robustness criterion for synthetic gene networks is the following: if intrinsic robustness + genetic robustness + environmental robustness ≦ network robustness, then the phenotype robustness can be maintained in spite of intrinsic parameter fluctuations, genetic variations, and environmental disturbances. Therefore, the trade-offs between intrinsic robustness, genetic robustness, environmental robustness, and network robustness in synthetic biology can also be investigated through corresponding phenotype robustness criteria from the systematic point of view. Finally, a robust synthetic design that involves network evolution algorithms with desired behavior under intrinsic parameter fluctuations, genetic variations, and environmental

  7. 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; WANG Jinlian

    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.

  8. Science Letters: A robust statistical procedure to discover expression biomarkers using microarray genomic expression data

    Institute of Scientific and Technical Information of China (English)

    ZOU Yang-yun; YANG Jian; ZHU Jun

    2006-01-01

    Microarray has become increasingly popular biotechnology in biological and medical researches, and has been widely applied in classification of treatment subtypes using expression patterns of biomarkers. We developed a statistical procedure to identify expression biomarkers for treatment subtype classification by constructing an F-statistic based on Henderson method Ⅲ.Monte Carlo simulations were conducted to examine the robustness and efficiency of the proposed method. Simulation results showed that our method could provide satisfying power of identifying differentially expressed genes (DEGs) with false discovery rate (FDR) lower than the given type Ⅰ error rate. In addition, we analyzed a leukemia dataset collected from 38 leukemia patients with 27 samples diagnosed as acute lymphoblastic leukemia (ALL) and 11 samples as acute myeloid leukemia (AML). We compared our results with those from the methods of significance analysis of microarray (SAM) and microarray analysis of variance (MAANOVA). Among these three methods, only expression biomarkers identified by our method can precisely identify the three human acute leukemia subtypes.

  9. Reverse engineering gene networks using singular value decomposition and robust regression

    Science.gov (United States)

    Yeung, M. K. Stephen; Tegnér, Jesper; Collins, James J.

    2002-01-01

    We propose a scheme to reverse-engineer gene networks on a genome-wide scale using a relatively small amount of gene expression data from microarray experiments. Our method is based on the empirical observation that such networks are typically large and sparse. It uses singular value decomposition to construct a family of candidate solutions and then uses robust regression to identify the solution with the smallest number of connections as the most likely solution. Our algorithm has O(log N) sampling complexity and O(N4) computational complexity. We test and validate our approach in a series of in numero experiments on model gene networks. PMID:11983907

  10. Engineering robust and tunable spatial structures with synthetic gene circuits.

    Science.gov (United States)

    Kong, Wentao; Blanchard, Andrew E; Liao, Chen; Lu, Ting

    2017-01-25

    Controllable spatial patterning is a major goal for the engineering of biological systems. Recently, synthetic gene circuits have become promising tools to achieve the goal; however, they need to possess both functional robustness and tunability in order to facilitate future applications. Here we show that, by harnessing the dual signaling and antibiotic features of nisin, simple synthetic circuits can direct Lactococcus lactis populations to form programmed spatial band-pass structures that do not require fine-tuning and are robust against environmental and cellular context perturbations. Although robust, the patterns are highly tunable, with their band widths specified by the external nisin gradient and cellular nisin immunity. Additionally, the circuits can direct cells to consistently generate designed patterns, even when the gradient is driven by structured nisin-producing bacteria and the patterning cells are composed of multiple species. A mathematical model successfully reproduces all of the observed patterns. Furthermore, the circuits allow us to establish predictable structures of synthetic communities and controllable arrays of cellular stripes and spots in space. This study offers new synthetic biology tools to program spatial structures. It also demonstrates that a deep mining of natural functionalities of living systems is a valuable route to build circuit robustness and tunability.

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

    Directory of Open Access Journals (Sweden)

    Hicks Leanne

    2007-06-01

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

  12. Robustness of mining the differentially expressed functional classes based on gene expression profiles%利用基因表达谱挖掘差异表达功能类的稳健性

    Institute of Scientific and Technical Information of China (English)

    颜兴起; 郭政; 李霞; 王栋; 屠康

    2006-01-01

    Gene Ontology广泛地应用于基于基因芯片数据的差异表达功能类分析.基因芯片技术存在检测缺失与检测误差等问题.本文探讨上述这二个因素对利用基因表达谱挖掘Gene Ontology中差异表达功能类的影响.结果显示,差异表达功能类对于检测缺失与检测误差干扰等有一定的稳健性.

  13. Robustness

    DEFF Research Database (Denmark)

    Sørensen, John Dalsgaard; Rizzuto, Enrico; Narasimhan, Harikrishna

    2012-01-01

    More frequent use of advanced types of structures with limited redundancy and serious consequences in case of failure combined with increased requirements to efficiency in design and execution followed by increased risk of human errors has made the need of requirements to robustness of structures......, a theoretical and risk-based framework is presented which facilitates the quantification of robustness, and thus supports the formulation of pre-normative guidelines....

  14. The flow of gene expression.

    Science.gov (United States)

    Misteli, Tom

    2004-03-01

    Gene expression is a highly interconnected multistep process. A recent meeting in Iguazu Falls, Argentina, highlighted the need to uncover both the molecular details of each single step as well as the mechanisms of coordination among processes in order to fully understand the expression of genes.

  15. Ascidian gene-expression profiles

    OpenAIRE

    Jeffery, William R.

    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. Gene expression profiling of solitary fibrous tumors.

    Directory of Open Access Journals (Sweden)

    François Bertucci

    Full Text Available BACKGROUND: Solitary fibrous tumors (SFTs are rare spindle-cell tumors. Their cell-of-origin and molecular basis are poorly known. They raise several clinical problems. Differential diagnosis may be difficult, prognosis is poorly apprehended by histoclinical features, and no effective therapy exists for advanced stages. METHODS: We profiled 16 SFT samples using whole-genome DNA microarrays and analyzed their expression profiles with publicly available profiles of 36 additional SFTs and 212 soft tissue sarcomas (STSs. Immunohistochemistry was applied to validate the expression of some discriminating genes. RESULTS: SFTs displayed whole-genome expression profiles more homogeneous and different from STSs, but closer to genetically-simple than genetically-complex STSs. The SFTs/STSs comparison identified a high percentage (∼30% of genes as differentially expressed, most of them without any DNA copy number alteration. One of the genes most overexpressed in SFTs encoded the ALDH1 stem cell marker. Several upregulated genes and associated ontologies were also related to progenitor/stem cells. SFTs also overexpressed genes encoding therapeutic targets such as kinases (EGFR, ERBB2, FGFR1, JAK2, histone deacetylases, or retinoic acid receptors. Their overexpression was found in all SFTs, regardless the anatomical location. Finally, we identified a 31-gene signature associated with the mitotic count, containing many genes related to cell cycle/mitosis, including AURKA. CONCLUSION: We established a robust repertoire of genes differentially expressed in SFTs. Certain overexpressed genes could provide new diagnostic (ALDH1A1, prognostic (AURKA and/or therapeutic targets.

  17. Order Under Uncertainty: Robust Differential Expression Analysis Using Probabilistic Models for Pseudotime Inference

    Science.gov (United States)

    Campbell, Kieran R.

    2016-01-01

    Single cell gene expression profiling can be used to quantify transcriptional dynamics in temporal processes, such as cell differentiation, using computational methods to label each cell with a ‘pseudotime’ where true time series experimentation is too difficult to perform. However, owing to the high variability in gene expression between individual cells, there is an inherent uncertainty in the precise temporal ordering of the cells. Pre-existing methods for pseudotime estimation have predominantly given point estimates precluding a rigorous analysis of the implications of uncertainty. We use probabilistic modelling techniques to quantify pseudotime uncertainty and propagate this into downstream differential expression analysis. We demonstrate that reliance on a point estimate of pseudotime can lead to inflated false discovery rates and that probabilistic approaches provide greater robustness and measures of the temporal resolution that can be obtained from pseudotime inference. PMID:27870852

  18. Robust expression of a bioactive mammalian protein in Chlamydomonas chloroplast

    Energy Technology Data Exchange (ETDEWEB)

    Mayfield, Stephen P

    2015-01-13

    Methods and compositions are disclosed to engineer chloroplast comprising heterologous mammalian genes via a direct replacement of chloroplast Photosystem II (PSII) reaction center protein coding regions to achieve expression of recombinant protein above 5% of total protein. When algae is used, algal expressed protein is produced predominantly as a soluble protein where the functional activity of the peptide is intact. As the host algae is edible, production of biologics in this organism for oral delivery of proteins/peptides, especially gut active proteins, without purification is disclosed.

  19. An integer optimization algorithm for robust identification of non-linear gene regulatory networks

    Directory of Open Access Journals (Sweden)

    Chemmangattuvalappil Nishanth

    2012-09-01

    Full Text Available Abstract Background Reverse engineering gene networks and identifying regulatory interactions are integral to understanding cellular decision making processes. Advancement in high throughput experimental techniques has initiated innovative data driven analysis of gene regulatory networks. However, inherent noise associated with biological systems requires numerous experimental replicates for reliable conclusions. Furthermore, evidence of robust algorithms directly exploiting basic biological traits are few. Such algorithms are expected to be efficient in their performance and robust in their prediction. Results We have developed a network identification algorithm to accurately infer both the topology and strength of regulatory interactions from time series gene expression data in the presence of significant experimental noise and non-linear behavior. In this novel formulism, we have addressed data variability in biological systems by integrating network identification with the bootstrap resampling technique, hence predicting robust interactions from limited experimental replicates subjected to noise. Furthermore, we have incorporated non-linearity in gene dynamics using the S-system formulation. The basic network identification formulation exploits the trait of sparsity of biological interactions. Towards that, the identification algorithm is formulated as an integer-programming problem by introducing binary variables for each network component. The objective function is targeted to minimize the network connections subjected to the constraint of maximal agreement between the experimental and predicted gene dynamics. The developed algorithm is validated using both in silico and experimental data-sets. These studies show that the algorithm can accurately predict the topology and connection strength of the in silico networks, as quantified by high precision and recall, and small discrepancy between the actual and predicted kinetic parameters

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

    Science.gov (United States)

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

    2014-06-01

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

  1. Human Lacrimal Gland Gene Expression

    Science.gov (United States)

    Aakalu, Vinay Kumar; Parameswaran, Sowmya; Maienschein-Cline, Mark; Bahroos, Neil; Shah, Dhara; Ali, Marwan; Krishnakumar, Subramanian

    2017-01-01

    Background The study of human lacrimal gland biology and development is limited. Lacrimal gland tissue is damaged or poorly functional in a number of disease states including dry eye disease. Development of cell based therapies for lacrimal gland diseases requires a better understanding of the gene expression and signaling pathways in lacrimal gland. Differential gene expression analysis between lacrimal gland and other embryologically similar tissues may be helpful in furthering our understanding of lacrimal gland development. Methods We performed global gene expression analysis of human lacrimal gland tissue using Affymetrix ® gene expression arrays. Primary data from our laboratory was compared with datasets available in the NLM GEO database for other surface ectodermal tissues including salivary gland, skin, conjunctiva and corneal epithelium. Results The analysis revealed statistically significant difference in the gene expression of lacrimal gland tissue compared to other ectodermal tissues. The lacrimal gland specific, cell surface secretory protein encoding genes and critical signaling pathways which distinguish lacrimal gland from other ectodermal tissues are described. Conclusions Differential gene expression in human lacrimal gland compared with other ectodermal tissue types revealed interesting patterns which may serve as the basis for future studies in directed differentiation among other areas. PMID:28081151

  2. Semi-supervised consensus clustering for gene expression data analysis

    OpenAIRE

    Wang, Yunli; Pan, Youlian

    2014-01-01

    Background Simple clustering methods such as hierarchical clustering and k-means are widely used for gene expression data analysis; but they are unable to deal with noise and high dimensionality associated with the microarray gene expression data. Consensus clustering appears to improve the robustness and quality of clustering results. Incorporating prior knowledge in clustering process (semi-supervised clustering) has been shown to improve the consistency between the data partitioning and do...

  3. 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 p...... with a 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.......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...... pool) of total RNA from left-sided sporadic colorectal carcinomas. We compared normal tissue to carcinoma tissue from Dukes' stages A-D (noninvasive to distant metastasis) and identified 908 known genes and 4,155 ESTs that changed remarkably from normal to tumor tissue. Based on intensive filtering 226...

  4. A robust data-driven approach for gene ontology annotation.

    Science.gov (United States)

    Li, Yanpeng; Yu, Hong

    2014-01-01

    Gene ontology (GO) and GO annotation are important resources for biological information management and knowledge discovery, but the speed of manual annotation became a major bottleneck of database curation. BioCreative IV GO annotation task aims to evaluate the performance of system that automatically assigns GO terms to genes based on the narrative sentences in biomedical literature. This article presents our work in this task as well as the experimental results after the competition. For the evidence sentence extraction subtask, we built a binary classifier to identify evidence sentences using reference distance estimator (RDE), a recently proposed semi-supervised learning method that learns new features from around 10 million unlabeled sentences, achieving an F1 of 19.3% in exact match and 32.5% in relaxed match. In the post-submission experiment, we obtained 22.1% and 35.7% F1 performance by incorporating bigram features in RDE learning. In both development and test sets, RDE-based method achieved over 20% relative improvement on F1 and AUC performance against classical supervised learning methods, e.g. support vector machine and logistic regression. For the GO term prediction subtask, we developed an information retrieval-based method to retrieve the GO term most relevant to each evidence sentence using a ranking function that combined cosine similarity and the frequency of GO terms in documents, and a filtering method based on high-level GO classes. The best performance of our submitted runs was 7.8% F1 and 22.2% hierarchy F1. We found that the incorporation of frequency information and hierarchy filtering substantially improved the performance. In the post-submission evaluation, we obtained a 10.6% F1 using a simpler setting. Overall, the experimental analysis showed our approaches were robust in both the two tasks.

  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. Zipf's Law in Gene Expression

    Science.gov (United States)

    Furusawa, Chikara; Kaneko, Kunihiko

    2003-02-01

    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 intracellular 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.

  7. 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...... an analytical approach to examine the suitability of correction methods by considering the inter-treatment bias as well as the inter-replicate variance, which allows use of the best correction method with minimum residual bias. Analyses of RNA sequencing and microarray data showed that the efficiencies...

  8. Homeobox gene expression in Brachiopoda

    DEFF Research Database (Denmark)

    Altenburger, Andreas; Martinez, Pedro; Wanninger, Andreas

    2011-01-01

    The molecular control that underlies brachiopod ontogeny is largely unknown. In order to contribute to this issue we analyzed the expression pattern of two homeobox containing genes, Not and Cdx, during development of the rhynchonelliform (i.e., articulate) brachiopod Terebratalia transversa. Not...

  9. 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.

  10. Neighboring Genes Show Correlated Evolution in Gene Expression

    Science.gov (United States)

    Ghanbarian, Avazeh T.; Hurst, Laurence D.

    2015-01-01

    When considering the evolution of a gene’s expression profile, we commonly assume that this is unaffected by its genomic neighborhood. This is, however, in contrast to what we know about the lack of autonomy between neighboring genes in gene expression profiles in extant taxa. Indeed, in all eukaryotic genomes genes of similar expression-profile tend to cluster, reflecting chromatin level dynamics. Does it follow that if a gene increases expression in a particular lineage then the genomic neighbors will also increase in their expression or is gene expression evolution autonomous? To address this here we consider evolution of human gene expression since the human-chimp common ancestor, allowing for both variation in estimation of current expression level and error in Bayesian estimation of the ancestral state. We find that in all tissues and both sexes, the change in gene expression of a focal gene on average predicts the change in gene expression of neighbors. The effect is highly pronounced in the immediate vicinity (genes increasing their expression in humans tend to avoid nuclear lamina domains and be enriched for the gene activator 5-hydroxymethylcytosine, we conclude that, most probably owing to chromatin level control of gene expression, a change in gene expression of one gene likely affects the expression evolution of neighbors, what we term expression piggybacking, an analog of hitchhiking. PMID:25743543

  11. Conserved Cis-Regulatory Modules Control Robustness in Msx1 Expression at Single-Cell Resolution

    Science.gov (United States)

    Vance, Keith W.; Woodcock, Dan J.; Reid, John E.; Bretschneider, Till; Ott, Sascha; Koentges, Georgy

    2015-01-01

    The process of transcription is highly stochastic leading to cell-to-cell variations and noise in gene expression levels. However, key essential genes have to be precisely expressed at the correct amount and time to ensure proper cellular development and function. Studies in yeast and bacterial systems have shown that gene expression noise decreases as mean expression levels increase, a relationship that is controlled by promoter DNA sequence. However, the function of distal cis-regulatory modules (CRMs), an evolutionary novelty of metazoans, in controlling transcriptional robustness and variability is poorly understood. In this study, we used live cell imaging of transfected reporters combined with a mathematical modelling and statistical inference scheme to quantify the function of conserved Msx1 CRMs and promoters in modulating single-cell real-time transcription rates in C2C12 mouse myoblasts. The results show that the mean expression–noise relationship is solely promoter controlled for this key pluripotency regulator. In addition, we demonstrate that CRMs modulate single-cell basal promoter rate distributions in a graded manner across a population of cells. This extends the rheostatic model of CRM action to provide a more detailed understanding of CRM function at single-cell resolution. We also identify a novel CRM transcriptional filter function that acts to reduce intracellular variability in transcription rates and show that this can be phylogenetically separable from rate modulating CRM activities. These results are important for understanding how the expression of key vertebrate developmental transcription factors is precisely controlled both within and between individual cells. PMID:26342140

  12. 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.

  13. 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 ...

  14. Detecting robust gene signature through integrated analysis of multiple types of high-throughput data in liver cancer

    Institute of Scientific and Technical Information of China (English)

    Xin-yu ZHANG; Tian-tian LI; Xiang-jun LIU

    2007-01-01

    Aim: To investigate the robust gene signature in liver cancer, we applied an integrated approach to perform a joint analysis of a highly diverse collection of liver cancer genome-wide datasets, including genomic alterations and transcrip- tion profiles. Methods: 1-class Significance Analysis of Microarrays coupled with ranking score method were used to identify the robust gene signature in liver tumor tissue. Results: In total, 1 625 051 gene expression measurements from 16 public microarrays, 2 pairs of serial analyses of gene expression experiments, and 252 loss of heterozygosity reports obtained from 568 publications were used in this integrated study. The resulting robust gene signatures included 90 genes, which may be of great importance to liver cancer research. A system assessment analysis revealed that our integrative method had an accuracy of 92% and a correlation coefficient value of 0.88. Conclusion: The system assessment results indicated that our method had the ability of integrating the datasets from various types of sources, and eliciting more accurate results, as can be very useful in the study of liver cancer.

  15. Control of alphavirus-based gene expression using engineered riboswitches.

    Science.gov (United States)

    Bell, Christie L; Yu, Dong; Smolke, Christina D; Geall, Andrew J; Beard, Clayton W; Mason, Peter W

    2015-09-01

    Alphavirus-based replicons are a promising nucleic acid vaccine platform characterized by robust gene expression and immune responses. To further explore their use in vaccination, replicons were engineered to allow conditional control over their gene expression. Riboswitches, comprising a ribozyme actuator and RNA aptamer sensor, were engineered into the replicon 3' UTR. Binding of ligand to aptamer modulates ribozyme activity and, therefore, gene expression. Expression from DNA-launched and VRP-packaged replicons containing riboswitches was successfully regulated, achieving a 47-fold change in expression and modulation of the resulting type I interferon response. Moreover, we developed a novel control architecture where riboswitches were integrated into the 3' and 5' UTR of the subgenomic RNA region of the TC-83 virus, leading to an 1160-fold regulation of viral replication. Our studies demonstrate that the use of riboswitches for control of RNA replicon expression and viral replication holds promise for development of novel and safer vaccination strategies.

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

    Science.gov (United States)

    Kang, Suyeon; Song, Jongwoo

    2017-09-02

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

  17. Robust Inference of Cell-to-Cell Expression Variations from Single- and K-Cell Profiling.

    Directory of Open Access Journals (Sweden)

    Manikandan Narayanan

    2016-07-01

    Full Text Available Quantifying heterogeneity in gene expression among single cells can reveal information inaccessible to cell-population averaged measurements. However, the expression level of many genes in single cells fall below the detection limit of even the most sensitive technologies currently available. One proposed approach to overcome this challenge is to measure random pools of k cells (e.g., 10 to increase sensitivity, followed by computational "deconvolution" of cellular heterogeneity parameters (CHPs, such as the biological variance of single-cell expression levels. Existing approaches infer CHPs using either single-cell or k-cell data alone, and typically within a single population of cells. However, integrating both single- and k-cell data may reap additional benefits, and quantifying differences in CHPs across cell populations or conditions could reveal novel biological information. Here we present a Bayesian approach that can utilize single-cell, k-cell, or both simultaneously to infer CHPs within a single condition or their differences across two conditions. Using simulated as well as experimentally generated single- and k-cell data, we found situations where each data type would offer advantages, but using both together can improve precision and better reconcile CHP information contained in single- and k-cell data. We illustrate the utility of our approach by applying it to jointly generated single- and k-cell data to reveal CHP differences in several key inflammatory genes between resting and inflammatory cytokine-activated human macrophages, delineating differences in the distribution of 'ON' versus 'OFF' cells and in continuous variation of expression level among cells. Our approach thus offers a practical and robust framework to assess and compare cellular heterogeneity within and across biological conditions using modern multiplexed technologies.

  18. Classification with binary gene expressions

    OpenAIRE

    Tuna, Salih; Niranjan, Mahesan

    2009-01-01

    Microarray gene expression measurements are reported, used and archived usually to high numerical precision. However, properties of mRNA molecules, such as their low stability and availability in small copy numbers, and the fact that measurements correspond to a population of cells, rather than a single cell, makes high precision meaningless. Recent work shows that reducing measurement precision leads to very little loss of information, right down to binary levels. In this paper we show how p...

  19. 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

  20. Robustness and state-space structure of Boolean gene regulatory models.

    Science.gov (United States)

    Willadsen, Kai; Wiles, Janet

    2007-12-21

    Robustness to perturbation is an important characteristic of genetic regulatory systems, but the relationship between robustness and model dynamics has not been clearly quantified. We propose a method for quantifying both robustness and dynamics in terms of state-space structures, for Boolean models of genetic regulatory systems. By investigating existing models of the Drosophila melanogaster segment polarity network and the Saccharomyces cerevisiae cell-cycle network, we show that the structure of attractor basins can yield insight into the underlying decision making required of the system, and also the way in which the system maximises its robustness. In particular, gene networks implementing decisions based on a few genes have simple state-space structures, and their attractors are robust by virtue of their simplicity. Gene networks with decisions that involve many interacting genes have correspondingly more complicated state-space structures, and robustness cannot be achieved through the structure of the attractor basins, but is achieved by larger attractor basins that dominate the state space. These different types of robustness are demonstrated by the two models: the D. melanogaster segment polarity network is robust due to simple attractor basins that implement decisions based on spatial signals; the S. cerevisiae cell-cycle network has a complicated state-space structure, and is robust only due to a giant attractor basin that dominates the state space.

  1. Gene expression throughout a vertebrate's embryogenesis

    Directory of Open Access Journals (Sweden)

    Hinton David E

    2011-02-01

    Full Text Available Abstract Background Describing the patterns of gene expression during embryonic development has broadened our understanding of the processes and patterns that define morphogenesis. Yet gene expression patterns have not been described throughout vertebrate embryogenesis. This study presents statistical analyses of gene expression during all 40 developmental stages in the teleost Fundulus heteroclitus using four biological replicates per stage. Results Patterns of gene expression for 7,000 genes appear to be important as they recapitulate developmental timing. Among the 45% of genes with significant expression differences between pairs of temporally adjacent stages, significant differences in gene expression vary from as few as five to more than 660. Five adjacent stages have disproportionately more significant changes in gene expression (> 200 genes relative to other stages: four to eight and eight to sixteen cell stages, onset of circulation, pre and post-hatch, and during complete yolk absorption. The fewest differences among adjacent stages occur during gastrulation. Yet, at stage 16, (pre-mid-gastrulation the largest number of genes has peak expression. This stage has an over representation of genes in oxidative respiration and protein expression (ribosomes, translational genes and proteases. Unexpectedly, among all ribosomal genes, both strong positive and negative correlations occur. Similar correlated patterns of expression occur among all significant genes. Conclusions These data provide statistical support for the temporal dynamics of developmental gene expression during all stages of vertebrate development.

  2. A simple and robust vector-based shRNA expression system used for RNA interference.

    Directory of Open Access Journals (Sweden)

    Xue-jun Wang

    Full Text Available BACKGROUND: RNA interference (RNAi mediated by small interfering RNAs (siRNAs or short hairpin RNAs (shRNAs has become a powerful genetic tool for conducting functional studies. Previously, vector-based shRNA-expression strategies capable of inducing RNAi in viable cells have been developed, however, these vector systems have some disadvantages, either because they were error-prone or cost prohibitive. RESULTS: In this report we described the development of a simple, robust shRNA expression system utilizing 1 long oligonucleotide or 2 short oligonucleotides for half the cost of conventional shRNA construction methods and with a >95% cloning success rate. The shRNA loop sequence and stem structure were also compared and carefully selected for better RNAi efficiency. Furthermore, an easier strategy was developed based on isocaudomers which permit rapid combination of the most efficient promoter-shRNA cassettes. Finally, using this method, the conservative target sites for hepatitis B virus (HBV knockdown were systemically screened and HBV antigen expression shown to be successfully suppressed in the presence of connected multiple shRNAs both in vitro and in vivo. CONCLUSION: This novel design describes an inexpensive and effective way to clone and express single or multiple shRNAs from the same vector with the capacity for potent and effective silencing of target genes.

  3. A toolkit and robust pipeline for the generation of fosmid-based reporter genes in C. elegans.

    Directory of Open Access Journals (Sweden)

    Baris Tursun

    Full Text Available Engineering fluorescent proteins into large genomic clones, contained within BACs or fosmid vectors, is a tool to visualize and study spatiotemporal gene expression patterns in transgenic animals. Because these reporters cover large genomic regions, they most likely capture all cis-regulatory information and can therefore be expected to recapitulate all aspects of endogenous gene expression. Inserting tags at the target gene locus contained within genomic clones by homologous recombination ("recombineering" represents the most straightforward method to generate these reporters. In this methodology paper, we describe a simple and robust pipeline for recombineering of fosmids, which we apply to generate reporter constructs in the nematode C. elegans, whose genome is almost entirely covered in an available fosmid library. We have generated a toolkit that allows for insertion of fluorescent proteins (GFP, YFP, CFP, VENUS, mCherry and affinity tags at specific target sites within fosmid clones in a virtually seamless manner. Our new pipeline is less complex and, in our hands, works more robustly than previously described recombineering strategies to generate reporter fusions for C. elegans expression studies. Furthermore, our toolkit provides a novel recombineering cassette which inserts a SL2-spliced intercistronic region between the gene of interest and the fluorescent protein, thus creating a reporter controlled by all 5' and 3' cis-acting regulatory elements of the examined gene without the direct translational fusion between the two. With this configuration, the onset of expression and tissue specificity of secreted, sub-cellular compartmentalized or short-lived gene products can be easily detected. We describe other applications of fosmid recombineering as well. The simplicity, speed and robustness of the recombineering pipeline described here should prompt the routine use of this strategy for expression studies in C. elegans.

  4. On the Interplay between Entropy and Robustness of Gene Regulatory Networks

    Directory of Open Access Journals (Sweden)

    Bor-Sen Chen

    2010-05-01

    Full Text Available The interplay between entropy and robustness of gene network is a core mechanism of systems biology. The entropy is a measure of randomness or disorder of a physical system due to random parameter fluctuation and environmental noises in gene regulatory networks. The robustness of a gene regulatory network, which can be measured as the ability to tolerate the random parameter fluctuation and to attenuate the effect of environmental noise, will be discussed from the robust H∞ stabilization and filtering perspective. In this review, we will also discuss their balancing roles in evolution and potential applications in systems and synthetic biology.

  5. Antisense expression increases gene expression variability and locus interdependency

    OpenAIRE

    Xu, Zhenyu; Wei, Wu; Gagneur, Julien; Clauder-Münster, Sandra; Smolik, Miłosz; Huber, Wolfgang; Steinmetz, Lars M.

    2011-01-01

    Genome-wide transcription profiling has revealed extensive expression of non-coding RNAs antisense to genes, yet their functions, if any, remain to be understood. In this study, we perform a systematic analysis of sense–antisense expression in response to genetic and environmental changes in yeast. We find that antisense expression is associated with genes of larger expression variability. This is characterized by more ‘switching off' at low levels of expression for genes with antisense compa...

  6. Super-paramagnetic clustering of yeast gene expression profiles

    CERN Document Server

    Getz, G; Domany, E; Zhang, M Q

    2000-01-01

    High-density DNA arrays, used to monitor gene expression at a genomic scale, have produced vast amounts of information which require the development of efficient computational methods to analyze them. The important first step is to extract the fundamental patterns of gene expression inherent in the data. This paper describes the application of a novel clustering algorithm, Super-Paramagnetic Clustering (SPC) to analysis of gene expression profiles that were generated recently during a study of the yeast cell cycle. SPC was used to organize genes into biologically relevant clusters that are suggestive for their co-regulation. Some of the advantages of SPC are its robustness against noise and initialization, a clear signature of cluster formation and splitting, and an unsupervised self-organized determination of the number of clusters at each resolution. Our analysis revealed interesting correlated behavior of several groups of genes which has not been previously identified.

  7. Super-paramagnetic clustering of yeast gene expression profiles

    Science.gov (United States)

    Getz, G.; Levine, E.; Domany, E.; Zhang, M. Q.

    2000-04-01

    High-density DNA arrays, used to monitor gene expression at a genomic scale, have produced vast amounts of information which require the development of efficient computational methods to analyze them. The important first step is to extract the fundamental patterns of gene expression inherent in the data. This paper describes the application of a novel clustering algorithm, super-paramagnetic clustering (SPC) to analysis of gene expression profiles that were generated recently during a study of the yeast cell cycle. SPC was used to organize genes into biologically relevant clusters that are suggestive for their co-regulation. Some of the advantages of SPC are its robustness against noise and initialization, a clear signature of cluster formation and splitting, and an unsupervised self-organized determination of the number of clusters at each resolution. Our analysis revealed interesting correlated behavior of several groups of genes which has not been previously identified.

  8. 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 components, we observed that the residual expression levels (in 'functional genomic mRNA' profiling) correlated strongly with copy number. DNA copy number correlated positively with expression levels for 99% of all abundantly expressed human genes, indicating global gene dosage sensitivity. By applying...

  9. Noise in eukaryotic gene expression

    Science.gov (United States)

    Blake, William J.; KÆrn, Mads; Cantor, Charles R.; Collins, J. J.

    2003-04-01

    Transcription in eukaryotic cells has been described as quantal, with pulses of messenger RNA produced in a probabilistic manner. This description reflects the inherently stochastic nature of gene expression, known to be a major factor in the heterogeneous response of individual cells within a clonal population to an inducing stimulus. Here we show in Saccharomyces cerevisiae that stochasticity (noise) arising from transcription contributes significantly to the level of heterogeneity within a eukaryotic clonal population, in contrast to observations in prokaryotes, and that such noise can be modulated at the translational level. We use a stochastic model of transcription initiation specific to eukaryotes to show that pulsatile mRNA production, through reinitiation, is crucial for the dependence of noise on transcriptional efficiency, highlighting a key difference between eukaryotic and prokaryotic sources of noise. Furthermore, we explore the propagation of noise in a gene cascade network and demonstrate experimentally that increased noise in the transcription of a regulatory protein leads to increased cell-cell variability in the target gene output, resulting in prolonged bistable expression states. This result has implications for the role of noise in phenotypic variation and cellular differentiation.

  10. Identification of four soybean reference genes for gene expression normalization

    Science.gov (United States)

    Gene expression analysis requires the use of reference genes stably expressed independently of specific tissues or environmental conditions. Housekeeping genes (e.g., actin, tubulin, ribosomal, polyubiquitin and elongation factor 1-alpha) are commonly used as reference genes with the assumption tha...

  11. SIBER: systematic identification of bimodally expressed genes using RNAseq data.

    Science.gov (United States)

    Tong, Pan; Chen, Yong; Su, Xiao; Coombes, Kevin R

    2013-03-01

    Identification of bimodally expressed genes is an important task, as genes with bimodal expression play important roles in cell differentiation, signalling and disease progression. Several useful algorithms have been developed to identify bimodal genes from microarray data. Currently, no method can deal with data from next-generation sequencing, which is emerging as a replacement technology for microarrays. We present SIBER (systematic identification of bimodally expressed genes using RNAseq data) for effectively identifying bimodally expressed genes from next-generation RNAseq data. We evaluate several candidate methods for modelling RNAseq count data and compare their performance in identifying bimodal genes through both simulation and real data analysis. We show that the lognormal mixture model performs best in terms of power and robustness under various scenarios. We also compare our method with alternative approaches, including profile analysis using clustering and kurtosis (PACK) and cancer outlier profile analysis (COPA). Our method is robust, powerful, invariant to shifting and scaling, has no blind spots and has a sample-size-free interpretation. The R package SIBER is available at the website http://bioinformatics.mdanderson.org/main/OOMPA:Overview.

  12. MRI of Transgene Expression: Correlation to Therapeutic Gene Expression

    Directory of Open Access Journals (Sweden)

    Tomotsugu Ichikawa

    2002-01-01

    Full Text Available Magnetic resonance imaging (MRI can provide highresolution 3D maps of structural and functional information, yet its use of mapping in vivo gene expression has only recently been explored. A potential application for this technology is to noninvasively image transgene expression. The current study explores the latter using a nonregulatable internalizing engineered transferrin receptor (ETR whose expression can be probed for with a superparamagnetic Tf-CLIO probe. Using an HSV-based amplicon vector system for transgene delivery, we demonstrate that: 1 ETR is a sensitive MR marker gene; 2 several transgenes can be efficiently expressed from a single amplicon; 3 expression of each transgene results in functional gene product; and 4 ETR gene expression correlates with expression of therapeutic genes when the latter are contained within the same amplicon. These data, taken together, suggest that MRI of ETR expression can serve as a surrogate for measuring therapeutic transgene expression.

  13. Mating alters gene expression patterns in Drosophila melanogaster male heads

    Directory of Open Access Journals (Sweden)

    Ellis Lisa L

    2010-10-01

    Full Text Available Abstract Background Behavior is a complex process resulting from the integration of genetic and environmental information. Drosophila melanogaster rely on multiple sensory modalities for reproductive success, and mating causes physiological changes in both sexes that affect reproductive output or behavior. Some of these effects are likely mediated by changes in gene expression. Courtship and mating alter female transcript profiles, but it is not known how mating affects male gene expression. Results We used Drosophila genome arrays to identify changes in gene expression profiles that occur in mated male heads. Forty-seven genes differed between mated and control heads 2 hrs post mating. Many mating-responsive genes are highly expressed in non-neural head tissues, including an adipose tissue called the fat body. One fat body-enriched gene, female-specific independent of transformer (fit, is a downstream target of the somatic sex-determination hierarchy, a genetic pathway that regulates Drosophila reproductive behaviors as well as expression of some fat-expressed genes; three other mating-responsive loci are also downstream components of this pathway. Another mating-responsive gene expressed in fat, Juvenile hormone esterase (Jhe, is necessary for robust male courtship behavior and mating success. Conclusions Our study demonstrates that mating causes changes in male head gene expression profiles and supports an increasing body of work implicating adipose signaling in behavior modulation. Since several mating-induced genes are sex-determination hierarchy target genes, additional mating-responsive loci may be downstream components of this pathway as well.

  14. 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.

  15. Adaptive Evolution of Gene Expression in Drosophila

    Directory of Open Access Journals (Sweden)

    Armita Nourmohammad

    2017-08-01

    Full Text Available Gene expression levels are important quantitative traits that link genotypes to molecular functions and fitness. In Drosophila, population-genetic studies have revealed substantial adaptive evolution at the genomic level, but the evolutionary modes of gene expression remain controversial. Here, we present evidence that adaptation dominates the evolution of gene expression levels in flies. We show that 64% of the observed expression divergence across seven Drosophila species are adaptive changes driven by directional selection. Our results are derived from time-resolved data of gene expression divergence across a family of related species, using a probabilistic inference method for gene-specific selection. Adaptive gene expression is stronger in specific functional classes, including regulation, sensory perception, sexual behavior, and morphology. Moreover, we identify a large group of genes with sex-specific adaptation of expression, which predominantly occurs in males. Our analysis opens an avenue to map system-wide selection on molecular quantitative traits independently of their genetic basis.

  16. Interdependence of cell growth and gene expression: origins and consequences.

    Science.gov (United States)

    Scott, Matthew; Gunderson, Carl W; Mateescu, Eduard M; Zhang, Zhongge; Hwa, Terence

    2010-11-19

    In bacteria, the rate of cell proliferation and the level of gene expression are intimately intertwined. Elucidating these relations is important both for understanding the physiological functions of endogenous genetic circuits and for designing robust synthetic systems. We describe a phenomenological study that reveals intrinsic constraints governing the allocation of resources toward protein synthesis and other aspects of cell growth. A theory incorporating these constraints can accurately predict how cell proliferation and gene expression affect one another, quantitatively accounting for the effect of translation-inhibiting antibiotics on gene expression and the effect of gratuitous protein expression on cell growth. The use of such empirical relations, analogous to phenomenological laws, may facilitate our understanding and manipulation of complex biological systems before underlying regulatory circuits are elucidated.

  17. Differentially Expressed Genes and Signature Pathways of Human Prostate Cancer.

    Directory of Open Access Journals (Sweden)

    Jennifer S Myers

    Full Text Available Genomic technologies including microarrays and next-generation sequencing have enabled the generation of molecular signatures of prostate cancer. Lists of differentially expressed genes between malignant and non-malignant states are thought to be fertile sources of putative prostate cancer biomarkers. However such lists of differentially expressed genes can be highly variable for multiple reasons. As such, looking at differential expression in the context of gene sets and pathways has been more robust. Using next-generation genome sequencing data from The Cancer Genome Atlas, differential gene expression between age- and stage- matched human prostate tumors and non-malignant samples was assessed and used to craft a pathway signature of prostate cancer. Up- and down-regulated genes were assigned to pathways composed of curated groups of related genes from multiple databases. The significance of these pathways was then evaluated according to the number of differentially expressed genes found in the pathway and their position within the pathway using Gene Set Enrichment Analysis and Signaling Pathway Impact Analysis. The "transforming growth factor-beta signaling" and "Ran regulation of mitotic spindle formation" pathways were strongly associated with prostate cancer. Several other significant pathways confirm reported findings from microarray data that suggest actin cytoskeleton regulation, cell cycle, mitogen-activated protein kinase signaling, and calcium signaling are also altered in prostate cancer. Thus we have demonstrated feasibility of pathway analysis and identified an underexplored area (Ran for investigation in prostate cancer pathogenesis.

  18. A robust data-driven approach for gene ontology annotation

    OpenAIRE

    2014-01-01

    Gene ontology (GO) and GO annotation are important resources for biological information management and knowledge discovery, but the speed of manual annotation became a major bottleneck of database curation. BioCreative IV GO annotation task aims to evaluate the performance of system that automatically assigns GO terms to genes based on the narrative sentences in biomedical literature. This article presents our work in this task as well as the experimental results after the competition. For th...

  19. Robust dynamic balance of AP-1 transcription factors in a neuronal gene regulatory network

    Directory of Open Access Journals (Sweden)

    Schwaber James S

    2010-12-01

    and analysis results, we demonstrate that a dynamic balance among distinct dimers of the AP-1 family of transcription factors underlies the robust activation of neuronal gene expression in the NTS response to AT1R activation. Such a differential sensitivity to limited set of mechanisms is likely to underlie the stable homeostatic physiological response.

  20. Subject independent facial expression recognition with robust face detection using a convolutional neural network.

    Science.gov (United States)

    Matsugu, Masakazu; Mori, Katsuhiko; Mitari, Yusuke; Kaneda, Yuji

    2003-01-01

    Reliable detection of ordinary facial expressions (e.g. smile) despite the variability among individuals as well as face appearance is an important step toward the realization of perceptual user interface with autonomous perception of persons. We describe a rule-based algorithm for robust facial expression recognition combined with robust face detection using a convolutional neural network. In this study, we address the problem of subject independence as well as translation, rotation, and scale invariance in the recognition of facial expression. The result shows reliable detection of smiles with recognition rate of 97.6% for 5600 still images of more than 10 subjects. The proposed algorithm demonstrated the ability to discriminate smiling from talking based on the saliency score obtained from voting visual cues. To the best of our knowledge, it is the first facial expression recognition model with the property of subject independence combined with robustness to variability in facial appearance.

  1. Interpolation based consensus clustering for gene expression time series.

    Science.gov (United States)

    Chiu, Tai-Yu; Hsu, Ting-Chieh; Yen, Chia-Cheng; Wang, Jia-Shung

    2015-04-16

    Unsupervised analyses such as clustering are the essential tools required to interpret time-series expression data from microarrays. Several clustering algorithms have been developed to analyze gene expression data. Early methods such as k-means, hierarchical clustering, and self-organizing maps are popular for their simplicity. However, because of noise and uncertainty of measurement, these common algorithms have low accuracy. Moreover, because gene expression is a temporal process, the relationship between successive time points should be considered in the analyses. In addition, biological processes are generally continuous; therefore, the datasets collected from time series experiments are often found to have an insufficient number of data points and, as a result, compensation for missing data can also be an issue. An affinity propagation-based clustering algorithm for time-series gene expression data is proposed. The algorithm explores the relationship between genes using a sliding-window mechanism to extract a large number of features. In addition, the time-course datasets are resampled with spline interpolation to predict the unobserved values. Finally, a consensus process is applied to enhance the robustness of the method. Some real gene expression datasets were analyzed to demonstrate the accuracy and efficiency of the algorithm. The proposed algorithm has benefitted from the use of cubic B-splines interpolation, sliding-window, affinity propagation, gene relativity graph, and a consensus process, and, as a result, provides both appropriate and effective clustering of time-series gene expression data. The proposed method was tested with gene expression data from the Yeast galactose dataset, the Yeast cell-cycle dataset (Y5), and the Yeast sporulation dataset, and the results illustrated the relationships between the expressed genes, which may give some insights into the biological processes involved.

  2. Effect of random and hub gene disruptions on environmental and mutational robustness in Escherichia coli

    Directory of Open Access Journals (Sweden)

    Schneider Dominique

    2006-09-01

    Full Text Available Background Genome-wide profiling has allowed the regulatory interaction networks of many organisms to be visualised and the pattern of connections between genes to be studied. These networks are non-random, following a power-law distribution with a small number of well-connected 'hubs' and many genes with only one or a few connections. Theoretical work predicts that power-law networks display several unique properties. One of the most biologically interesting of these is an intrinsic robustness to disturbance such that removal of a random gene will have little effect on network function. Conversely, targeted removal of a hub gene is expected to have a large effect. Results We compared the response of Escherichia coli to environmental and mutational stress following disruption of random or hub genes. We found that disruption of random genes had less effect on robustness to environmental stress than did the targeted disruption of hub genes. In contrast, random disruption strains were slightly less robust to the effect of mutational stress than were hub disruption strains. When we compared the effect of each disruption on environmental and mutational stress, we found a negative relationship, such that strains that were more environmentally robust tended to be less robust to mutational stress. Conclusion Our results demonstrate that mutant strains of E. coli respond differently to stress, depending on whether random or hub genes are disrupted. This difference indicates that the power-law distribution of regulatory interactions has biological significance, making random disruptions less deleterious to organisms facing environmental stress. That E. coli can reduce the effect of environmental stress without reducing the phenotypic effect of additional mutations, indicates that robustness and evolvability need not be antagonistic.

  3. GSMA: Gene Set Matrix Analysis, An Automated Method for Rapid Hypothesis Testing of Gene Expression Data

    Directory of Open Access Journals (Sweden)

    Chris Cheadle

    2007-01-01

    Full Text Available Background: Microarray technology has become highly valuable for identifying complex global changes in gene expression patterns. The assignment of functional information to these complex patterns remains a challenging task in effectively interpreting data and correlating results from across experiments, projects and laboratories. Methods which allow the rapid and robust evaluation of multiple functional hypotheses increase the power of individual researchers to data mine gene expression data more efficiently.Results: We have developed (gene set matrix analysis GSMA as a useful method for the rapid testing of group-wise up- or downregulation of gene expression simultaneously for multiple lists of genes (gene sets against entire distributions of gene expression changes (datasets for single or multiple experiments. The utility of GSMA lies in its flexibility to rapidly poll gene sets related by known biological function or as designated solely by the end-user against large numbers of datasets simultaneously.Conclusions: GSMA provides a simple and straightforward method for hypothesis testing in which genes are tested by groups across multiple datasets for patterns of expression enrichment.

  4. Genes confer similar robustness to environmental, stochastic, and genetic perturbations in yeast.

    Directory of Open Access Journals (Sweden)

    Ben Lehner

    Full Text Available Gene inactivation often has little or no apparent consequence for the phenotype of an organism. This property-enetic (or mutational robustness-is pervasive, and has important implications for disease and evolution, but is not well understood. Dating back to at least Waddington, it has been suggested that mutational robustness may be related to the requirement to withstand environmental or stochastic perturbations. Here I show that global quantitative data from yeast are largely consistent with this idea. Considering the effects of mutations in all nonessential genes shows that genes that confer robustness to environmental or stochastic change also buffer the effects of genetic change, and with similar efficacy. This means that selection during evolution for environmental or stochastic robustness (also referred to as canalization may frequently have the side effect of increasing genetic robustness. A dynamic environment may therefore promote the evolution of phenotypic complexity. It also means that "hub" genes in genetic interaction (synthetic lethal networks are generally genes that confer environmental resilience and phenotypic stability.

  5. 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.

  6. 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.

  7. 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.

  8. 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.

  9. REC8 is a novel tumor suppressor gene epigenetically robustly targeted by the PI3K pathway in thyroid cancer.

    Science.gov (United States)

    Liu, Dingxie; Shen, Xiaopei; Zhu, Guangwu; Xing, Mingzhao

    2015-11-17

    The role of the PI3K pathway in human cancer has been well established, but much of its molecular mechanism, particularly the epigenetic aspect, remains to be defined. We hypothesized that aberrant methylation and hence altered expression of certain unknown important genes induced by the genetically activated PI3K pathway signaling is a major epigenetic mechanism in human tumorigenesis. Through a genome-wide search for such genes that were epigenetically controlled by the PI3K pathway in thyroid cancer cells, we found a wide range of genes with broad functions epigenetically targeted by the PI3K pathway. The most prominent among these genes was REC8, classically known as a meiotic-specific gene, which we found to be robustly down-regulated by the PI3K pathway through hypermethylation. REC8 hypermethylation was strongly associated with genetic alterations and activities of the PI3K pathway in thyroid cancer cell lines, thyroid cancer tumors, and some other human cancers; it was also associated with poor clinicopathological outcomes of thyroid cancer, including advanced disease stages and patient mortality. Demethylating the hypermethylated REC8 gene restored its expression in thyroid cancer cells in which the PI3K pathway was genetically over-activated and induced expression of REC8 protein inhibited the proliferation and colony formation of these cells. These findings are consistent with REC8 being a novel major bona fide tumor suppressor gene and a robust epigenetic target of the PI3K pathway. Aberrant inactivation of REC8 through hypermethylation by the PI3K pathway may represent an important mechanism mediating the oncogenic functions of the PI3K pathway.

  10. Amplification of kinetic oscillations in gene expression

    Science.gov (United States)

    Zhdanov, V. P.

    2008-10-01

    Because of the feedbacks between the DNA transcription and mRNA translation, the gene expression in cells may exhibit bistability and oscillations. The deterministic and stochastic calculations presented illustrate how the bistable kinetics of expression of one gene in a cell can be influenced by the kinetic oscillations in the expression of another gene. Due to stability of the states of the bistable kinetics of gene 1 and the relatively small difference between the maximum and minimum protein amounts during the oscillations of gene 2, the induced oscillations of gene 1 are found to typically be related either to the low-or high-reactive state of this gene. The quality of the induced oscillations may be appreciably better than that of the inducing oscillations. This means that gene 1 can serve as an amplifier of the kinetic oscillations of gene 2.

  11. 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.

  12. Tool for quantification of staphylococcal enterotoxin gene expression in cheese.

    Science.gov (United States)

    Duquenne, Manon; Fleurot, Isabelle; Aigle, Marina; Darrigo, Claire; Borezée-Durant, Elise; Derzelle, Sylviane; Bouix, Marielle; Deperrois-Lafarge, Véronique; Delacroix-Buchet, Agnès

    2010-03-01

    Cheese is a complex and dynamic microbial ecosystem characterized by the presence of a large variety of bacteria, yeasts, and molds. Some microorganisms, including species of lactobacilli or lactococci, are known to contribute to the organoleptic quality of cheeses, whereas the presence of other microorganisms may lead to spoilage or constitute a health risk. Staphylococcus aureus is recognized worldwide as an important food-borne pathogen, owing to the production of enterotoxins in food matrices. In order to study enterotoxin gene expression during cheese manufacture, we developed an efficient procedure to recover total RNA from cheese and applied a robust strategy to study gene expression by reverse transcription-quantitative PCR (RT-qPCR). This method yielded pure preparations of undegraded RNA suitable for RT-qPCR. To normalize RT-qPCR data, expression of 10 potential reference genes was investigated during S. aureus growth in milk and in cheese. The three most stably expressed reference genes during cheese manufacture were ftsZ, pta, and gyrB, and these were used as internal controls for RT-qPCR of the genes sea and sed, encoding staphylococcal enterotoxins A and D, respectively. Expression of these staphylococcal enterotoxin genes was monitored during the first 72 h of the cheese-making process, and mRNA data were correlated with enterotoxin production.

  13. 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.

  14. Regulation of Neuronal Gene Expression and Survival by Basal NMDA Receptor Activity: A Role for Histone Deacetylase 4

    OpenAIRE

    Chen, Yelin; Wang, Yuanyuan; Modrusan, Zora; Sheng, Morgan; Kaminker, Joshua S.

    2014-01-01

    Neuronal gene expression is modulated by activity via calcium-permeable receptors such as NMDA receptors (NMDARs). While gene expression changes downstream of evoked NMDAR activity have been well studied, much less is known about gene expression changes that occur under conditions of basal neuronal activity. In mouse dissociated hippocampal neuronal cultures, we found that a broad NMDAR antagonist, AP5, induced robust gene expression changes under basal activity, but subtype-specific antagoni...

  15. Gene Expression Profiling of Gastric Cancer

    Science.gov (United States)

    Marimuthu, Arivusudar; Jacob, Harrys K.C.; Jakharia, Aniruddha; Subbannayya, Yashwanth; Keerthikumar, Shivakumar; Kashyap, Manoj Kumar; Goel, Renu; Balakrishnan, Lavanya; Dwivedi, Sutopa; Pathare, Swapnali; Dikshit, Jyoti Bajpai; Maharudraiah, Jagadeesha; Singh, Sujay; Sameer Kumar, Ghantasala S; Vijayakumar, M.; Veerendra Kumar, Kariyanakatte Veeraiah; Premalatha, Chennagiri Shrinivasamurthy; Tata, Pramila; Hariharan, Ramesh; Roa, Juan Carlos; Prasad, T.S.K; Chaerkady, Raghothama; Kumar, Rekha Vijay; Pandey, Akhilesh

    2015-01-01

    Gastric cancer is the second leading cause of cancer death worldwide, both in men and women. A genomewide gene expression analysis was carried out to identify differentially expressed genes in gastric adenocarcinoma tissues as compared to adjacent normal tissues. We used Agilent’s whole human genome oligonucleotide microarray platform representing ~41,000 genes to carry out gene expression analysis. Two-color microarray analysis was employed to directly compare the expression of genes between tumor and normal tissues. Through this approach, we identified several previously known candidate genes along with a number of novel candidate genes in gastric cancer. Testican-1 (SPOCK1) was one of the novel molecules that was 10-fold upregulated in tumors. Using tissue microarrays, we validated the expression of testican-1 by immunohistochemical staining. It was overexpressed in 56% (160/282) of the cases tested. Pathway analysis led to the identification of several networks in which SPOCK1 was among the topmost networks of interacting genes. By gene enrichment analysis, we identified several genes involved in cell adhesion and cell proliferation to be significantly upregulated while those corresponding to metabolic pathways were significantly downregulated. The differentially expressed genes identified in this study are candidate biomarkers for gastric adenoacarcinoma. PMID:27030788

  16. 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......, overexpression was achieved by introducing an additional gene copy into a phage attachment site on the chromosome. This resulted in a series of strains with phosphofructokinase activities from 1.4 to 11 times the wild-type activity level. In this example, the pfk gene was cloned upstream of a gusA gene encoding...

  17. 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.

  18. Gene expression profiling during murine tooth development

    Directory of Open Access Journals (Sweden)

    Maria A dos Santos silva Landin

    2012-07-01

    Full Text Available The aim of this study was to describe the expression of genes, including ameloblastin (Ambn, amelogenin X chromosome (Amelx and enamelin (Enam during early (pre-secretory tooth development. The expression of these genes has predominantly been studied at post-secretory stages. Deoxyoligonucleotide microarrays were used to study gene expression during development of the murine first molar tooth germ at 24h intervals, starting at the eleventh embryonic day (E11.5 and up to the seventh day after birth (P7. The profile search function of Spotfire software was used to select genes with similar expression profile as the enamel genes (Ambn, Amelx and Enam. Microarray results where validated using real-time Reverse Transcription-Polymerase Chain Reaction (real-time RT-PCR, and translated proteins identified by Western blotting. In situ localisation of the Ambn, Amelx and Enam mRNAs were monitored from E12.5 to E17.5 using deoxyoligonucleotide probes. Bioinformatics analysis was used to associate biological functions with differentially (p ≤0.05 expressed (DE genes.Microarray results showed a total of 4362 genes including Ambn, Amelx and Enam to be significant differentially expressed throughout the time-course. The expression of the three enamel genes was low at pre-natal stages (E11.5-P0 increasing after birth (P1-P7. Profile search lead to isolation of 87 genes with significantly similar expression to the three enamel proteins. The mRNAs expressed in dental epithelium and epithelium derived cells. Although expression of Ambn, Amelx and Enam were lower during early tooth development compared to secretory stages enamel proteins were detectable by Western blotting. Bioinformatic analysis associated the 87 genes with multiple biological functions. Around thirty-five genes were associated with fifteen transcription factors.

  19. Gene Expression Patterns in Ovarian Carcinomas

    Science.gov (United States)

    Schaner, Marci E.; Ross, Douglas T.; Ciaravino, Giuseppe; Sørlie, Therese; Troyanskaya, Olga; Diehn, Maximilian; Wang, Yan C.; Duran, George E.; Sikic, Thomas L.; Caldeira, Sandra; Skomedal, Hanne; Tu, I-Ping; Hernandez-Boussard, Tina; Johnson, Steven W.; O'Dwyer, Peter J.; Fero, Michael J.; Kristensen, Gunnar B.; Børresen-Dale, Anne-Lise; Hastie, Trevor; Tibshirani, Robert; van de Rijn, Matt; Teng, Nelson N.; Longacre, Teri A.; Botstein, David; Brown, Patrick O.; Sikic, Branimir I.

    2003-01-01

    We used DNA microarrays to characterize the global gene expression patterns in surface epithelial cancers of the ovary. We identified groups of genes that distinguished the clear cell subtype from other ovarian carcinomas, grade I and II from grade III serous papillary carcinomas, and ovarian from breast carcinomas. Six clear cell carcinomas were distinguished from 36 other ovarian carcinomas (predominantly serous papillary) based on their gene expression patterns. The differences may yield insights into the worse prognosis and therapeutic resistance associated with clear cell carcinomas. A comparison of the gene expression patterns in the ovarian cancers to published data of gene expression in breast cancers revealed a large number of differentially expressed genes. We identified a group of 62 genes that correctly classified all 125 breast and ovarian cancer specimens. Among the best discriminators more highly expressed in the ovarian carcinomas were PAX8 (paired box gene 8), mesothelin, and ephrin-B1 (EFNB1). Although estrogen receptor was expressed in both the ovarian and breast cancers, genes that are coregulated with the estrogen receptor in breast cancers, including GATA-3, LIV-1, and X-box binding protein 1, did not show a similar pattern of coexpression in the ovarian cancers. PMID:12960427

  20. Microanalysis of gene expression in cultured cells

    NARCIS (Netherlands)

    E. van der Veer (Eveliene)

    1982-01-01

    textabstractIn this thesis two aspects of gene expression in cultured cells have been studied: the heterogeneity in gene expression in relation with the development and application of microchemical techniques for the prenatal diagnosis of inborn errors of metabolism and the possibility of inducing g

  1. Arabidopsis gene expression patterns during spaceflight

    Science.gov (United States)

    Paul, A.-L.; Ferl, R. J.

    The exposure of Arabidopsis thaliana (Arabidopsis) plants to spaceflight environments resulted in the differential expression of hundreds of genes. A 5 day mission on orbiter Columbia in 1999 (STS-93) carried transgenic Arabidopsis plants engineered with a transgene composed of the alcohol dehydrogenase (Adh) gene promoter linked to the β -Glucuronidase (GUS) reporter gene. The plants were used to evaluate the effects of spaceflight on two fronts. First, expression patterns visualized with the Adh/GUS transgene were used to address specifically the possibility that spaceflight induces a hypoxic stress response, and to assess whether any spaceflight response was similar to control terrestrial hypoxia-induced gene expression patterns. (Paul et al., Plant Physiol. 2001, 126:613). Second, genome-wide patterns of native gene expression were evaluated utilizing the Affymetrix ATH1 GeneChip? array of 8,000 Arabidopsis genes. As a control for the veracity of the array analyses, a selection of genes identified with the arrays was further characterized with quantitative Real-Time RT PCR (ABI - TaqmanTM). Comparison of the patterns of expression for arrays of hybridized with RNA isolated from plants exposed to spaceflight compared to the control arrays revealed hundreds of genes that were differentially expressed in response to spaceflight, yet most genes that are hallmarks of hypoxic stress were unaffected. These results will be discussed in light of current models for plant responses to the spaceflight environment, and with regard to potential future flight opportunities.

  2. Expression of Sox genes in tooth development.

    Science.gov (United States)

    Kawasaki, Katsushige; Kawasaki, Maiko; Watanabe, Momoko; Idrus, Erik; Nagai, Takahiro; Oommen, Shelly; Maeda, Takeyasu; Hagiwara, Nobuko; Que, Jianwen; Sharpe, Paul T; Ohazama, Atsushi

    2015-01-01

    Members of the Sox gene family play roles in many biological processes including organogenesis. We carried out comparative in situ hybridization analysis of seventeen sox genes (Sox1-14, 17, 18, 21) during murine odontogenesis from the epithelial thickening to the cytodifferentiation stages. Localized expression of five Sox genes (Sox6, 9, 13, 14 and 21) was observed in tooth bud epithelium. Sox13 showed restricted expression in the primary enamel knots. At the early bell stage, three Sox genes (Sox8, 11, 17 and 21) were expressed in pre-ameloblasts, whereas two others (Sox5 and 18) showed expression in odontoblasts. Sox genes thus showed a dynamic spatio-temporal expression during tooth development.

  3. Expression of Sox genes in tooth development

    Science.gov (United States)

    KAWASAKI, KATSUSHIGE; KAWASAKI, MAIKO; WATANABE, MOMOKO; IDRUS, ERIK; NAGAI, TAKAHIRO; OOMMEN, SHELLY; MAEDA, TAKEYASU; HAGIWARA, NOBUKO; QUE, JIANWEN; SHARPE, PAUL T.; OHAZAMA, ATSUSHI

    2017-01-01

    Members of the Sox gene family play roles in many biological processes including organogenesis. We carried out comparative in situ hybridization analysis of seventeen sox genes (Sox1-14, 17, 18, 21) during murine odontogenesis from the epithelial thickening to the cytodifferentiation stages. Localized expression of five Sox genes (Sox6, 9, 13, 14 and 21) was observed in tooth bud epithelium. Sox13 showed restricted expression in the primary enamel knots. At the early bell stage, three Sox genes (Sox8, 11, 17 and 21) were expressed in pre-ameloblasts, whereas two others (Sox5 and 18) showed expression in odontoblasts. Sox genes thus showed a dynamic spatio-temporal expression during tooth development. PMID:26864488

  4. The underlying molecular and network level mechanisms in the evolution of robustness in gene regulatory networks.

    Directory of Open Access Journals (Sweden)

    Mario Pujato

    Full Text Available Gene regulatory networks show robustness to perturbations. Previous works identified robustness as an emergent property of gene network evolution but the underlying molecular mechanisms are poorly understood. We used a multi-tier modeling approach that integrates molecular sequence and structure information with network architecture and population dynamics. Structural models of transcription factor-DNA complexes are used to estimate relative binding specificities. In this model, mutations in the DNA cause changes on two levels: (a at the sequence level in individual binding sites (modulating binding specificity, and (b at the network level (creating and destroying binding sites. We used this model to dissect the underlying mechanisms responsible for the evolution of robustness in gene regulatory networks. Results suggest that in sparse architectures (represented by short promoters, a mixture of local-sequence and network-architecture level changes are exploited. At the local-sequence level, robustness evolves by decreasing the probabilities of both the destruction of existent and generation of new binding sites. Meanwhile, in highly interconnected architectures (represented by long promoters, robustness evolves almost entirely via network level changes, deleting and creating binding sites that modify the network architecture.

  5. 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...

  6. 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.

  7. Population genetics of translational robustness

    OpenAIRE

    Wilke, Claus O; Drummond, D. Allan

    2005-01-01

    Recent work has shown that expression level is the main predictor of a gene’s evolutionary rate, and that more highly expressed genes evolve slower. A possible explanation for this observation is selection for proteins which fold properly despite mistranslation, in short selection for translational robustness. Translational robustness leads to the somewhat paradoxical prediction that highly expressed genes are extremely tolerant to missense substitutions but nevertheless evolve very slo...

  8. Population genetics of translational robustness.

    Science.gov (United States)

    Wilke, Claus O; Drummond, D Allan

    2006-05-01

    Recent work has shown that expression level is the main predictor of a gene's evolutionary rate and that more highly expressed genes evolve slower. A possible explanation for this observation is selection for proteins that fold properly despite mistranslation, in short selection for translational robustness. Translational robustness leads to the somewhat paradoxical prediction that highly expressed genes are extremely tolerant to missense substitutions but nevertheless evolve very slowly. Here, we study a simple theoretical model of translational robustness that allows us to gain analytic insight into how this paradoxical behavior arises.

  9. Differential gene expression during Trypanosoma cruzi metacyclogenesis

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    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.

  10. Multivariate search for differentially expressed gene combinations

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    Klebanov Lev

    2004-10-01

    Full Text Available Abstract Background To identify differentially expressed genes, it is standard practice to test a two-sample hypothesis for each gene with a proper adjustment for multiple testing. Such tests are essentially univariate and disregard the multidimensional structure of microarray data. A more general two-sample hypothesis is formulated in terms of the joint distribution of any sub-vector of expression signals. Results By building on an earlier proposed multivariate test statistic, we propose a new algorithm for identifying differentially expressed gene combinations. The algorithm includes an improved random search procedure designed to generate candidate gene combinations of a given size. Cross-validation is used to provide replication stability of the search procedure. A permutation two-sample test is used for significance testing. We design a multiple testing procedure to control the family-wise error rate (FWER when selecting significant combinations of genes that result from a successive selection procedure. A target set of genes is composed of all significant combinations selected via random search. Conclusions A new algorithm has been developed to identify differentially expressed gene combinations. The performance of the proposed search-and-testing procedure has been evaluated by computer simulations and analysis of replicated Affymetrix gene array data on age-related changes in gene expression in the inner ear of CBA mice.

  11. Gene Expression Profiling in Porcine Fetal Thymus

    Institute of Scientific and Technical Information of China (English)

    Yanjiong Chen; Shengbin Li; Lin Ye; Jianing Geng; Yajun Deng; Songnian Hu

    2003-01-01

    obtain an initial overview of gene diversity and expression pattern in porcinethymus, 11,712 ESTs (Expressed Sequence Tags) from 100-day-old porcine thymus(FTY) were sequenced and 7,071 cleaned ESTs were used for gene expressionanalysis. Clustered by the PHRAP program, 959 contigs and 3,074 singlets wereobtained. Blast search showed that 806 contigs and 1,669 singlets (totally 5,442ESTs) had homologues in GenBank and 1,629 ESTs were novel. According to theGene Ontology classification, 36.99% ESTs were cataloged into the gene expressiongroup, indicating that although the functional gene (18.78% in defense group) ofthymus is expressed in a certain degree, the 100-day-old porcine thymus still existsin a developmental stage. Comparative analysis showed that the gene expressionpattern of the 100-day-old porcine thymus is similar to that of the human infantthymus.

  12. 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.

  13. Nucleosome repositioning underlies dynamic gene expression.

    Science.gov (United States)

    Nocetti, Nicolas; Whitehouse, Iestyn

    2016-03-15

    Nucleosome repositioning at gene promoters is a fundamental aspect of the regulation of gene expression. However, the extent to which nucleosome repositioning is used within eukaryotic genomes is poorly understood. Here we report a comprehensive analysis of nucleosome positions as budding yeast transit through an ultradian cycle in which expression of >50% of all genes is highly synchronized. We present evidence of extensive nucleosome repositioning at thousands of gene promoters as genes are activated and repressed. During activation, nucleosomes are relocated to allow sites of general transcription factor binding and transcription initiation to become accessible. The extent of nucleosome shifting is closely related to the dynamic range of gene transcription and generally related to DNA sequence properties and use of the coactivators TFIID or SAGA. However, dynamic gene expression is not limited to SAGA-regulated promoters and is an inherent feature of most genes. While nucleosome repositioning occurs pervasively, we found that a class of genes required for growth experience acute nucleosome shifting as cells enter the cell cycle. Significantly, our data identify that the ATP-dependent chromatin-remodeling enzyme Snf2 plays a fundamental role in nucleosome repositioning and the expression of growth genes. We also reveal that nucleosome organization changes extensively in concert with phases of the cell cycle, with large, regularly spaced nucleosome arrays being established in mitosis. Collectively, our data and analysis provide a framework for understanding nucleosome dynamics in relation to fundamental DNA-dependent transactions.

  14. 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;

    2012-01-01

    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 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...... of these robustly defined disease modules is significantly enriched with brain-expressed genes and with genetic variants that were implicated in a GWAS study, which could imply a causal role in schizophrenia etiology. The most highly connected intramodular hub gene in this module (ABCF1), is located in...

  15. Global Analysis of miRNA Gene Clusters and Gene Families Reveals Dynamic and Coordinated Expression

    Directory of Open Access Journals (Sweden)

    Li Guo

    2014-01-01

    Full Text Available To further understand the potential expression relationships of miRNAs in miRNA gene clusters and gene families, a global analysis was performed in 4 paired tumor (breast cancer and adjacent normal tissue samples using deep sequencing datasets. The compositions of miRNA gene clusters and families are not random, and clustered and homologous miRNAs may have close relationships with overlapped miRNA species. Members in the miRNA group always had various expression levels, and even some showed larger expression divergence. Despite the dynamic expression as well as individual difference, these miRNAs always indicated consistent or similar deregulation patterns. The consistent deregulation expression may contribute to dynamic and coordinated interaction between different miRNAs in regulatory network. Further, we found that those clustered or homologous miRNAs that were also identified as sense and antisense miRNAs showed larger expression divergence. miRNA gene clusters and families indicated important biological roles, and the specific distribution and expression further enrich and ensure the flexible and robust regulatory network.

  16. Digital gene expression signatures for maize development.

    Science.gov (United States)

    Eveland, Andrea L; Satoh-Nagasawa, Namiko; Goldshmidt, Alexander; Meyer, Sandra; Beatty, Mary; Sakai, Hajime; Ware, Doreen; Jackson, David

    2010-11-01

    Genome-wide expression signatures detect specific perturbations in developmental programs and contribute to functional resolution of key regulatory networks. In maize (Zea mays) inflorescences, mutations in the RAMOSA (RA) genes affect the determinacy of axillary meristems and thus alter branching patterns, an important agronomic trait. In this work, we developed and tested a framework for analysis of tag-based, digital gene expression profiles using Illumina's high-throughput sequencing technology and the newly assembled B73 maize reference genome. We also used a mutation in the RA3 gene to identify putative expression signatures specific to stem cell fate in axillary meristem determinacy. The RA3 gene encodes a trehalose-6-phosphate phosphatase and may act at the interface between developmental and metabolic processes. Deep sequencing of digital gene expression libraries, representing three biological replicate ear samples from wild-type and ra3 plants, generated 27 million 20- to 21-nucleotide reads with frequencies spanning 4 orders of magnitude. Unique sequence tags were anchored to 3'-ends of individual transcripts by DpnII and NlaIII digests, which were multiplexed during sequencing. We mapped 86% of nonredundant signature tags to the maize genome, which associated with 37,117 gene models and unannotated regions of expression. In total, 66% of genes were detected by at least nine reads in immature maize ears. We used comparative genomics to leverage existing information from Arabidopsis (Arabidopsis thaliana) and rice (Oryza sativa) in functional analyses of differentially expressed maize genes. Results from this study provide a basis for the analysis of short-read expression data in maize and resolved specific expression signatures that will help define mechanisms of action for the RA3 gene.

  17. Constructing gene co-expression networks and predicting functions of unknown genes by random matrix theory

    Directory of Open Access Journals (Sweden)

    Gao Haichun

    2007-08-01

    Full Text Available Abstract Background Large-scale sequencing of entire genomes has ushered in a new age in biology. One of the next grand challenges is to dissect the cellular networks consisting of many individual functional modules. Defining co-expression networks without ambiguity based on genome-wide microarray data is difficult and current methods are not robust and consistent with different data sets. This is particularly problematic for little understood organisms since not much existing biological knowledge can be exploited for determining the threshold to differentiate true correlation from random noise. Random matrix theory (RMT, which has been widely and successfully used in physics, is a powerful approach to distinguish system-specific, non-random properties embedded in complex systems from random noise. Here, we have hypothesized that the universal predictions of RMT are also applicable to biological systems and the correlation threshold can be determined by characterizing the correlation matrix of microarray profiles using random matrix theory. Results Application of random matrix theory to microarray data of S. oneidensis, E. coli, yeast, A. thaliana, Drosophila, mouse and human indicates that there is a sharp transition of nearest neighbour spacing distribution (NNSD of correlation matrix after gradually removing certain elements insider the matrix. Testing on an in silico modular model has demonstrated that this transition can be used to determine the correlation threshold for revealing modular co-expression networks. The co-expression network derived from yeast cell cycling microarray data is supported by gene annotation. The topological properties of the resulting co-expression network agree well with the general properties of biological networks. Computational evaluations have showed that RMT approach is sensitive and robust. Furthermore, evaluation on sampled expression data of an in silico modular gene system has showed that under

  18. Gene expression profile of sprinter's muscle.

    Science.gov (United States)

    Yoshioka, M; Tanaka, H; Shono, N; Shindo, M; St-Amand, J

    2007-12-01

    We have characterized the global gene expression profile in left vastus lateralis muscles of sprinters and sedentary men. The gene expression profile was analyzed by using serial analysis of gene expression (SAGE) method. The abundantly expressed transcripts in the sprinter's muscle were mainly involved in contraction and energy metabolism, whereas six transcripts were corresponding to potentially novel transcripts. Thirty-eight transcripts were differentially expressed between the sprinter and sedentary individuals. Moreover, sprinters showed higher expressions of both uncharacterized and potentially novel transcripts. Sprinters also highly expressed seven transcripts, such as glycine-rich protein, myosin heavy polypeptide (MYH) 2, expressed sequence tag similar to (EST) fructose-bisphosphate aldolase 1 isoform A (ALDOA), glyceraldehyde-3-phosphate dehydrogenase and ATP synthase F0 subunit 6. On the other hand, 20 transcripts such as MYH1, tropomyosin 2 and 3, troponin C slow, C2 fast, I slow, T1 slow and T3 fast, myoglobin, creatine kinase, ALDOA, glycogen phosphorylase, cytochrome c oxidase II and III, and NADH dehydrogenase 1 and 2 showed lower expression levels in the sprinters than the sedentary controls. The current study has characterized the global gene expressions in sprinters and identified a number of transcripts that can be subjected to further mechanistic analysis.

  19. Widespread ectopic expression of olfactory receptor genes

    Directory of Open Access Journals (Sweden)

    Yanai Itai

    2006-05-01

    Full Text Available Abstract Background Olfactory receptors (ORs are the largest gene family in the human genome. Although they are expected to be expressed specifically in olfactory tissues, some ectopic expression has been reported, with special emphasis on sperm and testis. The present study systematically explores the expression patterns of OR genes in a large number of tissues and assesses the potential functional implication of such ectopic expression. Results We analyzed the expression of hundreds of human and mouse OR transcripts, via EST and microarray data, in several dozens of human and mouse tissues. Different tissues had specific, relatively small OR gene subsets which had particularly high expression levels. In testis, average expression was not particularly high, and very few highly expressed genes were found, none corresponding to ORs previously implicated in sperm chemotaxis. Higher expression levels were more common for genes with a non-OR genomic neighbor. Importantly, no correlation in expression levels was detected for human-mouse orthologous pairs. Also, no significant difference in expression levels was seen between intact and pseudogenized ORs, except for the pseudogenes of subfamily 7E which has undergone a human-specific expansion. Conclusion The OR superfamily as a whole, show widespread, locus-dependent and heterogeneous expression, in agreement with a neutral or near neutral evolutionary model for transcription control. These results cannot reject the possibility that small OR subsets might play functional roles in different tissues, however considerable care should be exerted when offering a functional interpretation for ectopic OR expression based only on transcription information.

  20. Time course of gene expression during mouse skeletal muscle hypertrophy

    Science.gov (United States)

    Lee, Jonah D.; England, Jonathan H.; Esser, Karyn A.; McCarthy, John J.

    2013-01-01

    The purpose of this study was to perform a comprehensive transcriptome analysis during skeletal muscle hypertrophy to identify signaling pathways that are operative throughout the hypertrophic response. Global gene expression patterns were determined from microarray results on days 1, 3, 5, 7, 10, and 14 during plantaris muscle hypertrophy induced by synergist ablation in adult mice. Principal component analysis and the number of differentially expressed genes (cutoffs ≥2-fold increase or ≥50% decrease compared with control muscle) revealed three gene expression patterns during overload-induced hypertrophy: early (1 day), intermediate (3, 5, and 7 days), and late (10 and 14 days) patterns. Based on the robust changes in total RNA content and in the number of differentially expressed genes, we focused our attention on the intermediate gene expression pattern. Ingenuity Pathway Analysis revealed a downregulation of genes encoding components of the branched-chain amino acid degradation pathway during hypertrophy. Among these genes, five were predicted by Ingenuity Pathway Analysis or previously shown to be regulated by the transcription factor Kruppel-like factor-15, which was also downregulated during hypertrophy. Moreover, the integrin-linked kinase signaling pathway was activated during hypertrophy, and the downregulation of muscle-specific micro-RNA-1 correlated with the upregulation of five predicted targets associated with the integrin-linked kinase pathway. In conclusion, we identified two novel pathways that may be involved in muscle hypertrophy, as well as two upstream regulators (Kruppel-like factor-15 and micro-RNA-1) that provide targets for future studies investigating the importance of these pathways in muscle hypertrophy. PMID:23869057

  1. Time course of gene expression during mouse skeletal muscle hypertrophy.

    Science.gov (United States)

    Chaillou, Thomas; Lee, Jonah D; England, Jonathan H; Esser, Karyn A; McCarthy, John J

    2013-10-01

    The purpose of this study was to perform a comprehensive transcriptome analysis during skeletal muscle hypertrophy to identify signaling pathways that are operative throughout the hypertrophic response. Global gene expression patterns were determined from microarray results on days 1, 3, 5, 7, 10, and 14 during plantaris muscle hypertrophy induced by synergist ablation in adult mice. Principal component analysis and the number of differentially expressed genes (cutoffs ≥2-fold increase or ≥50% decrease compared with control muscle) revealed three gene expression patterns during overload-induced hypertrophy: early (1 day), intermediate (3, 5, and 7 days), and late (10 and 14 days) patterns. Based on the robust changes in total RNA content and in the number of differentially expressed genes, we focused our attention on the intermediate gene expression pattern. Ingenuity Pathway Analysis revealed a downregulation of genes encoding components of the branched-chain amino acid degradation pathway during hypertrophy. Among these genes, five were predicted by Ingenuity Pathway Analysis or previously shown to be regulated by the transcription factor Kruppel-like factor-15, which was also downregulated during hypertrophy. Moreover, the integrin-linked kinase signaling pathway was activated during hypertrophy, and the downregulation of muscle-specific micro-RNA-1 correlated with the upregulation of five predicted targets associated with the integrin-linked kinase pathway. In conclusion, we identified two novel pathways that may be involved in muscle hypertrophy, as well as two upstream regulators (Kruppel-like factor-15 and micro-RNA-1) that provide targets for future studies investigating the importance of these pathways in muscle hypertrophy.

  2. Simultaneous clustering of multiple gene expression and physical interaction datasets.

    Directory of Open Access Journals (Sweden)

    Manikandan Narayanan

    2010-04-01

    Full Text Available Many genome-wide datasets are routinely generated to study different aspects of biological systems, but integrating them to obtain a coherent view of the underlying biology remains a challenge. We propose simultaneous clustering of multiple networks as a framework to integrate large-scale datasets on the interactions among and activities of cellular components. Specifically, we develop an algorithm JointCluster that finds sets of genes that cluster well in multiple networks of interest, such as coexpression networks summarizing correlations among the expression profiles of genes and physical networks describing protein-protein and protein-DNA interactions among genes or gene-products. Our algorithm provides an efficient solution to a well-defined problem of jointly clustering networks, using techniques that permit certain theoretical guarantees on the quality of the detected clustering relative to the optimal clustering. These guarantees coupled with an effective scaling heuristic and the flexibility to handle multiple heterogeneous networks make our method JointCluster an advance over earlier approaches. Simulation results showed JointCluster to be more robust than alternate methods in recovering clusters implanted in networks with high false positive rates. In systematic evaluation of JointCluster and some earlier approaches for combined analysis of the yeast physical network and two gene expression datasets under glucose and ethanol growth conditions, JointCluster discovers clusters that are more consistently enriched for various reference classes capturing different aspects of yeast biology or yield better coverage of the analysed genes. These robust clusters, which are supported across multiple genomic datasets and diverse reference classes, agree with known biology of yeast under these growth conditions, elucidate the genetic control of coordinated transcription, and enable functional predictions for a number of uncharacterized genes.

  3. Regulation of Gene Expression in Protozoa Parasites

    Directory of Open Access Journals (Sweden)

    Consuelo Gomez

    2010-01-01

    Full Text Available 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 drug resistance, and the comprehension of the mechanisms implicated in that control could help to develop novel therapeutic strategies. However, until now these mechanisms are poorly understood in protozoa. Recent investigations into gene expression in protozoa parasites suggest that they possess many of the canonical machineries employed by higher eukaryotes for the control of gene expression at transcriptional, posttranscriptional, and epigenetic levels, but they also contain exclusive mechanisms. Here, we review the current understanding about the regulation of gene expression in Plasmodium sp., Trypanosomatids, Entamoeba histolytica and Trichomonas vaginalis.

  4. Expression of polarity genes in human cancer.

    Science.gov (United States)

    Lin, Wan-Hsin; Asmann, Yan W; Anastasiadis, Panos Z

    2015-01-01

    Polarity protein complexes are crucial for epithelial apical-basal polarity and directed cell migration. Since alterations of these processes are common in cancer, polarity proteins have been proposed to function as tumor suppressors or oncogenic promoters. Here, we review the current understanding of polarity protein functions in epithelial homeostasis, as well as tumor formation and progression. As most previous studies focused on the function of single polarity proteins in simplified model systems, we used a genomics approach to systematically examine and identify the expression profiles of polarity genes in human cancer. The expression profiles of polarity genes were distinct in different human tissues and classified cancer types. Additionally, polarity expression profiles correlated with disease progression and aggressiveness, as well as with identified cancer types, where specific polarity genes were commonly altered. In the case of Scribble, gene expression analysis indicated its common amplification and upregulation in human cancer, suggesting a tumor promoting function.

  5. Regulation of meiotic gene expression in plants

    Directory of Open Access Journals (Sweden)

    Adele eZhou

    2014-08-01

    Full Text Available With the recent advances in genomics and sequencing technologies, databases of transcriptomes representing many cellular processes have been built. Meiotic transcriptomes in plants have been studied in Arabidopsis thaliana, rice (Oryza sativa, wheat (Triticum aestivum, petunia (Petunia hybrida, sunflower (Helianthus annuus, and maize (Zea mays. Studies in all organisms, but particularly in plants, indicate that a very large number of genes are expressed during meiosis, though relatively few of them seem to be required for the completion of meiosis. In this review, we focus on gene expression at the RNA level and analyze the meiotic transcriptome datasets and explore expression patterns of known meiotic genes to elucidate how gene expression could be regulated during meiosis. We also discuss mechanisms, such as chromatin organization and non-coding RNAs, that might be involved in the regulation of meiotic transcription patterns.

  6. Gene therapy during cardiac surgery: role of surgical technique to minimize collateral organ gene expression.

    Science.gov (United States)

    Katz, Michael G; Swain, JaBaris D; Fargnoli, Anthony S; Bridges, Charles R

    2010-12-01

    Effective gene therapy for heart failure has not yet been achieved clinically. The aim of this study is to quantitatively assess the cardiac isolation efficiency of the molecular cardiac surgery with recirculating delivery (MCARD™) and to evaluate its efficacy as a means to limit collateral organ gene expression. 10(14) genome copies (GC) of recombinant adeno-associated viral vector 6 encoding green fluorescent protein under control of the cytomegalovirus promoter was delivered to the nine arrested sheep hearts. Blood samples were assessed using real-time quantitative polymerase chain reaction (RT QPCR). Collateral organ gene expression was assessed at four-weeks using immunohistochemical staining. The blood vector GC concentration in the cardiac circuit during complete isolation trended from 9.59±0.73 to 9.05±0.65 (log GC/cm(3)), and no GC were detectable in the systemic circuit (P800-fold (P99% isolation efficiency. Conversely, incomplete isolation resulted in equalization of vector GC concentration in the circuits, leading to robust collateral organ gene expression. MCARD™ is an efficient, clinically translatable myocardial delivery platform for cardiac specific gene therapy. The cardiac surgical techniques utilized are critically important to limit collateral organ gene expression.

  7. Optimal Reference Genes for Gene Expression Normalization in Trichomonas vaginalis.

    Science.gov (United States)

    dos Santos, Odelta; de Vargas Rigo, Graziela; Frasson, Amanda Piccoli; Macedo, Alexandre José; Tasca, Tiana

    2015-01-01

    Trichomonas vaginalis is the etiologic agent of trichomonosis, the most common non-viral sexually transmitted disease worldwide. This infection is associated with several health consequences, including cervical and prostate cancers and HIV acquisition. Gene expression analysis has been facilitated because of available genome sequences and large-scale transcriptomes in T. vaginalis, particularly using quantitative real-time polymerase chain reaction (qRT-PCR), one of the most used methods for molecular studies. Reference genes for normalization are crucial to ensure the accuracy of this method. However, to the best of our knowledge, a systematic validation of reference genes has not been performed for T. vaginalis. In this study, the transcripts of nine candidate reference genes were quantified using qRT-PCR under different cultivation conditions, and the stability of these genes was compared using the geNorm and NormFinder algorithms. The most stable reference genes were α-tubulin, actin and DNATopII, and, conversely, the widely used T. vaginalis reference genes GAPDH and β-tubulin were less stable. The PFOR gene was used to validate the reliability of the use of these candidate reference genes. As expected, the PFOR gene was upregulated when the trophozoites were cultivated with ferrous ammonium sulfate when the DNATopII, α-tubulin and actin genes were used as normalizing gene. By contrast, the PFOR gene was downregulated when the GAPDH gene was used as an internal control, leading to misinterpretation of the data. These results provide an important starting point for reference gene selection and gene expression analysis with qRT-PCR studies of T. vaginalis.

  8. 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...

  9. Bayesian modeling of differential gene expression.

    Science.gov (United States)

    Lewin, Alex; Richardson, Sylvia; Marshall, Clare; Glazier, Anne; Aitman, Tim

    2006-03-01

    We present a Bayesian hierarchical model for detecting differentially expressing genes that includes simultaneous estimation of array effects, and show how to use the output for choosing lists of genes for further investigation. We give empirical evidence that expression-level dependent array effects are needed, and explore different nonlinear functions as part of our model-based approach to normalization. The model includes gene-specific variances but imposes some necessary shrinkage through a hierarchical structure. Model criticism via posterior predictive checks is discussed. Modeling the array effects (normalization) simultaneously with differential expression gives fewer false positive results. To choose a list of genes, we propose to combine various criteria (for instance, fold change and overall expression) into a single indicator variable for each gene. The posterior distribution of these variables is used to pick the list of genes, thereby taking into account uncertainty in parameter estimates. In an application to mouse knockout data, Gene Ontology annotations over- and underrepresented among the genes on the chosen list are consistent with biological expectations.

  10. Perspectives: Gene Expression in Fisheries Management

    Science.gov (United States)

    Nielsen, Jennifer L.; Pavey, Scott A.

    2010-01-01

    Functional genes and gene expression have been connected to physiological traits linked to effective production and broodstock selection in aquaculture, selective implications of commercial fish harvest, and adaptive changes reflected in non-commercial fish populations subject to human disturbance and climate change. Gene mapping using single nucleotide polymorphisms (SNPs) to identify functional genes, gene expression (analogue microarrays and real-time PCR), and digital sequencing technologies looking at RNA transcripts present new concepts and opportunities in support of effective and sustainable fisheries. Genomic tools have been rapidly growing in aquaculture research addressing aspects of fish health, toxicology, and early development. Genomic technologies linking effects in functional genes involved in growth, maturation and life history development have been tied to selection resulting from harvest practices. Incorporating new and ever-increasing knowledge of fish genomes is opening a different perspective on local adaptation that will prove invaluable in wild fish conservation and management. Conservation of fish stocks is rapidly incorporating research on critical adaptive responses directed at the effects of human disturbance and climate change through gene expression studies. Genomic studies of fish populations can be generally grouped into three broad categories: 1) evolutionary genomics and biodiversity; 2) adaptive physiological responses to a changing environment; and 3) adaptive behavioral genomics and life history diversity. We review current genomic research in fisheries focusing on those that use microarrays to explore differences in gene expression among phenotypes and within or across populations, information that is critically important to the conservation of fish and their relationship to humans.

  11. Gene Expression Profiles of Inflammatory Myopathies

    Directory of Open Access Journals (Sweden)

    J Gordon Millichap

    2002-11-01

    Full Text Available The simultaneous expression of 10,000 genes was measured, using Affymetrix GeneChip microarrays, in muscle specimens from 45 patients with various myopathies (dystrophy, congenital myopathy, and inflammatory myopathy examined at Brigham and Women’s Hospital, and Children’s Hospital, Harvard Medical School, Boston, MA.

  12. 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

  13. 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.

  14. Gene expression studies using microarrays

    NARCIS (Netherlands)

    Burgess, Janette

    2001-01-01

    1. The rapid progression of the collaborative sequencing programmes that are unravelling the complete genome sequences of many organisms are opening pathways for new approaches to gene analysis. As the sequence data become available, the bottleneck in biological research will shift to understanding

  15. A gene expression fingerprint of C. elegans embryonic motor neurons

    Directory of Open Access Journals (Sweden)

    Dupuy Denis

    2005-03-01

    Full Text Available Abstract Background Differential gene expression specifies the highly diverse cell types that constitute the nervous system. With its sequenced genome and simple, well-defined neuroanatomy, the nematode C. elegans is a useful model system in which to correlate gene expression with neuron identity. The UNC-4 transcription factor is expressed in thirteen embryonic motor neurons where it specifies axonal morphology and synaptic function. These cells can be marked with an unc-4::GFP reporter transgene. Here we describe a powerful strategy, Micro-Array Profiling of C. elegans cells (MAPCeL, and confirm that this approach provides a comprehensive gene expression profile of unc-4::GFP motor neurons in vivo. Results Fluorescence Activated Cell Sorting (FACS was used to isolate unc-4::GFP neurons from primary cultures of C. elegans embryonic cells. Microarray experiments detected 6,217 unique transcripts of which ~1,000 are enriched in unc-4::GFP neurons relative to the average nematode embryonic cell. The reliability of these data was validated by the detection of known cell-specific transcripts and by expression in UNC-4 motor neurons of GFP reporters derived from the enriched data set. In addition to genes involved in neurotransmitter packaging and release, the microarray data include transcripts for receptors to a remarkably wide variety of signaling molecules. The added presence of a robust array of G-protein pathway components is indicative of complex and highly integrated mechanisms for modulating motor neuron activity. Over half of the enriched genes (537 have human homologs, a finding that could reflect substantial overlap with the gene expression repertoire of mammalian motor neurons. Conclusion We have described a microarray-based method, MAPCeL, for profiling gene expression in specific C. elegans motor neurons and provide evidence that this approach can reveal candidate genes for key roles in the differentiation and function of these cells

  16. Insulin gene: organisation, expression and regulation.

    Science.gov (United States)

    Dumonteil, E; Philippe, J

    1996-06-01

    Insulin, a major hormone of the endocrine pancreas, plays a key role in the control of glucose homeostasis. This review discusses the mechanisms of cell-specific expression and regulation of the insulin gene. Whereas expression is restricted to islet beta-cells in adults, the insulin gene is more widely expressed at several embryonic stages, although the role of extrapancreatic expression is still unclear. beta-cell-specific expression relies on the interactions of 5'-flanking sequence motifs of the promoter with a number of ubiquitous and islet-specific transcription factors. IEF1 and IPF-1, by their binding to the E and A boxes, respectively, of the insulin gene promoter, appear to be the major determinants of beta-cell-specific expression. IEF1 is a heterodimer of the basic helix-loop-helix family of transcription factors, whereas IPF-1 belongs to the homeodomain-containing family. beta-cell specific determinants are conserved throughout evolution, although the human insulin gene 5'-flanking sequence also contains a polymorphic minisatellite which is unique to primates and may play a role in insulin gene regulation. Glucose modulates insulin gene transcription, with multiple elements of the promoter involved in glucose responsiveness. Remarkably, IPF-1 and IEF1 are involved in both beta-cell-specific expression and glucose regulation of the insulin gene. cAMP also regulates insulin gene transcription through a CRE, in response to various hormonal stimuli. On the whole, recent studies have provided a better understanding of beta-cell differentiation and function.

  17. A simulation to analyze feature selection methods utilizing gene ontology for gene expression classification.

    Science.gov (United States)

    Gillies, Christopher E; Siadat, Mohammad-Reza; Patel, Nilesh V; Wilson, George D

    2013-12-01

    Gene expression profile classification is a pivotal research domain assisting in the transformation from traditional to personalized medicine. A major challenge associated with gene expression data classification is the small number of samples relative to the large number of genes. To address this problem, researchers have devised various feature selection algorithms to reduce the number of genes. Recent studies have been experimenting with the use of semantic similarity between genes in Gene Ontology (GO) as a method to improve feature selection. While there are few studies that discuss how to use GO for feature selection, there is no simulation study that addresses when to use GO-based feature selection. To investigate this, we developed a novel simulation, which generates binary class datasets, where the differentially expressed genes between two classes have some underlying relationship in GO. This allows us to investigate the effects of various factors such as the relative connectedness of the underlying genes in GO, the mean magnitude of separation between differentially expressed genes denoted by δ, and the number of training samples. Our simulation results suggest that the connectedness in GO of the differentially expressed genes for a biological condition is the primary factor for determining the efficacy of GO-based feature selection. In particular, as the connectedness of differentially expressed genes increases, the classification accuracy improvement increases. To quantify this notion of connectedness, we defined a measure called Biological Condition Annotation Level BCAL(G), where G is a graph of differentially expressed genes. Our main conclusions with respect to GO-based feature selection are the following: (1) it increases classification accuracy when BCAL(G) ≥ 0.696; (2) it decreases classification accuracy when BCAL(G) ≤ 0.389; (3) it provides marginal accuracy improvement when 0.389genes in a biological condition increases beyond 50 and

  18. 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

  19. The Constrained Maximal Expression Level Owing to Haploidy Shapes Gene Content on the Mammalian X Chromosome.

    Directory of Open Access Journals (Sweden)

    Laurence D Hurst

    2015-12-01

    tissue of expression profiles of X-linked genes. Tissues whose tissue-specific genes are very highly expressed (e.g., secretory tissues, tissues abundant in structural proteins are also tissues in which gene expression is relatively rare on the X chromosome. These trends cannot be fully accounted for in terms of alternative models of biased expression. In conclusion, the notion that it is hard for genes on the Therian X to be highly expressed, owing to transcriptional traffic jams, provides a simple yet robustly supported rationale of many peculiar features of X's gene content, gene expression, and evolution.

  20. The Constrained Maximal Expression Level Owing to Haploidy Shapes Gene Content on the Mammalian X Chromosome

    Science.gov (United States)

    Hurst, Laurence D.; Ghanbarian, Avazeh T.; Forrest, Alistair R. R.; Huminiecki, Lukasz

    2015-01-01

    profiles of X-linked genes. Tissues whose tissue-specific genes are very highly expressed (e.g., secretory tissues, tissues abundant in structural proteins) are also tissues in which gene expression is relatively rare on the X chromosome. These trends cannot be fully accounted for in terms of alternative models of biased expression. In conclusion, the notion that it is hard for genes on the Therian X to be highly expressed, owing to transcriptional traffic jams, provides a simple yet robustly supported rationale of many peculiar features of X’s gene content, gene expression, and evolution. PMID:26685068

  1. The Constrained Maximal Expression Level Owing to Haploidy Shapes Gene Content on the Mammalian X Chromosome.

    Science.gov (United States)

    Hurst, Laurence D; Ghanbarian, Avazeh T; Forrest, Alistair R R; Huminiecki, Lukasz

    2015-12-01

    profiles of X-linked genes. Tissues whose tissue-specific genes are very highly expressed (e.g., secretory tissues, tissues abundant in structural proteins) are also tissues in which gene expression is relatively rare on the X chromosome. These trends cannot be fully accounted for in terms of alternative models of biased expression. In conclusion, the notion that it is hard for genes on the Therian X to be highly expressed, owing to transcriptional traffic jams, provides a simple yet robustly supported rationale of many peculiar features of X's gene content, gene expression, and evolution.

  2. The Constrained Maximal Expression Level Owing to Haploidy Shapes Gene Content on the Mammalian X Chromosome

    KAUST Repository

    Hurst, Laurence D.

    2015-12-18

    profiles of X-linked genes. Tissues whose tissue-specific genes are very highly expressed (e.g., secretory tissues, tissues abundant in structural proteins) are also tissues in which gene expression is relatively rare on the X chromosome. These trends cannot be fully accounted for in terms of alternative models of biased expression. In conclusion, the notion that it is hard for genes on the Therian X to be highly expressed, owing to transcriptional traffic jams, provides a simple yet robustly supported rationale of many peculiar features of X’s gene content, gene expression, and evolution.

  3. Polo-Like Kinase 3 Appears Dispensable for Normal Retinal Development Despite Robust Embryonic Expression.

    Directory of Open Access Journals (Sweden)

    Jillian J Goetz

    Full Text Available During retinogenesis seven different cell types are generated in distinct yet overlapping timepoints from a population of retinal progenitor cells. Previously, we performed single cell transcriptome analyses of retinal progenitor cells to identify candidate genes that may play roles in the generation of early-born retinal neurons. Based on its expression pattern in subsets of early retinal cells, polo-like kinase 3 (Plk3 was identified as one such candidate gene. Further characterization of Plk3 expression by in situ hybridization revealed that this gene is expressed as cells exit the cell cycle. We obtained a Plk3 deficient mouse and investigated changes in the retina's morphology and transcriptome through immunohistochemistry, in situ hybridization and gene expression profiling. These experiments have been performed initially on adult mice and subsequently extended throughout retinal development. Although morphological studies revealed no consistent changes in retinogenesis upon Plk3 loss, microarray profiling revealed potential candidate genes altered in Plk3-KO mice. Further studies will be necessary to understand the connection between these changes in gene expression and the loss of a protein kinase such as Plk3.

  4. 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.

  5. 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.

  6. Vitamin D-mediated gene expression.

    Science.gov (United States)

    Lowe, K E; Maiyar, A C; Norman, A W

    1992-01-01

    The steroid hormone 1,25(OH)2D3 modulates the expression of a wide variety of genes in a tissue- and developmentally specific manner. It is well established that 1,25(OH)2D3 can up- or downregulate the expression of genes involved in cell proliferation, differentiation, and mineral homeostasis. The hormone exerts its genomic effects via interactions with the vitamin D receptor or VDR, a member of the superfamily of hormone-activated nuclear receptors which can regulate eukaryotic gene expression. The ligand-bound receptor acts as a transcription factor that binds to specific DNA sequences, HREs, in target gene promoters. The DNA-binding domains of the steroid hormone receptors are highly conserved and contain two zinc-finger motifs that recognize the HREs. The spacing and orientation of the HRE half-sites, as well as the HRE sequence, are critical for proper discrimination by the various receptors. Other nuclear factors such as fos and jun can influence vitamin D-mediated gene expression. A wide range of experimental techniques has been used to increase our understanding of how 1,25(OH)2D3 and its receptor play a central role in gene expression.

  7. Modulation of imprinted gene expression following superovulation.

    Science.gov (United States)

    Fortier, Amanda L; McGraw, Serge; Lopes, Flavia L; Niles, Kirsten M; Landry, Mylène; Trasler, Jacquetta M

    2014-05-05

    Although assisted reproductive technologies increase the risk of low birth weight and genomic imprinting disorders, the precise underlying causes remain unclear. Using a mouse model, we previously showed that superovulation alters the expression of imprinted genes in the placenta at 9.5days (E9.5) of gestation. Here, we investigate whether effects of superovulation on genomic imprinting persisted at later stages of development and assess the surviving fetuses for growth and morphological abnormalities. Superovulation, followed by embryo transfer at E3.5, as compared to spontaneous ovulation (controls), resulted in embryos of normal size and weight at 14.5 and 18.5days of gestation. The normal monoallelic expression of the imprinted genes H19, Snrpn and Kcnq1ot1 was unaffected in either the placentae or the embryos from the superovulated females at E14.5 or E18.5. However, for the paternally expressed imprinted gene Igf2, superovulation generated placentae with reduced production of the mature protein at E9.5 and significantly more variable mRNA levels at E14.5. We propose that superovulation results in the ovulation of abnormal oocytes with altered expression of imprinted genes, but that the coregulated genes of the imprinted gene network result in modulated expression. Copyright © 2014. Published by Elsevier Ireland Ltd.

  8. Gene expression of the endolymphatic sac.

    Science.gov (United States)

    Friis, Morten; Martin-Bertelsen, Tomas; Friis-Hansen, Lennart; Winther, Ole; Henao, Ricardo; Sørensen, Mads Sølvsten; Qvortrup, Klaus

    2011-12-01

    The endolymphatic sac is part of the membranous inner ear and is thought to play a role in the fluid homeostasis and immune defense of the inner ear; however, the exact function of the endolymphatic sac is not fully known. Many of the detected mRNAs in this study suggest that the endolymphatic sac has multiple and diverse functions in the inner ear. 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. 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. In all, 463 genes were identified specific for the endolymphatic sac. Functional annotation clustering revealed 29 functional clusters.

  9. Regulation of gene expression in human tendinopathy

    Science.gov (United States)

    2011-01-01

    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. PMID:21539748

  10. An Analysis of Gene Expression Data using Penalized Fuzzy C-Means Approach

    OpenAIRE

    Banu, P. K. Nizar; Inbarani, H. Hannah

    2013-01-01

    With the rapid advances of microarray technologies, large amounts of high-dimensional gene expression data are being generated, which poses significant computational challenges. A first step towards addressing this challenge is the use of clustering techniques, which is essential in the data mining process to reveal natural structures and identify interesting patterns in the underlying data. A robust gene expression clustering approach to minimize undesirable clustering is proposed. In this p...

  11. Noise minimization in eukaryotic gene expression.

    Directory of Open Access Journals (Sweden)

    Hunter B Fraser

    2004-06-01

    Full Text Available 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.

  12. 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.

  13. Paternally expressed genes predominate in the placenta.

    Science.gov (United States)

    Wang, Xu; Miller, Donald C; Harman, Rebecca; Antczak, Douglas F; Clark, Andrew G

    2013-06-25

    The discovery of genomic imprinting through studies of manipulated mouse embryos indicated that the paternal genome has a major influence on placental development. However, previous research has not demonstrated paternal bias in imprinted genes. We applied RNA sequencing to trophoblast tissue from reciprocal hybrids of horse and donkey, where genotypic differences allowed parent-of-origin identification of most expressed genes. Using this approach, we identified a core group of 15 ancient imprinted genes, of which 10 were paternally expressed. An additional 78 candidate imprinted genes identified by RNA sequencing also showed paternal bias. Pyrosequencing was used to confirm the imprinting status of six of the genes, including the insulin receptor (INSR), which may play a role in growth regulation with its reciprocally imprinted ligand, histone acetyltransferase-1 (HAT1), a gene involved in chromatin modification, and lymphocyte antigen 6 complex, locus G6C, a newly identified imprinted gene in the major histocompatibility complex. The 78 candidate imprinted genes displayed parent-of-origin expression bias in placenta but not fetus, and most showed less than 100% silencing of the imprinted allele. Some displayed variability in imprinting status among individuals. This variability results in a unique epigenetic signature for each placenta that contributes to variation in the intrauterine environment and thus presents the opportunity for natural selection to operate on parent-of-origin differential regulation. Taken together, these features highlight the plasticity of imprinting in mammals and the central importance of the placenta as a target tissue for genomic imprinting.

  14. Soybean physiology and gene expression during drought.

    Science.gov (United States)

    Stolf-Moreira, R; Medri, M E; Neumaier, N; Lemos, N G; Pimenta, J A; Tobita, S; Brogin, R L; Marcelino-Guimarães, F C; Oliveira, M C N; Farias, J R B; Abdelnoor, R V; Nepomuceno, A L

    2010-10-05

    Soybean genotypes MG/BR46 (Conquista) and BR16, drought-tolerant and -sensitive, respectively, were compared in terms of morphophysiological and gene-expression responses to water stress during two stages of development. Gene-expression analysis showed differential responses in Gmdreb1a and Gmpip1b mRNA expression within 30 days of water-deficit initiation in MG/BR46 (Conquista) plants. Within 45 days of initiating stress, Gmp5cs and Gmpip1b had relatively higher expression. Initially, BR16 showed increased expression only for Gmdreb1a, and later (45 days) for Gmp5cs, Gmdefensin and Gmpip1b. Only BR16 presented down-regulated expression of genes, such as Gmp5cs and Gmpip1b, 30 days after the onset of moisture stress, and Gmgols after 45 days of stress. The faster perception of water stress in MG/BR46 (Conquista) and the better maintenance of up-regulated gene expression than in the sensitive BR16 genotype imply mechanisms by which the former is better adapted to tolerate moisture deficiency.

  15. Early gene expression changes with rush immunotherapy

    Directory of Open Access Journals (Sweden)

    Barnett Sherry

    2011-09-01

    Full Text Available Abstract Background To examine whether whole genome expression profiling could reveal changes in mRNA expression of peripheral blood mononuclear cells (PBMC from allergic patients undergoing rush immunotherapy (RIT that might be manifest within the first few months of treatment. Methods For this study, PBMC from three allergic patients undergoing RIT were assessed at four timepoints: prior to RIT, at 1 week and 7 week post-RIT, during build-up and at 4 months, after establishment of a maintenance dose. PBMC mRNA gene expression changes over time were determined by oligonucleotide microarrays using the Illumina Human-6 BeadChip Platform, which simultaneously interrogates expression profiles of > 47,000 transcripts. Differentially expressed genes were identified using well-established statistical analysis for microarrays. In addition, we analyzed peripheral blood basophil high-affinity IgE receptor (Fc epsilon RI expression and T-regulatory cell frequency as detected by expression of CD3+CD4+CD25bright cells at each timepoint using flow cytometry. Results In comparing the initial 2 timepoints with the final 2 timepoints and analyzing for genes with ≥1.5-fold expression change (p less than or equal to 0.05, BH-FDR, we identified 507 transcripts. At a 2-fold change (p less than or equal to 0.05, BH-FDR, we found 44 transcripts. Of these, 28 were up-regulated and 16 were down-regulated genes. From these datasets, we have identified changes in immunologically relevant genes from both the innate and adaptive response with upregulation of expressed genes for molecules including IL-1β, IL-8, CD40L, BTK and BCL6. At the 4 month timepoint, we noted a downward trend in Fc epsilon RI expression in each of the three patients and increased allergen-specific IgG4 levels. No change was seen in the frequency of peripheral T-regulatory cells expressed over the four timepoints. Conclusions We observed significant changes in gene expression early in peripheral

  16. The effects of antenatal depression and antidepressant treatment on placental gene expression

    Directory of Open Access Journals (Sweden)

    Jocelien DA Olivier

    2015-01-01

    Full Text Available The effects of antenatal depression and antidepressant treatment during pregnancy on both mother and child are vigorously studied, but the underlying biology for these effects is largely unknown. The placenta plays a crucial role in the growth and development of the fetus. We performed a gene expression study on the fetal side of the placenta to investigate gene expression patterns in mothers with antenatal depression and in mothers using antidepressant treatment during pregnancy.Placental samples from mothers with normal pregnancies, from mothers with antenatal depression, and from mothers using antidepressants were collected. We performed a pilot microarray study to investigate alterations in the gene expression and selected several genes from the microarray for biological validation with qPCR in a larger sample.In mothers with antenatal depression 108 genes were differentially expressed, whereas 109 genes were differentially expressed in those using antidepressants. Validation of the microarray revealed more robust gene expression differences in the seven genes picked for confirmation in antidepressant-treated women than in depressed women. Among the genes that were validated ROCK2 and C12orf39 were differentially expressed in both depressed and antidepressant-treated women, whereas ROCK1, GCC2, KTN1, and DNM1L were only differentially expressed in the antidepressant-treated women. In conclusion, antenatal depression and antidepressant exposure during pregnancy are associated with altered gene expression in the placenta. Findings on those genes picked for validation were more robust among antidepressant-treated women than in depressed women, possibly due to the fact that depression is a multifactorial condition with varying degrees of endocrine disruption. It remains to be established whether the alterations found in the gene expression of the placenta are found in the fetus as well.

  17. 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.

  18. Gene expression profiling for targeted cancer treatment.

    Science.gov (United States)

    Yuryev, Anton

    2015-01-01

    There is certain degree of frustration and discontent in the area of microarray gene expression data analysis of cancer datasets. It arises from the mathematical problem called 'curse of dimensionality,' which is due to the small number of samples available in training sets, used for calculating transcriptional signatures from the large number of differentially expressed (DE) genes, measured by microarrays. The new generation of causal reasoning algorithms can provide solutions to the curse of dimensionality by transforming microarray data into activity of a small number of cancer hallmark pathways. This new approach can make feature space dimensionality optimal for mathematical signature calculations. The author reviews the reasons behind the current frustration with transcriptional signatures derived from DE genes in cancer. He also provides an overview of the novel methods for signature calculations based on differentially variable genes and expression regulators. Furthermore, the authors provide perspectives on causal reasoning algorithms that use prior knowledge about regulatory events described in scientific literature to identify expression regulators responsible for the differential expression observed in cancer samples. The author advocates causal reasoning methods to calculate cancer pathway activity signatures. The current challenge for these algorithms is in ensuring quality of the knowledgebase. Indeed, the development of cancer hallmark pathway collections, together with statistical algorithms to transform activity of expression regulators into pathway activity, are necessary for causal reasoning to be used in cancer research.

  19. [Ribozyme riboswitch based gene expression regulation systems for gene therapy applications: progress and challenges].

    Science.gov (United States)

    Feng, Jing-Xian; Wang, Jia-wen; Lin, Jun-sheng; Diao, Yong

    2014-11-01

    Robust and efficient control of therapeutic gene expression is needed for timing and dosing of gene therapy drugs in clinical applications. Ribozyme riboswitch provides a promising building block for ligand-controlled gene-regulatory system, based on its property that exhibits tunable gene regulation, design modularity, and target specificity. Ribozyme riboswitch can be used in various gene delivery vectors. In recent years, there have been breakthroughs in extending ribozyme riboswitch's application from gene-expression control to cellular function and fate control. High throughput screening platforms were established, that allow not only rapid optimization of ribozyme riboswitch in a microbial host, but also straightforward transfer of selected devices exhibiting desired activities to mammalian cell lines in a predictable manner. Mathematical models were employed successfully to explore the performance of ribozyme riboswitch quantitively and its rational design predictably. However, to progress toward gene therapy relevant applications, both precision rational design of regulatory circuits and the biocompatibility of regulatory ligand are still of crucial importance.

  20. Predicting metastasized seminoma using gene expression.

    Science.gov (United States)

    Ruf, Christian G; Linbecker, Michael; Port, Matthias; Riecke, Armin; Schmelz, Hans U; Wagner, Walter; Meineke, Victor; Abend, Michael

    2012-07-01

    Treatment options for testis cancer depend on the histological subtype as well as on the clinical stage. An accurate staging is essential for correct treatment. The 'golden standard' for staging purposes is CT, but occult metastasis cannot be detected with this method. Currently, parameters such as primary tumour size, vessel invasion or invasion of the rete testis are used for predicting occult metastasis. Last year the association of these parameters with metastasis could not be validated in a new independent cohort. Gene expression analysis in testis cancer allowed discrimination between the different histological subtypes (seminoma and non-seminoma) as well as testis cancer and normal testis tissue. In a two-stage study design we (i) screened the whole genome (using human whole genome microarrays) for candidate genes associated with the metastatic stage in seminoma and (ii) validated and quantified gene expression of our candidate genes (real-time quantitative polymerase chain reaction) on another independent group. Gene expression measurements of two of our candidate genes (dopamine receptor D1 [DRD1] and family with sequence similarity 71, member F2 [FAM71F2]) examined in primary testis cancers made it possible to discriminate the metastasis status in seminoma. The discriminative ability of the genes exceeded the predictive significance of currently used histological/pathological parameters. Based on gene expression analysis the present study provides suggestions for improved individual decision making either in favour of early adjuvant therapy or increased surveillance. To evaluate the usefulness of gene expression profiling for predicting metastatic status in testicular seminoma at the time of first diagnosis compared with established clinical and pathological parameters. Total RNA was isolated from testicular tumours of metastasized patients (12 patients, clinical stage IIa-III), non-metastasized patients (40, clinical stage I) and adjacent 'normal' tissue

  1. Gene expression profiles in skeletal muscle after gene electrotransfer

    DEFF Research Database (Denmark)

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

    2007-01-01

    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......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......) 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...

  2. 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

  3. Lithium ions induce prestalk-associated gene expression and inhibit prespore gene expression in Dictyostelium discoideum

    NARCIS (Netherlands)

    Peters, Dorien J.M.; Lookeren Campagne, Michiel M. van; Haastert, Peter J.M. van; Spek, Wouter; Schaap, Pauline

    1989-01-01

    We investigated the effect of Li+ on two types of cyclic AMP-regulated gene expression and on basal and cyclic AMP-stimulated inositol 1,4,5-trisphosphate (Ins(1,4,5)P3) levels. Li+ effectively inhibits cyclic AMP-induced prespore gene expression, half-maximal inhibition occurring at about 2mM-LiCl.

  4. Robust Facial Expression Recognition via Sparse Representation and Multiple Gabor filters

    Directory of Open Access Journals (Sweden)

    Rania Salah El-Sayed

    2013-04-01

    Full Text Available Facial expressions recognition plays important role in human communication. It has become one of the most challenging tasks in the pattern recognition field. It has many applications such as: human computer interaction, video surveillance, forensic applications, criminal investigations, and in many other fields. In this paper we propose a method for facial expression recognition (FER. This method provides new insights into two issues in FER: feature extraction and robustness. For feature extraction we are using sparse representation approach after applying multiple Gabor filter and then using support vector machine (SVM as classifier. We conduct extensive experiments on standard facial expressions database to verify the performance of proposed method. And we compare the result with other approach.

  5. Defining the robust behaviour of the plant clock gene circuit with absolute RNA timeseries and open infrastructure.

    Science.gov (United States)

    Flis, Anna; Fernández, Aurora Piñas; Zielinski, Tomasz; Mengin, Virginie; Sulpice, Ronan; Stratford, Kevin; Hume, Alastair; Pokhilko, Alexandra; Southern, Megan M; Seaton, Daniel D; McWatters, Harriet G; Stitt, Mark; Halliday, Karen J; Millar, Andrew J

    2015-10-01

    Our understanding of the complex, transcriptional feedback loops in the circadian clock mechanism has depended upon quantitative, timeseries data from disparate sources. We measure clock gene RNA profiles in Arabidopsis thaliana seedlings, grown with or without exogenous sucrose, or in soil-grown plants and in wild-type and mutant backgrounds. The RNA profiles were strikingly robust across the experimental conditions, so current mathematical models are likely to be broadly applicable in leaf tissue. In addition to providing reference data, unexpected behaviours included co-expression of PRR9 and ELF4, and regulation of PRR5 by GI. Absolute RNA quantification revealed low levels of PRR9 transcripts (peak approx. 50 copies cell(-1)) compared with other clock genes, and threefold higher levels of LHY RNA (more than 1500 copies cell(-1)) than of its close relative CCA1. The data are disseminated from BioDare, an online repository for focused timeseries data, which is expected to benefit mechanistic modelling. One data subset successfully constrained clock gene expression in a complex model, using publicly available software on parallel computers, without expert tuning or programming. We outline the empirical and mathematical justification for data aggregation in understanding highly interconnected, dynamic networks such as the clock, and the observed design constraints on the resources required to make this approach widely accessible. © 2015 The Authors.

  6. Polyandry and sex-specific gene expression.

    Science.gov (United States)

    Mank, Judith E; Wedell, Nina; Hosken, David J

    2013-03-05

    Polyandry is widespread in nature, and has important evolutionary consequences for the evolution of sexual dimorphism and sexual conflict. Although many of the phenotypic consequences of polyandry have been elucidated, our understanding of the impacts of polyandry and mating systems on the genome is in its infancy. Polyandry can intensify selection on sexual characters and generate more intense sexual conflict. This has consequences for sequence evolution, but also for sex-biased gene expression, which acts as a link between mating systems, sex-specific selection and the evolution of sexual dimorphism. We discuss this and the remarkable confluence of sexual-conflict theory and patterns of gene expression, while also making predictions about transcription patterns, mating systems and sexual conflict. Gene expression is a key link in the genotype-phenotype chain, and although in its early stages, understanding the sexual selection-transcription relationship will provide significant insights into this critical association.

  7. 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.

  8. Gene expression profiles in irradiated cancer cells

    Science.gov (United States)

    Minafra, L.; Bravatà, V.; Russo, G.; Ripamonti, M.; Gilardi, M. C.

    2013-07-01

    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. Gene expression profiles in irradiated cancer cells

    Energy Technology Data Exchange (ETDEWEB)

    Minafra, L.; Bravatà, V.; Russo, G.; Ripamonti, M.; Gilardi, M. C. [IBFM CNR - LATO, Cefalù, Segrate (Italy)

    2013-07-26

    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.

  10. Gene Expression in the Human Endolymphatic Sac

    DEFF Research Database (Denmark)

    Møller, Martin Nue; Kirkeby, Svend; Vikeså, Jonas

    2015-01-01

    OBJECTIVES/HYPOTHESIS: The purpose of the present study is to explore, demonstrate, and describe the expression of genes related to the solute carrier (SLC) molecules of ion transporters in the human endolymphatic sac. STUDY DESIGN: cDNA microarrays and immunohistochemistry were used for analyses...... of fresh human endolymphatic sac tissue samples. METHODS: Twelve tissue samples of the human endolymphatic sac were obtained during translabyrinthine surgery for vestibular schwannoma. Microarray technology was used to investigate tissue sample expression of solute carrier family genes, using adjacent dura...... mater as control. Immunohistochemistry was used for verification of translation of selected genes, as well as localization of the specific protein within the sac. RESULTS: An extensive representation of the SLC family genes were upregulated in the human endolymphatic sac, including SLC26a4 Pendrin, SLC4...

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

    Science.gov (United States)

    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

    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 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 these robustly defined disease modules is significantly enriched with brain-expressed genes and with genetic variants that were implicated in a GWAS study, which could imply a causal role in schizophrenia etiology. The most highly connected intramodular hub gene in this module (ABCF1), is located in, and regulated by the major histocompatibility (MHC) complex, which is intriguing in light of the fact that common allelic variants from the MHC region have been implicated in schizophrenia. This suggests that the MHC increases schizophrenia susceptibility via altered gene expression of regulatory genes in this network.

  12. Exosome-associated AAV2 vector mediates robust gene delivery into the murine retina upon intravitreal injection

    Science.gov (United States)

    Wassmer, Sarah J.; Carvalho, Livia S.; György, Bence; Vandenberghe, Luk H.; Maguire, Casey A.

    2017-01-01

    Widespread gene transfer to the retina is challenging as it requires vector systems to overcome physical and biochemical barriers to enter and diffuse throughout retinal tissue. We investigated whether exosome-associated adeno-associated virus, (exo-AAV) enabled broad retinal targeting following intravitreal (IVT) injection, as exosomes have been shown to traverse biological barriers and mediate widespread distribution upon systemic injection. We packaged an AAV genome encoding green fluorescent protein (GFP) into conventional AAV2 and exo-AAV2 vectors. Vectors were IVT injected into the eyes of adult mice. GFP expression was noninvasively monitored by fundus imaging and retinal expression was analyzed 4 weeks post-injection by qRT-PCR and histology. Exo-AAV2 outperformed conventional AAV2 in GFP expression based on fundus image analysis and qRT-PCR. Exo-AAV2 demonstrated deeper penetration in the retina, efficiently reaching the inner nuclear and outer plexiform, and to a lesser extent the outer nuclear layer. Cell targets were ganglion cells, bipolar cells, Müller cells, and photoreceptors. Exo-AAV2 serves as a robust gene delivery tool for murine retina, and the simplicity of production and isolation should make it widely applicable to basic research of the eye. PMID:28361998

  13. 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

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

    Directory of Open Access Journals (Sweden)

    Urbanski Henryk F

    2010-06-01

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

  16. Mechanical Feedback and Arrest in Gene Expression

    Science.gov (United States)

    Sevier, Stuart; Levine, Herbert

    The ability to watch biochemical events at the single-molecule level has increasingly revealed that stochasticity plays a leading role in many biological phenomena. One important and well know example is the noisy, ``bursty'' manner of transcription. Recent experiments have revealed relationships between the level and noise in gene expression hinting at deeper stochastic connections. In this talk we will discuss how the mechanical nature of transcription can explain this relationship and examine the limits that the physical aspects of transcription place on gene expression.

  17. 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.

  18. Optogenetics for gene expression in mammalian cells.

    Science.gov (United States)

    Müller, Konrad; Naumann, Sebastian; Weber, Wilfried; Zurbriggen, Matias D

    2015-02-01

    Molecular switches that are controlled by chemicals have evolved as central research instruments in mammalian cell biology. However, these tools are limited in terms of their spatiotemporal resolution due to freely diffusing inducers. These limitations have recently been addressed by the development of optogenetic, genetically encoded, and light-responsive tools that can be controlled with the unprecedented spatiotemporal precision of light. In this article, we first provide a brief overview of currently available optogenetic tools that have been designed to control diverse cellular processes. Then, we focus on recent developments in light-controlled gene expression technologies and provide the reader with a guideline for choosing the most suitable gene expression system.

  19. Genes Expressed in Human Tumor Endothelium

    Science.gov (United States)

    St. Croix, Brad; Rago, Carlo; Velculescu, Victor; Traverso, Giovanni; Romans, Katharine E.; Montgomery, Elizabeth; Lal, Anita; Riggins, Gregory J.; Lengauer, Christoph; Vogelstein, Bert; Kinzler, Kenneth W.

    2000-08-01

    To gain a molecular understanding of tumor angiogenesis, we compared gene expression patterns of endothelial cells derived from blood vessels of normal and malignant colorectal tissues. Of over 170 transcripts predominantly expressed in the endothelium, 79 were differentially expressed, including 46 that were specifically elevated in tumor-associated endothelium. Several of these genes encode extracellular matrix proteins, but most are of unknown function. Most of these tumor endothelial markers were expressed in a wide range of tumor types, as well as in normal vessels associated with wound healing and corpus luteum formation. These studies demonstrate that tumor and normal endothelium are distinct at the molecular level, a finding that may have significant implications for the development of anti-angiogenic therapies.

  20. [Imprinting genes and it's expression in Arabidopsis].

    Science.gov (United States)

    Zhang, Hong-Yu; Xu, Pei-Zhou; Yang, Hua; Wu, Xian-Jun

    2010-07-01

    Genomic imprinting refers to the phenomenon that the expression of a gene copy depends on its parent of origin. The Arabidopsis imprinted FIS (Fertilisation-independent seed) genes, mea, fis2, and fie, play essential roles in the repression of central cell and the regulation of early endosperm development. fis mutants display two phenotypes: autonomous diploid endosperm development when fertilization is absent and un-cellularised endosperm formation when fertilization occurs. The FIS Polycomb protein complex including the above three FIS proteins catalyzes histone H3 K27 tri-methylation on target loci. DME (DEMETER), a DNA glycosylase, and AtMET1 (Methyltransferase1), a DNA methyltransferase, are involved in the regulation of imprinted expression of both mea and fis2. This review summarizes the studies on the Arabidopsis imprinted FIS genes and other related genes. Recent works have shown that the insertion of transposons may affect nearby gene expression, which may be the main driving force behind the evolution of genomic imprinting. This summary covers the achievements on Arabidopsis imprinted genes will provide important information for studies on genomic imprinting in the important crops such as rice and maize.

  1. Designing genes for successful protein expression.

    Science.gov (United States)

    Welch, Mark; Villalobos, Alan; Gustafsson, Claes; Minshull, Jeremy

    2011-01-01

    DNA sequences are now far more readily available in silico than as physical DNA. De novo gene synthesis is an increasingly cost-effective method for building genetic constructs, and effectively removes the constraint of basing constructs on extant sequences. This allows scientists and engineers to experimentally test their hypotheses relating sequence to function. Molecular biologists, and now synthetic biologists, are characterizing and cataloging genetic elements with specific functions, aiming to combine them to perform complex functions. However, the most common purpose of synthetic genes is for the expression of an encoded protein. The huge number of different proteins makes it impossible to characterize and catalog each functional gene. Instead, it is necessary to abstract design principles from experimental data: data that can be generated by making predictions followed by synthesizing sequences to test those predictions. Because of the degeneracy of the genetic code, design of gene sequences to encode proteins is a high-dimensional problem, so there is no single simple formula to guarantee success. Nevertheless, there are several straightforward steps that can be taken to greatly increase the probability that a designed sequence will result in expression of the encoded protein. In this chapter, we discuss gene sequence parameters that are important for protein expression. We also describe algorithms for optimizing these parameters, and troubleshooting procedures that can be helpful when initial attempts fail. Finally, we show how many of these methods can be accomplished using the synthetic biology software tool Gene Designer.

  2. Genes of periodontopathogens expressed during human disease.

    Science.gov (United States)

    Song, Yo-Han; Kozarov, Emil V; Walters, Sheila M; Cao, Sam Linsen; Handfield, Martin; Hillman, Jeffrey D; Progulske-Fox, Ann

    2002-12-01

    Since many bacterial genes are environmentally regulated, the screening for virulence-associated factors using classical genetic and molecular biology approaches can be biased under laboratory growth conditions of a given pathogen, because the required conditions for expression of many virulence factors may not occur during in vitro growth. Thus, technologies have been developed during the past several years to identify genes that are expressed during disease using animal models of human disease. However, animal models are not always truly representative of human disease, and with many pathogens, there is no appropriate animal model. A new technology, in vivo-induced antigen technology (IVIAT) was thus engineered and tested in our laboratory to screen for genes of pathogenic organisms induced specifically in humans, without the use of animal or artificial models of infection. This technology uses pooled sera from patients to probe for genes expressed exclusively in vivo (or ivi, in vivo-induced genes). IVIAT was originally designed for the study of Actinobacillus actinomycetemcomitans pathogenesis, but we have now extended it to other oral pathogens including Porphyromonas gingivalis. One hundred seventy-one thousand (171,000) clones from P. gingivalis strain W83 were screened and 144 were confirmed positive. Over 300,000 A. actinomycetemcomitans clones were probed, and 116 were confirmed positive using a quantitative blot assay. MAT has proven useful in identifying previously unknown in vivo-induced genes that are likely involved in virulence and are thus excellent candidates for use in diagnostic : and therapeutic strategies, including vaccine design.

  3. Sequence and gene expression evolution of paralogous genes in willows.

    Science.gov (United States)

    Harikrishnan, Srilakshmy L; Pucholt, Pascal; Berlin, Sofia

    2015-12-22

    Whole genome duplications (WGD) have had strong impacts on species diversification by triggering evolutionary novelties, however, relatively little is known about the balance between gene loss and forces involved in the retention of duplicated genes originating from a WGD. We analyzed putative Salicoid duplicates in willows, originating from the Salicoid WGD, which took place more than 45 Mya. Contigs were constructed by de novo assembly of RNA-seq data derived from leaves and roots from two genotypes. Among the 48,508 contigs, 3,778 pairs were, based on fourfold synonymous third-codon transversion rates and syntenic positions, predicted to be Salicoid duplicates. Both copies were in most cases expressed in both tissues and 74% were significantly differentially expressed. Mean Ka/Ks was 0.23, suggesting that the Salicoid duplicates are evolving by purifying selection. Gene Ontology enrichment analyses showed that functions related to DNA- and nucleic acid binding were over-represented among the non-differentially expressed Salicoid duplicates, while functions related to biosynthesis and metabolism were over-represented among the differentially expressed Salicoid duplicates. We propose that the differentially expressed Salicoid duplicates are regulatory neo- and/or subfunctionalized, while the non-differentially expressed are dose sensitive, hence, functionally conserved. Multiple evolutionary processes, thus drive the retention of Salicoid duplicates in willows.

  4. A comparative analysis of biclustering algorithms for gene expression data.

    Science.gov (United States)

    Eren, Kemal; Deveci, Mehmet; Küçüktunç, Onur; Çatalyürek, Ümit V

    2013-05-01

    The need to analyze high-dimension biological data is driving the development of new data mining methods. Biclustering algorithms have been successfully applied to gene expression data to discover local patterns, in which a subset of genes exhibit similar expression levels over a subset of conditions. However, it is not clear which algorithms are best suited for this task. Many algorithms have been published in the past decade, most of which have been compared only to a small number of algorithms. Surveys and comparisons exist in the literature, but because of the large number and variety of biclustering algorithms, they are quickly outdated. In this article we partially address this problem of evaluating the strengths and weaknesses of existing biclustering methods. We used the BiBench package to compare 12 algorithms, many of which were recently published or have not been extensively studied. The algorithms were tested on a suite of synthetic data sets to measure their performance on data with varying conditions, such as different bicluster models, varying noise, varying numbers of biclusters and overlapping biclusters. The algorithms were also tested on eight large gene expression data sets obtained from the Gene Expression Omnibus. Gene Ontology enrichment analysis was performed on the resulting biclusters, and the best enrichment terms are reported. Our analyses show that the biclustering method and its parameters should be selected based on the desired model, whether that model allows overlapping biclusters, and its robustness to noise. In addition, we observe that the biclustering algorithms capable of finding more than one model are more successful at capturing biologically relevant clusters.

  5. Reshaping of global gene expression networks and sex‐biased gene expression by integration of a young gene

    National Research Council Canada - National Science Library

    Chen, Sidi; Ni, Xiaochun; Krinsky, Benjamin H; Zhang, Yong E; Vibranovski, Maria D; White, Kevin P; Long, Manyuan

    2012-01-01

    ...‐biased gene expression in Drosophila . This 4–6 million‐year‐old factor, named Zeus for its role in male fecundity, originated through retroposition of a highly conserved housekeeping gene, Caf40...

  6. The TRANSFAC system on gene expression regulation.

    Science.gov (United States)

    Wingender, E; Chen, X; Fricke, E; Geffers, R; Hehl, R; Liebich, I; Krull, M; Matys, V; Michael, H; Ohnhäuser, R; Prüss, M; Schacherer, F; Thiele, S; Urbach, S

    2001-01-01

    The TRANSFAC database on transcription factors and their DNA-binding sites and profiles (http://www.gene-regulation.de/) has been quantitatively extended and supplemented by a number of modules. These modules give information about pathologically relevant mutations in regulatory regions and transcription factor genes (PathoDB), scaffold/matrix attached regions (S/MARt DB), signal transduction (TRANSPATH) and gene expression sources (CYTOMER). Altogether, these distinct database modules constitute the TRANSFAC system. They are accompanied by a number of program routines for identifying potential transcription factor binding sites or for localizing individual components in the regulatory network of a cell.

  7. Threshold-dominated regulation hides genetic variation in gene expression networks

    Directory of Open Access Journals (Sweden)

    Plahte Erik

    2007-12-01

    Full Text Available Abstract Background In dynamical models with feedback and sigmoidal response functions, some or all variables have thresholds around which they regulate themselves or other variables. A mathematical analysis has shown that when the dose-response functions approach binary or on/off responses, any variable with an equilibrium value close to one of its thresholds is very robust to parameter perturbations of a homeostatic state. We denote this threshold robustness. To check the empirical relevance of this phenomenon with response function steepnesses ranging from a near on/off response down to Michaelis-Menten conditions, we have performed a simulation study to investigate the degree of threshold robustness in models for a three-gene system with one downstream gene, using several logical input gates, but excluding models with positive feedback to avoid multistationarity. Varying parameter values representing functional genetic variation, we have analysed the coefficient of variation (CV of the gene product concentrations in the stable state for the regulating genes in absolute terms and compared to the CV for the unregulating downstream gene. The sigmoidal or binary dose-response functions in these models can be considered as phenomenological models of the aggregated effects on protein or mRNA expression rates of all cellular reactions involved in gene expression. Results For all the models, threshold robustness increases with increasing response steepness. The CVs of the regulating genes are significantly smaller than for the unregulating gene, in particular for steep responses. The effect becomes less prominent as steepnesses approach Michaelis-Menten conditions. If the parameter perturbation shifts the equilibrium value too far away from threshold, the gene product is no longer an effective regulator and robustness is lost. Threshold robustness arises when a variable is an active regulator around its threshold, and this function is maintained by

  8. Global state measures of the dentate gyrus gene expression system predict antidepressant-sensitive behaviors.

    Directory of Open Access Journals (Sweden)

    Benjamin A Samuels

    Full Text Available BACKGROUND: Selective serotonin reuptake inhibitors (SSRIs such as fluoxetine are the most common form of medication treatment for major depression. However, approximately 50% of depressed patients fail to achieve an effective treatment response. Understanding how gene expression systems respond to treatments may be critical for understanding antidepressant resistance. METHODS: We take a novel approach to this problem by demonstrating that the gene expression system of the dentate gyrus responds to fluoxetine (FLX, a commonly used antidepressant medication, in a stereotyped-manner involving changes in the expression levels of thousands of genes. The aggregate behavior of this large-scale systemic response was quantified with principal components analysis (PCA yielding a single quantitative measure of the global gene expression system state. RESULTS: Quantitative measures of system state were highly correlated with variability in levels of antidepressant-sensitive behaviors in a mouse model of depression treated with fluoxetine. Analysis of dorsal and ventral dentate samples in the same mice indicated that system state co-varied across these regions despite their reported functional differences. Aggregate measures of gene expression system state were very robust and remained unchanged when different microarray data processing algorithms were used and even when completely different sets of gene expression levels were used for their calculation. CONCLUSIONS: System state measures provide a robust method to quantify and relate global gene expression system state variability to behavior and treatment. State variability also suggests that the diversity of reported changes in gene expression levels in response to treatments such as fluoxetine may represent different perspectives on unified but noisy global gene expression system state level responses. Studying regulation of gene expression systems at the state level may be useful in guiding new

  9. The frustrated gene: origins of eukaryotic gene expression

    OpenAIRE

    Madhani, Hiten D.

    2013-01-01

    Eukarytotic gene expression is frustrated by a series of steps that are generally not observed in prokaryotes and are therefore not essential for the basic chemistry of transcription and translation. Their evolution may have been driven by the need to defend against parasitic nucleic acids.

  10. A combined analysis of microarray gene expression studies of the human prefrontal cortex identifies genes implicated in schizophrenia.

    Science.gov (United States)

    Pérez-Santiago, Josué; Diez-Alarcia, Rebeca; Callado, Luis F; Zhang, Jin X; Chana, Gursharan; White, Cory H; Glatt, Stephen J; Tsuang, Ming T; Everall, Ian P; Meana, J Javier; Woelk, Christopher H

    2012-11-01

    Small cohort sizes and modest levels of gene expression changes in brain tissue have plagued the statistical approaches employed in microarray studies investigating the mechanism of schizophrenia. To combat these problems a combined analysis of six prior microarray studies was performed to facilitate the robust statistical analysis of gene expression data from the dorsolateral prefrontal cortex of 107 patients with schizophrenia and 118 healthy subjects. Multivariate permutation tests identified 144 genes that were differentially expressed between schizophrenia and control groups. Seventy of these genes were identified as differentially expressed in at least one component microarray study but none of these individual studies had the power to identify the remaining 74 genes, demonstrating the utility of a combined approach. Gene ontology terms and biological pathways that were significantly enriched for differentially expressed genes were related to neuronal cell-cell signaling, mesenchymal induction, and mitogen-activated protein kinase signaling, which have all previously been associated with the etiopathogenesis of schizophrenia. The differential expression of BAG3, C4B, EGR1, MT1X, NEUROD6, SST and S100A8 was confirmed by real-time quantitative PCR in an independent cohort using postmortem human prefrontal cortex samples. Comparison of gene expression between schizophrenic subjects with and without detectable levels of antipsychotics in their blood suggests that the modulation of MT1X and S100A8 may be the result of drug exposure. In conclusion, this combined analysis has resulted in a statistically robust identification of genes whose dysregulation may contribute to the mechanism of schizophrenia.

  11. 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.

  12. Identification of genes expressed during myocardial development

    Institute of Scientific and Technical Information of China (English)

    陈小圆; 陈健宏; 张碧琪; 梁瑛; 梁平

    2003-01-01

    Objective To identify genes expressed in the fetal heart that are potentially important for myocardial development and cardiomyocyte proliferation.Methods mRNAs from fetal (29 weeks) and adult cardiomyocytes were use for suppression subtractive hybridization (SSH). Both forward (fetal as tester) and reverse (adult as driver) subtractions were performed. Clones confirmed by dot-blot analysis to be differentially expressed were sequenced and analyzed.Results Differential expressions were detected for 39 out of 96 (41%) clones on forward subtraction and 24 out of 80 (30%) clones on reverse. For fetal dominating genes, 28 clones matched to 10 known genes (COL1A2, COL3A1, endomucin, HBG1, HBG2, PCBP2, LOC51144, TGFBI, vinculin and PND), 9 clones to 5 cDNAs of unknown functions (accession AK021715, AF085867, AB040948, AB051460 and AB051512) and 2 clones had homology to hEST sequences. For the reverse subtraction, all clones showed homology to mitochondrial transcripts.Conclusions We successfully applied SSH to detect those genes differentially expressed in fetal cardiac myocytes, some of which have not been shown relative to myocardial development.

  13. Stochastic gene expression conditioned on large deviations

    Science.gov (United States)

    Horowitz, Jordan M.; Kulkarni, Rahul V.

    2017-06-01

    The intrinsic stochasticity of gene expression can give rise to large fluctuations and rare events that drive phenotypic variation in a population of genetically identical cells. Characterizing the fluctuations that give rise to such rare events motivates the analysis of large deviations in stochastic models of gene expression. Recent developments in non-equilibrium statistical mechanics have led to a framework for analyzing Markovian processes conditioned on rare events and for representing such processes by conditioning-free driven Markovian processes. We use this framework, in combination with approaches based on queueing theory, to analyze a general class of stochastic models of gene expression. Modeling gene expression as a Batch Markovian Arrival Process (BMAP), we derive exact analytical results quantifying large deviations of time-integrated random variables such as promoter activity fluctuations. We find that the conditioning-free driven process can also be represented by a BMAP that has the same form as the original process, but with renormalized parameters. The results obtained can be used to quantify the likelihood of large deviations, to characterize system fluctuations conditional on rare events and to identify combinations of model parameters that can give rise to dynamical phase transitions in system dynamics.

  14. Trigger finger, tendinosis, and intratendinous gene expression.

    Science.gov (United States)

    Lundin, A-C; Aspenberg, P; Eliasson, P

    2014-04-01

    The pathogenesis of trigger finger has generally been ascribed to primary changes in the first annular ligament. In contrast, we recently found histological changes in the tendons, similar to the findings in Achilles tendinosis or tendinopathy. We therefore hypothesized that trigger finger tendons would show differences in gene expression in comparison to normal tendons in a pattern similar to what is published for Achilles tendinosis. We performed quantitative real-time polymerase chain reaction on biopsies from finger flexor tendons, 13 trigger fingers and 13 apparently healthy control tendons, to assess the expression of 10 genes which have been described to be differently expressed in tendinosis (collagen type 1a1, collagen 3a1, MMP-2, MMP-3, ADAMTS-5, TIMP-3, aggrecan, biglycan, decorin, and versican). In trigger finger tendons, collagen types 1a1 and 3a1, aggrecan and biglycan were all up-regulated, and MMP-3and TIMP-3 were down-regulated. These changes were statistically significant and have been previously described for Achilles tendinosis. The remaining four genes were not significantly altered. The changes in gene expression support the hypothesis that trigger finger is a form of tendinosis. Because trigger finger is a common condition, often treated surgically, it could provide opportunities for clinical research on tendinosis. © 2012 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

  15. 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...

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

    Science.gov (United States)

    Wong, Darren C J; Sweetman, Crystal; Ford, Christopher M

    2014-07-15

    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 biological processes may exhibit similar expression patterns across diverse sets of experimental conditions. While bioinformatics resources such as GCN analysis are widely available for efficient gene function prediction in model plant species including Arabidopsis, soybean and rice, in citrus these tools are not yet developed. We have constructed a comprehensive GCN for citrus inferred from 297 publicly available Affymetrix Genechip Citrus Genome microarray datasets, providing gene co-expression relationships at a genome-wide scale (33,000 transcripts). The comprehensive citrus GCN consists of a global GCN (condition-independent) and four condition-dependent GCNs that survey the sweet orange species only, all citrus fruit tissues, all citrus leaf tissues, or stress-exposed plants. All of these GCNs are clustered using genome-wide, gene-centric (guide) and graph clustering algorithms for flexibility of gene function prediction. For each putative cluster, gene ontology (GO) enrichment and gene expression specificity analyses were performed to enhance gene function, expression and regulation pattern prediction. The guide-gene approach was used to infer novel roles of genes involved in disease susceptibility and vitamin C metabolism, and graph-clustering approaches were used to investigate isoprenoid/phenylpropanoid metabolism in citrus peel, and citric acid catabolism via the GABA shunt in citrus fruit. Integration of citrus gene co-expression networks, functional enrichment analysis and gene

  17. Gene Expression Dynamics Inspector (GEDI): for integrative analysis of expression profiles

    Science.gov (United States)

    Eichler, Gabriel S.; Huang, Sui; Ingber, Donald E.

    2003-01-01

    Genome-wide expression profiles contain global patterns that evade visual detection in current gene clustering analysis. Here, a Gene Expression Dynamics Inspector (GEDI) is described that uses self-organizing maps to translate high-dimensional expression profiles of time courses or sample classes into animated, coherent and robust mosaics images. GEDI facilitates identification of interesting patterns of molecular activity simultaneously across gene, time and sample space without prior assumption of any structure in the data, and then permits the user to retrieve genes of interest. Important changes in genome-wide activities may be quickly identified based on 'Gestalt' recognition and hence, GEDI may be especially useful for non-specialist end users, such as physicians. AVAILABILITY: GEDI v1.0 is written in Matlab, and binary Matlab.dll files which require Matlab to run can be downloaded for free by academic institutions at http://www.chip.org/ge/gedihome.html Supplementary information: http://www.chip.org/ge/gedihome.html.

  18. Gene expression profiling of human erythroid progenitors by micro-serial analysis of gene expression.

    Science.gov (United States)

    Fujishima, Naohito; Hirokawa, Makoto; Aiba, Namiko; Ichikawa, Yoshikazu; Fujishima, Masumi; Komatsuda, Atsushi; Suzuki, Yoshiko; Kawabata, Yoshinari; Miura, Ikuo; Sawada, Ken-ichi

    2004-10-01

    We compared the expression profiles of highly purified human CD34+ cells and erythroid progenitor cells by micro-serial analysis of gene expression (microSAGE). Human CD34+ cells were purified from granulocyte colony-stimulating factor-mobilized blood stem cells, and erythroid progenitors were obtained by cultivating these cells in the presence of stem cell factor, interleukin 3, and erythropoietin. Our 10,202 SAGE tags allowed us to identify 1354 different transcripts appearing more than once. Erythroid progenitor cells showed increased expression of LRBA, EEF1A1, HSPCA, PILRB, RANBP1, NACA, and SMURF. Overexpression of HSPCA was confirmed by real-time polymerase chain reaction analysis. MicroSAGE revealed an unexpected preferential expression of several genes in erythroid progenitor cells in addition to the known functional genes, including hemoglobins. Our results provide reference data for future studies of gene expression in various hematopoietic disorders, including myelodysplastic syndrome and leukemia.

  19. 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.

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

    Science.gov (United States)

    Seita, Jun; Sahoo, Debashis; Rossi, Derrick J; Bhattacharya, Deepta; Serwold, Thomas; Inlay, Matthew A; Ehrlich, Lauren I R; Fathman, John W; Dill, David L; Weissman, Irving L

    2012-01-01

    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.

  1. 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

  2. Regulation of noise in gene expression.

    Science.gov (United States)

    Sanchez, Alvaro; Choubey, Sandeep; Kondev, Jane

    2013-01-01

    The biochemical processes leading to the synthesis of new proteins are random, as they typically involve a small number of diffusing molecules. They lead to fluctuations in the number of proteins in a single cell as a function of time and to cell-to-cell variability of protein abundances. These in turn can lead to phenotypic heterogeneity in a population of genetically identical cells. Phenotypic heterogeneity may have important consequences for the development of multicellular organisms and the fitness of bacterial colonies, raising the question of how it is regulated. Here we review the experimental evidence that transcriptional regulation affects noise in gene expression, and discuss how the noise strength is encoded in the architecture of the promoter region. We discuss how models based on specific molecular mechanisms of gene regulation can make experimentally testable predictions for how changes to the promoter architecture are reflected in gene expression noise.

  3. Fluid Mechanics, Arterial Disease, and Gene Expression.

    Science.gov (United States)

    Tarbell, John M; Shi, Zhong-Dong; Dunn, Jessilyn; Jo, Hanjoong

    2014-01-01

    This review places modern research developments in vascular mechanobiology in the context of hemodynamic phenomena in the cardiovascular system and the discrete localization of vascular disease. The modern origins of this field are traced, beginning in the 1960s when associations between flow characteristics, particularly blood flow-induced wall shear stress, and the localization of atherosclerotic plaques were uncovered, and continuing to fluid shear stress effects on the vascular lining endothelial) cells (ECs), including their effects on EC morphology, biochemical production, and gene expression. The earliest single-gene studies and genome-wide analyses are considered. The final section moves from the ECs lining the vessel wall to the smooth muscle cells and fibroblasts within the wall that are fluid me chanically activated by interstitial flow that imposes shear stresses on their surfaces comparable with those of flowing blood on EC surfaces. Interstitial flow stimulates biochemical production and gene expression, much like blood flow on ECs.

  4. Robust stratification of breast cancer subtypes using differential patterns of transcript isoform expression.

    Directory of Open Access Journals (Sweden)

    Thomas P Stricker

    2017-03-01

    Full Text Available Breast cancer, the second leading cause of cancer death of women worldwide, is a heterogenous disease with multiple different subtypes. These subtypes carry important implications for prognosis and therapy. Interestingly, it is known that these different subtypes not only have different biological behaviors, but also have distinct gene expression profiles. However, it has not been rigorously explored whether particular transcriptional isoforms are also differentially expressed among breast cancer subtypes, or whether transcript isoforms from the same sets of genes can be used to differentiate subtypes. To address these questions, we analyzed the patterns of transcript isoform expression using a small set of RNA-sequencing data for eleven Estrogen Receptor positive (ER+ subtype and fourteen triple negative (TN subtype tumors. We identified specific sets of isoforms that distinguish these tumor subtypes with higher fidelity than standard mRNA expression profiles. We found that alternate promoter usage, alternative splicing, and alternate 3'UTR usage are differentially regulated in breast cancer subtypes. Profiling of isoform expression in a second, independent cohort of 68 tumors confirmed that expression of splice isoforms differentiates breast cancer subtypes. Furthermore, analysis of RNAseq data from 594 cases from the TCGA cohort confirmed the ability of isoform usage to distinguish breast cancer subtypes. Also using our expression data, we identified several RNA processing factors that were differentially expressed between tumor subtypes and/or regulated by estrogen receptor, including YBX1, YBX2, MAGOH, MAGOHB, and PCBP2. RNAi knock-down of these RNA processing factors in MCF7 cells altered isoform expression. These results indicate that global dysregulation of splicing in breast cancer occurs in a subtype-specific and reproducible manner and is driven by specific differentially expressed RNA processing factors.

  5. The Relationship between Gene Network Structure and Expression Variation among Individuals and Species.

    Directory of Open Access Journals (Sweden)

    Karen E Sears

    2015-08-01

    Full Text Available Variation among individuals is a prerequisite of evolution by natural selection. As such, identifying the origins of variation is a fundamental goal of biology. We investigated the link between gene interactions and variation in gene expression among individuals and species using the mammalian limb as a model system. We first built interaction networks for key genes regulating early (outgrowth; E9.5-11 and late (expansion and elongation; E11-13 limb development in mouse. This resulted in an Early (ESN and Late (LSN Stage Network. Computational perturbations of these networks suggest that the ESN is more robust. We then quantified levels of the same key genes among mouse individuals and found that they vary less at earlier limb stages and that variation in gene expression is heritable. Finally, we quantified variation in gene expression levels among four mammals with divergent limbs (bat, opossum, mouse and pig and found that levels vary less among species at earlier limb stages. We also found that variation in gene expression levels among individuals and species are correlated for earlier and later limb development. In conclusion, results are consistent with the robustness of the ESN buffering among-individual variation in gene expression levels early in mammalian limb development, and constraining the evolution of early limb development among mammalian species.

  6. 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

  7. Shrinkage covariance matrix approach based on robust trimmed mean in gene sets detection

    Science.gov (United States)

    Karjanto, Suryaefiza; Ramli, Norazan Mohamed; Ghani, Nor Azura Md; Aripin, Rasimah; Yusop, Noorezatty Mohd

    2015-02-01

    Microarray involves of placing an orderly arrangement of thousands of gene sequences in a grid on a suitable surface. The technology has made a novelty discovery since its development and obtained an increasing attention among researchers. The widespread of microarray technology is largely due to its ability to perform simultaneous analysis of thousands of genes in a massively parallel manner in one experiment. Hence, it provides valuable knowledge on gene interaction and function. The microarray data set typically consists of tens of thousands of genes (variables) from just dozens of samples due to various constraints. Therefore, the sample covariance matrix in Hotelling's T2 statistic is not positive definite and become singular, thus it cannot be inverted. In this research, the Hotelling's T2 statistic is combined with a shrinkage approach as an alternative estimation to estimate the covariance matrix to detect significant gene sets. The use of shrinkage covariance matrix overcomes the singularity problem by converting an unbiased to an improved biased estimator of covariance matrix. Robust trimmed mean is integrated into the shrinkage matrix to reduce the influence of outliers and consequently increases its efficiency. The performance of the proposed method is measured using several simulation designs. The results are expected to outperform existing techniques in many tested conditions.

  8. Topological features in cancer gene expression data.

    Science.gov (United States)

    Lockwood, S; Krishnamoorthy, B

    2015-01-01

    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 topological structures that capture persistent, i.e., topologically significant, features of the data set in its first homology group. Furthermore, we demonstrate that many members of these loops have been implicated for cancer biogenesis in scientific literature. We illustrate our method on five different data sets belonging to brain, breast, leukemia, and ovarian cancers.

  9. 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.

  10. Transcriptome-Level Signatures in Gene Expression and Gene Expression Variability during Bacterial Adaptive Evolution

    Science.gov (United States)

    Erickson, Keesha E.; Otoupal, Peter B.

    2017-01-01

    ABSTRACT Antibiotic-resistant bacteria are an increasingly serious public health concern, as strains emerge that demonstrate resistance to almost all available treatments. One factor that contributes to the crisis is the adaptive ability of bacteria, which exhibit remarkable phenotypic and gene expression heterogeneity in order to gain a survival advantage in damaging environments. This high degree of variability in gene expression across biological populations makes it a challenging task to identify key regulators of bacterial adaptation. Here, we research the regulation of adaptive resistance by investigating transcriptome profiles of Escherichia coli upon adaptation to disparate toxins, including antibiotics and biofuels. We locate potential target genes via conventional gene expression analysis as well as using a new analysis technique examining differential gene expression variability. By investigating trends across the diverse adaptation conditions, we identify a focused set of genes with conserved behavior, including those involved in cell motility, metabolism, membrane structure, and transport, and several genes of unknown function. To validate the biological relevance of the observed changes, we synthetically perturb gene expression using clustered regularly interspaced short palindromic repeat (CRISPR)-dCas9. Manipulation of select genes in combination with antibiotic treatment promotes adaptive resistance as demonstrated by an increased degree of antibiotic tolerance and heterogeneity in MICs. We study the mechanisms by which identified genes influence adaptation and find that select differentially variable genes have the potential to impact metabolic rates, mutation rates, and motility. Overall, this work provides evidence for a complex nongenetic response, encompassing shifts in gene expression and gene expression variability, which underlies adaptive resistance. IMPORTANCE Even initially sensitive bacteria can rapidly thwart antibiotic treatment

  11. 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.

  12. Predicting gene expression from sequence: a reexamination.

    Directory of Open Access Journals (Sweden)

    Yuan Yuan

    2007-11-01

    Full Text Available Although much of the information regarding genes' expressions is encoded in the genome, deciphering such information has been very challenging. We reexamined Beer and Tavazoie's (BT approach to predict mRNA expression patterns of 2,587 genes in Saccharomyces cerevisiae from the information in their respective promoter sequences. Instead of fitting complex Bayesian network models, we trained naïve Bayes classifiers using only the sequence-motif matching scores provided by BT. Our simple models correctly predict expression patterns for 79% of the genes, based on the same criterion and the same cross-validation (CV procedure as BT, which compares favorably to the 73% accuracy of BT. The fact that our approach did not use position and orientation information of the predicted binding sites but achieved a higher prediction accuracy, motivated us to investigate a few biological predictions made by BT. We found that some of their predictions, especially those related to motif orientations and positions, are at best circumstantial. For example, the combinatorial rules suggested by BT for the PAC and RRPE motifs are not unique to the cluster of genes from which the predictive model was inferred, and there are simpler rules that are statistically more significant than BT's ones. We also show that CV procedure used by BT to estimate their method's prediction accuracy is inappropriate and may have overestimated the prediction accuracy by about 10%.

  13. Expression of MTLC gene in gastric carcinoma

    Institute of Scientific and Technical Information of China (English)

    Guang-Bin Qiu; Li-Guo Gong; Dong-Mei Hao; Zhi-Hong Zhen; Kai-Lai Sun

    2003-01-01

    AIM: To investigate the expression of c-myc target from laryngeal cancer cells (MTLC) gene in gastric carcinoma (GC)tissues and the effect of MTLC over-expression on gastric carcinoma cell line BGC823.METHODS: RT-PCR was performed to determine the expression of MTLC mRNA in GC and matched control tissues.BGC823 cells were transfected with an expression vector pcDNA3.1-MTLC by liposome and screened by G418. Growth of cells expressing MTLC was observed daily by manual counting. Apoptotic cells were determined by TdT-mediated dUTP nick-end labeling (TUNEL) assay.RESULTS: The expression of MTLC mRNAs was downregulated in 9(60%) of 15 cases of GC tissues. The growth rates of the BGC823 cells expressing MTLC were indistinguishable from that of control cells. A marked acceleration of apoptosis was observed in MTLC-expressing cells.CONCLUSION: MTLC was down-regulated in the majority of GC tissues and could promote apoptosis of GC cell lines,which suggests that MTLC may play an important role in the carcinogenesis of gastric carcinoma.

  14. Dynamics of Wolbachia pipientis Gene Expression Across the Drosophila melanogaster Life Cycle.

    Science.gov (United States)

    Gutzwiller, Florence; Carmo, Catarina R; Miller, Danny E; Rice, Danny W; Newton, Irene L G; Hawley, R Scott; Teixeira, Luis; Bergman, Casey M

    2015-10-23

    Symbiotic interactions between microbes and their multicellular hosts have manifold biological consequences. To better understand how bacteria maintain symbiotic associations with animal hosts, we analyzed genome-wide gene expression for the endosymbiotic α-proteobacteria Wolbachia pipientis across the entire life cycle of Drosophila melanogaster. We found that the majority of Wolbachia genes are expressed stably across the D. melanogaster life cycle, but that 7.8% of Wolbachia genes exhibit robust stage- or sex-specific expression differences when studied in the whole-organism context. Differentially-expressed Wolbachia genes are typically up-regulated after Drosophila embryogenesis and include many bacterial membrane, secretion system, and ankyrin repeat-containing proteins. Sex-biased genes are often organized as small operons of uncharacterized genes and are mainly up-regulated in adult Drosophila males in an age-dependent manner. We also systematically investigated expression levels of previously-reported candidate genes thought to be involved in host-microbe interaction, including those in the WO-A and WO-B prophages and in the Octomom region, which has been implicated in regulating bacterial titer and pathogenicity. Our work provides comprehensive insight into the developmental dynamics of gene expression for a widespread endosymbiont in its natural host context, and shows that public gene expression data harbor rich resources to probe the functional basis of the Wolbachia-Drosophila symbiosis and annotate the transcriptional outputs of the Wolbachia genome.

  15. Toward stable gene expression in CHO cells

    Science.gov (United States)

    Mariati; Koh, Esther YC; Yeo, Jessna HM; Ho, Steven CL; Yang, Yuansheng

    2014-01-01

    Maintaining high gene expression level during long-term culture is critical when producing therapeutic recombinant proteins using mammalian cells. Transcriptional silencing of promoters, most likely due to epigenetic events such as DNA methylation and histone modifications, is one of the major mechanisms causing production instability. Previous studies demonstrated that the core CpG island element (IE) from the hamster adenine phosphoribosyltransferase gene is effective to prevent DNA methylation. We generated one set of modified human cytomegalovirus (hCMV) promoters by insertion of one or two copies of IE in either forward or reverse orientations into different locations of the hCMV promoter. The modified hCMV with one copy of IE inserted between the hCMV enhancer and core promoter in reverse orientation (MR1) was most effective at enhancing expression stability in CHO cells without comprising expression level when compared with the wild type hCMV. We also found that insertion of IE into a chimeric murine CMV (mCMV) enhancer and human elongation factor-1α core (hEF) promoter in reverse orientation did not enhance expression stability, indicating that the effect of IE on expression stability is possibly promoter specific. PMID:25482237

  16. 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

  17. Engineering genes for predictable protein expression.

    Science.gov (United States)

    Gustafsson, Claes; Minshull, Jeremy; Govindarajan, Sridhar; Ness, Jon; Villalobos, Alan; Welch, Mark

    2012-05-01

    The DNA sequence used to encode a polypeptide can have dramatic effects on its expression. Lack of readily available tools has until recently inhibited meaningful experimental investigation of this phenomenon. Advances in synthetic biology and the application of modern engineering approaches now provide the tools for systematic analysis of the sequence variables affecting heterologous expression of recombinant proteins. We here discuss how these new tools are being applied and how they circumvent the constraints of previous approaches, highlighting some of the surprising and promising results emerging from the developing field of gene engineering.

  18. Facile promoter deletion in Escherichia coli in response to leaky expression of very robust and benign proteins from common expression vectors

    Directory of Open Access Journals (Sweden)

    Kawe Martin

    2009-01-01

    Full Text Available Abstract Background Overexpression of proteins in Escherichia coli is considered routine today, at least when the protein is soluble and not otherwise toxic for the host. We report here that the massive overproduction of even such "benign" proteins can cause surprisingly efficient promoter deletions in the expression plasmid, leading to the growth of only non-producers, when expression is not well repressed in the newly transformed bacterial cell. Because deletion is so facile, it might impact on high-throughput protein production, e.g. for structural genomics, where not every expression parameter will be monitored. Results We studied the high-level expression of several robust non-toxic proteins using a T5 promoter under lac operator control. Full induction leads to no significant growth retardation. We compared expression from almost identical plasmids with or without the lacI gene together in strains expressing different levels of LacI. Any combination without net overexpression of LacI led to an efficient promoter deletion in the plasmid, although the number of growing colonies and even the plasmid size – all antibiotic-resistant non-producers – was almost normal, and thus the problem not immediately recognizable. However, by assuring sufficient repression during the initial establishment phase of the plasmid, deletion was completely prevented. Conclusion The deletions in the insufficiently repressed system are caused entirely by the burden of high-level translation. Since the E. coli Dps protein, known to protect DNA against stress in the stationary phase, is accumulated in the deletion mutants, the mutation may have taken place during a transient stationary phase. The cause of the deletion is thus distinct from the well known interference of high-level transcription with plasmid replication. The deletion can be entirely prevented by overexpressing LacI, a useful precaution even without any signs of stress caused by the protein.

  19. 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...

  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. Global gene expression in Escherichia coli biofilms

    DEFF Research Database (Denmark)

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

    2003-01-01

    in expression have no current defined function. These genes, as well as those induced by stresses relevant to biofilm growth such as oxygen and nutrient limitation, may be important factors that trigger enhanced resistance mechanisms of sessile communities to antibiotics and hydrodynamic shear forces.......It is now apparent that microorganisms undergo significant changes during the transition from planktonic to biofilm growth. These changes result in phenotypic adaptations that allow the formation of highly organized and structured sessile communities, which possess enhanced resistance...... to 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...

  2. Aberrant Gene Expression in Acute Myeloid Leukaemia

    DEFF Research Database (Denmark)

    Bagger, Frederik Otzen

    model to investigate the role of telomerase in AML, we were able to translate the observed effect into human AML patients and identify specific genes involved, which also predict survival patterns in AML patients. During these studies we have applied methods for investigating differentially expressed......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....... Here GEPs from purified healthy haematopoietic populations, with different levels of differentiation, form the basis for comparison with diseased samples. We present a mathematical transformation of mRNA microarray data to make it possible to compare AML samples, carrying expanded aberrant...

  3. Combinatorial engineering for heterologous gene expression.

    Science.gov (United States)

    Zwick, Friederike; Lale, Rahmi; Valla, Svein

    2013-01-01

    Tools for strain engineering with predictable outcome are of crucial importance for the nascent field of synthetic biology. The success of combining different DNA biological parts is often restricted by poorly understood factors deriving from the complexity of the systems. We have previously identified variants for different regulatory elements of the expression cassette XylS/Pm. When such elements are combined they act in a manner consistent with their individual behavior, as long as they affect different functions, such as transcription and translation. Interestingly, sequence context does not seem to influence the final outcome significantly. Expression of reporter gene bla could be increased up to 75 times at the protein level by combining three variants in one cassette. For other tested reporter genes similar results were obtained, except that the stimulatory effect was quantitatively less. Combination of individually characterized DNA parts thus stands as suitable method to achieve a desired phenotype.

  4. Structure, expression and functions of MTA genes.

    Science.gov (United States)

    Kumar, Rakesh; Wang, Rui-An

    2016-05-15

    Metastatic associated proteins (MTA) are integrators of upstream regulatory signals with the ability to act as master coregulators for modifying gene transcriptional activity. The MTA family includes three genes and multiple alternatively spliced variants. The MTA proteins neither have their own enzymatic activity nor have been shown to directly interact with DNA. However, MTA proteins interact with a variety of chromatin remodeling factors and complexes with enzymatic activities for modulating the plasticity of nucleosomes, leading to the repression or derepression of target genes or other extra-nuclear and nucleosome remodeling and histone deacetylase (NuRD)-complex independent activities. The functions of MTA family members are driven by the steady state levels and subcellular localization of MTA proteins, the dynamic nature of modifying signals and enzymes, the structural features and post-translational modification of protein domains, interactions with binding proteins, and the nature of the engaged and resulting features of nucleosomes in the proximity of target genes. In general, MTA1 and MTA2 are the most upregulated genes in human cancer and correlate well with aggressive phenotypes, therapeutic resistance, poor prognosis and ultimately, unfavorable survival of cancer patients. Here we will discuss the structure, expression and functions of the MTA family of genes in the context of cancer cells.

  5. A robust and efficient method for estimating enzyme complex abundance and metabolic flux from expression data

    OpenAIRE

    Barker, Brandon E.; Sadagopan, Narayanan; Wang, Yiping; Smallbone, Kieran; Myers, Christopher R.; Xi, Hongwei; Locasale, Jason W.; Gu, Zhenglong

    2014-01-01

    A major theme in constraint-based modeling is unifying experimental data, such as biochemical information about the reactions that can occur in a system or the composition and localization of enzyme complexes, with highthroughput data including expression data, metabolomics, or DNA sequencing. The desired result is to increase predictive capability resulting in improved understanding of metabolism. The approach typically employed when only gene (or protein) intensities are available is the cr...

  6. An empirical likelihood ratio test robust to individual heterogeneity for differential expression analysis of RNA-seq.

    Science.gov (United States)

    Xu, Maoqi; Chen, Liang

    2016-10-21

    The individual sample heterogeneity is one of the biggest obstacles in biomarker identification for complex diseases such as cancers. Current statistical models to identify differentially expressed genes between disease and control groups often overlook the substantial human sample heterogeneity. Meanwhile, traditional nonparametric tests lose detailed data information and sacrifice the analysis power, although they are distribution free and robust to heterogeneity. Here, we propose an empirical likelihood ratio test with a mean-variance relationship constraint (ELTSeq) for the differential expression analysis of RNA sequencing (RNA-seq). As a distribution-free nonparametric model, ELTSeq handles individual heterogeneity by estimating an empirical probability for each observation without making any assumption about read-count distribution. It also incorporates a constraint for the read-count overdispersion, which is widely observed in RNA-seq data. ELTSeq demonstrates a significant improvement over existing methods such as edgeR, DESeq, t-tests, Wilcoxon tests and the classic empirical likelihood-ratio test when handling heterogeneous groups. It will significantly advance the transcriptomics studies of cancers and other complex disease.

  7. A robust linkage map of the porcine autosome based on gene-associated SNPs

    DEFF Research Database (Denmark)

    Vingborg, Rikke K K; Gregersen, Vivi R; Zhan, Bujie;

    2009-01-01

    Background Genetic linkage maps are necessary for mapping of mendelian traits and quantitative trait loci (QTLs). To identify the actual genes, which control these traits, a map based on gene-associated single nucleotide polymorphism (SNP) markers is highly valuable. In this study, the SNPs were...... genotyped in a large family material comprising more than 5,000 piglets derived from 12 Duroc boars crossed with 236 Danish Landrace/Danish Large White sows. The SNPs were identified in sequence alignments of 4,600 different amplicons obtained from the 12 boars and containing coding regions of genes derived...... from expressed sequence tags (ESTs) and genomic shotgun sequences. Results Linkage maps of all 18 porcine autosomes were constructed based on 456 gene-associated and six porcine EST-based SNPs. The total length of the averaged-sex whole porcine autosome was estimated to 1,711.8 cM resulting...

  8. Robust global microRNA expression profiling using next-generation sequencing technologies.

    Science.gov (United States)

    Tam, Shirley; de Borja, Richard; Tsao, Ming-Sound; McPherson, John D

    2014-03-01

    miRNAs are a class of regulatory molecules involved in a wide range of cellular functions, including growth, development and apoptosis. Given their widespread roles in biological processes, understanding their patterns of expression in normal and diseased states will provide insights into the consequences of aberrant expression. As such, global miRNA expression profiling of human malignancies is gaining popularity in both basic and clinically driven research. However, to date, the majority of such analyses have used microarrays and quantitative real-time PCR. With the introduction of digital count technologies, such as next-generation sequencing (NGS) and the NanoString nCounter System, we have at our disposal many more options. To make effective use of these different platforms, the strengths and pitfalls of several miRNA profiling technologies were assessed, including a microarray platform, NGS technologies and the NanoString nCounter System. Overall, NGS had the greatest detection sensitivity, largest dynamic range of detection and highest accuracy in differential expression analysis when compared with gold-standard quantitative real-time PCR. Its technical reproducibility was high, with intrasample correlations of at least 0.95 in all cases. Furthermore, miRNA analysis of formalin-fixed, paraffin-embedded (FFPE) tissue was also evaluated. Expression profiles between paired frozen and FFPE samples were similar, with Spearman's ρ>0.93. These results show the superior sensitivity, accuracy and robustness of NGS for the comprehensive profiling of miRNAs in both frozen and FFPE tissues.

  9. Proteomic and gene expression patterns of keratoconus

    Directory of Open Access Journals (Sweden)

    Arkasubhra Ghosh

    2013-01-01

    Full Text Available Keratoconus is a progressive corneal thinning disease associated with significant tissue remodeling activities and activation of a variety of signaling networks. However, it is not understood how differential gene and protein expression direct function in keratoconus corneas to drive the underlying pathology, ectasia. Research in the field has focused on discovering differentially expressed genes and proteins and quantifying their levels and activities in keratoconus patient samples. In this study, both microarray analysis of total ribonucleic acid (RNA and whole proteome analyses are carried out using corneal epithelium and tears from keratoconus patients and compared to healthy controls. A number of structural proteins, signaling molecules, cytokines, proteases, and enzymes have been found to be deregulated in keratoconus corneas. Together, the data provide clues to the complex process of corneal degradation which suggest novel ways to clinically diagnose and manage the disease. This review will focus on discussing these recent advances in the knowledge of keratoconus biology from a gene expression and function point-of-view.

  10. 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.

  11. Fibroblast and lymphoblast gene expression profiles in schizophrenia: are non-neural cells informative?

    Directory of Open Access Journals (Sweden)

    Nicholas A Matigian

    Full Text Available Lymphoblastoid cell lines (LCLs and fibroblasts provide conveniently derived non-neuronal samples in which to investigate the aetiology of schizophrenia (SZ using gene expression profiling. This assumes that heritable mechanisms associated with risk of SZ have systemic effects and result in changes to gene expression in all tissues. The broad aim of this and other similar studies is that comparison of the transcriptomes of non-neuronal tissues from SZ patients and healthy controls may identify gene/pathway dysregulation underpinning the neurobiological defects associated with SZ. Using microarrays consisting of 18,664 probes we compared gene expression profiles of LCLs from SZ cases and healthy controls. To identify robust associations with SZ that were not patient or tissue specific, we also examined fibroblasts from an independent series of SZ cases and controls using the same microarrays. In both tissue types ANOVA analysis returned approximately the number of differentially expressed genes expected by chance. No genes were significantly differentially expressed in either tissue when corrected for multiple testing. Even using relaxed parameters (p or = 2-fold change between the groups of SZ cases and controls common to both LCLs and fibroblasts. We conclude that despite encouraging data from previous microarray studies assessing non-neural tissues, the lack of a convergent set of differentially expressed genes associated with SZ using fibroblasts and LCLs indicates the utility of non-neuronal tissues for detection of gene expression differences and/or pathways associated with SZ remains to be demonstrated.

  12. 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.

  13. Integration of gene expression and GWAS results supports involvement of calcium signaling in Schizophrenia.

    Science.gov (United States)

    Hertzberg, L; Katsel, P; Roussos, P; Haroutunian, V; Domany, E

    2015-05-01

    The number of Genome Wide Association Studies (GWAS) of schizophrenia is rapidly growing. However, the small effect of individual genes limits the number of reliably implicated genes, which are too few and too diverse to perform reliable pathway analysis; hence the biological roles of the genes implicated in schizophrenia are unclear. To overcome these limitations we combine GWAS with genome-wide expression data from human post-mortem brain samples of schizophrenia patients and controls, taking these steps: 1) Identify 36 GWAS-based genes which are expressed in our dataset. 2) Find a cluster of 19 genes with highly correlated expression. We show that this correlation pattern is robust and statistically significant. 3) GO-enrichment analysis of these 19 genes reveals significant enrichment of ion channels and calcium-related processes. This finding (based on analyzing a small number of coherently expressed genes) is validated and enhanced in two ways: First, the emergence of calcium channels and calcium signaling is corroborated by identifying proteins that interact with those encoded by the cluster of 19. Second, extend the 19 cluster genes into 1028 genes, whose expression is highly correlated with the cluster's average profile. When GO-enrichment analysis is performed on this extended set, many schizophrenia related pathways appear, with calcium-related processes enriched with high statistical significance. Our results give further, expression-based validation to GWAS results, support a central role of calcium-signaling in the pathogenesis of schizophrenia, and point to additional pathways potentially related to the disease.

  14. Ranking: a closer look on globalisation methods for normalisation of gene expression arrays

    Science.gov (United States)

    Kroll, Torsten C.; Wölfl, Stefan

    2002-01-01

    Data from gene expression arrays are influenced by many experimental parameters that lead to variations not simply accessible by standard quantification methods. To compare measurements from gene expression array experiments, quantitative data are commonly normalised using reference genes or global normalisation methods based on mean or median values. These methods are based on the assumption that (i) selected reference genes are expressed at a standard level in all experiments or (ii) that mean or median signal of expression will give a quantitative reference for each individual experiment. We introduce here a new ranking diagram, with which we can show how the different normalisation methods compare, and how they are influenced by variations in measurements (noise) that occur in every experiment. Furthermore, we show that an upper trimmed mean provides a simple and robust method for normalisation of larger sets of experiments by comparative analysis. PMID:12034851

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

    Science.gov (United States)

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

    2015-09-09

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

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

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    Jennifer M. Hughes-Large

    2016-03-01

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

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

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    Jun Yao

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

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

    Science.gov (United States)

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

    2012-01-01

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

  19. Gravity-Induced Gene Expression in Plants.

    Science.gov (United States)

    Sederoff, Heike; Heber, Steffen; Howard, Brian; Myburg-Nichols, Henrietta; Hammond, Rebecca; Salinas-Mondragon, Raul; Brown, Christopher S.

    Plants sense changes in their orientation towards the vector of gravity and respond with directional growth. Several metabolites in the signal transduction cascade have been identified. However, very little is known about the interaction between these sensing and signal transduction events and even less is known about their role in the differential growth response. Gravity induced changes in transcript abundance have been identified in Arabidopsis whole seedlings and root apices (Moseyko et al. 2002; Kimbrough et al. 2004). Gravity induced transcript abundance changes can be observed within less than 1 min after stimulation (Salinas-Mondragon et al. 2005). Gene expression however requires not only transcription but also translation of the mRNA. Translation can only occur when mRNA is associated with ribosomes, even though not all mRNA associated with ribosomes is actively translated. To approximate translational capacity we quantified whole genome transcript abundances in corn stem pulvini during the first hour after gravity stimulation in total and poly-ribosomal fractions. As in Arabidopsis root apices, transcript abundances of several clusters of genes responded to gravity stimulation. The vast majority of these transcripts were also found to associate with polyribosomes in the same temporal and quantitative pattern. These genes are transcriptionally regulated by gravity stimulation, but do not exhibit translational regulation. However, a small group of genes showed increased transcriptional regulation after gravity stimulation, but no association with polysomes. These transcripts likely are translationally repressed. The mechanism of translational repression for these transcripts is unknown. Based on the hypothesis that the genes essential for gravitropic responses should be expressed in most or all species, we compared the temporal gravity induced expression pattern of all orthologs identified between maize and Arabidopsis. A small group of genes showed high

  20. 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.

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

    DEFF Research Database (Denmark)

    Kristensen, Bo; Georg, Birgitte; Fahrenkrug, Jan

    1997-01-01

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

  2. A general co-expression network-based approach to gene expression analysis: comparison and applications

    Directory of Open Access Journals (Sweden)

    Zhang Weixiong

    2010-02-01

    Full Text Available Abstract Background Co-expression network-based approaches have become popular in analyzing microarray data, such as for detecting functional gene modules. However, co-expression networks are often constructed by ad hoc methods, and network-based analyses have not been shown to outperform the conventional cluster analyses, partially due to the lack of an unbiased evaluation metric. Results Here, we develop a general co-expression network-based approach for analyzing both genes and samples in microarray data. Our approach consists of a simple but robust rank-based network construction method, a parameter-free module discovery algorithm and a novel reference network-based metric for module evaluation. We report some interesting topological properties of rank-based co-expression networks that are very different from that of value-based networks in the literature. Using a large set of synthetic and real microarray data, we demonstrate the superior performance of our approach over several popular existing algorithms. Applications of our approach to yeast, Arabidopsis and human cancer microarray data reveal many interesting modules, including a fatal subtype of lymphoma and a gene module regulating yeast telomere integrity, which were missed by the existing methods. Conclusions We demonstrated that our novel approach is very effective in discovering the modular structures in microarray data, both for genes and for samples. As the method is essentially parameter-free, it may be applied to large data sets where the number of clusters is difficult to estimate. The method is also very general and can be applied to other types of data. A MATLAB implementation of our algorithm can be downloaded from http://cs.utsa.edu/~jruan/Software.html.

  3. Gene Expression Profiling of Xeroderma Pigmentosum

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    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.

  4. X chromosome regulation of autosomal gene expression in bovine blastocysts

    Science.gov (United States)

    Itoh, Yuichiro; Arnold, Arthur P.

    2014-01-01

    Although X chromosome inactivation in female mammals evolved to balance the expression of X chromosome and autosomal genes in the two sexes, female embryos pass through developmental stages in which both X chromosomes are active in somatic cells. Bovine blastocysts show higher expression of many X genes in XX than XY embryos, suggesting that X inactivation is not complete. Here we reanalyzed bovine blastocyst microarray expression data from a network perspective with a focus on interactions between X chromosome and autosomal genes. Whereas male to female ratios of expression of autosomal genes were distributed around a mean of 1, X chromosome genes were clearly shifted towards higher expression in females. We generated gene coexpression networks and identified a major module of genes with correlated gene expression that includes female-biased X genes and sexually dimorphic autosomal genes for which the sexual dimorphism is likely driven by the X genes. In this module, expression of X chromosome genes correlates with autosome genes, more than the expression of autosomal genes with each other. Our study identifies correlated patterns of autosomal and X-linked genes that are likely influenced by the sexual imbalance of X gene expression when X inactivation is inefficient. PMID:24817096

  5. Comparative gene expression profiles between heterotic and non-heterotic hybrids of tetraploid Medicago sativa

    Directory of Open Access Journals (Sweden)

    Nettleton Dan

    2009-08-01

    Full Text Available Abstract Background Heterosis, the superior performance of hybrids relative to parents, has clear agricultural value, but its genetic control is unknown. Our objective was to test the hypotheses that hybrids expressing heterosis for biomass yield would show more gene expression levels that were different from midparental values and outside the range of parental values than hybrids that do not exhibit heterosis. Results We tested these hypotheses in three Medicago sativa (alfalfa genotypes and their three hybrids, two of which expressed heterosis for biomass yield and a third that did not, using Affymetrix M. truncatula GeneChip arrays. Alfalfa hybridized to approximately 47% of the M. truncatula probe sets. Probe set signal intensities were analyzed using MicroArray Suite v.5.0 (MAS and robust multi-array average (RMA algorithms. Based on MAS analysis, the two heterotic hybrids performed similarly, with about 27% of genes showing differential expression among the parents and their hybrid compared to 12.5% for the non-heterotic hybrid. At a false discovery rate of 0.15, 4.7% of differentially expressed genes in hybrids (~300 genes showed nonadditive expression compared to only 0.5% (16 genes in the non-heterotic hybrid. Of the nonadditively expressed genes, approximately 50% showed expression levels that fell outside the parental range in heterotic hybrids, but only one of 16 showed a similar profile in the non-heterotic hybrid. Genes whose expression differed in the parents were three times more likely to show nonadditive expression than genes whose parental transcript levels were equal. Conclusion The higher proportions of probe sets with expression level that differed from the parental midparent value and that were more extreme than either parental value in the heterotic hybrids compared to a non-heterotic hybrid were also found using RMA. We conclude that nonadditive expression of transcript levels may contribute to heterosis for biomass

  6. Spatial and temporal analysis of gene expression during growth and fusion of the mouse facial prominences.

    Science.gov (United States)

    Feng, Weiguo; Leach, Sonia M; Tipney, Hannah; Phang, Tzulip; Geraci, Mark; Spritz, Richard A; Hunter, Lawrence E; Williams, Trevor

    2009-12-16

    Orofacial malformations resulting from genetic and/or environmental causes are frequent human birth defects yet their etiology is often unclear because of insufficient information concerning the molecular, cellular and morphogenetic processes responsible for normal facial development. We have, therefore, derived a comprehensive expression dataset for mouse orofacial development, interrogating three distinct regions - the mandibular, maxillary and frontonasal prominences. To capture the dynamic changes in the transcriptome during face formation, we sampled five time points between E10.5-E12.5, spanning the developmental period from establishment of the prominences to their fusion to form the mature facial platform. Seven independent biological replicates were used for each sample ensuring robustness and quality of the dataset. Here, we provide a general overview of the dataset, characterizing aspects of gene expression changes at both the spatial and temporal level. Considerable coordinate regulation occurs across the three prominences during this period of facial growth and morphogenesis, with a switch from expression of genes involved in cell proliferation to those associated with differentiation. An accompanying shift in the expression of polycomb and trithorax genes presumably maintains appropriate patterns of gene expression in precursor or differentiated cells, respectively. Superimposed on the many coordinated changes are prominence-specific differences in the expression of genes encoding transcription factors, extracellular matrix components, and signaling molecules. Thus, the elaboration of each prominence will be driven by particular combinations of transcription factors coupled with specific cell:cell and cell:matrix interactions. The dataset also reveals several prominence-specific genes not previously associated with orofacial development, a subset of which we externally validate. Several of these latter genes are components of bidirectional

  7. Spatial and temporal analysis of gene expression during growth and fusion of the mouse facial prominences.

    Directory of Open Access Journals (Sweden)

    Weiguo Feng

    Full Text Available Orofacial malformations resulting from genetic and/or environmental causes are frequent human birth defects yet their etiology is often unclear because of insufficient information concerning the molecular, cellular and morphogenetic processes responsible for normal facial development. We have, therefore, derived a comprehensive expression dataset for mouse orofacial development, interrogating three distinct regions - the mandibular, maxillary and frontonasal prominences. To capture the dynamic changes in the transcriptome during face formation, we sampled five time points between E10.5-E12.5, spanning the developmental period from establishment of the prominences to their fusion to form the mature facial platform. Seven independent biological replicates were used for each sample ensuring robustness and quality of the dataset. Here, we provide a general overview of the dataset, characterizing aspects of gene expression changes at both the spatial and temporal level. Considerable coordinate regulation occurs across the three prominences during this period of facial growth and morphogenesis, with a switch from expression of genes involved in cell proliferation to those associated with differentiation. An accompanying shift in the expression of polycomb and trithorax genes presumably maintains appropriate patterns of gene expression in precursor or differentiated cells, respectively. Superimposed on the many coordinated changes are prominence-specific differences in the expression of genes encoding transcription factors, extracellular matrix components, and signaling molecules. Thus, the elaboration of each prominence will be driven by particular combinations of transcription factors coupled with specific cell:cell and cell:matrix interactions. The dataset also reveals several prominence-specific genes not previously associated with orofacial development, a subset of which we externally validate. Several of these latter genes are components of

  8. Gene Expression Omnibus: NCBI gene expression and hybridization array data repository.

    Science.gov (United States)

    Edgar, Ron; Domrachev, Michael; Lash, Alex E

    2002-01-01

    The Gene Expression Omnibus (GEO) project was initiated in response to the growing demand for a public repository for high-throughput gene expression data. GEO provides a flexible and open design that facilitates submission, storage and retrieval of heterogeneous data sets from high-throughput gene expression and genomic hybridization experiments. GEO is not intended to replace in house gene expression databases that benefit from coherent data sets, and which are constructed to facilitate a particular analytic method, but rather complement these by acting as a tertiary, central data distribution hub. The three central data entities of GEO are platforms, samples and series, and were designed with gene expression and genomic hybridization experiments in mind. A platform is, essentially, a list of probes that define what set of molecules may be detected. A sample describes the set of molecules that are being probed and references a single platform used to generate its molecular abundance data. A series organizes samples into the meaningful data sets which make up an experiment. The GEO repository is publicly accessible through the World Wide Web at http://www.ncbi.nlm.nih.gov/geo.

  9. Gene expression in developing watermelon fruit

    Science.gov (United States)

    Wechter, W Patrick; Levi, Amnon; Harris, Karen R; Davis, Angela R; Fei, Zhangjun; Katzir, Nurit; Giovannoni, James J; Salman-Minkov, Ayelet; Hernandez, Alvaro; Thimmapuram, Jyothi; Tadmor, Yaakov; Portnoy, Vitaly; Trebitsh, Tova

    2008-01-01

    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 genotype with a similar

  10. 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

  11. 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.

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

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    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.

  13. 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.

  14. microRNA as a potential vector for the propagation of robustness in protein expression and oscillatory dynamics within a ceRNA network.

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    Claude Gérard

    Full Text Available microRNAs (miRNAs are small noncoding RNAs that are important post-transcriptional regulators of gene expression. miRNAs can induce thresholds in protein synthesis. Such thresholds in protein output can be also achieved by oligomerization of transcription factors (TF for the control of gene expression. First, we propose a minimal model for protein expression regulated by miRNA and by oligomerization of TF. We show that miRNA and oligomerization of TF generate a buffer, which increases the robustness of protein output towards molecular noise as well as towards random variation of kinetics parameters. Next, we extend the model by considering that the same miRNA can bind to multiple messenger RNAs, which accounts for the dynamics of a minimal competing endogenous RNAs (ceRNAs network. The model shows that, through common miRNA regulation, TF can control the expression of all proteins formed by the ceRNA network, even if it drives the expression of only one gene in the network. The model further suggests that the threshold in protein synthesis mediated by the oligomerization of TF can be propagated to the other genes, which can increase the robustness of the expression of all genes in such ceRNA network. Furthermore, we show that a miRNA could increase the time delay of a "Goodwin-like" oscillator model, which may favor the occurrence of oscillations of large amplitude. This result predicts important roles of miRNAs in the control of the molecular mechanisms leading to the emergence of biological rhythms. Moreover, a model for the latter oscillator embedded in a ceRNA network indicates that the oscillatory behavior can be propagated, via the shared miRNA, to all proteins formed by such ceRNA network. Thus, by means of computational models, we show that miRNAs could act as vectors allowing the propagation of robustness in protein synthesis as well as oscillatory behaviors within ceRNA networks.

  15. The relationship among gene expression, the evolution of gene dosage, and the rate of protein evolution.

    Directory of Open Access Journals (Sweden)

    Jean-François Gout

    2010-05-01

    Full Text Available The understanding of selective constraints affecting genes is a major issue in biology. It is well established that gene expression level is a major determinant of the rate of protein evolution, but the reasons for this relationship remain highly debated. Here we demonstrate that gene expression is also a major determinant of the evolution of gene dosage: the rate of gene losses after whole genome duplications in the Paramecium lineage is negatively correlated to the level of gene expression, and this relationship is not a byproduct of other factors known to affect the fate of gene duplicates. This indicates that changes in gene dosage are generally more deleterious for highly expressed genes. This rule also holds for other taxa: in yeast, we find a clear relationship between gene expression level and the fitness impact of reduction in gene dosage. To explain these observations, we propose a model based on the fact that the optimal expression level of a gene corresponds to a trade-off between the benefit and cost of its expression. This COSTEX model predicts that selective pressure against mutations changing gene expression level or affecting the encoded protein should on average be stronger in highly expressed genes and hence that both the frequency of gene loss and the rate of protein evolution should correlate negatively with gene expression. Thus, the COSTEX model provides a simple and common explanation for the general relationship observed between the level of gene expression and the different facets of gene evolution.

  16. Pandemic H1N1 influenza A directly induces a robust and acute inflammatory gene signature in primary human bronchial epithelial cells downstream of membrane fusion.

    Science.gov (United States)

    Paquette, Stéphane G; Banner, David; Chi, Le Thi Bao; Leόn, Alberto J; Xu, Luoling; Ran, Longsi; Huang, Stephen S H; Farooqui, Amber; Kelvin, David J; Kelvin, Alyson A

    2014-01-05

    Pandemic H1N1 influenza A (H1N1pdm) elicits stronger pulmonary inflammation than previously circulating seasonal H1N1 influenza A (sH1N1), yet mechanisms of inflammatory activation in respiratory epithelial cells during H1N1pdm infection are unclear. We investigated host responses to H1N1pdm/sH1N1 infection and virus entry mechanisms in primary human bronchial epithelial cells in vitro. H1N1pdm infection rapidly initiated a robust inflammatory gene signature (3 h post-infection) not elicited by sH1N1 infection. Protein secretion inhibition had no effect on gene induction. Infection with membrane fusion deficient H1N1pdm failed to induce robust inflammatory gene expression which was rescued with restoration of fusion ability, suggesting H1N1pdm directly triggered the inflammatory signature downstream of membrane fusion. Investigation of intra-virion components revealed H1N1pdm viral RNA (vRNA) triggered a stronger inflammatory phenotype than sH1N1 vRNA. Thus, our study is first to report H1N1pdm induces greater inflammatory gene expression than sH1N1 in vitro due to direct virus-epithelial cell interaction.

  17. Effects of transcriptional pausing on gene expression dynamics.

    Directory of Open Access Journals (Sweden)

    Tiina Rajala

    2010-03-01

    Full Text Available Stochasticity in gene expression affects many cellular processes and is a source of phenotypic diversity between genetically identical individuals. Events in elongation, particularly RNA polymerase pausing, are a source of this noise. Since the rate and duration of pausing are sequence-dependent, this regulatory mechanism of transcriptional dynamics is evolvable. The dependency of pause propensity on regulatory molecules makes pausing a response mechanism to external stress. Using a delayed stochastic model of bacterial transcription at the single nucleotide level that includes the promoter open complex formation, pausing, arrest, misincorporation and editing, pyrophosphorolysis, and premature termination, we investigate how RNA polymerase pausing affects a gene's transcriptional dynamics and gene networks. We show that pauses' duration and rate of occurrence affect the bursting in RNA production, transcriptional and translational noise, and the transient to reach mean RNA and protein levels. In a genetic repressilator, increasing the pausing rate and the duration of pausing events increases the period length but does not affect the robustness of the periodicity. We conclude that RNA polymerase pausing might be an important evolvable feature of genetic networks.

  18. GRAPE: a pathway template method to characterize tissue-specific functionality from gene expression profiles.

    Science.gov (United States)

    Klein, Michael I; Stern, David F; Zhao, Hongyu

    2017-06-26

    Personalizing treatment regimes based on gene expression profiles of individual tumors will facilitate management of cancer. Although many methods have been developed to identify pathways perturbed in tumors, the results are often not generalizable across independent datasets due to the presence of platform/batch effects. There is a need to develop methods that are robust to platform/batch effects and able to identify perturbed pathways in individual samples. We present Gene-Ranking Analysis of Pathway Expression (GRAPE) as a novel method to identify abnormal pathways in individual samples that is robust to platform/batch effects in gene expression profiles generated by multiple platforms. GRAPE first defines a template consisting of an ordered set of pathway genes to characterize the normative state of a pathway based on the relative rankings of gene expression levels across a set of reference samples. This template can be used to assess whether a sample conforms to or deviates from the typical behavior of the reference samples for this pathway. We demonstrate that GRAPE performs well versus existing methods in classifying tissue types within a single dataset, and that GRAPE achieves superior robustness and generalizability across different datasets. A powerful feature of GRAPE is the ability to represent individual gene expression profiles as a vector of pathways scores. We present applications to the analyses of breast cancer subtypes and different colonic diseases. We perform survival analysis of several TCGA subtypes and find that GRAPE pathway scores perform well in comparison to other methods. GRAPE templates offer a novel approach for summarizing the behavior of gene-sets across a collection of gene expression profiles. These templates offer superior robustness across distinct experimental batches compared to existing methods. GRAPE pathway scores enable identification of abnormal gene-set behavior in individual samples using a non-competitive approach that

  19. Pandemic H1N1 influenza A directly induces a robust and acute inflammatory gene signature in primary human bronchial epithelial cells downstream of membrane fusion

    Energy Technology Data Exchange (ETDEWEB)

    Paquette, Stéphane G. [Division of Experimental Therapeutics, Toronto General Hospital Research Institute, University Health Network, Toronto, Ontario (Canada); Institute of Medical Science, Faculty of Medicine, University of Toronto, Toronto, Ontario (Canada); Banner, David [Division of Experimental Therapeutics, Toronto General Hospital Research Institute, University Health Network, Toronto, Ontario (Canada); Chi, Le Thi Bao [Department of Microbiology, Hue University of Medicine and Pharmacy, Thua Thien Hue (Viet Nam); Carlo Urbani Centre, Hue University of Medicine and Pharmacy, Thua Thien Hue (Viet Nam); Leon, Alberto J. [Division of Experimental Therapeutics, Toronto General Hospital Research Institute, University Health Network, Toronto, Ontario (Canada); International Institute of Infection and Immunity, Shantou University Medical College, Shantou, Guangdong (China); Xu, Luoling; Ran, Longsi [Division of Experimental Therapeutics, Toronto General Hospital Research Institute, University Health Network, Toronto, Ontario (Canada); Huang, Stephen S.H. [Division of Experimental Therapeutics, Toronto General Hospital Research Institute, University Health Network, Toronto, Ontario (Canada); Department of Immunology, Faculty of Medicine, University of Toronto, Toronto, Ontario (Canada); Farooqui, Amber [Division of Experimental Therapeutics, Toronto General Hospital Research Institute, University Health Network, Toronto, Ontario (Canada); International Institute of Infection and Immunity, Shantou University Medical College, Shantou, Guangdong (China); and others

    2014-01-05

    Pandemic H1N1 influenza A (H1N1pdm) elicits stronger pulmonary inflammation than previously circulating seasonal H1N1 influenza A (sH1N1), yet mechanisms of inflammatory activation in respiratory epithelial cells during H1N1pdm infection are unclear. We investigated host responses to H1N1pdm/sH1N1 infection and virus entry mechanisms in primary human bronchial epithelial cells in vitro. H1N1pdm infection rapidly initiated a robust inflammatory gene signature (3 h post-infection) not elicited by sH1N1 infection. Protein secretion inhibition had no effect on gene induction. Infection with membrane fusion deficient H1N1pdm failed to induce robust inflammatory gene expression which was rescued with restoration of fusion ability, suggesting H1N1pdm directly triggered the inflammatory signature downstream of membrane fusion. Investigation of intra-virion components revealed H1N1pdm viral RNA (vRNA) triggered a stronger inflammatory phenotype than sH1N1 vRNA. Thus, our study is first to report H1N1pdm induces greater inflammatory gene expression than sH1N1 in vitro due to direct virus–epithelial cell interaction. - Highlights: • We investigated H1N1pdm/sH1N1 infection in primary epithelial cells. • H1N1pdm directly initiated a robust inflammatory gene signature, sH1N1 did not. • H1N1pdm viral RNA triggered a stronger response than sH1N1. • H1N1pdm induces greater response due to direct virus–cell interaction. • These results have potential to impact vaccine and therapeutic development.

  20. Expressing exogenous genes in newts by transgenesis.

    Science.gov (United States)

    Casco-Robles, Martin Miguel; Yamada, Shouta; Miura, Tomoya; Nakamura, Kenta; Haynes, Tracy; Maki, Nobuyasu; Del Rio-Tsonis, Katia; Tsonis, Panagiotis A; Chiba, Chikafumi

    2011-05-01

    The great regenerative abilities of newts provide the impetus for studies at the molecular level. However, efficient methods for gene regulation have historically been quite limited. Here we describe a protocol for transgenically expressing exogenous genes in the newt Cynops pyrrhogaster. This method is simple: a reaction mixture of I-SceI meganuclease and a plasmid DNA carrying a transgene cassette flanked by the enzyme recognition sites is directly injected into fertilized eggs. The protocol achieves a high efficiency of transgenesis, comparable to protocols used in other animal systems, and it provides a practical number of transgenic newts (∼20% of injected embryos) that survive beyond metamorphosis and that can be applied to regenerative studies. The entire protocol for obtaining transgenic adult newts takes 4-5 months.

  1. An efficient RNA isolation procedure and identification of reference genes for normalization of gene expression in blueberry.

    Science.gov (United States)

    Vashisth, Tripti; Johnson, Lisa Klima; Malladi, Anish

    2011-12-01

    Application of transcriptomics approaches can greatly enhance our understanding of blueberry physiology. The success of transcriptomics approaches is dependent on the extraction of high-quality RNA which is complicated by the abundance of polyphenolics and polysaccharides in blueberry. Additionally, transcriptomics requires the accurate quantification of transcript abundance. Quantitative real-time polymerase chain reaction (qRT-PCR) is a robust method to determine transcript abundance. Normalization of gene expression using stably expressed reference genes is essential in qRT-PCR. An evaluation of the stability of expression of reference genes has not yet been reported in blueberry. The objectives of this study were to develop an effective procedure for extracting RNA from different organs and to evaluate potential reference genes for qRT-PCR analyses in blueberry. RNA of high quality and yield was extracted from eight and six organs of rabbiteye and southern highbush blueberry, respectively, using a modified cetyltrimethyl ammonium bromide-based method. The expression stability of 12 reference genes was evaluated. UBIQUITIN-CONJUGATING ENZYME (UBC28), RNA HELICASE-LIKE (RH8), CLATHRIN ADAPTER COMPLEXES MEDIUM SUBUNIT FAMILY PROTEIN (CACSa), and POLYUBIQUITIN (UBQ3b) were the most stably expressed genes across multiple organs in both blueberry species. Further, the expression stability of the reference genes in the branch abscission zone following treatment with fruit abscission-inducing compounds was analyzed. CACSa, RH8, and UBC28 were the most stably expressed genes in the abscission zone under abscission-inducing conditions. We suggest a preliminary evaluation of UBC28, CACSa, RH8, and UBQ3b to identify the most suitable reference genes for the experimental conditions under consideration in blueberry.

  2. Gene expression-targeted isoflavone therapy.

    Science.gov (United States)

    Węgrzyn, Alicja

    2012-04-01

    Lysosomal storage diseases (LSD) form a group of inherited metabolic disorders caused by dysfunction of one of the lysosomal proteins, resulting in the accumulation of certain compounds. Although these disorders are among first genetic diseases for which specific treatments were proposed, there are still serious unsolved problems that require development of novel therapeutic procedures. An example is neuronopathy, which develops in most of LSD and cannot be treated efficiently by currently approved therapies. Recently, a new potential therapy, called gene expression-targeted isoflavone therapy (GET IT), has been proposed for a group of LSD named mucopolysaccharidoses (MPS), in which storage of incompletely degraded glycosaminoglycans (GAGs) results in severe symptoms of virtually all tissues and organs, including central nervous system. The idea of this therapy is to inhibit synthesis of GAGs by modulating expression of genes coding for enzymes involved in synthesis of these compounds. Such a modulation is possible by using isoflavones, particularly genistein, which interfere with a signal transduction process necessary for stimulation of expression of certain genes. Results of in vitro experiments and studies on animal models indicated a high efficiency of GET IT, including correction of behavior of affected mice. However, clinical trials, performed with soy isoflavone extracts, revealed only limited efficacy. This caused a controversy about GET IT as a potential, effective treatment of patients suffering from MPS, especially neuronopathic forms of these diseases. It this critical review, I present possible molecular mechanisms of therapeutic action of isoflavones (particularly genistein) and suggest that efficacy of GET IT might be sufficiently high when using relatively high doses of synthetic genistein (which was employed in experiments on cell cultures and mouse models) rather than low doses of soy isoflavone extracts (which were used in clinical trials). This

  3. 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

  4. 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.

  5. Apopotic gene Bax expression in carotid plaque

    Institute of Scientific and Technical Information of China (English)

    Bao-Zhong MEN; Ding-Biao ZHOU; Huai-Yin SHI; Xiao-Ming ZHANG

    2006-01-01

    The expression of BAX in carotid atherosclerosis and its regulation is far from defined. Objectives To investigate BAX expression in stable/fibrous and instable/vulnerable carotid plaque and its clinical significance. Methods 25 cases of carotid plaque specimens obtained from endarterectomy were divided into two groups, stable/fibrous 14 cases, vulnerable/instable 11 cases; aortic artery and its branches from hepatic transplantation donors 6 case as control. The expression of proapoptotic BAX was detected by immunohistochemistry(IHC), in situ hybridization(ISH) and in situ TdT dUTP nick end labeling (TUNEL). Results 5 cases of BAX ( + ) were detected by ICH and ISH, 4 case of TUNEL ( + ) were detected by TUNEL in stable/fibrous carotid plaque , while 10 cases were BAX ( + )by IHC(P < 0.05) , 11case by ISH and 9 case by TUNEL were detected in instable/vulnerable carotid plaque ( P < 0.01 ), respectively. The intensity of BAX ( + ) cells by IHC and ISH was 8.63 ± 2.62 and 10.32 ± 3.12 in fibrous plaques, whereas 122 ± 21.64and 152 ± 23.35 in vulnerable plaques, respectively. No expression of BAX was found in controlled group. Conclusion The higher expression of Bax in vulnerable carotid plaque may be one mechanisms in molecular pathogenesis of carotid atherosclerosis which affect plaque stability and be the cause of higher incidence of stroke than fibrous carotid plaques, the regulation of BAX expression in different stage of atherosclerosis may provide targets in gene therapy for carotid atherosclerosis.

  6. 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

  7. Transcriptome profiling in conifers and the PiceaGenExpress database show patterns of diversification within gene families and interspecific conservation in vascular gene expression

    Directory of Open Access Journals (Sweden)

    Raherison Elie

    2012-08-01

    Full Text Available Abstract Background Conifers have very large genomes (13 to 30 Gigabases that are mostly uncharacterized although extensive cDNA resources have recently become available. This report presents a global overview of transcriptome variation in a conifer tree and documents conservation and diversity of gene expression patterns among major vegetative tissues. Results An oligonucleotide microarray was developed from Picea glauca and P. sitchensis cDNA datasets. It represents 23,853 unique genes and was shown to be suitable for transcriptome profiling in several species. A comparison of secondary xylem and phelloderm tissues showed that preferential expression in these vascular tissues was highly conserved among Picea spp. RNA-Sequencing strongly confirmed tissue preferential expression and provided a robust validation of the microarray design. A small database of transcription profiles called PiceaGenExpress was developed from over 150 hybridizations spanning eight major tissue types. In total, transcripts were detected for 92% of the genes on the microarray, in at least one tissue. Non-annotated genes were predominantly expressed at low levels in fewer tissues than genes of known or predicted function. Diversity of expression within gene families may be rapidly assessed from PiceaGenExpress. In conifer trees, dehydrins and late embryogenesis abundant (LEA osmotic regulation proteins occur in large gene families compared to angiosperms. Strong contrasts and low diversity was observed in the dehydrin family, while diverse patterns suggested a greater degree of diversification among LEAs. Conclusion Together, the oligonucleotide microarray and the PiceaGenExpress database represent the first resource of this kind for gymnosperm plants. The spruce transcriptome analysis reported here is expected to accelerate genetic studies in the large and important group comprised of conifer trees.

  8. 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...... 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 expressers of both...

  9. 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 genes...

  10. Spatiotemporal patterns of gene expression during fetal monkey brain development.

    Science.gov (United States)

    Redmond, D Eugene; Zhao, Ji-Liang; Randall, Jeffry D; Eklund, Aron C; Eusebi, Leonard O V; Roth, Robert H; Gullans, Steven R; Jensen, Roderick V

    2003-12-19

    Human DNA microarrays are used to study the spatiotemporal patterns of gene expression during the course of fetal monkey brain development. The 444 most dynamically expressed genes in four major brain areas are reported at five different fetal ages. The spatiotemporal profiles of gene expression show both regional specificity as well as waves of gene expression across the developing brain. These patterns of expression are used to identify statistically significant clusters of co-regulated genes. This study demonstrates for the first time in the primate the relevance, timing, and spatial locations of expression for many developmental genes identified in other animals and provides clues to the functions of many unknowns. Two different microarray platforms are used to provide high-throughput cross validation of the most important gene expression changes. These results may lead to new understanding of brain development and new strategies for treating and repairing disorders of brain function.

  11. The Effects of Hallucinogens on Gene Expression.

    Science.gov (United States)

    Martin, David A; Nichols, Charles D

    2017-07-05

    The classic serotonergic hallucinogens, or psychedelics, have the ability to profoundly alter perception and behavior. These can include visual distortions, hallucinations, detachment from reality, and mystical experiences. Some psychedelics, like LSD, are able to produce these effects with remarkably low doses of drug. Others, like psilocybin, have recently been demonstrated to have significant clinical efficacy in the treatment of depression, anxiety, and addiction that persist for at least several months after only a single therapeutic session. How does this occur? Much work has recently been published from imaging studies showing that psychedelics alter brain network connectivity. They facilitate a disintegration of the default mode network, producing a hyperconnectivity between brain regions that allow centers that do not normally communicate with each other to do so. The immediate and acute effects on both behaviors and network connectivity are likely mediated by effector pathways downstream of serotonin 5-HT2A receptor activation. These acute molecular processes also influence gene expression changes, which likely influence synaptic plasticity and facilitate more long-term changes in brain neurochemistry ultimately underlying the therapeutic efficacy of a single administration to achieve long-lasting effects. In this review, we summarize what is currently known about the molecular genetic responses to psychedelics within the brain and discuss how gene expression changes may contribute to altered cellular physiology and behaviors.

  12. Identification of Human HK Genes and Gene Expression Regulation Study in Cancer from Transcriptomics Data Analysis

    Science.gov (United States)

    Zhang, Zhang; Liu, Jingxing; Wu, Jiayan; Yu, Jun

    2013-01-01

    The regulation of gene expression is essential for eukaryotes, as it drives the processes of cellular differentiation and morphogenesis, leading to the creation of different cell types in multicellular organisms. RNA-Sequencing (RNA-Seq) provides researchers with a powerful toolbox for characterization and quantification of transcriptome. Many different human tissue/cell transcriptome datasets coming from RNA-Seq technology are available on public data resource. The fundamental issue here is how to develop an effective analysis method to estimate expression pattern similarities between different tumor tissues and their corresponding normal tissues. We define the gene expression pattern from three directions: 1) expression breadth, which reflects gene expression on/off status, and mainly concerns ubiquitously expressed genes; 2) low/high or constant/variable expression genes, based on gene expression level and variation; and 3) the regulation of gene expression at the gene structure level. The cluster analysis indicates that gene expression pattern is higher related to physiological condition rather than tissue spatial distance. Two sets of human housekeeping (HK) genes are defined according to cell/tissue types, respectively. To characterize the gene expression pattern in gene expression level and variation, we firstly apply improved K-means algorithm and a gene expression variance model. We find that cancer-associated HK genes (a HK gene is specific in cancer group, while not in normal group) are expressed higher and more variable in cancer condition than in normal condition. Cancer-associated HK genes prefer to AT-rich genes, and they are enriched in cell cycle regulation related functions and constitute some cancer signatures. The expression of large genes is also avoided in cancer group. These studies will help us understand which cell type-specific patterns of gene expression differ among different cell types, and particularly for cancer. PMID:23382867

  13. Brief isoflurane anaesthesia affects differential gene expression, gene ontology and gene networks in rat brain.

    Science.gov (United States)

    Lowes, Damon A; Galley, Helen F; Moura, Alessandro P S; Webster, Nigel R

    2017-01-15

    Much is still unknown about the mechanisms of effects of even brief anaesthesia on the brain and previous studies have simply compared differential expression profiles with and without anaesthesia. We hypothesised that network analysis, in addition to the traditional differential gene expression and ontology analysis, would enable identification of the effects of anaesthesia on interactions between genes. Rats (n=10 per group) were randomised to anaesthesia with isoflurane in oxygen or oxygen only for 15min, and 6h later brains were removed. Differential gene expression and gene ontology analysis of microarray data was performed. Standard clustering techniques and principal component analysis with Bayesian rules were used along with social network analysis methods, to quantitatively model and describe the gene networks. Anaesthesia had marked effects on genes in the brain with differential regulation of 416 probe sets by at least 2 fold. Gene ontology analysis showed 23 genes were functionally related to the anaesthesia and of these, 12 were involved with neurotransmitter release, transport and secretion. Gene network analysis revealed much greater connectivity in genes from brains from anaesthetised rats compared to controls. Other importance measures were also altered after anaesthesia; median [range] closeness centrality (shortest path) was lower in anaesthetized animals (0.07 [0-0.30]) than controls (0.39 [0.30-0.53], pgenes after anaesthesia and suggests future targets for investigation. Copyright © 2016 Elsevier B.V. All rights reserved.

  14. 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.

  15. Coactivators in PPAR-Regulated Gene Expression

    Directory of Open Access Journals (Sweden)

    Navin Viswakarma

    2010-01-01

    Full Text Available Peroxisome proliferator-activated receptor (PPARα, β (also known as δ, and γ function as sensors for fatty acids and fatty acid derivatives and control important metabolic pathways involved in the maintenance of energy balance. PPARs also regulate other diverse biological processes such as development, differentiation, inflammation, and neoplasia. In the nucleus, PPARs exist as heterodimers with retinoid X receptor-α bound to DNA with corepressor molecules. Upon ligand activation, PPARs undergo conformational changes that facilitate the dissociation of corepressor molecules and invoke a spatiotemporally orchestrated recruitment of transcription cofactors including coactivators and coactivator-associated proteins. While a given nuclear receptor regulates the expression of a prescribed set of target genes, coactivators are likely to influence the functioning of many regulators and thus affect the transcription of many genes. Evidence suggests that some of the coactivators such as PPAR-binding protein (PBP/PPARBP/thyroid hormone receptor-associated protein 220 (TRAP220/mediator complex subunit 1 (MED1 may exert a broader influence on the functions of several nuclear receptors and their target genes. Investigations into the role of coactivators in the function of PPARs should strengthen our understanding of the complexities of metabolic diseases associated with energy metabolism.

  16. Gene expression profiling of mouse embryos with microarrays

    OpenAIRE

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

    2010-01-01

    Global expression profiling by DNA microarrays provides a snapshot of cell and tissue status and becomes an essential tool in biological and medical sciences. Typical questions that can be addressed by microarray analysis in developmental biology include: (1) to find a set of genes expressed in a specific cell type; (2) to identify genes expressed commonly in multiple cell types; (3) to follow the time-course changes of gene expression patterns; (4) to demonstrate cell’s identity by showing s...

  17. 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

  18. 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...

  19. Gene Expression Profile of Endotoxin-stimulated Leukocytes of the Term New Born: Control of Cytokine Gene Expression by Interleukin-10

    Science.gov (United States)

    Davidson, Dennis; Zaytseva, Alla; Miskolci, Veronika; Castro-Alcaraz, Susana; Vancurova, Ivana; Patel, Hardik

    2013-01-01

    Introduction Increasing evidence now supports the association between the fetal inflammatory response syndrome (FIRS) with the pathogenesis of preterm labor, intraventricular hemorrhage and bronchopulmonary dysplasia. Polymorphonuclear leukocyte (PMNs) and mononuclear cell (MONOs) infiltration of the placenta is associated with these disorders. The aim of this study was to reveal cell-specific differences in gene expression and cytokine release in response to endotoxin that would elucidate inflammatory control mechanisms in the newly born. Methods PMNs and MONOs were separately isolated from the same cord blood sample. A genome-wide microarray screened for gene expression and related pathways at 4 h of LPS stimulation (n = 5). RT-qPCR and ELISA were performed for selected cytokines at 4 h and 18 h of LPS stimulation. Results Compared to PMNs, MONOs had a greater diversity and more robust gene expression that included pro-inflammatory (PI) cytokines, chemokines and growth factors at 4 h. Only MONOs had genes changing expression (all up regulated including interleukin-10) that were clustered in the JAK/STAT pathway. Pre-incubation with IL-10 antibody, for LPS-stimulated MONOs, led to up regulated PI and IL-10 gene expression and release of PI cytokines after 4 h. Discussion The present study suggests a dominant role of MONO gene expression in control of the fetal inflammatory response syndrome at 4 hrs of LPS stimulation. LPS-stimulated MONOs but not PMNs of the newborn have the ability to inhibit PI cytokine gene expression by latent IL-10 release. PMID:23326478

  20. Gene expression profile of endotoxin-stimulated leukocytes of the term new born: control of cytokine gene expression by interleukin-10.

    Directory of Open Access Journals (Sweden)

    Dennis Davidson

    Full Text Available INTRODUCTION: Increasing evidence now supports the association between the fetal inflammatory response syndrome (FIRS with the pathogenesis of preterm labor, intraventricular hemorrhage and bronchopulmonary dysplasia. Polymorphonuclear leukocyte (PMNs and mononuclear cell (MONOs infiltration of the placenta is associated with these disorders. The aim of this study was to reveal cell-specific differences in gene expression and cytokine release in response to endotoxin that would elucidate inflammatory control mechanisms in the newly born. METHODS: PMNs and MONOs were separately isolated from the same cord blood sample. A genome-wide microarray screened for gene expression and related pathways at 4 h of LPS stimulation (n = 5. RT-qPCR and ELISA were performed for selected cytokines at 4 h and 18 h of LPS stimulation. RESULTS: Compared to PMNs, MONOs had a greater diversity and more robust gene expression that included pro-inflammatory (PI cytokines, chemokines and growth factors at 4 h. Only MONOs had genes changing expression (all up regulated including interleukin-10 that were clustered in the JAK/STAT pathway. Pre-incubation with IL-10 antibody, for LPS-stimulated MONOs, led to up regulated PI and IL-10 gene expression and release of PI cytokines after 4 h. DISCUSSION: The present study suggests a dominant role of MONO gene expression in control of the fetal inflammatory response syndrome at 4 hrs of LPS stimulation. LPS-stimulated MONOs but not PMNs of the newborn have the ability to inhibit PI cytokine gene expression by latent IL-10 release.

  1. Targeting c-Myc-activated genes with a correlation method: Detection of global changes in large gene expression network dynamics

    Science.gov (United States)

    Remondini, D.; O'Connell, B.; Intrator, N.; Sedivy, J. M.; Neretti, N.; Castellani, G. C.; Cooper, L. N.

    2005-01-01

    This work studies the dynamics of a gene expression time series network. The network, which is obtained from the correlation of gene expressions, exhibits global dynamic properties that emerge after a cell state perturbation. The main features of this network appear to be more robust when compared with those obtained with a network obtained from a linear Markov model. In particular, the network properties strongly depend on the exact time sequence relationships between genes and are destroyed by random temporal data shuffling. We discuss in detail the problem of finding targets of the c-myc protooncogene, which encodes a transcriptional regulator whose inappropriate expression has been correlated with a wide array of malignancies. The data used for network construction are a time series of gene expression, collected by microarray analysis of a rat fibroblast cell line expressing a conditional Myc-estrogen receptor oncoprotein. We show that the correlation-based model can establish a clear relationship between network structure and the cascade of c-myc-activated genes. PMID:15867157

  2. 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.

  3. Modeling of gap gene expression in Drosophila Kruppel mutants.

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    Konstantin Kozlov

    Full Text Available The segmentation gene network in Drosophila embryo solves the fundamental problem of embryonic patterning: how to establish a periodic pattern of gene expression, which determines both the positions and the identities of body segments. The gap gene network constitutes the first zygotic regulatory tier in this process. Here we have applied the systems-level approach to investigate the regulatory effect of gap gene Kruppel (Kr on segmentation gene expression. We acquired a large dataset on the expression of gap genes in Kr null mutants and demonstrated that the expression levels of these genes are significantly reduced in the second half of cycle 14A. To explain this novel biological result we applied the gene circuit method which extracts regulatory information from spatial gene expression data. Previous attempts to use this formalism to correctly and quantitatively reproduce gap gene expression in mutants for a trunk gap gene failed, therefore here we constructed a revised model and showed that it correctly reproduces the expression patterns of gap genes in Kr null mutants. We found that the remarkable alteration of gap gene expression patterns in Kr mutants can be explained by the dynamic decrease of activating effect of Cad on a target gene and exclusion of Kr gene from the complex network of gap gene interactions, that makes it possible for other interactions, in particular, between hb and gt, to come into effect. The successful modeling of the quantitative aspects of gap gene expression in mutant for the trunk gap gene Kr is a significant achievement of this work. This result also clearly indicates that the oversimplified representation of transcriptional regulation in the previous models is one of the reasons for unsuccessful attempts of mutant simulations.

  4. Bioinformatics analysis of the gene expression profile in Bladder carcinoma

    Directory of Open Access Journals (Sweden)

    Jing Xiao

    2013-01-01

    Full Text Available Bladder carcinoma, which has the ninth highest incidence among malignant tumors in the world, is a complex, multifactorial disease. The malignant transformation of bladder cells results from DNA mutations and alterations in gene expression levels. In this work, we used a bioinformatics approach to investigate the molecular mechanisms of bladder carcinoma. Biochips downloaded from the Gene Expression Omnibus (GEO were used to analyze the gene expression profile in urinary bladder cells from individuals with carcinoma. The gene expression profile of normal genomes was used as a control. The analysis of gene expression revealed important alterations in genes involved in biological processes and metabolic pathways. We also identified some small molecules capable of reversing the altered gene expression in bladder carcinoma; these molecules could provide a basis for future therapies for the treatment of this disease.

  5. Gene expression patterns in Rainbow Trout, Oncorhynchus mykiss, exposed to a suite of model toxicants

    Energy Technology Data Exchange (ETDEWEB)

    Hook, Sharon E.; Skillman, Ann D.; Small, Jonathan A.; Schultz, Irv R.

    2006-05-25

    profile and mode of toxic action. Our array results showed good agreement with q RT PCR, which demonstrates that the arrays are a robust measure of gene expression. The specificity of the gene expression profile in response to a model toxicant, the link between genes upregulated and mode of toxic action, and the consistency between array and qPCR results all suggest that cDNA microarrays have the potential to screen environmental contaminants for biomarkers and mode of toxic action.

  6. Shaping Robust System through Evolution

    CERN Document Server

    Kaneko, Kunihiko

    2008-01-01

    Biological functions are generated as a result of developmental dynamics that form phenotypes governed by genotypes. The dynamical system for development is shaped through genetic evolution following natural selection based on the fitness of the phenotype. Here we study how this dynamical system is robust to noise during development and to genetic change by mutation. We adopt a simplified transcription regulation network model to govern gene expression, which gives a fitness function. Through simulations of the network that undergoes mutation and selection, we show that a certain level of noise in gene expression is required for the network to acquire both types of robustness. The results reveal how the noise that cells encounter during development shapes any network's robustness, not only to noise but also to mutations. We also establish a relationship between developmental and mutational robustness through phenotypic variances caused by genetic variation and epigenetic noise. A universal relationship betwee...

  7. Gene expression during fruit ripening in avocado.

    Science.gov (United States)

    Christoffersen, R E; Warm, E; Laties, G G

    1982-06-01

    The poly(A) (+)RNA populations from avocado fruit (Persea americana Mill cv. Hass) at four stages of ripening were isolated by two cycles of oligo-dT-cellulose chromatography and examined by invitro translation, using the rabbit reticulocyte lysate system, followed by two-dimensional gel electrophoresis (isoelectric focusing followed by sodium dodecyl sulfate polyacrylamide gel electrophoresis) of the resulting translation products. Three mRNAs increased dramatically with the climacteric rise in respiration and ethylene production. The molecular weights of the corresponding translation products from the ripening-related mRNAs are 80,000, 36,000, and 16,500. These results indicate that ripening may be linked to the expression of specific genes.

  8. Evolution of Gene Expression Balance Among Homeologs of Natural Polyploids

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    Jasdeep S. Mutti

    2017-04-01

    Full Text Available Polyploidy is a major evolutionary process in eukaryotes, yet the expression balance of homeologs in natural polyploids is largely unknown. To study this expression balance, the expression patterns of 2180 structurally well-characterized genes of wheat were studied, of which 813 had the expected three copies and 375 had less than three. Copy numbers of the remaining 992 ranged from 4 to 14, including homeologs, orthologs, and paralogs. Of the genes with three structural copies corresponding to homeologs, 55% expressed from all three, 38% from two, and the remaining 7% expressed from only one of the three copies. Homeologs of 76–87% of the genes showed differential expression patterns in different tissues, thus have evolved different gene expression controls, possibly resulting in novel functions. Homeologs of 55% of the genes showed tissue-specific expression, with the largest percentage (14% in the anthers and the smallest (7% in the pistils. The highest number (1.72/3 of homeologs/gene expression was in the roots and the lowest (1.03/3 in the anthers. As the expression of homeologs changed with changes in structural copy number, about 30% of the genes showed dosage dependence. Chromosomal location also impacted expression pattern as a significantly higher proportion of genes in the proximal regions showed expression from all three copies compared to that present in the distal regions.

  9. Evolution of Gene Expression Balance Among Homeologs of Natural Polyploids.

    Science.gov (United States)

    Mutti, Jasdeep S; Bhullar, Ramanjot K; Gill, Kulvinder S

    2017-04-03

    Polyploidy is a major evolutionary process in eukaryotes, yet the expression balance of homeologs in natural polyploids is largely unknown. To study this expression balance, the expression patterns of 2180 structurally well-characterized genes of wheat were studied, of which 813 had the expected three copies and 375 had less than three. Copy numbers of the remaining 992 ranged from 4 to 14, including homeologs, orthologs, and paralogs. Of the genes with three structural copies corresponding to homeologs, 55% expressed from all three, 38% from two, and the remaining 7% expressed from only one of the three copies. Homeologs of 76-87% of the genes showed differential expression patterns in different tissues, thus have evolved different gene expression controls, possibly resulting in novel functions. Homeologs of 55% of the genes showed tissue-specific expression, with the largest percentage (14%) in the anthers and the smallest (7%) in the pistils. The highest number (1.72/3) of homeologs/gene expression was in the roots and the lowest (1.03/3) in the anthers. As the expression of homeologs changed with changes in structural copy number, about 30% of the genes showed dosage dependence. Chromosomal location also impacted expression pattern as a significantly higher proportion of genes in the proximal regions showed expression from all three copies compared to that present in the distal regions.

  10. Dissecting specific and global transcriptional regulation of bacterial gene expression

    NARCIS (Netherlands)

    Gerosa, Luca; Kochanowski, Karl; Heinemann, Matthias; Sauer, Uwe

    2013-01-01

    Gene expression is regulated by specific transcriptional circuits but also by the global expression machinery as a function of growth. Simultaneous specific and global regulation thus constitutes an additional-but often neglected-layer of complexity in gene expression. Here, we develop an experiment

  11. Phenotypic plasticity and divergence in gene expression.

    Science.gov (United States)

    Healy, Timothy M; Schulte, Patricia M

    2015-07-01

    The extent to which phenotypic plasticity, or the ability of a single genotype to produce different phenotypes in different environments, impedes or promotes genetic divergence has been a matter of debate within evolutionary biology for many decades (see, for example, Ghalambor et al. ; Pfennig et al. ). Similarly, the role of evolution in shaping phenotypic plasticity remains poorly understood (Pigliucci ). In this issue of Molecular Ecology, Dayan et al. () provide empirical data relevant to these questions by assessing the extent of plasticity and divergence in the expression levels of 2272 genes in muscle tissue from killifish (genus Fundulus) exposed to different temperatures. F. heteroclitus (Fig. A) and F. grandis are minnows that inhabit estuarine marshes (Fig. B) along the coasts of the Atlantic Ocean and Gulf of Mexico in North America. These habitats undergo large variations in temperature both daily and seasonally, and these fish are known to demonstrate substantial phenotypic plasticity in response to temperature change (e.g. Fangue et al. ). Furthermore, the range of F. heteroclitus spans a large latitudinal gradient of temperatures, such that northern populations experience temperatures that are on average ~10°C colder than do southern populations (Schulte ). By comparing gene expression patterns between populations of these fish from different thermal habitats held in the laboratory at three different temperatures, Dayan et al. () address two important questions regarding the interacting effects of plasticity and evolution: (i) How does phenotypic plasticity affect adaptive divergence? and (ii) How does adaptive divergence affect plasticity?

  12. Expression regulation of design process gene in product design

    DEFF Research Database (Denmark)

    Fang, Lusheng; Li, Bo; Tong, Shurong

    2011-01-01

    is proposed and analyzed, as well as its three categories i.e., the operator gene, the structural gene and the regulator gene. Second, the trigger mechanism that design objectives and constraints trigger the operator gene is constructed. Third, the expression principle of structural gene is analyzed......To improve the design process efficiency, this paper proposes the principle and methodology that design process gene controls the characteristics of design process under the framework of design process reuse and optimization based on design process gene. First, the concept of design process gene...... with the example of design management gene. Last, the regulation mode that the regulator gene regulates the expression of the structural gene is established and it is illustrated by taking the design process management gene as an example. © (2011) Trans Tech Publications....

  13. Id expression in amphioxus and lamprey highlights the role of gene cooption during neural crest evolution

    Science.gov (United States)

    Meulemans, Daniel; McCauley, David; Bronner-Fraser, Marianne

    2003-01-01

    Neural crest cells are unique to vertebrates and generate many of the adult structures that differentiate them from their closest invertebrate relatives, the cephalochordates. Id genes are robust markers of neural crest cells at all stages of development. We compared Id gene expression in amphioxus and lamprey to ask if cephalochordates deploy Id genes at the neural plate border and dorsal neural tube in a manner similar to vertebrates. Furthermore, we examined whether Id expression in these cells is a basal vertebrate trait or a derived feature of gnathostomes. We found that while expression of Id genes in the mesoderm and endoderm is conserved between amphioxus and vertebrates, expression in the lateral neural plate border and dorsal neural tube is a vertebrate novelty. Furthermore, expression of lamprey Id implies that recruitment of Id genes to these cells occurred very early in the vertebrate lineage. Based on expression in amphioxus we postulate that Id cooption conferred sensory cell progenitor-like properties upon the lateral neurectoderm, and pharyngeal mesoderm-like properties upon cranial neural crest. Amphioxus Id expression is also consistent with homology between the anterior neurectoderm of amphioxus and the presumptive placodal ectoderm of vertebrates. These observations support the idea that neural crest evolution was driven in large part by cooption of multipurpose transcriptional regulators from other tissues and cell types.

  14. Characterization of chemically induced liver injuries using gene co-expression modules.

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    Gregory J Tawa

    Full Text Available Liver injuries due to ingestion or exposure to chemicals and industrial toxicants pose a serious health risk that may be hard to assess due to a lack of non-invasive diagnostic tests. Mapping chemical injuries to organ-specific damage and clinical outcomes via biomarkers or biomarker panels will provide the foundation for highly specific and robust diagnostic tests. Here, we have used DrugMatrix, a toxicogenomics database containing organ-specific gene expression data matched to dose-dependent chemical exposures and adverse clinical pathology assessments in Sprague Dawley rats, to identify groups of co-expressed genes (modules specific to injury endpoints in the liver. We identified 78 such gene co-expression modules associated with 25 diverse injury endpoints categorized from clinical pathology, organ weight changes, and histopathology. Using gene expression data associated with an injury condition, we showed that these modules exhibited different patterns of activation characteristic of each injury. We further showed that specific module genes mapped to 1 known biochemical pathways associated with liver injuries and 2 clinically used diagnostic tests for liver fibrosis. As such, the gene modules have characteristics of both generalized and specific toxic response pathways. Using these results, we proposed three gene signature sets characteristic of liver fibrosis, steatosis, and general liver injury based on genes from the co-expression modules. Out of all 92 identified genes, 18 (20% genes have well-documented relationships with liver disease, whereas the rest are novel and have not previously been associated with liver disease. In conclusion, identifying gene co-expression modules associated with chemically induced liver injuries aids in generating testable hypotheses and has the potential to identify putative biomarkers of adverse health effects.

  15. Characterization of Chemically Induced Liver Injuries Using Gene Co-Expression Modules

    Science.gov (United States)

    Tawa, Gregory J.; AbdulHameed, Mohamed Diwan M.; Yu, Xueping; Kumar, Kamal; Ippolito, Danielle L.; Lewis, John A.; Stallings, Jonathan D.; Wallqvist, Anders

    2014-01-01

    Liver injuries due to ingestion or exposure to chemicals and industrial toxicants pose a serious health risk that may be hard to assess due to a lack of non-invasive diagnostic tests. Mapping chemical injuries to organ-specific damage and clinical outcomes via biomarkers or biomarker panels will provide the foundation for highly specific and robust diagnostic tests. Here, we have used DrugMatrix, a toxicogenomics database containing organ-specific gene expression data matched to dose-dependent chemical exposures and adverse clinical pathology assessments in Sprague Dawley rats, to identify groups of co-expressed genes (modules) specific to injury endpoints in the liver. We identified 78 such gene co-expression modules associated with 25 diverse injury endpoints categorized from clinical pathology, organ weight changes, and histopathology. Using gene expression data associated with an injury condition, we showed that these modules exhibited different patterns of activation characteristic of each injury. We further showed that specific module genes mapped to 1) known biochemical pathways associated with liver injuries and 2) clinically used diagnostic tests for liver fibrosis. As such, the gene modules have characteristics of both generalized and specific toxic response pathways. Using these results, we proposed three gene signature sets characteristic of liver fibrosis, steatosis, and general liver injury based on genes from the co-expression modules. Out of all 92 identified genes, 18 (20%) genes have well-documented relationships with liver disease, whereas the rest are novel and have not previously been associated with liver disease. In conclusion, identifying gene co-expression modules associated with chemically induced liver injuries aids in generating testable hypotheses and has the potential to identify putative biomarkers of adverse health effects. PMID:25226513

  16. 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

    2015-06-02

    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.

  17. Individual variation of adipose gene expression and identification of covariated genes by cDNA microarrays

    NARCIS (Netherlands)

    Boeuf, S.; Keijer, J.; Franssen-Hal, van N.L.W.; Klaus, S.

    2002-01-01

    Gene expression profiling through the application of microarrays provides comprehensive assessment of gene expression levels in a given tissue or cell population, as well as information on changes of gene expression in altered physiological or pathological situations. Microarrays are particularly su

  18. A robust and efficient method for estimating enzyme complex abundance and metabolic flux from expression data.

    Science.gov (United States)

    Barker, Brandon E; Sadagopan, Narayanan; Wang, Yiping; Smallbone, Kieran; Myers, Christopher R; Xi, Hongwei; Locasale, Jason W; Gu, Zhenglong

    2015-12-01

    A major theme in constraint-based modeling is unifying experimental data, such as biochemical information about the reactions that can occur in a system or the composition and localization of enzyme complexes, with high-throughput data including expression data, metabolomics, or DNA sequencing. The desired result is to increase predictive capability and improve our understanding of metabolism. The approach typically employed when only gene (or protein) intensities are available is the creation of tissue-specific models, which reduces the available reactions in an organism model, and does not provide an objective function for the estimation of fluxes. We develop a method, flux assignment with LAD (least absolute deviation) convex objectives and normalization (FALCON), that employs metabolic network reconstructions along with expression data to estimate fluxes. In order to use such a method, accurate measures of enzyme complex abundance are needed, so we first present an algorithm that addresses quantification of complex abundance. Our extensions to prior techniques include the capability to work with large models and significantly improved run-time performance even for smaller models, an improved analysis of enzyme complex formation, the ability to handle large enzyme complex rules that may incorporate multiple isoforms, and either maintained or significantly improved correlation with experimentally measured fluxes. FALCON has been implemented in MATLAB and ATS, and can be downloaded from: https://github.com/bbarker/FALCON. ATS is not required to compile the software, as intermediate C source code is available. FALCON requires use of the COBRA Toolbox, also implemented in MATLAB.

  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.

  20. Variance of gene expression identifies altered network constraints in neurological disease.

    Directory of Open Access Journals (Sweden)

    Jessica C Mar

    2011-08-01

    Full Text Available Gene expression analysis has become a ubiquitous tool for studying a wide range of human diseases. In a typical analysis we compare distinct phenotypic groups and attempt to identify genes that are, on average, significantly different between them. Here we describe an innovative approach to the analysis of gene expression data, one that identifies differences in expression variance between groups as an informative metric of the group phenotype. We find that genes with different expression variance profiles are not randomly distributed across cell signaling networks. Genes with low-expression variance, or higher constraint, are significantly more connected to other network members and tend to function as core members of signal transduction pathways. Genes with higher expression variance have fewer network connections and also tend to sit on the periphery of the cell. Using neural stem cells derived from patients suffering from Schizophrenia (SZ, Parkinson's disease (PD, and a healthy control group, we find marked differences in expression variance in cell signaling pathways that shed new light on potential mechanisms associated with these diverse neurological disorders. In particular, we find that expression variance of core networks in the SZ patient group was considerably constrained, while in contrast the PD patient group demonstrated much greater variance than expected. One hypothesis is that diminished variance in SZ patients corresponds to an increased degree of constraint in these pathways and a corresponding reduction in robustness of the stem cell networks. These results underscore the role that variation plays in biological systems and suggest that analysis of expression variance is far more important in disease than previously recognized. Furthermore, modeling patterns of variability in gene expression could fundamentally alter the way in which we think about how cellular networks are affected by disease processes.

  1. Radiolabeled PNAs for imaging gene expression

    Energy Technology Data Exchange (ETDEWEB)

    Wickstrom, Eric; Sauter, Edward; Tian, Xianben; Rao, Sampath; Quin, Weyng; Thakur, Mathew [Thomas Jefferson Univ., PA (United States)

    2002-09-01

    Scintigraphic imaging of gene expression in vivo by non-invasive means could precisely direct physicians to appropriate intervention at the onset of disease and could contribute extensively to the management of patients. However no method is currently available to image specific over expressed oncogene mRNAs in vivo by scintigraphic imaging. Nevertheless, we have observed that Tc 99 m peptides can delineate tumors, and that PNA-peptides are specific for receptors on malignant cells and are taken up specifically and concentrated in nuclei. We hypothesize that antisense Tc 99 m PNA peptides will be taken up by human breast cancer cells, hybridize to complementary mRNA targets, and permit imaging of oncogene mRNAs in human breast cancer xenografts in a mouse model, providing a proof-of-principle for non-invasive detection of precancerous and invasive breast cancer. Oncogenes cyclin D1, erB-2, c-MYC and tumor suppressor p53 will be probed. If successful, this technique will be useful for diagnostic imaging of other solid tumors as well. (author)

  2. Screening and expression of genes from metagenomes.

    Science.gov (United States)

    Leis, Benedikt; Angelov, Angel; Liebl, Wolfgang

    2013-01-01

    Microorganisms are the most abundant and widely spread organisms on earth. They colonize a huge variety of natural and anthropogenic environments, including very specialized ecological niches and even extreme habitats, which are made possible by the immense metabolic diversity and genetic adaptability of microbes. As most of the organisms from environmental samples defy cultivation, cultivation-independent metagenomics approaches have been applied since more than one decade to access and characterize the phylogenetic diversity in microbial communities as well as their metabolic potential and ecological functions. Thereby, metagenomics has fully emerged as an own scientific field for mining new biocatalysts for many industrially relevant processes in biotechnology and pharmaceutics. This review summarizes common metagenomic approaches ranging from sampling, isolation of nucleic acids, construction of metagenomic libraries and their evaluation. Sequence-based screenings implement next-generation sequencing platforms, microarrays or PCR-based methods, while function-based analysis covers heterologous expression of metagenomic libraries in diverse screening setups. Major constraints and advantages of each strategy are described. The importance of alternative host-vector systems is discussed, and in order to underline the role of phylogenetic and physiological distance from the gene donor and the expression host employed, a case study is presented that describes the screening of a genomic library from an extreme thermophilic bacterium in both Escherichia coli and Thermus thermophilus. Metatranscriptomics, metaproteomics and single-cell-based methods are expected to complement metagenomic screening efforts to identify novel biocatalysts from environmental samples.

  3. Integrated analysis of gene expression by association rules discovery

    Directory of Open Access Journals (Sweden)

    Carazo Jose M

    2006-02-01

    Full Text Available Abstract Background Microarray technology is generating huge amounts of data about the expression level of thousands of genes, or even whole genomes, across different experimental conditions. To extract biological knowledge, and to fully understand such datasets, it is essential to include external biological information about genes and gene products to the analysis of expression data. However, most of the current approaches to analyze microarray datasets are mainly focused on the analysis of experimental data, and external biological information is incorporated as a posterior process. Results In this study we present a method for the integrative analysis of microarray data based on the Association Rules Discovery data mining technique. The approach integrates gene annotations and expression data to discover intrinsic associations among both data sources based on co-occurrence patterns. We applied the proposed methodology to the analysis of gene expression datasets in which genes were annotated with metabolic pathways, transcriptional regulators and Gene Ontology categories. Automatically extracted associations revealed significant relationships among these gene attributes and expression patterns, where many of them are clearly supported by recently reported work. Conclusion The integration of external biological information and gene expression data can provide insights about the biological processes associated to gene expression programs. In this paper we show that the proposed methodology is able to integrate multiple gene annotations and expression data in the same analytic framework and extract meaningful associations among heterogeneous sources of data. An implementation of the method is included in the Engene software package.

  4. Using RNA-Seq data to select refence genes for normalizing gene expression in apple roots

    Science.gov (United States)

    Gene expression in apple roots in response to various stress conditions is a less-explored research subject. Reliable reference genes for normalizing quantitative gene expression data have not been carefully investigated. In this study, the suitability of a set of 15 apple genes were evaluated for t...

  5. Integrative meta-analysis of differential gene expression in acute myeloid leukemia.

    Directory of Open Access Journals (Sweden)

    Brady G Miller

    Full Text Available BACKGROUND: Acute myeloid leukemia (AML is a heterogeneous disease with an overall poor prognosis. Gene expression profiling studies of patients with AML has provided key insights into disease pathogenesis while exposing potential diagnostic and prognostic markers and therapeutic targets. A systematic comparison of the large body of gene expression profiling studies in AML has the potential to test the extensibility of conclusions based on single studies and provide further insights into AML. METHODOLOGY/PRINCIPAL FINDINGS: In this study, we systematically compared 25 published reports of gene expression profiling in AML. There were a total of 4,918 reported genes of which one third were reported in more than one study. We found that only a minority of reported prognostically-associated genes (9.6% were replicated in at least one other study. In a combined analysis, we comprehensively identified both gene sets and functional gene categories and pathways that exhibited significant differential regulation in distinct prognostic categories, including many previously unreported associations. CONCLUSIONS/SIGNIFICANCE: We developed a novel approach for granular, cross-study analysis of gene-by-gene data and their relationships with established prognostic features and patient outcome. We identified many robust novel prognostic molecular features in AML that were undetected in prior studies, and which provide insights into AML pathogenesis with potential diagnostic, prognostic, and therapeutic implications. Our database and integrative analysis are available online (http://gat.stamlab.org.

  6. CDX2 gene expression in acute lymphoblastic leukemia

    Directory of Open Access Journals (Sweden)

    Hanaa H. Arnaoaut

    2014-06-01

    Full Text Available CDX genes are classically known as regulators of axial elongation during early embryogenesis. An unsuspected role for CDX genes has been revealed during hematopoietic development. The CDX gene family member CDX2 belongs to the most frequent aberrantly expressed proto-oncogenes in human acute leukemias and is highly leukemogenic in experimental models. We used reversed transcriptase polymerase chain reaction (RT-PCR to determine the expression level of CDX2 gene in 30 pediatric patients with acute lymphoblastic leukemia (ALL at diagnosis and 30 healthy volunteers. ALL patients were followed up to detect minimal residual disease (MRD on days 15 and 42 of induction. We found that CDX2 gene was expressed in 50% of patients and not expressed in controls. Associations between gene expression and different clinical and laboratory data of patients revealed no impact on different findings. With follow up, we could not confirm that CDX2 expression had a prognostic significance.

  7. Optimal consistency in microRNA expression analysis using reference-gene-based normalization.

    Science.gov (United States)

    Wang, Xi; Gardiner, Erin J; Cairns, Murray J

    2015-05-01

    Normalization of high-throughput molecular expression profiles secures differential expression analysis between samples of different phenotypes or biological conditions, and facilitates comparison between experimental batches. While the same general principles apply to microRNA (miRNA) normalization, there is mounting evidence that global shifts in their expression patterns occur in specific circumstances, which pose a challenge for normalizing miRNA expression data. As an alternative to global normalization, which has the propensity to flatten large trends, normalization against constitutively expressed reference genes presents an advantage through their relative independence. Here we investigated the performance of reference-gene-based (RGB) normalization for differential miRNA expression analysis of microarray expression data, and compared the results with other normalization methods, including: quantile, variance stabilization, robust spline, simple scaling, rank invariant, and Loess regression. The comparative analyses were executed using miRNA expression in tissue samples derived from subjects with schizophrenia and non-psychiatric controls. We proposed a consistency criterion for evaluating methods by examining the overlapping of differentially expressed miRNAs detected using different partitions of the whole data. Based on this criterion, we found that RGB normalization generally outperformed global normalization methods. Thus we recommend the application of RGB normalization for miRNA expression data sets, and believe that this will yield a more consistent and useful readout of differentially expressed miRNAs, particularly in biological conditions characterized by large shifts in miRNA expression.

  8. Systematic repression of transcription factors reveals limited patterns of gene expression changes in ES cells

    Science.gov (United States)

    Nishiyama, Akira; Sharov, Alexei A.; Piao, Yulan; Amano, Misa; Amano, Tomokazu; Hoang, Hien G.; Binder, Bernard Y.; Tapnio, Richard; Bassey, Uwem; Malinou, Justin N.; Correa-Cerro, Lina S.; Yu, Hong; Xin, Li; Meyers, Emily; Zalzman, Michal; Nakatake, Yuhki; Stagg, Carole; Sharova, Lioudmila; Qian, Yong; Dudekula, Dawood; Sheer, Sarah; Cadet, Jean S.; Hirata, Tetsuya; Yang, Hsih-Te; Goldberg, Ilya; Evans, Michele K.; Longo, Dan L.; Schlessinger, David; Ko, Minoru S. H.

    2013-01-01

    Networks of transcription factors (TFs) are thought to determine and maintain the identity of cells. Here we systematically repressed each of 100 TFs with shRNA and carried out global gene expression profiling in mouse embryonic stem (ES) cells. Unexpectedly, only the repression of a handful of TFs significantly affected transcriptomes, which changed in two directions/trajectories: one trajectory by the repression of either Pou5f1 or Sox2; the other trajectory by the repression of either Esrrb, Sall4, Nanog, or Tcfap4. The data suggest that the trajectories of gene expression change are already preconfigured by the gene regulatory network and roughly correspond to extraembryonic and embryonic fates of cell differentiation, respectively. These data also indicate the robustness of the pluripotency gene network, as the transient repression of most TFs did not alter the transcriptomes. PMID:23462645

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

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    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. Serial Analysis of Gene Expression: Applications in Human Studies

    OpenAIRE

    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...

  11. A Pathway Based Classification Method for Analyzing Gene Expression for Alzheimer’s Disease Diagnosis

    Science.gov (United States)

    Voyle, Nicola; Keohane, Aoife; Newhouse, Stephen; Lunnon, Katie; Johnston, Caroline; Soininen, Hilkka; Kloszewska, Iwona; Mecocci, Patrizia; Tsolaki, Magda; Vellas, Bruno; Lovestone, Simon; Hodges, Angela; Kiddle, Steven; Dobson, Richard JB.

    2015-01-01

    Background: Recent studies indicate that gene expression levels in blood may be able to differentiate subjects with Alzheimer’s disease (AD) from normal elderly controls and mild cognitively impaired (MCI) subjects. However, there is limited replicability at the single marker level. A pathway-based interpretation of gene expression may prove more robust. Objectives: This study aimed to investigate whether a case/control classification model built on pathway level data was more robust than a gene level model and may consequently perform better in test data. The study used two batches of gene expression data from the AddNeuroMed (ANM) and Dementia Case Registry (DCR) cohorts. Methods: Our study used Illumina Human HT-12 Expression BeadChips to collect gene expression from blood samples. Random forest modeling with recursive feature elimination was used to predict case/control status. Age and APOE ɛ4 status were used as covariates for all analysis. Results: Gene and pathway level models performed similarly to each other and to a model based on demographic information only. Conclusions: Any potential increase in concordance from the novel pathway level approach used here has not lead to a greater predictive ability in these datasets. However, we have only tested one method for creating pathway level scores. Further, we have been able to benchmark pathways against genes in datasets that had been extensively harmonized. Further work should focus on the use of alternative methods for creating pathway level scores, in particular those that incorporate pathway topology, and the use of an endophenotype based approach. PMID:26484910

  12. A precisely regulated gene expression cassette potently modulates metastasis and survival in multiple solid cancers.

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    Kun Yu

    Full Text Available Successful tumor development and progression involves the complex interplay of both pro- and anti-oncogenic signaling pathways. Genetic components balancing these opposing activities are likely to require tight regulation, because even subtle alterations in their expression may disrupt this balance with major consequences for various cancer-associated phenotypes. Here, we describe a cassette of cancer-specific genes exhibiting precise transcriptional control in solid tumors. Mining a database of tumor gene expression profiles from six different tissues, we identified 48 genes exhibiting highly restricted levels of gene expression variation in tumors (n = 270 compared to nonmalignant tissues (n = 71. Comprising genes linked to multiple cancer-related pathways, the restricted expression of this "Poised Gene Cassette" (PGC was robustly validated across 11 independent cohorts of approximately 1,300 samples from multiple cancer types. In three separate experimental models, subtle alterations in PGC expression were consistently associated with significant differences in metastatic and invasive potential. We functionally confirmed this association in siRNA knockdown experiments of five PGC genes (p53CSV, MAP3K11, MTCH2, CPSF6, and SKIP, which either directly enhanced the invasive capacities or inhibited the proliferation of AGS cancer cells. In primary tumors, similar subtle alterations in PGC expression were also repeatedly associated with clinical outcome in multiple cohorts. Taken collectively, these findings support the existence of a common set of precisely controlled genes in solid tumors. Since inducing small activity changes in these genes may prove sufficient to potently influence various tumor phenotypes such as metastasis, targeting such precisely regulated genes may represent a promising avenue for novel anti-cancer therapies.

  13. 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.

  14. Analysis of the robustness of network-based disease-gene prioritization methods reveals redundancy in the human interactome and functional diversity of disease-genes.

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    Emre Guney

    Full Text Available Complex biological systems usually pose a trade-off between robustness and fragility where a small number of perturbations can substantially disrupt the system. Although biological systems are robust against changes in many external and internal conditions, even a single mutation can perturb the system substantially, giving rise to a pathophenotype. Recent advances in identifying and analyzing the sequential variations beneath human disorders help to comprehend a systemic view of the mechanisms underlying various disease phenotypes. Network-based disease-gene prioritization methods rank the relevance of genes in a disease under the hypothesis that genes whose proteins interact with each other tend to exhibit similar phenotypes. In this study, we have tested the robustness of several network-based disease-gene prioritization methods with respect to the perturbations of the system using various disease phenotypes from the Online Mendelian Inheritance in Man database. These perturbations have been introduced either in the protein-protein interaction network or in the set of known disease-gene associations. As the network-based disease-gene prioritization methods are based on the connectivity between known disease-gene associations, we have further used these methods to categorize the pathophenotypes with respect to the recoverability of hidden disease-genes. Our results have suggested that, in general, disease-genes are connected through multiple paths in the human interactome. Moreover, even when these paths are disturbed, network-based prioritization can reveal hidden disease-gene associations in some pathophenotypes such as breast cancer, cardiomyopathy, diabetes, leukemia, parkinson disease and obesity to a greater extend compared to the rest of the pathophenotypes tested in this study. Gene Ontology (GO analysis highlighted the role of functional diversity for such diseases.

  15. Effect of method of deduplication on estimation of differential gene expression using RNA-seq

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    Anna V. Klepikova

    2017-03-01

    Full Text Available Background RNA-seq is a useful tool for analysis of gene expression. However, its robustness is greatly affected by a number of artifacts. One of them is the presence of duplicated reads. Results To infer the influence of different methods of removal of duplicated reads on estimation of gene expression in cancer genomics, we analyzed paired samples of hepatocellular carcinoma (HCC and non-tumor liver tissue. Four protocols of data analysis were applied to each sample: processing without deduplication, deduplication using a method implemented in SAMtools, and deduplication based on one or two molecular indices (MI. We also analyzed the influence of sequencing layout (single read or paired end and read length. We found that deduplication without MI greatly affects estimated expression values; this effect is the most pronounced for highly expressed genes. Conclusion The use of unique molecular identifiers greatly improves accuracy of RNA-seq analysis, especially for highly expressed genes. We developed a set of scripts that enable handling of MI and their incorporation into RNA-seq analysis pipelines. Deduplication without MI affects results of differential gene expression analysis, producing a high proportion of false negative results. The absence of duplicate read removal is biased towards false positives. In those cases where using MI is not possible, we recommend using paired-end sequencing layout.

  16. Effect of method of deduplication on estimation of differential gene expression using RNA-seq

    Science.gov (United States)

    Chesnokov, Mikhail S.; Lazarevich, Natalia L.; Penin, Aleksey A.

    2017-01-01

    Background RNA-seq is a useful tool for analysis of gene expression. However, its robustness is greatly affected by a number of artifacts. One of them is the presence of duplicated reads. Results To infer the influence of different methods of removal of duplicated reads on estimation of gene expression in cancer genomics, we analyzed paired samples of hepatocellular carcinoma (HCC) and non-tumor liver tissue. Four protocols of data analysis were applied to each sample: processing without deduplication, deduplication using a method implemented in SAMtools, and deduplication based on one or two molecular indices (MI). We also analyzed the influence of sequencing layout (single read or paired end) and read length. We found that deduplication without MI greatly affects estimated expression values; this effect is the most pronounced for highly expressed genes. Conclusion The use of unique molecular identifiers greatly improves accuracy of RNA-seq analysis, especially for highly expressed genes. We developed a set of scripts that enable handling of MI and their incorporation into RNA-seq analysis pipelines. Deduplication without MI affects results of differential gene expression analysis, producing a high proportion of false negative results. The absence of duplicate read removal is biased towards false positives. In those cases where using MI is not possible, we recommend using paired-end sequencing layout. PMID:28321364

  17. Evidence for mitochondrial genetic control of autosomal gene expression.

    Science.gov (United States)

    Kassam, Irfahan; Qi, Tuan; Lloyd-Jones, Luke; Holloway, Alexander; Jan Bonder, Marc; Henders, Anjali K; Martin, Nicholas G; Powell, Joseph E; Franke, Lude; Montgomery, Grant W; Visscher, Peter M; McRae, Allan F

    2016-10-18

    The mitochondrial and nuclear genomes coordinate and co-evolve in eukaryotes in order to adapt to environmental changes. Variation in the mitochondrial genome is capable of affecting expression of genes on the nuclear genome. Sex-specific mitochondrial genetic control of gene expression has been demonstrated in Drosophila melanogaster, where males were found to drive most of the total variation in gene expression. This has potential implications for male-related health and disease resulting from variation in mtDNA solely inherited from the mother. We used a family-based study comprised of 47,323 gene expression probes and 78 mitochondrial SNPs (mtSNPs) from n = 846 individuals to examine the extent of mitochondrial genetic control of gene expression in humans. This identified 15 significant probe-mtSNP associations (P[Formula: see text]) corresponding to 5 unique genes on the mitochondrial and nuclear genomes, with three of these genes corresponding to mitochondrial genetic control of gene expression in the nuclear genome. The associated mtSNPs for three genes (one cis and two trans associations) were replicated (P expression in any of these five probes. Sex-specific effects were examined by applying our analysis to males and females separately and testing for differences in effect size. The MEST gene was identified as having the most significantly different effect sizes across the sexes (P [Formula: see text]). MEST was similarly expressed in males and females with the G allele; however, males with the C allele are highly expressed for MEST, while females show no expression of the gene. This study provides evidence for the mitochondrial genetic control of expression of several genes in humans, with little evidence found for sex-specific effects.

  18. Quantitative modeling of a gene's expression from its intergenic sequence.

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    Md Abul Hassan Samee

    2014-03-01

    Full Text Available Modeling a gene's expression from its intergenic locus and trans-regulatory context is a fundamental goal in computational biology. Owing to the distributed nature of cis-regulatory information and the poorly understood mechanisms that integrate such information, gene locus modeling is a more challenging task than modeling individual enhancers. Here we report the first quantitative model of a gene's expression pattern as a function of its locus. We model the expression readout of a locus in two tiers: 1 combinatorial regulation by transcription factors bound to each enhancer is predicted by a thermodynamics-based model and 2 independent contributions from multiple enhancers are linearly combined to fit the gene expression pattern. The model does not require any prior knowledge about enhancers contributing toward a gene's expression. We demonstrate that the model captures the complex multi-domain expression patterns of anterior-posterior patterning genes in the early Drosophila embryo. Altogether, we model the expression patterns of 27 genes; these include several gap genes, pair-rule genes, and anterior, posterior, trunk, and terminal genes. We find that the model-selected enhancers for each gene overlap strongly with its experimentally characterized enhancers. Our findings also suggest the presence of sequence-segments in the locus that would contribute ectopic expression patterns and hence were "shut down" by the model. We applied our model to identify the transcription factors responsible for forming the stripe boundaries of the studied genes. The resulting network of regulatory interactions exhibits a high level of agreement with known regulatory influences on the target genes. Finally, we analyzed whether and why our assumption of enhancer independence was necessary for the genes we studied. We found a deterioration of expression when binding sites in one enhancer were allowed to influence the readout of another enhancer. Thus, interference

  19. Heterologous gene expression in filamentous fungi.

    Science.gov (United States)

    Su, Xiaoyun; Schmitz, George; Zhang, Meiling; Mackie, Roderick I; Cann, Isaac K O

    2012-01-01

    Filamentous fungi are critical to production of many commercial enzymes and organic compounds. Fungal-based systems have several advantages over bacterial-based systems for protein production because high-level secretion of enzymes is a common trait of their decomposer lifestyle. Furthermore, in the large-scale production of recombinant proteins of eukaryotic origin, the filamentous fungi become the vehicle of choice due to critical processes shared in gene expression with other eukaryotic organisms. The complexity and relative dearth of understanding of the physiology of filamentous fungi, compared to bacteria, have hindered rapid development of these organisms as highly efficient factories for the production of heterologous proteins. In this review, we highlight several of the known benefits and challenges in using filamentous fungi (particularly Aspergillus spp., Trichoderma reesei, and Neurospora crassa) for the production of proteins, especially heterologous, nonfungal enzymes. We review various techniques commonly employed in recombinant protein production in the filamentous fungi, including transformation methods, selection of gene regulatory elements such as promoters, protein secretion factors such as the signal peptide, and optimization of coding sequence. We provide insights into current models of host genomic defenses such as repeat-induced point mutation and quelling. Furthermore, we examine the regulatory effects of transcript sequences, including introns and untranslated regions, pre-mRNA (messenger RNA) processing, transcript transport, and mRNA stability. We anticipate that this review will become a resource for researchers who aim at advancing the use of these fascinating organisms as protein production factories, for both academic and industrial purposes, and also for scientists with general interest in the biology of the filamentous fungi. Copyright © 2012 Elsevier Inc. All rights reserved.

  20. 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.

  1. Faster-X Evolution of Gene Expression in Drosophila

    Science.gov (United States)

    Meisel, Richard P.; Malone, John H.; Clark, Andrew G.

    2012-01-01

    DNA sequences on X chromosomes often have a faster rate of evolution when compared to similar loci on the autosomes, and well articulated models provide reasons why the X-linked mode of inheritance may be responsible for the faster evolution of X-linked genes. We analyzed microarray and RNA–seq data collected from females and males of six Drosophila species and found that the expression levels of X-linked genes also diverge faster than autosomal gene expression, similar to the “faster-X” effect often observed in DNA sequence evolution. Faster-X evolution of gene expression was recently described in mammals, but it was limited to the evolutionary lineages shortly following the creation of the therian X chromosome. In contrast, we detect a faster-X effect along both deep lineages and those on the tips of the Drosophila phylogeny. In Drosophila males, the dosage compensation complex (DCC) binds the X chromosome, creating a unique chromatin environment that promotes the hyper-expression of X-linked genes. We find that DCC binding, chromatin environment, and breadth of expression are all predictive of the rate of gene expression evolution. In addition, estimates of the intraspecific genetic polymorphism underlying gene expression variation suggest that X-linked expression levels are not under relaxed selective constraints. We therefore hypothesize that the faster-X evolution of gene expression is the result of the adaptive fixation of beneficial mutations at X-linked loci that change expression level in cis. This adaptive faster-X evolution of gene expression is limited to genes that are narrowly expressed in a single tissue, suggesting that relaxed pleiotropic constraints permit a faster response to selection. Finally, we present a conceptional framework to explain faster-X expression evolution, and we use this framework to examine differences in the faster-X effect between Drosophila and mammals. PMID:23071459

  2. A fast and efficient gene-network reconstruction method from multiple over-expression experiments

    Directory of Open Access Journals (Sweden)

    Thurner Stefan

    2009-08-01

    Full Text Available Abstract Background Reverse engineering of gene regulatory networks presents one of the big challenges in systems biology. Gene regulatory networks are usually inferred from a set of single-gene over-expressions and/or knockout experiments. Functional relationships between genes are retrieved either from the steady state gene expressions or from respective time series. Results We present a novel algorithm for gene network reconstruction on the basis of steady-state gene-chip data from over-expression experiments. The algorithm is based on a straight forward solution of a linear gene-dynamics equation, where experimental data is fed in as a first predictor for the solution. We compare the algorithm's performance with the NIR algorithm, both on the well known E. coli experimental data and on in-silico experiments. Conclusion We show superiority of the proposed algorithm in the number of correctly reconstructed links and discuss computational time and robustness. The proposed algorithm is not limited by combinatorial explosion problems and can be used in principle for large networks.

  3. TALE activators regulate gene expression in a position- and strand-dependent manner in mammalian cells.

    Science.gov (United States)

    Uhde-Stone, Claudia; Cheung, Edna; Lu, Biao

    2014-01-24

    Transcription activator-like effectors (TALEs) are a class of transcription factors that are readily programmable to regulate gene expression. Despite their growing popularity, little is known about binding site parameters that influence TALE-mediated gene activation in mammalian cells. We demonstrate that TALE activators modulate gene expression in mammalian cells in a position- and strand-dependent manner. To study the effects of binding site location, we engineered TALEs customized to recognize specific DNA sequences located in either the promoter or the transcribed region of reporter genes. We found that TALE activators robustly activated reporter genes when their binding sites were located within the promoter region. In contrast, TALE activators inhibited the expression of reporter genes when their binding sites were located on the sense strand of the transcribed region. Notably, this repression was independent of the effector domain utilized, suggesting a simple blockage mechanism. We conclude that TALE activators in mammalian cells regulate genes in a position- and strand-dependent manner that is substantially different from gene activation by native TALEs in plants. These findings have implications for optimizing the design of custom TALEs for genetic manipulation in mammalian cells.

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

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    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.

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

    Science.gov (United States)

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

    2007-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Tuncay Kagan

    2007-01-01

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

  7. 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.

  8. Accurate and unambiguous tag-to-gene mapping in serial analysis of gene expression

    Directory of Open Access Journals (Sweden)

    Melo Francisco

    2006-11-01

    Full Text Available Abstract Background In this study, we present a robust and reliable computational method for tag-to-gene assignment in serial analysis of gene expression (SAGE. The method relies on current genome information and annotation, incorporation of several new features, and key improvements over alternative methods, all of which are important to determine gene expression levels more accurately. The method provides a complete annotation of potential virtual SAGE tags within a genome, along with an estimation of their confidence for experimental observation that ranks tags that present multiple matches in the genome. Results We applied this method to the Saccharomyces cerevisiae genome, producing the most thorough and accurate annotation of potential virtual SAGE tags that is available today for this organism. The usefulness of this method is exemplified by the significant reduction of ambiguous cases in existing experimental SAGE data. In addition, we report new insights from the analysis of existing SAGE data. First, we found that experimental SAGE tags mapping onto introns, intron-exon boundaries, and non-coding RNA elements are observed in all available SAGE data. Second, a significant fraction of experimental SAGE tags was found to map onto genomic regions currently annotated as intergenic. Third, a significant number of existing experimental SAGE tags for yeast has been derived from truncated cDNAs, which are synthesized through oligo-d(T priming to internal poly-(A regions during reverse transcription. Conclusion We conclude that an accurate and unambiguous tag mapping process is essential to increase the quality and the amount of information that can be extracted from SAGE experiments. This is supported by the results obtained here and also by the large impact that the erroneous interpretation of these data could have on downstream applications.

  9. Social Regulation of Gene Expression in Threespine Sticklebacks.

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    Anna K Greenwood

    Full Text Available Identifying genes that are differentially expressed in response to social interactions is informative for understanding the molecular basis of social behavior. To address this question, we described changes in gene expression as a result of differences in the extent of social interactions. We housed threespine stickleback (Gasterosteus aculeatus females in either group conditions or individually for one week, then measured levels of gene expression in three brain regions using RNA-sequencing. We found that numerous genes in the hindbrain/cerebellum had altered expression in response to group or individual housing. However, relatively few genes were differentially expressed in either the diencephalon or telencephalon. The list of genes upregulated in fish from social groups included many genes related to neural development and cell adhesion as well as genes with functions in sensory signaling, stress, and social and reproductive behavior. The list of genes expressed at higher levels in individually-housed fish included several genes previously identified as regulated by social interactions in other animals. The identified genes are interesting targets for future research on the molecular mechanisms of normal social interactions.

  10. Large Scale Gene Expression Meta-Analysis Reveals Tissue-Specific, Sex-Biased Gene Expression in Humans

    Science.gov (United States)

    Mayne, Benjamin T.; Bianco-Miotto, Tina; Buckberry, Sam; Breen, James; Clifton, Vicki; Shoubridge, Cheryl; Roberts, Claire T.

    2016-01-01

    The severity and prevalence of many diseases are known to differ between the sexes. Organ specific sex-biased gene expression may underpin these and other sexually dimorphic traits. To further our understanding of sex differences in transcriptional regulation, we performed meta-analyses of sex biased gene expression in multiple human tissues. We analyzed 22 publicly available human gene expression microarray data sets including over 2500 samples from 15 different tissues and 9 different organs. Briefly, by using an inverse-variance method we determined the effect size difference of gene expression between males and females. We found the greatest sex differences in gene expression in the brain, specifically in the anterior cingulate cortex, (1818 genes), followed by the heart (375 genes), kidney (224 genes), colon (218 genes), and thyroid (163 genes). More interestingly, we found different parts of the brain with varying numbers and identity of sex-biased genes, indicating that specific cortical regions may influence sexually dimorphic traits. The majority of sex-biased genes in other tissues such as the bladder, liver, lungs, and pancreas were on the sex chromosomes or involved in sex hormone production. On average in each tissue, 32% of autosomal genes that were expressed in a sex-biased fashion contained androgen or estrogen hormone response elements. Interestingly, across all tissues, we found approximately two-thirds of autosomal genes that were sex-biased were not under direct influence of sex hormones. To our knowledge this is the largest analysis of sex-biased gene expression in human tissues to date. We identified many sex-biased genes that were not under the direct influence of sex chromosome genes or sex hormones. These may provide targets for future development of sex-specific treatments for diseases.

  11. Large scale gene expression meta-analysis reveals tissue-specific, sex-biased gene expression in humans

    Directory of Open Access Journals (Sweden)

    Benjamin Mayne

    2016-10-01

    Full Text Available The severity and prevalence of many diseases are known to differ between the sexes. Organ specific sex-biased gene expression may underpin these and other sexually dimorphic traits. To further our understanding of sex differences in transcriptional regulation, we performed meta-analyses of sex biased gene expression in multiple human tissues. We analysed 22 publicly available human gene expression microarray data sets including over 2500 samples from 15 different tissues and 9 different organs. Briefly, by using an inverse-variance method we determined the effect size difference of gene expression between males and females. We found the greatest sex differences in gene expression in the brain, specifically in the anterior cingulate cortex, (1818 genes, followed by the heart (375 genes, kidney (224 genes, colon (218 genes and thyroid (163 genes. More interestingly, we found different parts of the brain with varying numbers and identity of sex-biased genes, indicating that specific cortical regions may influence sexually dimorphic traits. The majority of sex-biased genes in other tissues such as the bladder, liver, lungs and pancreas were on the sex chromosomes or involved in sex hormone production. On average in each tissue, 32% of autosomal genes that were expressed in a sex-biased fashion contained androgen or estrogen hormone response elements. Interestingly, across all tissues, we found approximately two-thirds of autosomal genes that were sex-biased were not under direct influence of sex hormones. To our knowledge this is the largest analysis of sex-biased gene expression in human tissues to date. We identified many sex-biased genes that were not under the direct influence of sex chromosome genes or sex hormones. These may provide targets for future development of sex-specific treatments for diseases.

  12. 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

  13. Gene expression in a paleopolyploid: a transcriptome resource for the ciliate Paramecium tetraurelia

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    Kapusta Aurélie

    2010-10-01

    Full Text Available Abstract Background The genome of Paramecium tetraurelia, a unicellular model that belongs to the ciliate phylum, has been shaped by at least 3 successive whole genome duplications (WGD. These dramatic events, which have also been documented in plants, animals and fungi, are resolved over evolutionary time by the loss of one duplicate for the majority of genes. Thanks to a low rate of large scale genome rearrangement in Paramecium, an unprecedented large number of gene duplicates of different ages have been identified, making this organism an outstanding model to investigate the evolutionary consequences of polyploidization. The most recent WGD, with 51% of pre-duplication genes still in 2 copies, provides a snapshot of a phase of rapid gene loss that is not accessible in more ancient polyploids such as yeast. Results We designed a custom oligonucleotide microarray platform for P. tetraurelia genome-wide expression profiling and used the platform to measure gene expression during 1 the sexual cycle of autogamy, 2 growth of new cilia in response to deciliation and 3 biogenesis of secretory granules after massive exocytosis. Genes that are differentially expressed during these time course experiments have expression patterns consistent with a very low rate of subfunctionalization (partition of ancestral functions between duplicated genes in particular since the most recent polyploidization event. Conclusions A public transcriptome resource is now available for Paramecium tetraurelia. The resource has been integrated into the ParameciumDB model organism database, providing searchable access to the data. The microarray platform, freely available through NimbleGen Systems, provides a robust, cost-effective approach for genome-wide expression profiling in P. tetraurelia. The expression data support previous studies showing that at short evolutionary times after a whole genome duplication, gene dosage balance constraints and not functional change are

  14. Regulation of neuronal gene expression and survival by basal NMDA receptor activity: a role for histone deacetylase 4.

    Science.gov (United States)

    Chen, Yelin; Wang, Yuanyuan; Modrusan, Zora; Sheng, Morgan; Kaminker, Joshua S

    2014-11-12

    Neuronal gene expression is modulated by activity via calcium-permeable receptors such as NMDA receptors (NMDARs). While gene expression changes downstream of evoked NMDAR activity have been well studied, much less is known about gene expression changes that occur under conditions of basal neuronal activity. In mouse dissociated hippocampal neuronal cultures, we found that a broad NMDAR antagonist, AP5, induced robust gene expression changes under basal activity, but subtype-specific antagonists did not. While some of the gene expression changes are also known to be downstream of stimulated NMDAR activity, others appear specific to basal NMDAR activity. The genes altered by AP5 treatment of basal cultures were enriched for pathways related to class IIa histone deacetylases (HDACs), apoptosis, and synapse-related signaling. Specifically, AP5 altered the expression of all three class IIa HDACs that are highly expressed in the brain, HDAC4, HDAC5, and HDAC9, and also induced nuclear accumulation of HDAC4. HDAC4 knockdown abolished a subset of the gene expression changes induced by AP5, and led to neuronal death under long-term tetrodotoxin or AP5 treatment in rat hippocampal organotypic slice cultures. These data suggest that basal, but not evoked, NMDAR activity regulates gene expression in part through HDAC4, and, that HDAC4 has neuroprotective functions under conditions of low NMDAR activity.

  15. Regulating gene-expression by mechanical force

    Science.gov (United States)

    Visscher, Koen

    2008-10-01

    Initiation of transcription is an attractive target for controlling gene expression. Initiation typically involves binding of RNA polymerase to the DNA, followed by a rapid transition into a ``closed'' complex, and a subsequent transition into the ``open'' complex in which the DNA is locally melted. Nature makes good use of this target, for example in the form of repressor proteins that bind DNA and inhibit transcription. Here we will show that initiation of transcription is also dependent upon DNA tension and thus may be controlled by force alone, without the need for any accessory proteins. Using a three-bead assay in conjunction with optical tweezers we have shown that transient interactions of T7 RNA polymerase with the DNA promoter site shorten significantly, by up to a factor of ˜20, when DNA tension is increased. Experiments in the presence and absence of nucleotides have allowed us to conclude that force is likely to affect the rate constants into and/or out of the open complex, rather than the off-rate from the closed complex.

  16. Cell cycle gene expression under clinorotation

    Science.gov (United States)

    Artemenko, Olga

    2016-07-01

    Cyclins and cyclin-dependent kinase (CDK) are main regulators of the cell cycle of eukaryotes. It's assumes a significant change of their level in cells under microgravity conditions and by other physical factors actions. The clinorotation use enables to determine the influence of gravity on simulated events in the cell during the cell cycle - exit from the state of quiet stage and promotion presynthetic phase (G1) and DNA synthesis phase (S) of the cell cycle. For the clinorotation effect study on cell proliferation activity is the necessary studies of molecular mechanisms of cell cycle regulation and development of plants under altered gravity condition. The activity of cyclin D, which is responsible for the events of the cell cycle in presynthetic phase can be controlled by the action of endogenous as well as exogenous factors, but clinorotation is one of the factors that influence on genes expression that regulate the cell cycle.These data can be used as a model for further research of cyclin - CDK complex for study of molecular mechanisms regulation of growth and proliferation. In this investigation we tried to summarize and analyze known literature and own data we obtained relatively the main regulators of the cell cycle in altered gravity condition.

  17. Gene Expression Profiling in an in Vitro Model of Angiogenesis

    OpenAIRE

    Kahn, Jeanne; Mehraban, Fuad; Ingle, Gladys; Xin, Xiaohua; Bryant, Juliet E.; Vehar, Gordon; Schoenfeld, Jill; Grimaldi, Chrisopher J.; Peale, Franklin; Draksharapu, Aparna; Lewin, David A.; Gerritsen, Mary E.

    2000-01-01

    In the present study we have used a novel, comprehensive mRNA profiling technique (GeneCalling) for determining differential gene expression profiles of human endothelial cells undergoing differentiation into tubelike structures. One hundred fifteen cDNA fragments were identified and shown to represent 90 distinct genes. Although some of the genes identified have previously been implicated in angiogenesis, potential roles for many new genes, including OX-40, white protein homolog, KIAA0188, a...

  18. Expression Divergence of Tandemly Arrayed Genes in Human and Mouse

    Directory of Open Access Journals (Sweden)

    Valia Shoja

    2007-01-01

    Full Text Available Tandemly arrayed genes (TAGs account for about one third of the duplicated genes in eukaryotic genomes, yet there has not been any systematic study of their gene expression patterns. Taking advantage of recently published large-scale microarray data sets, we studied the expression divergence of 361 two-member TAGs in human and 212 two-member TAGs in mouse and examined the effect of sequence divergence, gene orientation, and chromosomal proximity on the divergence of TAG expression patterns. Our results show that there is a weak negative correlation between sequence divergence of TAG members and their expression similarity. There is also a weak negative correlation between chromosomal proximity of TAG members and their expression similarity. We did not detect any significant relationship between gene orientation and expression similarity. We also found that downstream TAG members do not show significantly narrower expression breadth than upstream members, contrary to what we predict based on TAG expression divergence hypothesis that we propose. Finally, we show that both chromosomal proximity and expression correlation in TAGs do not differ significantly from their neighboring non-TAG gene pairs, suggesting that tandem duplication is unlikely to be the cause for the higher-than-random expression association between neighboring genes on a chromosome in human and mouse.

  19. Unstable Expression of Commonly Used Reference Genes in Rat Pancreatic Islets Early after Isolation Affects Results of Gene Expression Studies.

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    Lucie Kosinová

    Full Text Available The use of RT-qPCR provides a powerful tool for gene expression studies; however, the proper interpretation of the obtained data is crucially dependent on accurate normalization based on stable reference genes. Recently, strong evidence has been shown indicating that the expression of many commonly used reference genes may vary significantly due to diverse experimental conditions. The isolation of pancreatic islets is a complicated procedure which creates severe mechanical and metabolic stress leading possibly to cellular damage and alteration of gene expression. Despite of this, freshly isolated islets frequently serve as a control in various gene expression and intervention studies. The aim of our study was to determine expression of 16 candidate reference genes and one gene of interest (F3 in isolated rat pancreatic islets during short-term cultivation in order to find a suitable endogenous control for gene expression studies. We compared the expression stability of the most commonly used reference genes and evaluated the reliability of relative and absolute quantification using RT-qPCR during 0-120 hrs after isolation. In freshly isolated islets, the expression of all tested genes was markedly depressed and it increased several times throughout the first 48 hrs of cultivation. We observed significant variability among samples at 0 and 24 hrs but substantial stabilization from 48 hrs onwards. During the first 48 hrs, relative quantification failed to reflect the real changes in respective mRNA concentrations while in the interval 48-120 hrs, the relative expression generally paralleled the results determined by absolute quantification. Thus, our data call into question the suitability of relative quantification for gene expression analysis in pancreatic islets during the first 48 hrs of cultivation, as the results may be significantly affected by unstable expression of reference genes. However, this method could provide reliable information

  20. In silico evolution of the hunchback gene indicates redundancy in cis-regulatory organization and spatial gene expression.

    Science.gov (United States)

    Zagrijchuk, Elizaveta A; Sabirov, Marat A; Holloway, David M; Spirov, Alexander V

    2014-04-01

    Biological development depends on the coordinated expression of genes in time and space. Developmental genes have extensive cis-regulatory regions which control their expression. These regions are organized in a modular manner, with different modules controlling expression at different times and locations. Both how modularity evolved and what function it serves are open questions. We present a computational model for the cis-regulation of the hunchback (hb) gene in the fruit fly (Drosophila). We simulate evolution (using an evolutionary computation approach from computer science) to find the optimal cis-regulatory arrangements for fitting experimental hb expression patterns. We find that the cis-regulatory region tends to readily evolve modularity. These cis-regulatory modules (CRMs) do not tend to control single spatial domains, but show a multi-CRM/multi-domain correspondence. We find that the CRM-domain correspondence seen in Drosophila evolves with a high probability in our model, supporting the biological relevance of the approach. The partial redundancy resulting from multi-CRM control may confer some biological robustness against corruption of regulatory sequences. The technique developed on hb could readily be applied to other multi-CRM developmental genes.

  1. In silico evolution of the hunchback gene indicates redundancy in cis-regulatory organization and spatial gene expression

    Science.gov (United States)

    Zagrijchuk, Elizaveta A.; Sabirov, Marat A.; Holloway, David M.; Spirov, Alexander V.

    2014-01-01

    Biological development depends on the coordinated expression of genes in time and space. Developmental genes have extensive cis-regulatory regions which control their expression. These regions are organized in a modular manner, with different modules controlling expression at different times and locations. Both how modularity evolved and what function it serves are open questions. We present a computational model for the cis-regulation of the hunchback (hb) gene in the fruit fly (Drosophila). We simulate evolution (using an evolutionary computation approach from computer science) to find the optimal cis-regulatory arrangements for fitting experimental hb expression patterns. We find that the cis-regulatory region tends to readily evolve modularity. These cis-regulatory modules (CRMs) do not tend to control single spatial domains, but show a multi-CRM/multi-domain correspondence. We find that the CRM-domain correspondence seen in Drosophila evolves with a high probability in our model, supporting the biological relevance of the approach. The partial redundancy resulting from multi-CRM control may confer some biological robustness against corruption of regulatory sequences. The technique developed on hb could readily be applied to other multi-CRM developmental genes. PMID:24712536

  2. Strategies for aggregating gene expression data: The collapseRows R function

    Directory of Open Access Journals (Sweden)

    Miller Jeremy A

    2011-08-01

    Full Text Available Abstract Background Genomic and other high dimensional analyses often require one to summarize multiple related variables by a single representative. This task is also variously referred to as collapsing, combining, reducing, or aggregating variables. Examples include summarizing several probe measurements corresponding to a single gene, representing the expression profiles of a co-expression module by a single expression profile, and aggregating cell-type marker information to de-convolute expression data. Several standard statistical summary techniques can be used, but network methods also provide useful alternative methods to find representatives. Currently few collapsing functions are developed and widely applied. Results We introduce the R function collapseRows that implements several collapsing methods and evaluate its performance in three applications. First, we study a crucial step of the meta-analysis of microarray data: the merging of independent gene expression data sets, which may have been measured on different platforms. Toward this end, we collapse multiple microarray probes for a single gene and then merge the data by gene identifier. We find that choosing the probe with the highest average expression leads to best between-study consistency. Second, we study methods for summarizing the gene expression profiles of a co-expression module. Several gene co-expression network analysis applications show that the optimal collapsing strategy depends on the analysis goal. Third, we study aggregating the information of cell type marker genes when the aim is to predict the abundance of cell types in a tissue sample based on gene expression data ("expression deconvolution". We apply different collapsing methods to predict cell type abundances in peripheral human blood and in mixtures of blood cell lines. Interestingly, the most accurate prediction method involves choosing the most highly connected "hub" marker gene. Finally, to facilitate

  3. Gene ordering in partitive clustering using microarray expressions.

    Science.gov (United States)

    Ray, Shubhra Sankar; Bandyopadhyay, Sanghamitra; Pal, Sankar K

    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.

  4. 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.

  5. 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.

  6. Transgenic zebrafish recapitulating tbx16 gene early developmental expression.

    Directory of Open Access Journals (Sweden)

    Simon Wells

    Full Text Available We describe the creation of a transgenic zebrafish expressing GFP driven by a 7.5 kb promoter region of the tbx16 gene. This promoter segment is sufficient to recapitulate early embryonic expression of endogenous tbx16 in the presomitic mesoderm, the polster and, subsequently, in the hatching gland. Expression of GFP in the transgenic lines later in development diverges to some extent from endogenous tbx16 expression with the serendipitous result that one line expresses GFP specifically in commissural primary ascending (CoPA interneurons of the developing spinal cord. Using this line we demonstrate that the gene mafba (valentino is expressed in CoPA interneurons.

  7. Gene expression profiles of the developing human retina

    Institute of Scientific and Technical Information of China (English)

    WANG Feng; LI Huiming; LIU Wenwen; XU Ping; HU Gengxi; CHENG Yidong; JIA Libin; HUANG Qian

    2004-01-01

    Retina is a multilayer and highly specialized tissue important in converting light into neural signals. In humans, the critical period for the formation of complex multiplayer structure takes place during embryogenesis between 12 and 28 weeks. The morphologic changes during retinal development in humans have been studied but little is known about the molecular events essential for the formation of the retina. To gain further insights into this process, cDNA microarrays containing 16361 human gene probes were used to measure the gene expression levels in retinas. Of the 16361 genes, 68.7%, 71.4% and 69.7% showed positive hybridization with cDNAs made from 12-16 week fetal, 22-26 week fetal and adult retinas. A total of 814 genes showed a minimum of 3-fold changes between the lowest and highest expression levels among three time points and among them, 106 genes had expression levels with the hybridization intensity above 100 at one or more time points. The clustering analysis suggested that the majority of differentially expressed genes were down-regulated during the retinal development. The differentially expressed genes were further classified according to functions of known genes, and were ranked in decreasing order according to frequency: development, differentiation, signal transduction, protein synthesis and translation, metabolism, DNA binding and transcription, DNA synthesis-repair-recombination, immuno-response, ion channel- transport, cell receptor, cytoskeleton, cell cycle, pro-oncogene, stress and apoptosis related genes. Among these 106 differentially expressed genes, 60 are already present in NEI retina cDNA or EST Databank but the remaining 46 genes are absent and thus identified as "function unknown". To validate gene expression data from the microarray, real-time RT-PCR was performed for 46 "function unknown" genes and 6 known retina specific expression genes, and β-actin was used as internal control. Twenty-seven of these genes showed very similar

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

    Directory of Open Access Journals (Sweden)

    Rasmussen Lene J

    2008-06-01

    Full Text Available Abstract Background The mechanism of sex determination in zebrafish is largely unknown and neither sex chromosomes nor a sex-determining gene have been identified. This indicates that sex determination in zebrafish is mediated by genetic signals from autosomal genes. The aim of this study was to determine 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 the present study, we have used quantitative real-time PCR to investigate the expression of ar, sox9a, dmrt1, fig alpha, cyp19a1a and cyp19a1b during the expected sex determination and gonadal sex differentiation period. The expression of the genes expected to be high in males (ar, sox9a and dmrt1a and high in females (fig alpha and cyp19a1a was segregated in two groups with more than 10 times difference in expression levels. All of the investigated genes showed peaks in expression levels during the time of sex determination and gonadal sex differentiation. Expression of all genes was 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 expressers of both "female" genes (fig alpha and cyp19a1a. When comparing all five genes with expected sex related expression 56% show expression expected for either male or female. Furthermore, the expression of all genes was investigated in different tissue of adult male and female zebrafish. Conclusion In zebrafish, the first significant peak in gene expression during the investigated period (2–40 dph was dmrt1 at 10 dph which indicates involvement of this gene

  9. AT(1) receptor Gαq protein-independent signalling transcriptionally activates only a few genes directly, but robustly potentiates gene regulation from the β2-adrenergic receptor

    DEFF Research Database (Denmark)

    Christensen, Gitte Lund; Knudsen, Steen; Schneider, Mikael;

    2011-01-01

    of Gαq protein-dependent and -independent regulation of AT(1)R mediated gene expression. We found angiotensin II to regulate 212 genes, whereas Gαq-independent signalling obtained with the biased agonist, SII angiotensin II only regulated few genes. Interestingly, SII angiotensin II, like Ang II vastly...

  10. Early life DNA vaccination with the H gene of Canine distemper virus induces robust protection against distemper

    DEFF Research Database (Denmark)

    Jensen, Trine Hammer; Nielsen, Line; Aasted, Bent;

    2009-01-01

    Young mink kits (n = 8)were vaccinated withDNA plasmids encoding the viral haemagglutinin protein (H) of a vaccine strain of Canine distemper virus (CDV). Virus neutralising (VN) antibodieswere induced after 2 immunisations and after the third immunisation all kits had high VN antibody titres...... demonstrate that early life DNA vaccination with the H gene of a CDV vaccine strain induced robust protective immunity against a recent wild type CDV....

  11. 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

  12. 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

  13. Arabidopsis gene expression patterns are altered during spaceflight

    Science.gov (United States)

    Paul, Anna-Lisa; Popp, Michael P.; Gurley, William B.; Guy, Charles; Norwood, Kelly L.; Ferl, Robert J.

    The exposure of Arabidopsis thaliana (Arabidopsis) plants to spaceflight environments results in differential gene expression. A 5-day mission on orbiter Columbia in 1999 (STS-93) carried transgenic Arabidopsis plants engineered with a transgene composed of the alcohol dehydrogenase (Adh) gene promoter linked to the β-Glucuronidase (GUS) reporter gene. The plants were used to evaluate the effects of spaceflight on gene expression patterns initially by using the Adh/GUS transgene to address specifically the possibility that spaceflight induces a hypoxic stress response (Paul, A.L., Daugherty, C.J., Bihn, E.A., Chapman, D.K., Norwood, K.L., Ferl, R.J., 2001. Transgene expression patterns indicate that spaceflight affects stress signal perception and transduction in arabidopsis, Plant Physiol. 126, 613-621). As a follow-on to the reporter gene analysis, we report here the evaluation of genome-wide patterns of native gene expression within Arabidopsis shoots utilizing the Agilent DNA array of 21,000 Arabidopsis genes. As a control for the veracity of the array analyses, a selection of genes was further characterized with quantitative Real-Time RT PCR (ABI - Taqman®). Comparison of the patterns of expression for arrays probed with RNA isolated from plants exposed to spaceflight compared to RNA isolated from ground control plants revealed 182 genes that were differentially expressed in response to the spaceflight mission by more than 4-fold, and of those only 50 genes were expressed at levels chosen to support a conservative change call. None of the genes that are hallmarks of hypoxic stress were induced to this level. However, genes related to heat shock were dramatically induced - but in a pattern and under growth conditions that are not easily explained by elevated temperatures. These gene expression data are discussed in light of current models for plant responses to the spaceflight environment and with regard to potential future spaceflight experiment

  14. Gene expression profiling of mouse embryos with microarrays

    Science.gov (United States)

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

    2011-01-01

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

  15. Genome-wide gene expression analysis of anguillid herpesvirus 1

    NARCIS (Netherlands)

    Beurden, van S.J.; Peeters, B.P.H.; Rottier, P.J.M.; Davison, A.A.; Engelsma, M.Y.

    2013-01-01

    Background Whereas temporal gene expression in mammalian herpesviruses has been studied extensively, little is known about gene expression in fish herpesviruses. Here we report a genome-wide transcription analysis of a fish herpesvirus, anguillid herpesvirus 1, in cell culture, studied during the

  16. 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...

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

    NARCIS (Netherlands)

    Staal, Y.; van Herwijnen, M.H.M.; van Schooten, F.J.; van Delft, J.H.M.

    2005-01-01

    BACKGROUND: DNA microarrays are widely used in gene expression analyses. To increase throughput and minimize costs without reducing gene expression data obtained, we investigated whether four mRNA samples can be analyzed simultaneously by applying four different fluorescent dyes. RESULTS: Following

  18. FGX : a frequentist gene expression index for Affymetrix arrays

    NARCIS (Netherlands)

    Purutçuoğlu, Vilda; Wit, Ernst

    2007-01-01

    We consider a new frequentist gene expression index for Affymetrix oligonucleotide DNA arrays, using a similar probe intensity model as suggested previously, called the Bayesian gene expression index (BGX). According to this model, the perfect match and mismatch values are assumed to be correlated a

  19. Genome organization and expression of the rat ACBP gene family

    DEFF Research Database (Denmark)

    Mandrup, S; Andreasen, P H; Knudsen, J

    1993-01-01

    pool former. We have molecularly cloned and characterized the rat ACBP gene family which comprises one expressed and four processed pseudogenes. One of these was shown to exist in two allelic forms. A comprehensive computer-aided analysis of the promoter region of the expressed ACBP gene revealed...

  20. RNA preparation and characterization for gene expression studies

    DEFF Research Database (Denmark)

    Stangegaard, Michael

    2009-01-01

    Much information can be obtained from knowledge of the relative expression level of each gene in the transcriptome. With the current advances in technology as little as a single cell is required as starting material for gene expression experiments. The mRNA from a single cell may be linearly ampl...

  1. Gene expression during anthesis and senescence in Iris flowers

    NARCIS (Netherlands)

    Doorn, van W.G.; Balk, P.A.; Houwelingen, van A.M.; Hoebrechts, F.A.; Hall, R.D.; Vorst, O.; Schoot, van der C.; Wordragen, van M.F.

    2003-01-01

    We investigated changes in gene expression in Iris hollandicaflowers by microarray technology. Flag tepals were sampled daily, from three days prior to flower opening to the onset of visible senescence symptoms. Gene expression profiles were compared with biochemical data including lipid and protein

  2. 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

  3. 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.

  4. Features of Gene Expression of Bacillus pumilus Metalloendopeptidase.

    Science.gov (United States)

    Rudakova, N L; Sabirova, A R; Balaban, N P; Tikhonova, A O; Sharipova, M R

    2016-08-01

    Features of gene expression of the secreted Bacillus pumilus metalloendopeptidase belonging to the adamalysin/reprolysin family were investigated. In the regulatory region of the gene, we identified hypothetical binding sites for transcription factors CcpA and TnrA. We found that the expression of the metalloendopeptidase gene is controlled by mechanisms of carbon and nitrogen catabolite repression. In experiments involving nitrogen metabolism regulatory protein mutant strains, we found that the control of the metalloendopeptidase gene expression involves proteins of ammonium transport GlnK and AmtB interacting with the TnrA-regulator.

  5. The effect of negative autoregulation on eukaryotic gene expression

    Science.gov (United States)

    Nevozhay, Dmitry; Adams, Rhys; Murphy, Kevin; Josic, Kresimir; Balázsi, G. Ábor

    2009-03-01

    Negative autoregulation is a frequent motif in gene regulatory networks, which has been studied extensively in prokaryotes. Nevertheless, some effects of negative feedback on gene expression in eukaryotic transcriptional networks remain unknown. We studied how the strength of negative feedback regulation affects the characteristics of gene expression in yeast cells carrying synthetic transcriptional cascades. We observed a drastic reduction of gene expression noise and a change in the shape of the dose-response curve. We explained these experimentally observed effects by stochastic simulations and a simple set of algebraic equations.

  6. Genetic architecture of gene expression in the chicken

    Directory of Open Access Journals (Sweden)

    Stanley Dragana

    2013-01-01

    Full Text Available Abstract Background The annotation of many genomes is limited, with a large proportion of identified genes lacking functional assignments. The construction of gene co-expression networks is a powerful approach that presents a way of integrating information from diverse gene expression datasets into a unified analysis which allows inferences to be drawn about the role of previously uncharacterised genes. Using this approach, we generated a condition-free gene co-expression network for the chicken using data from 1,043 publically available Affymetrix GeneChip Chicken Genome Arrays. This data was generated from a diverse range of experiments, including different tissues and experimental conditions. Our aim was to identify gene co-expression modules and generate a tool to facilitate exploration of the functional chicken genome. Results Fifteen modules, containing between 24 and 473 genes, were identified in the condition-free network. Most of the modules showed strong functional enrichment for particular Gene Ontology categories. However, a few showed no enrichment. Transcription factor binding site enrichment was also noted. Conclusions We have demonstrated that this chicken gene co-expression network is a useful tool in gene function prediction and the identification of putative novel transcription factors and binding sites. This work highlights the relevance of this methodology for functional prediction in poorly annotated genomes such as the chicken.

  7. Decreasing the stochasticity of mammalian gene expression by a synthetic gene circuit

    Science.gov (United States)

    Nevozhay, Dmitry; Zal, Tomasz; Balazsi, Gabor

    2012-02-01

    Gene therapy and functional genetic studies usually require precisely controlled and uniform gene expression in a population of cells for reliable level of protein production. Due to this requirement, stochastic gene expression is perceived as undesirable in these fields and ideally has to be minimized. The number of approaches for decreasing gene expression stochasticity in mammalian cells is limited. This creates an unmet need to develop new gene expression systems for this purpose. Based on earlier synthetic constructs in yeast, we developed and assessed a negative feedback-based mammalian gene circuit, with uniform and low level of stochasticity in gene expression at different levels of induction. In addition, this new synthetic construct enables highly precise gene expression control in mammalian cells, due to the linear dependence of gene expression on the inducer concentration applied to the system. This mammalian gene expression circuit has potential applicability for the development of new treatment modalities in gene therapy and research tools in functional genetics. In addition, this work creates a roadmap for moving synthetic gene circuits from microbes into mammalian cells.

  8. Transcriptomic analysis of gene expression profiles of stomach carcinoma reveal abnormal expression of mitotic components.

    Science.gov (United States)

    Tong, Hongfei; Wang, Jisheng; Chen, Hui; Wang, Zhaohong; Fan, Henwei; Ni, Zhonglin

    2017-02-01

    In order to explore the etiology of gastric cancer on global gene expression level, we developed advanced bioinformatic analysis to investigate the variations of global gene expression and the interactions among them. We downloaded the dataset GSE63288 from Gene Expression Omnibus (GEO) database which included 22 human gastric cancer and 22 healthy control samples. We identified the differential expression genes, and explored the Gene ontology (GO) and pathways of the differentially expressed genes. Furthermore, integrative interaction network and co-expression network were employed to identify the key genes which may contribute to gastric cancer progression. The results indicated that 5 kinases including BUB1, TTK protein kinase, Citron Rho-interacting kinase (CIT), ZAK and NEK2 were upregulated in gastric cancer. Interestingly, BUB1, TTK, CIT and NEK2 have shown high expression similarities and bound with each other, and participated in multiple phases of mitosis. Moreover, a subnet of co-expression genes e.g. KIF14, PRC1, CENPF and CENPI was also involved in mitosis which was functionally coupled with the kinases above. By validation assays, the results indicated that CIT, PRC1, TTK and KIF14 were significantly upregulated in gastric cancer. These evidences have suggested that aberrant expression of these genes may drive gastric cancer including progression, invasion and metastasis. Although the causal relationships between gastric cancer and the genes are still lacking, it was reasonable to take them as biomarkers for diagnosis of gastric cancer. Copyright © 2016 Elsevier Inc. All rights reserved.

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

    Science.gov (United States)

    Chen, James J

    2007-05-01

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

  10. Distribution of population-averaged observables in stochastic gene expression

    Science.gov (United States)

    Bhattacharyya, Bhaswati; Kalay, Ziya

    2014-01-01

    Observation of phenotypic diversity in a population of genetically identical cells is often linked to the stochastic nature of chemical reactions involved in gene regulatory networks. We investigate the distribution of population-averaged gene expression levels as a function of population, or sample, size for several stochastic gene expression models to find out to what extent population-averaged quantities reflect the underlying mechanism of gene expression. We consider three basic gene regulation networks corresponding to transcription with and without gene state switching and translation. Using analytical expressions for the probability generating function of observables and large deviation theory, we calculate the distribution and first two moments of the population-averaged mRNA and protein levels as a function of model parameters, population size, and number of measurements contained in a data set. We validate our results using stochastic simulations also report exact results on the asymptotic properties of population averages which show qualitative differences among different models.

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

    DEFF Research Database (Denmark)

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

    2010-01-01

    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...... 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 events...

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

    DEFF Research Database (Denmark)

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

    2010-01-01

    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...... 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 events...

  13. A predictive approach to identify genes differentially expressed

    Science.gov (United States)

    Saraiva, Erlandson F.; Louzada, Francisco; Milan, Luís A.; Meira, Silvana; Cobre, Juliana

    2012-10-01

    The main objective of gene expression data analysis is to identify genes that present significant changes in expression levels between a treatment and a control biological condition. In this paper, we propose a Bayesian approach to identify genes differentially expressed calculating credibility intervals from predictive densities which are constructed using sampled mean treatment effect from all genes in study excluding the treatment effect of genes previously identified with statistical evidence for difference. We compare our Bayesian approach with the standard ones based on the use of the t-test and modified t-tests via a simulation study, using small sample sizes which are common in gene expression data analysis. Results obtained indicate that the proposed approach performs better than standard ones, especially for cases with mean differences and increases in treatment variance in relation to control variance. We also apply the methodologies to a publicly available data set on Escherichia coli bacteria.

  14. 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.

  15. A riboswitch-based inducible gene expression system for mycobacteria.

    Directory of Open Access Journals (Sweden)

    Jessica C Seeliger

    Full Text Available Research on the human pathogen Mycobacterium tuberculosis (Mtb would benefit from novel tools for regulated gene expression. Here we describe the characterization and application of a synthetic riboswitch-based system, which comprises a mycobacterial promoter for transcriptional control and a riboswitch for translational control. The system was used to induce and repress heterologous protein overexpression reversibly, to create a conditional gene knockdown, and to control gene expression in a macrophage infection model. Unlike existing systems for controlling gene expression in Mtb, the riboswitch does not require the co-expression of any accessory proteins: all of the regulatory machinery is encoded by a short DNA segment directly upstream of the target gene. The inducible riboswitch platform has the potential to be a powerful general strategy for creating customized gene regulation systems in Mtb.

  16. Fundamental principles of energy consumption for gene expression

    Science.gov (United States)

    Huang, Lifang; Yuan, Zhanjiang; Yu, Jianshe; Zhou, Tianshou

    2015-12-01

    How energy is consumed in gene expression is largely unknown mainly due to complexity of non-equilibrium mechanisms affecting expression levels. Here, by analyzing a representative gene model that considers complexity of gene expression, we show that negative feedback increases energy consumption but positive feedback has an opposite effect; promoter leakage always reduces energy consumption; generating more bursts needs to consume more energy; and the speed of promoter switching is at the cost of energy consumption. We also find that the relationship between energy consumption and expression noise is multi-mode, depending on both the type of feedback and the speed of promoter switching. Altogether, these results constitute fundamental principles of energy consumption for gene expression, which lay a foundation for designing biologically reasonable gene modules. In addition, we discuss possible biological implications of these principles by combining experimental facts.

  17. Expression profiling of chickpea genes differentially regulated during a resistance response to Ascochyta rabiei.

    Science.gov (United States)

    Coram, Tristan E; Pang, Edwin C K

    2006-11-01

    Using microarray technology and a set of chickpea (Cicer arietinum L.) unigenes, grasspea (Lathyrus sativus L.) expressed sequence tags (ESTs) and lentil (Lens culinaris Med.) resistance gene analogues, the ascochyta blight (Ascochyta rabiei (Pass.) L.) resistance response was studied in four chickpea genotypes, including resistant, moderately resistant, susceptible and wild relative (Cicer echinospermum L.) genotypes. The experimental system minimized environmental effects and was conducted in reference design, in which samples from mock-inoculated controls acted as reference against post-inoculation samples. Robust data quality was achieved through the use of three biological replicates (including a dye swap), the inclusion of negative controls and strict selection criteria for differentially expressed genes, including a fold change cut-off determined by self-self hybridizations, Student's t-test and multiple testing correction (P resistant and A. rabiei-susceptible genotypes revealed potential gene 'signatures' predictive of effective A. rabiei resistance. These genes included several pathogenesis-related proteins, SNAKIN2 antimicrobial peptide, proline-rich protein, disease resistance response protein DRRG49-C, environmental stress-inducible protein, leucine-zipper protein, polymorphic antigen membrane protein, Ca-binding protein and several unknown proteins. The potential involvement of these genes and their pathways of induction are discussed. This study represents the first large-scale gene expression profiling in chickpea, and future work will focus on the functional validation of the genes of interest.

  18. Single muscle fiber gene expression with run taper.

    Directory of Open Access Journals (Sweden)

    Kevin Murach

    Full Text Available This study evaluated gene expression changes in gastrocnemius slow-twitch myosin heavy chain I (MHC I and fast-twitch (MHC IIa muscle fibers of collegiate cross-country runners (n = 6, 20±1 y, VO₂max = 70±1 ml•kg-1•min-1 during two distinct training phases. In a controlled environment, runners performed identical 8 kilometer runs (30:18±0:30 min:s, 89±1% HRmax while in heavy training (∼72 km/wk and following a 3 wk taper. Training volume during the taper leading into peak competition was reduced ∼50% which resulted in improved race times and greater cross-section and improved function of MHC IIa fibers. Single muscle fibers were isolated from pre and 4 hour post run biopsies in heavily trained and tapered states to examine the dynamic acute exercise response of the growth-related genes Fibroblast growth factor-inducible 14 (FN14, Myostatin (MSTN, Heat shock protein 72 (HSP72, Muscle ring-finger protein-1 (MURF1, Myogenic factor 6 (MRF4, and Insulin-like growth factor 1 (IGF1 via qPCR. FN14 increased 4.3-fold in MHC IIa fibers with exercise in the tapered state (P<0.05. MSTN was suppressed with exercise in both fiber types and training states (P<0.05 while MURF1 and HSP72 responded to running in MHC IIa and I fibers, respectively, regardless of training state (P<0.05. Robust induction of FN14 (previously shown to strongly correlate with hypertrophy and greater overall transcriptional flexibility with exercise in the tapered state provides an initial molecular basis for fast-twitch muscle fiber performance gains previously observed after taper in competitive endurance athletes.

  19. Genes expressed in specific areas of the human fetal cerebral cortex display distinct patterns of evolution.

    Directory of Open Access Journals (Sweden)

    Nelle Lambert

    Full Text Available The developmental mechanisms through which the cerebral cortex increased in size and complexity during primate evolution are essentially unknown. To uncover genetic networks active in the developing cerebral cortex, we combined three-dimensional reconstruction of human fetal brains at midgestation and whole genome expression profiling. This novel approach enabled transcriptional characterization of neurons from accurately defined cortical regions containing presumptive Broca and Wernicke language areas, as well as surrounding associative areas. We identified hundreds of genes displaying differential expression between the two regions, but no significant difference in gene expression between left and right hemispheres. Validation by qRTPCR and in situ hybridization confirmed the robustness of our approach and revealed novel patterns of area- and layer-specific expression throughout the developing cortex. Genes differentially expressed between cortical areas were significantly associated with fast-evolving non-coding sequences harboring human-specific substitutions that could lead to divergence in their repertoires of transcription factor binding sites. Strikingly, while some of these sequences were accelerated in the human lineage only, many others were accelerated in chimpanzee and/or mouse lineages, indicating that genes important for cortical development may be particularly prone to changes in transcriptional regulation across mammals. Genes differentially expressed between cortical regions were also enriched for transcriptional targets of FoxP2, a key gene for the acquisition of language abilities in humans. Our findings point to a subset of genes with a unique combination of cortical areal expression and evolutionary patterns, suggesting that they play important roles in the transcriptional network underlying human-specific neural traits.

  20. Mucin gene expression in human middle ear epithelium.

    Science.gov (United States)

    Kerschner, Joseph Edward

    2007-09-01

    To investigate the expression of recently identified human mucin genes in human middle ear epithelial (MEE) specimens from in vivo middle ear (ME) tissue and to compare this mucin gene expression with mucin gene expression in an immortalized cell culture in vitro source of human MEE. Human MEE was harvested as in vivo specimens, and human MEE cell cultures were established for in vitro experimentation. RNA was extracted from MEE and primers designed for reverse-transcription polymerase chain reaction to assess for mucin gene MUC1, MUC2, MUC3, MUC4, MUC5AC, MUC5B, MUC6, MUC7, MUC8, MUC9, MUC11, MUC12, MUC13, MUC15, MUC16, MUC18, MUC19, and MUC20 expression. Mucin gene expression in the in vivo and in vitro ME tissue was compared against tissues with known expression of the mucin genes in question. Mucin genes MUC1, MUC2, MUC3, MUC4, MUC5AC, MUC5B, MUC7, MUC8, MUC9, MUC11, MUC13, MUC15, MUC16, MUC18, MUC19, and MUC20 were identified and expressed in both the in vivo and in vitro samples of MEE. Mucin genes MUC6, MUC12, and MUC17 were not identified in either tissue samples. Many of the mucin genes that have been recently identified are expressed in human MEE. These genes are expressed in a similar manner in both in vivo and in vitro models. Understanding the mechanisms in which these genes regulate the physiology and pathophysiology of MEE will provide a more thorough understanding of the molecular mechanics of the MEE and disease conditions such as otitis media.

  1. Evaluating the consistency of gene sets used in the analysis of bacterial gene expression data

    Directory of Open Access Journals (Sweden)

    Tintle Nathan L

    2012-08-01

    Full Text Available Abstract Background Statistical analyses of whole genome expression data require functional information about genes in order to yield meaningful biological conclusions. The Gene Ontology (GO and Kyoto Encyclopedia of Genes and Genomes (KEGG are common sources of functionally grouped gene sets. For bacteria, the SEED and MicrobesOnline provide alternative, complementary sources of gene sets. To date, no comprehensive evaluation of the data obtained from these resources has been performed. Results We define a series of gene set consistency metrics directly related to the most common classes of statistical analyses for gene expression data, and then perform a comprehensive analysis of 3581 Affymetrix® gene expression arrays across 17 diverse bacteria. We find that gene sets obtained from GO and KEGG demonstrate lower consistency than those obtained from the SEED and MicrobesOnline, regardless of gene set size. Conclusions Despite the widespread use of GO and KEGG gene sets in bacterial gene expression data analysis, the SEED and MicrobesOnline provide more consistent sets for a wide variety of statistical analyses. Increased use of the SEED and MicrobesOnline gene sets in the analysis of bacterial gene expression data may improve statistical power and utility of expression data.

  2. Gene expression profile analysis of human intervertebral disc degeneration

    OpenAIRE

    Kai Chen; Dajiang Wu; Xiaodong Zhu; Haijian Ni; Xianzhao Wei; Ningfang Mao; Yang Xie; Yunfei Niu; Ming Li

    2013-01-01

    In this study, we used microarray analysis to investigate the biogenesis and progression of intervertebral disc degeneration. The gene expression profiles of 37 disc tissue samples obtained from patients with herniated discs and degenerative disc disease collected by the National Cancer Institute Cooperative Tissue Network were analyzed. Differentially expressed genes between more and less degenerated discs were identified by significant analysis of microarray. A total of 555 genes were signi...

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

    DEFF Research Database (Denmark)

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

    2007-01-01

    Ribosomal DNA (rDNA) is a specialised chromosomal location that is dedicated to high-level transcription of ribosomal RNA genes. Interestingly, rDNAs are frequently interrupted by parasitic elements, some of which carry protein genes. These are non-LTR retrotransposons and group II introns...... that 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...

  4. Protamine stimulates bone sialoprotein gene expression.

    Science.gov (United States)

    Zhou, Liming; Matsumura, Hiroyoshi; Mezawa, Masaru; Takai, Hideki; Nakayama, Yohei; Mitarai, Makoto; Ogata, Yorimasa

    2013-03-10

    Protamine is a small, arginine-rich, nuclear protein that replaces histone late in the haploid phase of spermatogenesis and is believed to be essential for sperm head condensation and DNA stabilization. Protamine has many biological activities and has roles in hematopoiesis, immune responses, the nervous system and bone metabolism. Bone sialoprotein (BSP) is a mineralized connective tissue-specific protein expressed in differentiated osteoblasts that appears to function in the initial mineralization of bone. Protamine (71.35 ng/ml) increased BSP mRNA levels by 6h in osteoblast-like ROS 17/2.8 cells. In a transient transfection assay, protamine (71.35 ng/ml) increased luciferase activity of the construct (-116 to +60) in ROS 17/2.8 cells and rat bone marrow stromal cells. Luciferase activities induced by protamine were blocked by protein kinase A, tyrosine kinase and ERK1/2 inhibitors. Introduction of 2 bp mutations to the luciferase constructs showed that the effects of protamine were mediated by a cAMP response element (CRE), a fibroblast growth factor 2 response element (FRE) and a homeodomain protein-binding site (HOX). Gel shift analyses showed that protamine (71.35 ng/ml) increased the nuclear protein binding to CRE, FRE and HOX. CREB, phospho-CREB, c-Fos, c-Jun, JunD and Fra2 antibodies disrupted the formation of CRE-protein complexes. Dlx5, Msx2, Runx2 and Smad1 antibodies disrupted FRE- and HOX-protein complex formations. These studies demonstrate that protamine induces BSP transcription by targeting CRE, FRE and HOX sites in the proximal promoter of the rat BSP gene. Moreover, phospho-CREB, c-Fos, c-Jun, JunD, Fra2, Dlx5, Msx2, Runx2 and Smadl transcription factors appear to be key regulators of protamine effects on BSP transcription.

  5. Binary gene induction and protein expression in individual cells

    Directory of Open Access Journals (Sweden)

    Conolly Rory B

    2006-04-01

    Full Text Available Abstract Background Eukaryotic gene transcription is believed to occur in either a binary or a graded fashion. With binary induction, a transcription activator (TA regulates the probability with which a gene template is switched from the inactive to the active state without affecting the rate at which RNA molecules are produced from the template. With graded, also called rheostat-like, induction the gene template has continuously varying levels of transcriptional activity, and the TA regulates the rate of RNA production. Support for each of these two mechanisms arises primarily from experimental studies measuring reporter proteins in individual cells, rather than from direct measurement of induction events at the gene template. Methods and results In this paper, using a computational model of stochastic gene expression, we have studied the biological and experimental conditions under which a binary induction mode operating at the gene template can give rise to differentially expressed "phenotypes" (i.e., binary, hybrid or graded at the protein level. We have also investigated whether the choice of reporter genes plays a significant role in determining the observed protein expression patterns in individual cells, given the diverse properties of commonly-used reporter genes. Our simulation confirmed early findings that the lifetimes of active/inactive promoters and half-lives of downstream mRNA/protein products are important determinants of various protein expression patterns, but showed that the induction time and the sensitivity with which the expressed genes are detected are also important experimental variables. Using parameter conditions representative of reporter genes including green fluorescence protein (GFP and β-galactosidase, we also demonstrated that graded gene expression is more likely to be observed with GFP, a longer-lived protein with low detection sensitivity. Conclusion The choice of reporter genes may determine whether protein

  6. A functional profile of gene expression in ARPE-19 cells

    Directory of Open Access Journals (Sweden)

    Johnson Dianna A

    2005-11-01

    Full Text Available Abstract Background Retinal pigment epithelium cells play an important role in the pathogenesis of age related macular degeneration. Their morphological, molecular and functional phenotype changes in response to various stresses. Functional profiling of genes can provide useful information about the physiological state of cells and how this state changes in response to disease or treatment. In this study, we have constructed a functional profile of the genes expressed by the ARPE-19 cell line of retinal pigment epithelium. Methods Using Affymetrix MAS 5.0 microarray analysis, genes expressed by ARPE-19 cells were identified. Using GeneChip® annotations, these genes were classified according to their known functions to generate a functional gene expression profile. Results We have determined that of approximately 19,044 unique gene sequences represented on the HG-U133A GeneChip® , 6,438 were expressed in ARPE-19 cells irrespective of the substrate on which they were grown (plastic, fibronectin, collagen, or Matrigel. Rather than focus our subsequent analysis on the identity or level of expression of each individual gene in this large data set, we examined the number of genes expressed within 130 functional categories. These categories were selected from a library of HG-U133A GeneChip® annotations linked to the Affymetrix MAS 5.0 data sets. Using this functional classification scheme, we were able to categorize about 70% of the expressed genes and condense the original data set of over 6,000 data points into a format with 130 data points. The resulting ARPE-19 Functional Gene Expression Profile is displayed as a percentage of ARPE-19-expressed genes. Conclusion The Profile can readily be compared with equivalent microarray data from other appropriate samples in order to highlight cell-specific attributes or treatment-induced changes in gene expression. The usefulness of these analyses is based on the assumption that the numbers of genes

  7. Validation of reference genes for quantifying changes in gene expression in virus-infected tobacco.

    Science.gov (United States)

    Baek, Eseul; Yoon, Ju-Yeon; Palukaitis, Peter

    2017-10-01

    To facilitate quantification of gene expression changes in virus-infected tobacco plants, eight housekeeping genes were evaluated for their stability of expression during infection by one of three systemically-infecting viruses (cucumber mosaic virus, potato virus X, potato virus Y) or a hypersensitive-response-inducing virus (tobacco mosaic virus; TMV) limited to the inoculated leaf. Five reference-gene validation programs were used to establish the order of the most stable genes for the systemically-infecting viruses as ribosomal protein L25 > β-Tubulin > Actin, and the least stable genes Ubiquitin-conjugating enzyme (UCE) genes were EF1α > Cysteine protease > Actin, and the least stable genes were GAPDH genes, three defense responsive genes were examined to compare their relative changes in gene expression caused by each virus. Copyright © 2017 Elsevier Inc. All rights reserved.

  8. Relating perturbation magnitude to temporal gene expression in biological systems

    Directory of Open Access Journals (Sweden)

    Pfrender Michael E

    2009-03-01

    Full Text Available Abstract Background Most transcriptional activity is a result of environmental variability. This cause (environment and effect (gene expression relationship is essential to survival in any changing environment. The specific relationship between environmental perturbation and gene expression – and stability of the response – has yet to be measured in detail. We describe a method to quantitatively relate perturbation magnitude to response at the level of gene expression. We test our method using Saccharomyces cerevisiae as a model organism and osmotic stress as an environmental stress. Results Patterns of gene expression were measured in response to increasing sodium chloride concentrations (0, 0.5, 0.7, 1.0, and 1.2 M for sixty genes impacted by osmotic shock. Expression of these genes was quantified over five time points using reverse transcriptase real-time polymerase chain reaction. Magnitudes of cumulative response for specific pathways, and the set of all genes, were obtained by combining the temporal response envelopes for genes exhibiting significant changes in expression with time. A linear relationship between perturbation magnitude and response was observed for the range of concentrations studied. Conclusion This study develops a quantitative approach to describe the stability of gene response and pathways to environmental perturbation and illustrates the utility of this approach. The approach should be applicable to quantitatively evaluate the response of organisms via the magnitude of response and stability of the transcriptome to environmental change.

  9. Clustering Algorithms: Their Application to Gene Expression Data

    Science.gov (United States)

    Oyelade, Jelili; Isewon, Itunuoluwa; Oladipupo, Funke; Aromolaran, Olufemi; Uwoghiren, Efosa; Ameh, Faridah; Achas, Moses; Adebiyi, Ezekiel

    2016-01-01

    Gene expression data hide vital information required to understand the biological process that takes place in a particular organism in relation to its environment. Deciphering the hidden patterns in gene expression data proffers a prodigious preference to strengthen the understanding of functional genomics. The complexity of biological networks and the volume of genes present increase the challenges of comprehending and interpretation of the resulting mass of data, which consists of millions of measurements; these data also inhibit vagueness, imprecision, and noise. Therefore, the use of clustering techniques is a first step toward addressing these challenges, which is essential in the data mining process to reveal natural structures and identify interesting patterns in the underlying data. The clustering of gene expression data has been proven to be useful in making known the natural structure inherent in gene expression data, understanding gene functions, cellular processes, and subtypes of cells, mining useful information from noisy data, and understanding gene regulation. The other benefit of clustering gene expression data is the identification of homology, which is very important in vaccine design. This review examines the various clustering algorithms applicable to the gene expression data in order to discover and provide useful knowledge of the appropriate clustering technique that will guarantee stability and high degree of accuracy in its analysis procedure. PMID:27932867

  10. Genome-wide patterns of Arabidopsis gene expression in nature.

    Directory of Open Access Journals (Sweden)

    Christina L Richards

    Full Text Available Organisms in the wild are subject to multiple, fluctuating environmental factors, and it is in complex natural environments that genetic regulatory networks actually function and evolve. We assessed genome-wide gene expression patterns in the wild in two natural accessions of the model plant Arabidopsis thaliana and examined the nature of transcriptional variation throughout its life cycle and gene expression correlations with natural environmental fluctuations. We grew plants in a natural field environment and measured genome-wide time-series gene expression from the plant shoot every three days, spanning the seedling to reproductive stages. We find that 15,352 genes were expressed in the A. thaliana shoot in the field, and accession and flowering status (vegetative versus flowering were strong components of transcriptional variation in this plant. We identified between ∼110 and 190 time-varying gene expression clusters in the field, many of which were significantly overrepresented by genes regulated by abiotic and biotic environmental stresses. The two main principal components of vegetative shoot gene expression (PC(veg correlate to temperature and precipitation occurrence in the field. The largest PC(veg axes included thermoregulatory genes while the second major PC(veg was associated with precipitation and contained drought-responsive genes. By exposing A. thaliana to natural environments in an open field, we provide a framework for further understanding the genetic networks that are deployed in natural environments, and we connect plant molecular genetics in the laboratory to plant organismal ecology in the wild.

  11. X chromosome regulation of autosomal gene expression in bovine blastocysts

    OpenAIRE

    Itoh, Yuichiro; Arnold, Arthur P.

    2014-01-01

    Although X chromosome inactivation in female mammals evolved to balance the expression of X chromosome and autosomal genes in the two sexes, female embryos pass through developmental stages in which both X chromosomes are active in somatic cells. Bovine blastocysts show higher expression of many X genes in XX than XY embryos, suggesting that X inactivation is not complete. Here we reanalyzed bovine blastocyst microarray expression data from a network perspective with a focus on interactions b...

  12. X chromosome regulation of autosomal gene expression in bovine blastocysts

    OpenAIRE

    Itoh, Yuichiro; Arnold, Arthur P.

    2014-01-01

    Although X chromosome inactivation in female mammals evolved to balance the expression of X chromosome and autosomal genes in the two sexes, female embryos pass through developmental stages in which both X chromosomes are active in somatic cells. Bovine blastocysts show higher expression of many X genes in XX than XY embryos, suggesting that X inactivation is not complete. Here we reanalyzed bovine blastocyst microarray expression data from a network perspective with a focus on interactions b...

  13. With Reference to Reference Genes: A Systematic Review of Endogenous Controls in Gene Expression Studies.

    Science.gov (United States)

    Chapman, Joanne R; Waldenström, Jonas

    2015-01-01

    The choice of reference genes that are stably expressed amongst treatment groups is a crucial step in real-time quantitative PCR gene expression studies. Recent guidelines have specified that a minimum of two validated reference genes should be used for normalisation. However, a quantitative review of the literature showed that the average number of reference genes used across all studies was 1.2. Thus, the vast majority of studies continue to use a single gene, with β-actin (ACTB) and/or glyceraldehyde 3-phosphate dehydrogenase (GAPDH) being commonly selected in studies of vertebrate gene expression. Few studies (15%) tested a panel of potential reference genes for stability of expression before using them to normalise data. Amongst studies specifically testing reference gene stability, few found ACTB or GAPDH to be optimal, whereby these genes were significantly less likely to be chosen when larger panels of potential reference genes were screened. Fewer reference genes were tested for stability in non-model organisms, presumably owing to a dearth of available primers in less well characterised species. Furthermore, the experimental conditions under which real-time quantitative PCR analyses were conducted had a large influence on the choice of reference genes, whereby different studies of rat brain tissue showed different reference genes to be the most stable. These results highlight the importance of validating the choice of normalising reference genes before conducting gene expression studies.

  14. Development and evaluation of new mask protocols for gene expression profiling in humans and chimpanzees

    Directory of Open Access Journals (Sweden)

    Siegmund Kimberly D

    2009-03-01

    Full Text Available Abstract Background Cross-species gene expression analyses using oligonucleotide microarrays designed to evaluate a single species can provide spurious results due to mismatches between the interrogated transcriptome and arrayed probes. Based on the most recent human and chimpanzee genome assemblies, we developed updated and accessible probe masking methods that allow human Affymetrix oligonucleotide microarrays to be used for robust genome-wide expression analyses in both species. In this process, only data from oligonucleotide probes predicted to have robust hybridization sensitivity and specificity for both transcriptomes are retained for analysis. Results To characterize the utility of this resource, we applied our mask protocols to existing expression data from brains, livers, hearts, testes, and kidneys derived from both species and determined the effects probe numbers have on expression scores of specific transcripts. In all five tissues, probe sets with decreasing numbers of probes showed non-linear trends towards increased variation in expression scores. The relationships between expression variation and probe number in brain data closely matched those observed in simulated expression data sets subjected to random probe masking. However, there is evidence that additional factors affect the observed relationships between gene expression scores and probe number in tissues such as liver and kidney. In parallel, we observed that decreasing the number of probes within probe sets lead to linear increases in both gained and lost inferences of differential cross-species expression in all five tissues, which will affect the interpretation of expression data subject to masking. Conclusion We introduce a readily implemented and updated resource for human and chimpanzee transcriptome analysis through a commonly used microarray platform. Based on empirical observations derived from the analysis of five distinct data sets, we provide novel guidelines

  15. 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.

  16. 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.

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

    Science.gov (United States)

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

    2014-06-01

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

  18. BPH gene expression profile associated to prostate gland volume.

    Science.gov (United States)

    Descazeaud, Aurelien; Rubin, Mark A; Hofer, Matthias; Setlur, Sunita; Nikolaief, Nathalie; Vacherot, Francis; Soyeux, Pascale; Kheuang, Laurence; Abbou, Claude C; Allory, Yves; de la Taille, Alexandre

    2008-12-01

    The aim of the current study was to analyze gene expression profiles in benign prostatic hyperplasia and to compare them with phenotypic properties. Thirty-seven specimens of benign prostatic hyperplasia were obtained from symptomatic patients undergoing surgery. RNA was extracted and hybridized to Affymetrix Chips containing 54,000 gene expression probes. Gene expression profiles were analyzed using cluster, TreeView, and significance analysis of microarrays softwares. In an initial unsupervised analysis, our 37 samples clustered hierarchically in 2 groups of 18 and 19 samples, respectively. Five clinical parameters were statistically different between the 2 groups: in group 1 compared with group 2, patients had larger prostate glands, had higher prostate specific antigen levels, were more likely to be treated by alpha blockers, to be operated by prostatectomy, and to have major irritative symptoms. The sole independent parameter associated with this dichotome clustering, however, was the prostate gland volume. Therefore, the role of prostate volume was explored in a supervised analysis. Gene expression of prostate glands 60 mL were compared using significance analysis of microarrays and 227 genes were found differentially expressed between the 2 groups (>2 change and false discovery rate of <5%). Several specific pathways including growth factors genes, cell cycle genes, apoptose genes, inflammation genes, and androgen regulated genes, displayed major differences between small and large prostate glands.

  19. Validation of housekeeping genes for studying differential gene expression in the bovine myometrium.

    Science.gov (United States)

    Rekawiecki, Robert; Kowalik, Magdalena K; Kotwica, Jan

    2013-12-01

    The aim of this study was to determine the steady-state expression of 13 selected housekeeping genes in the myometrium of cyclic and pregnant cows. Cells taken from bovine myometrium on days 1-5, 6-10, 11-16 and 17-20 of the oestrous cycle and in weeks 3-5, 6-8 and 9-12 of pregnancy were used. Reverse transcribed RNA was amplified in real-time PCR using designed primers. Reaction efficiency was determined with the Linreg programme. The geNorm and NormFinder programmes were used to select the best housekeeping genes. They calculate the expression stability factor for each used housekeeping gene with the smallest value for most stably expressed genes. According to geNorm, the most stable housekeeping genes in the myometrium were C2orf29, TPB and TUBB2B, while the least stably expressed genes were 18S RNA, HPRT1 and GAPDH. NormFinder identified the best genes in the myometrium as C2orf29, MRPL12 and TBP, while the worst genes were 18S RNA, B2M and SF3A1. Differences in stability factors between the two programmes may also indicate that the physiological status of the female, e.g. pregnancy, affects the stability of expression of housekeeping genes. The different expression stability of housekeeping genes did not affect progesterone receptor expression but it could be important if small differences in gene expression were measured between studies.

  20. Gene expression profile analysis of type 2 diabetic mouse liver.

    Directory of Open Access Journals (Sweden)

    Fang Zhang

    Full Text Available Liver plays a key role in glucose metabolism and homeostasis, and impaired hepatic glucose metabolism contributes to the development of type 2 diabetes. However, the precise gene expression profile of diabetic liver and its association with diabetes and related diseases are yet to be further elucidated. In this study, we detected the gene expression profile by high-throughput sequencing in 9-week-old normal and type 2 diabetic db/db mouse liver. Totally 12132 genes were detected, and 2627 genes were significantly changed in diabetic mouse liver. Biological process analysis showed that the upregulated genes in diabetic mouse liver were mainly enriched in metabolic processes. Surprisingly, the downregulated genes in diabetic mouse liver were mainly enriched in immune-related processes, although all the altered genes were still mainly enriched in metabolic processes. Similarly, KEGG pathway analysis showed that metabolic pathways were the major pathways altered in diabetic mouse liver, and downregulated genes were enriched in immune and cancer pathways. Analysis of the key enzyme genes in fatty acid and glucose metabolism showed that some key enzyme genes were significantly increased and none of the detected key enzyme genes were decreased. In addition, FunDo analysis showed that liver cancer and hepatitis were most likely to be associated with diabetes. Taken together, this study provides the digital gene expression profile of diabetic mouse liver, and demonstrates the main diabetes-associated hepatic biological processes, pathways, key enzyme genes in fatty acid and glucose metabolism and potential hepatic diseases.

  1. Weighted gene co-expression based biomarker discovery for psoriasis detection.

    Science.gov (United States)

    Sundarrajan, Sudharsana; Arumugam, Mohanapriya

    2016-11-15

    Psoriasis is a chronic inflammatory disease of the skin with an unknown aetiology. The disease manifests itself as red and silvery scaly plaques distributed over the scalp, lower back and extensor aspects of the limbs. After receiving scant consideration for quite a few years, psoriasis has now become a prominent focus for new drug development. A group of closely connected and differentially co-expressed genes may act in a network and may serve as molecular signatures for an underlying phenotype. A weighted gene coexpression network analysis (WGCNA), a system biology approach has been utilized for identification of new molecular targets for psoriasis. Gene coexpression relationships were investigated in 58 psoriatic lesional samples resulting in five gene modules, clustered based on the gene coexpression patterns. The coexpression pattern was validated using three psoriatic datasets. 10 highly connected and informative genes from each module was selected and termed as psoriasis specific hub signatures. A random forest based binary classifier built using the expression profiles of signature genes robustly distinguished psoriatic samples from the normal samples in the validation set with an accuracy of 0.95 to 1. These signature genes may serve as potential candidates for biomarker discovery leading to new therapeutic targets. WGCNA, the network based approach has provided an alternative path to mine out key controllers and drivers of psoriasis. The study principle from the current work can be extended to other pathological conditions.

  2. Expression of HOX C homeobox genes in lymphoid cells.

    Science.gov (United States)

    Lawrence, H J; Stage, K M; Mathews, C H; Detmer, K; Scibienski, R; MacKenzie, M; Migliaccio, E; Boncinelli, E; Largman, C

    1993-08-01

    The class I homeobox genes located in four clusters in mammalian genomes (HOX A, HOX B, HOX C, and HOX D) appear to play a major role in fetal development. Previous surveys of homeobox gene expression in human leukemic cell lines have shown that certain HOX A genes are expressed only in myeloid cell lines, whereas HOX B gene expression is largely restricted to cells with erythroid potential. We now report a survey of the expression patterns of 9 homeobox genes from the HOX C locus in a panel of 24 human and 7 murine leukemic cell lines. The most striking observation is the lymphoid-specific pattern of expression of HOX C4, located at the 3' end of the locus. A major transcript of 1.9 kilobases is observed in both T-cell and B-cell lines. HOX C4 expression is also detected in normal human marrow and peripheral blood lymphocytes, but not in mature granulocytes or monocytes. HOX C8 is also expressed in human lymphoid cells but is expressed in other blood cell types as well. However, the HOX C8 transcript pattern is lineage specific. These data, in conjunction with earlier findings, suggest that homeobox gene expression influences lineage determination during hematopoiesis.

  3. A gene expression signature that defines breast cancer metastases.

    Science.gov (United States)

    Ellsworth, Rachel E; Seebach, Jeff; Field, Lori A; Heckman, Caroline; Kane, Jennifer; Hooke, Jeffrey A; Love, Brad; Shriver, Craig D

    2009-01-01

    The most important predictor of prognosis in breast cancer is lymph node status, yet little is known about molecular changes associated with lymph node metastasis. Here, gene expression analysis was performed on primary breast (PBT) and corresponding metastatic lymph node (MLN) tumors to identify molecular signatures associated with nodal metastasis. RNA was isolated after laser microdissection from frozen PBT and MLN from 20 patients with positive lymph nodes and hybridized to the microarray chips. Differential expression was determined using Mann-Whitney testing; Bonferroni corrected P values of 0.05 and 0.001 were calculated. Results were validated using TaqMan assays. Fifty-one genes were differentially expressed (P 100-fold higher expression in MLT while COL11A1, KRT14, MMP13, TAC1 and WNT2 had >100-fold higher expression in PBT. Gene expression differences between PBT and MLN suggests that expression of a unique set of genes is required for successful lymph node colonization. Genes expressed at higher levels in PBT are involved in degradation of the extracellular matrix, enabling cells with metastatic potential to disseminate, while genes expressed at higher levels in metastases are involved in transcription, signal transduction and immune response, providing cells with proliferation and survival advantages. These data improve our understanding of the biological processes involved in successful metastatis and provide new targets to arrest tumor cell dissemination and metastatic colonization.

  4. Dynamic association rules for gene expression data analysis.

    Science.gov (United States)

    Chen, Shu-Chuan; Tsai, Tsung-Hsien; Chung, Cheng-Han; Li, Wen-Hsiung

    2015-10-14

    The purpose of gene expression analysis is to look for the association between regulation of gene expression levels and phenotypic variations. This association based on gene expression profile has been used to determine whether the induction/repression of genes correspond to phenotypic variations including cell regulations, clinical diagnoses and drug development. Statistical analyses on microarray data have been developed to resolve gene selection issue. However, these methods do not inform us of causality between genes and phenotypes. In this paper, we propose the dynamic association rule algorithm (DAR algorithm) which helps ones to efficiently select a subset of significant genes for subsequent analysis. The DAR algorithm is based on association rules from market basket analysis in marketing. We first propose a statistical way, based on constructing a one-sided confidence interval and hypothesis testing, to determine if an association rule is meaningful. Based on the proposed statistical method, we then developed the DAR algorithm for gene expression data analysis. The method was applied to analyze four microarray datasets and one Next Generation Sequencing (NGS) dataset: the Mice Apo A1 dataset, the whole genome expression dataset of mouse embryonic stem cells, expression profiling of the bone marrow of Leukemia patients, Microarray Quality Control (MAQC) data set and the RNA-seq dataset of a mouse genomic imprinting study. A comparison of the proposed method with the t-test on the expression profiling of the bone marrow of Leukemia patients was conducted. We developed a statistical way, based on the concept of confidence interval, to determine the minimum support and minimum confidence for mining association relationships among items. With the minimum support and minimum confidence, one can find significant rules in one single step. The DAR algorithm was then developed for gene expression data analysis. Four gene expression datasets showed that the proposed

  5. Regulation of gene expression by Goodwin's loop with many genes

    Science.gov (United States)

    Sielewiesiuk, Jan; Łopaciuk, Agata

    2012-01-01

    The paper presents a simple analysis of a long Goodwin's loop containing many genes. The genes form a closed series. The rate of transcription of any gene is up or down regulated by theprotein product of the preceding gene. We describe the loop with a system of ordinary differential equations of order s. Oscillatory solutions of the system are possible at the odd number of repressions and any number of inductions if the product of all Hill's coefficients, related to both repressions and inductions, is larger than:

  6. The structure and expression of the human neuroligin-3 gene.

    Science.gov (United States)

    Philibert, R A; Winfield, S L; Sandhu, H K; Martin, B M; Ginns, E I

    2000-04-04

    The neuroligins are a family of proteins that are thought to mediate cell to cell interactions between neurons. During the sequencing at an Xq13 locus associated with a mental retardation syndrome in some studies, we discovered a portion of the human orthologue of the rat neuroligin-3 gene. We now report the structure and the expression of that gene. The gene spans approximately 30kb and contains eight exons. Unlike the rat gene, it codes for at least two mRNAs and at least one of which is expressed outside the CNS. Interestingly, the putative promoter for the gene overlaps the last exon of the neighboring HOPA gene and is located less than 1kb from an OPA element in which a polymorphism associated with mental retardation is found. These findings suggest a possible role for the neuroligin gene in mental retardation and that the role of the gene in humans may differ from its role in rats.

  7. Regulatory systems for hypoxia-inducible gene expression in ischemic heart disease gene therapy.

    Science.gov (United States)

    Kim, Hyun Ah; Rhim, Taiyoun; Lee, Minhyung

    2011-07-18

    Ischemic heart diseases are caused by narrowed coronary arteries that decrease the blood supply to the myocardium. In the ischemic myocardium, hypoxia-responsive genes are up-regulated by hypoxia-inducible factor-1 (HIF-1). Gene therapy for ischemic heart diseases uses genes encoding angiogenic growth factors and anti-apoptotic proteins as therapeutic genes. These genes increase blood supply into the myocardium by angiogenesis and protect cardiomyocytes from cell death. However, non-specific expression of these genes in normal tissues may be harmful, since growth factors and anti-apoptotic proteins may induce tumor growth. Therefore, tight gene regulation is required to limit gene expression to ischemic tissues, to avoid unwanted side effects. For this purpose, various gene expression strategies have been developed for ischemic-specific gene expression. Transcriptional, post-transcriptional, and post-translational regulatory strategies have been developed and evaluated in ischemic heart disease animal models. The regulatory systems can limit therapeutic gene expression to ischemic tissues and increase the efficiency of gene therapy. In this review, recent progresses in ischemic-specific gene expression systems are presented, and their applications to ischemic heart diseases are discussed.

  8. Gene expression in the urinary bladder: a common carcinoma in situ gene expression signature exists disregarding histopathological classification

    DEFF Research Database (Denmark)

    Andersen, Lars Dyrskjøt; Kruhøffer, Mogens; Andersen, Thomas Thykjær

    2004-01-01

    The presence of carcinoma in situ (CIS) lesions in the urinary bladder is associated with a high risk of disease progression to a muscle invasive stage. In this study, we used microarray expression profiling to examine the gene expression patterns in superficial transitional cell carcinoma (s...... urothelium and urothelium with CIS lesions from the same urinary bladder revealed that the gene expression found in sTCC with surrounding CIS is found also in CIS biopsies as well as in histologically normal samples adjacent to the CIS lesions. Furthermore, we also identified similar gene expression changes...

  9. Efficient expression of the yeast metallothionein gene in Escherichia coli

    Energy Technology Data Exchange (ETDEWEB)

    Berka, T.; Shatzman, A.; Zimmerman, J.; Strickler, J.; Rosenberg, M.

    1988-01-01

    The yeast metallothionein gene CUP1 was cloned into a bacterial expression system to achieve efficient, controlled expression of the stable, unprocessed protein product. The Escherichia coli-synthesized yeast metallothionein bound copper, cadmium, zinc, indicating that the protein was functional. Furthermore, E. coli cells expressing CUP1 acquired a new, inducible ability to selectively sequester heavy metal ions from the growth medium.

  10. Identifying the optimal gene and gene set in hepatocellular carcinoma based on differential expression and differential co-expression algorithm.

    Science.gov (United States)

    Dong, Li-Yang; Zhou, Wei-Zhong; Ni, Jun-Wei; Xiang, Wei; Hu, Wen-Hao; Yu, Chang; Li, Hai-Yan

    2017-02-01

    The objective of this study was to identify the optimal gene and gene set for hepatocellular carcinoma (HCC) utilizing differential expression and differential co-expression (DEDC) algorithm. The DEDC algorithm consisted of four parts: calculating differential expression (DE) by absolute t-value in t-statistics; computing differential co-expression (DC) based on Z-test; determining optimal thresholds on the basis of Chi-squared (χ2) maximization and the corresponding gene was the optimal gene; and evaluating functional relevance of genes categorized into different partitions to determine the optimal gene set with highest mean minimum functional information (FI) gain (Δ*G). The optimal thresholds divided genes into four partitions, high DE and high DC (HDE-HDC), high DE and low DC (HDE-LDC), low DE and high DC (LDE‑HDC), and low DE and low DC (LDE-LDC). In addition, the optimal gene was validated by conducting reverse transcription-polymerase chain reaction (RT-PCR) assay. The optimal threshold for DC and DE were 1.032 and 1.911, respectively. Using the optimal gene, the genes were divided into four partitions including: HDE-HDC (2,053 genes), HED-LDC (2,822 genes), LDE-HDC (2,622 genes), and LDE-LDC (6,169 genes). The optimal gene was microtubule‑associated protein RP/EB family member 1 (MAPRE1), and RT-PCR assay validated the significant difference between the HCC and normal state. The optimal gene set was nucleoside metabolic process (GO\\GO:0009116) with Δ*G = 18.681 and 24 HDE-HDC partitions in total. In conclusion, we successfully investigated the optimal gene, MAPRE1, and gene set, nucleoside metabolic process, which may be potential biomarkers for targeted therapy and provide significant insight for revealing the pathological mechanism underlying HCC.

  11. Building predictive gene signatures through simultaneous assessment of transcription factor activation and gene expression.

    Science.gov (United States)

    Building predictive gene signatures through simultaneous assessment of transcription factor activation and gene expression Exposure to many drugs and environmentally-relevant chemicals can cause adverse outcomes. These adverse outcomes, such as cancer, have been linked to mol...

  12. Expression robust 3D face recognition via mesh-based histograms of multiple order surface differential quantities

    KAUST Repository

    Li, Huibin

    2011-09-01

    This paper presents a mesh-based approach for 3D face recognition using a novel local shape descriptor and a SIFT-like matching process. Both maximum and minimum curvatures estimated in the 3D Gaussian scale space are employed to detect salient points. To comprehensively characterize 3D facial surfaces and their variations, we calculate weighted statistical distributions of multiple order surface differential quantities, including histogram of mesh gradient (HoG), histogram of shape index (HoS) and histogram of gradient of shape index (HoGS) within a local neighborhood of each salient point. The subsequent matching step then robustly associates corresponding points of two facial surfaces, leading to much more matched points between different scans of a same person than the ones of different persons. Experimental results on the Bosphorus dataset highlight the effectiveness of the proposed method and its robustness to facial expression variations. © 2011 IEEE.

  13. The inner nuclear membrane protein Src1 associates with subtelomeric genes and alters their regulated gene expression.

    Science.gov (United States)

    Grund, Stefanie E; Fischer, Tamás; Cabal, Ghislain G; Antúnez, Oreto; Pérez-Ortín, José E; Hurt, Ed

    2008-09-08

    Inner nuclear membrane proteins containing a LEM (LAP2, emerin, and MAN1) domain participate in different processes, including chromatin organization, gene expression, and nuclear envelope biogenesis. In this study, we identify a robust genetic interaction between transcription export (TREX) factors and yeast Src1, an integral inner nuclear membrane protein that is homologous to vertebrate LEM2. DNA macroarray analysis revealed that the expression of the phosphate-regulated genes PHO11, PHO12, and PHO84 is up-regulated in src1Delta cells. Notably, these PHO genes are located in subtelomeric regions of chromatin and exhibit a perinuclear location in vivo. Src1 spans the nuclear membrane twice and exposes its N and C domains with putative DNA-binding motifs to the nucleoplasm. Genome-wide chromatin immunoprecipitation-on-chip analyses indicated that Src1 is highly enriched at telomeres and subtelomeric regions of the yeast chromosomes. Our data show that the inner nuclear membrane protein Src1 functions at the interface between subtelomeric gene expression and TREX-dependent messenger RNA export through the nuclear pore complexes.

  14. Robust Parameter Identification to Perform the Modeling of pta and poxB Genes Deletion Effect on Escherichia Coli.

    Science.gov (United States)

    Guerrero-Torres, V; Rios-Lozano, M; Badillo-Corona, J A; Chairez, I; Garibay-Orijel, C

    2016-08-01

    The aim of this study was to design a robust parameter identification algorithm to characterize the effect of gene deletion on Escherichia coli (E. coli) MG1655. Two genes (pta and poxB) in the competitive pathways were deleted from this microorganism to inhibit pyruvate consumption. This condition deviated the E. coli metabolism toward the Krebs cycle. As a consequence, the biomass, substrate (glucose), lactic, and acetate acids as well as ethanol concentrations were modified. A hybrid model was proposed to consider the effect of gene deletion on the metabolism of E. coli. The model parameters were estimated by the application of a least mean square method based on the instrument variable technique. To evaluate the parametric identifier method, a set of robust exact differentiators, based on the super-twisting algorithm, was implemented. The hybrid model was successfully characterized by the parameters obtained from experimental information of E. coli MG1655. The significant difference between parameters obtained with wild-type strain and the modified (with deleted genes) justifies the application of the parametric identification algorithm. This characterization can be used to optimize the production of different byproducts of commercial interest.

  15. A hammerhead ribozyme inhibits ADE1 gene expression in yeast.

    Science.gov (United States)

    Ferbeyre, G; Bratty, J; Chen, H; Cedergren, R

    1995-03-21

    To study factors that affect in vivo ribozyme (Rz) activity, a model system has been devised in Saccharomyces cerevisiae based on the inhibition of ADE1 gene expression. This gene was chosen because Rz action can be evaluated visually by the Red phenotype produced when the activity of the gene product is inhibited. Different plasmid constructs allowed the expression of the Rz either in cis or in trans with respect to ADE1. Rz-related inhibition of ADE1 expression was correlated with a Red phenotype and a diminution of ADE1 mRNA levels only when the Rz gene was linked 5' to ADE1. The presence of the expected 3' cleavage fragment was demonstrated using a technique combining RNA ligation and PCR. This yeast system and detection technique are suited to the investigation of general factors affecting Rz-catalyzed inhibition of gene expression under in vivo conditions.

  16. Gene expression and behaviour in mouse models of HD.

    Science.gov (United States)

    Bowles, K R; Brooks, S P; Dunnett, S B; Jones, L

    2012-06-01

    Huntington's disease (HD) is an autosomal dominant neurodegenerative disease, resulting in expansion of the CAG repeat in exon 1 of the HTT gene. The resulting mutant huntingtin protein has been implicated in the disruption of a variety of cellular functions, including transcription. Mouse models of HD have been central to the development of our understanding of gene expression changes in this disease, and are now beginning to elucidate the relationship between gene expression and behaviour. Here, we review current mouse models of HD and their characterisation in terms of gene expression. In addition, we look at how this can inform behaviours observed in mouse models of disease. The relationship between gene expression and behaviour in mouse models of HD is important, as this will further our knowledge of disease progression and its underlying molecular events, highlight new treatment targets, and potentially provide new biomarkers for therapeutic trials. Copyright © 2011 Elsevier Inc. All rights reserved.

  17. Selection and validation of reference genes for quantitative gene expression studies in Erythroxylum coca

    OpenAIRE

    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 ...

  18. 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

  19. 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

  20. 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.

  1. 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.

  2. Gene expression profiling predicts the development of oral cancer.

    Science.gov (Unite