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Sample records for generate robust gene-expression

  1. 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.

  2. 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.

  3. 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.

  4. 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.

  5. 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.

  6. Reproducibility of gene expression across generations of Affymetrix microarrays

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    Haslett Judith N

    2003-06-01

    Full Text Available Abstract Background The development of large-scale gene expression profiling technologies is rapidly changing the norms of biological investigation. But the rapid pace of change itself presents challenges. Commercial microarrays are regularly modified to incorporate new genes and improved target sequences. Although the ability to compare datasets across generations is crucial for any long-term research project, to date no means to allow such comparisons have been developed. In this study the reproducibility of gene expression levels across two generations of Affymetrix GeneChips® (HuGeneFL and HG-U95A was measured. Results Correlation coefficients were computed for gene expression values across chip generations based on different measures of similarity. Comparing the absolute calls assigned to the individual probe sets across the generations found them to be largely unchanged. Conclusion We show that experimental replicates are highly reproducible, but that reproducibility across generations depends on the degree of similarity of the probe sets and the expression level of the corresponding transcript.

  7. 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

  8. 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.

  9. Combining gene expression data from different generations of oligonucleotide arrays

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    Kong Sek

    2004-10-01

    Full Text Available Abstract Background One of the important challenges in microarray analysis is to take full advantage of previously accumulated data, both from one's own laboratory and from public repositories. Through a comparative analysis on a variety of datasets, a more comprehensive view of the underlying mechanism or structure can be obtained. However, as we discover in this work, continual changes in genomic sequence annotations and probe design criteria make it difficult to compare gene expression data even from different generations of the same microarray platform. Results We first describe the extent of discordance between the results derived from two generations of Affymetrix oligonucleotide arrays, as revealed in cluster analysis and in identification of differentially expressed genes. We then propose a method for increasing comparability. The dataset we use consists of a set of 14 human muscle biopsy samples from patients with inflammatory myopathies that were hybridized on both HG-U95Av2 and HG-U133A human arrays. We find that the use of the probe set matching table for comparative analysis provided by Affymetrix produces better results than matching by UniGene or LocusLink identifiers but still remains inadequate. Rescaling of expression values for each gene across samples and data filtering by expression values enhance comparability but only for few specific analyses. As a generic method for improving comparability, we select a subset of probes with overlapping sequence segments in the two array types and recalculate expression values based only on the selected probes. We show that this filtering of probes significantly improves the comparability while retaining a sufficient number of probe sets for further analysis. Conclusions Compatibility between high-density oligonucleotide arrays is significantly affected by probe-level sequence information. With a careful filtering of the probes based on their sequence overlaps, data from different

  10. 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.

  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. 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.

  13. 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

  14. A Human "eFP" Browser for Generating Gene Expression Anatograms.

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    Patel, Rohan V; Hamanishi, Erin T; Provart, Nicholas J

    2016-01-01

    Transcriptomic studies help to further our understanding of gene function. Human transcriptomic studies tend to focus on a particular subset of tissue types or a particular disease state; however, it is possible to collate into a compendium multiple studies that have been profiled using the same expression analysis platform to provide an overview of gene expression levels in many different tissues or under different conditions. In order to increase the knowledge and understanding we gain from such studies, intuitive visualization of gene expression data in such a compendium can be useful. The Human eFP ("electronic Fluorescent Pictograph") Browser presented here is a tool for intuitive visualization of large human gene expression data sets on pictographic representations of the human body as gene expression "anatograms". Pictographic representations for new data sets may be generated easily. The Human eFP Browser can also serve as a portal to other gene-specific information through link-outs to various online resources.

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

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    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...

  16. A Human "eFP" Browser for Generating Gene Expression Anatograms.

    Directory of Open Access Journals (Sweden)

    Rohan V Patel

    Full Text Available Transcriptomic studies help to further our understanding of gene function. Human transcriptomic studies tend to focus on a particular subset of tissue types or a particular disease state; however, it is possible to collate into a compendium multiple studies that have been profiled using the same expression analysis platform to provide an overview of gene expression levels in many different tissues or under different conditions. In order to increase the knowledge and understanding we gain from such studies, intuitive visualization of gene expression data in such a compendium can be useful. The Human eFP ("electronic Fluorescent Pictograph" Browser presented here is a tool for intuitive visualization of large human gene expression data sets on pictographic representations of the human body as gene expression "anatograms". Pictographic representations for new data sets may be generated easily. The Human eFP Browser can also serve as a portal to other gene-specific information through link-outs to various online resources.

  17. 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

  18. Acetylated Deoxynivalenol Generates Differences of Gene Expression that Discriminate Trichothecene Toxicity

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    Tadahiro Suzuki

    2016-02-01

    Full Text Available Deoxynivalenol (DON, which is a toxic secondary metabolite generated by Fusarium species, is synthesized through two separate acetylation pathways. Both acetylation derivatives, 3-acetyl-DON (3ADON and 15-acetyl-DON (15ADON, also contaminate grain and corn widely. These derivatives are deacetylated via a variety of processes after ingestion, so it has been suggested that they have the same toxicity as DON. However, in the intestinal entry region such as the duodenum, the derivatives might come into contact with intestinal epithelium cells because metabolism by microflora or import into the body has not progressed. Therefore, the differences of toxicity between DON and these derivatives need to be investigated. Here, we observed gene expression changes in the yeast pdr5Δ mutant strain under concentration-dependent mycotoxin exposure conditions. 15ADON exposure induced significant gene expression changes and DON exposure generally had a similar but smaller effect. However, the glucose transporter genes HXT2 and HXT4 showed converse trends. 3ADON also induced a different expression trend in these genes than DON and 15ADON. These differences in gene expression suggest that DON and its derivatives have different effects on cells.

  19. 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.

  20. 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.

  1. 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.

  2. Effects of Nonylphenol on Brain Gene Expression Profiles in F1 Generation Rats

    Institute of Scientific and Technical Information of China (English)

    YIN-YIN XIA; PING ZHANG; YANG WANG

    2008-01-01

    Objective To explore the effects of nonylphenol on brain gene expression profiles in F1 generation rats by microarray technique.Methods mRNA was extracted from the brain of 2-day old F1 generation male rats Whose F0 female generation was either exposed to nonylphenol or free from nonylphenol exposure,and then it was reversely transcribed to cDNA hbeled with cy5 and cy3 fluorescence.Subsequently,cDNA probes were hybridized to two BiostarR-40S cDNA gene chips and fluorescent signals of cy5 and cy3 were scanned and analyzed. Results Two genes were differentially down-regulated.Conclusion Nonylphenol may disturb the neurcendocrine function of male rats when administered perinatally.

  3. 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

  4. 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

  5. Multimodal probabilistic generative models for time-course gene expression data and Gene Ontology (GO) tags.

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    Gabbur, Prasad; Hoying, James; Barnard, Kobus

    2015-10-01

    We propose four probabilistic generative models for simultaneously modeling gene expression levels and Gene Ontology (GO) tags. Unlike previous approaches for using GO tags, the joint modeling framework allows the two sources of information to complement and reinforce each other. We fit our models to three time-course datasets collected to study biological processes, specifically blood vessel growth (angiogenesis) and mitotic cell cycles. The proposed models result in a joint clustering of genes and GO annotations. Different models group genes based on GO tags and their behavior over the entire time-course, within biological stages, or even individual time points. We show how such models can be used for biological stage boundary estimation de novo. We also evaluate our models on biological stage prediction accuracy of held out samples. Our results suggest that the models usually perform better when GO tag information is included. Copyright © 2015 Elsevier Inc. All rights reserved.

  6. EXP-PAC: providing comparative analysis and storage of next generation gene expression data.

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    Church, Philip C; Goscinski, Andrzej; Lefèvre, Christophe

    2012-07-01

    Microarrays and more recently RNA sequencing has led to an increase in available gene expression data. How to manage and store this data is becoming a key issue. In response we have developed EXP-PAC, a web based software package for storage, management and analysis of gene expression and sequence data. Unique to this package is SQL based querying of gene expression data sets, distributed normalization of raw gene expression data and analysis of gene expression data across experiments and species. This package has been populated with lactation data in the international milk genomic consortium web portal (http://milkgenomics.org/). Source code is also available which can be hosted on a Windows, Linux or Mac APACHE server connected to a private or public network (http://mamsap.it.deakin.edu.au/~pcc/Release/EXP_PAC.html). Copyright © 2012 Elsevier Inc. All rights reserved.

  7. Generation and gene expression profiling of 48 transcription-factor-inducible mouse embryonic stem cell lines

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    Yamamizu, Kohei; Sharov, Alexei A.; Piao, Yulan; Amano, Misa; Yu, Hong; Nishiyama, Akira; Dudekula, Dawood B.; Schlessinger, David; Ko, Minoru S. H.

    2016-01-01

    Mouse embryonic stem cells (ESCs) can differentiate into a wide range – and possibly all cell types in vitro, and thus provide an ideal platform to study systematically the action of transcription factors (TFs) in cell differentiation. Previously, we have generated and analyzed 137 TF-inducible mouse ESC lines. As an extension of this “NIA Mouse ESC Bank,” we generated and characterized 48 additional mouse ESC lines, in which single TFs in each line could be induced in a doxycycline-controllable manner. Together, with the previous ESC lines, the bank now comprises 185 TF-manipulable ESC lines (>10% of all mouse TFs). Global gene expression (transcriptome) profiling revealed that the induction of individual TFs in mouse ESCs for 48 hours shifts their transcriptomes toward specific differentiation fates (e.g., neural lineages by Myt1 Isl1, and St18; mesodermal lineages by Pitx1, Pitx2, Barhl2, and Lmx1a; white blood cells by Myb, Etv2, and Tbx6, and ovary by Pitx1, Pitx2, and Dmrtc2). These data also provide and lists of inferred target genes of each TF and possible functions of these TFs. The results demonstrate the utility of mouse ESC lines and their transcriptome data for understanding the mechanism of cell differentiation and the function of TFs. PMID:27150017

  8. Processing of gene expression data generated by quantitative real-time RT-PCR.

    Science.gov (United States)

    Muller, Patrick Y; Janovjak, Harald; Miserez, André R; Dobbie, Zuzana

    2002-06-01

    Quantitative real-time PCR represents a highly sensitive and powerful technique for the quantitation of nucleic acids. It has a tremendous potential for the high-throughput analysis of gene expression in research and routine diagnostics. However, the major hurdle is not the practical performance of the experiments themselves but rather the efficient evaluation and the mathematical and statistical analysis of the enormous amount of data gained by this technology, as these functions are not included in the software provided by the manufacturers of the detection systems. In this work, we focus on the mathematical evaluation and analysis of the data generated by quantitative real-time PCR, the calculation of the final results, the propagation of experimental variation of the measured values to the final results, and the statistical analysis. We developed a Microsoft Excel-based software application coded in Visual Basic for Applications, called Q-Gene, which addresses these points. Q-Gene manages and expedites the planning, performance, and evaluation of quantitative real-time PCR experiments, as well as the mathematical and statistical analysis, storage, and graphical presentation of the data. The Q-Gene software application is a tool to cope with complex quantitative real-time PCR experiments at a high-throughput scale and considerably expedites and rationalizes the experimental setup, data analysis, and data management while ensuring highest reproducibility.

  9. 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.

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

    OpenAIRE

    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 ...

  12. Incidence of "quasi-ditags" in catalogs generated by Serial Analysis of Gene Expression (SAGE)

    OpenAIRE

    Sharov Alexei A; Anisimov Sergey V

    2004-01-01

    Abstract Background Serial Analysis of Gene Expression (SAGE) is a functional genomic technique that quantitatively analyzes the cellular transcriptome. The analysis of SAGE libraries relies on the identification of ditags from sequencing files; however, the software used to examine SAGE libraries cannot distinguish between authentic versus false ditags ("quasi-ditags"). Results We provide examples of quasi-ditags that originate from cloning and sequencing artifacts (i.e. genomic contaminatio...

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

    Directory of Open Access Journals (Sweden)

    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.

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

    Directory of Open Access Journals (Sweden)

    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.

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

    Science.gov (United States)

    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.

  16. Incidence of "quasi-ditags" in catalogs generated by Serial Analysis of Gene Expression (SAGE)

    Science.gov (United States)

    Anisimov, Sergey V; Sharov, Alexei A

    2004-01-01

    Background Serial Analysis of Gene Expression (SAGE) is a functional genomic technique that quantitatively analyzes the cellular transcriptome. The analysis of SAGE libraries relies on the identification of ditags from sequencing files; however, the software used to examine SAGE libraries cannot distinguish between authentic versus false ditags ("quasi-ditags"). Results We provide examples of quasi-ditags that originate from cloning and sequencing artifacts (i.e. genomic contamination or random combinations of nucleotides) that are included in SAGE libraries. We have employed a mathematical model to predict the frequency of quasi-ditags in random nucleotide sequences, and our data show that clones containing less than or equal to 2 ditags (which include chromosomal cloning artifacts) should be excluded from the analysis of SAGE catalogs. Conclusions Cloning and sequencing artifacts contaminating SAGE libraries could be eliminated using simple pre-screening procedure to increase the reliability of the data. PMID:15491492

  17. Incidence of "quasi-ditags" in catalogs generated by Serial Analysis of Gene Expression (SAGE

    Directory of Open Access Journals (Sweden)

    Sharov Alexei A

    2004-10-01

    Full Text Available Abstract Background Serial Analysis of Gene Expression (SAGE is a functional genomic technique that quantitatively analyzes the cellular transcriptome. The analysis of SAGE libraries relies on the identification of ditags from sequencing files; however, the software used to examine SAGE libraries cannot distinguish between authentic versus false ditags ("quasi-ditags". Results We provide examples of quasi-ditags that originate from cloning and sequencing artifacts (i.e. genomic contamination or random combinations of nucleotides that are included in SAGE libraries. We have employed a mathematical model to predict the frequency of quasi-ditags in random nucleotide sequences, and our data show that clones containing less than or equal to 2 ditags (which include chromosomal cloning artifacts should be excluded from the analysis of SAGE catalogs. Conclusions Cloning and sequencing artifacts contaminating SAGE libraries could be eliminated using simple pre-screening procedure to increase the reliability of the data.

  18. A gene expression resource generated by genome-wide lacZ profiling in the mouse

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    Elizabeth Tuck

    2015-11-01

    Full Text Available Knowledge of the expression profile of a gene is a critical piece of information required to build an understanding of the normal and essential functions of that gene and any role it may play in the development or progression of disease. High-throughput, large-scale efforts are on-going internationally to characterise reporter-tagged knockout mouse lines. As part of that effort, we report an open access adult mouse expression resource, in which the expression profile of 424 genes has been assessed in up to 47 different organs, tissues and sub-structures using a lacZ reporter gene. Many specific and informative expression patterns were noted. Expression was most commonly observed in the testis and brain and was most restricted in white adipose tissue and mammary gland. Over half of the assessed genes presented with an absent or localised expression pattern (categorised as 0-10 positive structures. A link between complexity of expression profile and viability of homozygous null animals was observed; inactivation of genes expressed in ≥21 structures was more likely to result in reduced viability by postnatal day 14 compared with more restricted expression profiles. For validation purposes, this mouse expression resource was compared with Bgee, a federated composite of RNA-based expression data sets. Strong agreement was observed, indicating a high degree of specificity in our data. Furthermore, there were 1207 observations of expression of a particular gene in an anatomical structure where Bgee had no data, indicating a large amount of novelty in our data set. Examples of expression data corroborating and extending genotype-phenotype associations and supporting disease gene candidacy are presented to demonstrate the potential of this powerful resource.

  19. Comparison of gene expression in HCT116 treatment derivatives generated by two different 5-fluorouracil exposure protocols

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    Haug Terje

    2004-04-01

    Full Text Available Abstract Background Established colorectal cancer cell lines subjected to different 5-fluorouracil (5-FU treatment protocols are often used as in vitro model systems for investigations of downstream cellular responses to 5-FU and to generate 5-FU-resistant derivatives for the investigation of biological mechanisms involved in drug resistance. We subjected HCT116 colon cancer cells to two different 5-FU treatment protocols in an attempt to generate resistant derivatives: one that simulated the clinical bolus regimens using clinically-achievable 5-FU levels, the other that utilized serial passage in the presence of increasing 5-FU concentrations (continuous exposure. HCT116 Bolus3, ContinB, and ContinD, corresponding to independently-derived cell lines generated either by bolus exposure or continuous exposure, respectively, were characterized for growth- and apoptosis-associated phenotypes, and gene expression using 8.5 K oligonucleotide microarrays. Comparative gene expression analyses were done in order to determine if transcriptional profiles for the respective treatment derivatives were similar or substantially different, and to identify the signaling and regulatory pathways involved in mediating the downstream response to 5-FU exposure and possibly involved in development of resistance. Results HCT116 ContinB and ContinD cells were respectively 27-fold and >100-fold more resistant to 5-FU and had reduced apoptotic fractions in response to transient 5-FU challenge compared to the parental cell line, whereas HCT116 Bolus3 cells were not resistant to 5-FU after 3 cycles of bolus 5-FU treatment and had the same apoptotic response to transient 5-FU challenge as the parental cell line. However, gene expression levels and expression level changes for all detected genes in Bolus3 cells were similar to those seen in both the ContinB (strongest correlation and ContinD derivatives, as demonstrated by correlation and cluster analyses. Regulatory pathways

  20. Gene expression changes in the coccolithophore Emiliania huxleyi after 500 generations of selection to ocean acidification.

    Science.gov (United States)

    Lohbeck, Kai T; Riebesell, Ulf; Reusch, Thorsten B H

    2014-07-07

    Coccolithophores are unicellular marine algae that produce biogenic calcite scales and substantially contribute to marine primary production and carbon export to the deep ocean. Ongoing ocean acidification particularly impairs calcifying organisms, mostly resulting in decreased growth and calcification. Recent studies revealed that the immediate physiological response in the coccolithophore Emiliania huxleyi to ocean acidification may be partially compensated by evolutionary adaptation, yet the underlying molecular mechanisms are currently unknown. Here, we report on the expression levels of 10 candidate genes putatively relevant to pH regulation, carbon transport, calcification and photosynthesis in E. huxleyi populations short-term exposed to ocean acidification conditions after acclimation (physiological response) and after 500 generations of high CO2 adaptation (adaptive response). The physiological response revealed downregulation of candidate genes, well reflecting the concomitant decrease of growth and calcification. In the adaptive response, putative pH regulation and carbon transport genes were up-regulated, matching partial restoration of growth and calcification in high CO2-adapted populations. Adaptation to ocean acidification in E. huxleyi likely involved improved cellular pH regulation, presumably indirectly affecting calcification. Adaptive evolution may thus have the potential to partially restore cellular pH regulatory capacity and thereby mitigate adverse effects of ocean acidification. © 2014 The Author(s) Published by the Royal Society. All rights reserved.

  1. PPARG: Gene Expression Regulation and Next-Generation Sequencing for Unsolved Issues

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    Valerio Costa

    2010-01-01

    Full Text Available Peroxisome proliferator-activated receptor gamma (PPARγ is one of the most extensively studied ligand-inducible transcription factors (TFs, able to modulate its transcriptional activity through conformational changes. It is of particular interest because of its pleiotropic functions: it plays a crucial role in the expression of key genes involved in adipogenesis, lipid and glucid metabolism, atherosclerosis, inflammation, and cancer. Its protein isoforms, the wide number of PPARγ target genes, ligands, and coregulators contribute to determine the complexity of its function. In addition, the presence of genetic variants is likely to affect expression levels of target genes although the impact of PPARG gene variations on the expression of target genes is not fully understood. The introduction of massively parallel sequencing platforms—in the Next Generation Sequencing (NGS era—has revolutionized the way of investigating the genetic causes of inherited diseases. In this context, DNA-Seq for identifying—within both coding and regulatory regions of PPARG gene—novel nucleotide variations and haplotypes associated to human diseases, ChIP-Seq for defining a PPARγ binding map, and RNA-Seq for unraveling the wide and intricate gene pathways regulated by PPARG, represent incredible steps toward the understanding of PPARγ in health and disease.

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

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    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.

  3. Gene expression responses of HeLa cells to chemical species generated by an atmospheric plasma flow

    Energy Technology Data Exchange (ETDEWEB)

    Yokoyama, Mayo, E-mail: yokoyama@plasma.ifs.tohoku.ac.jp [Institute of Fluid Science, Tohoku University, 2-1-1 Katahira, Aoba-ku, Sendai 980-8577 (Japan); Johkura, Kohei, E-mail: kohei@shinshu-u.ac.jp [Department of Histology and Embryology, Shinshu University School of Medicine, 3-1-1 Asahi, Matsumoto 390-8621 (Japan); Sato, Takehiko, E-mail: sato@ifs.tohoku.ac.jp [Institute of Fluid Science, Tohoku University, 2-1-1 Katahira, Aoba-ku, Sendai 980-8577 (Japan)

    2014-08-08

    Highlights: • Response of HeLa cells to a plasma-irradiated medium was revealed by DNA microarray. • Gene expression pattern was basically different from that in a H{sub 2}O{sub 2}-added medium. • Prominently up-/down-regulated genes were partly shared by the two media. • Gene ontology analysis showed both similar and different responses in the two media. • Candidate genes involved in response to ROS were detected in each medium. - Abstract: Plasma irradiation generates many factors able to affect the cellular condition, and this feature has been studied for its application in the field of medicine. We previously reported that hydrogen peroxide (H{sub 2}O{sub 2}) was the major cause of HeLa cell death among the chemical species generated by high level irradiation of a culture medium by atmospheric plasma. To assess the effect of plasma-induced factors on the response of live cells, HeLa cells were exposed to a medium irradiated by a non-lethal plasma flow level, and their gene expression was broadly analyzed by DNA microarray in comparison with that in a corresponding concentration of 51 μM H{sub 2}O{sub 2}. As a result, though the cell viability was sufficiently maintained at more than 90% in both cases, the plasma-medium had a greater impact on it than the H{sub 2}O{sub 2}-medium. Hierarchical clustering analysis revealed fundamentally different cellular responses between these two media. A larger population of genes was upregulated in the plasma-medium, whereas genes were downregulated in the H{sub 2}O{sub 2}-medium. However, a part of the genes that showed prominent differential expression was shared by them, including an immediate early gene ID2. In gene ontology analysis of upregulated genes, the plasma-medium showed more diverse ontologies than the H{sub 2}O{sub 2}-medium, whereas ontologies such as “response to stimulus” were common, and several genes corresponded to “response to reactive oxygen species.” Genes of AP-1 proteins, e.g., JUN

  4. Royal Decree: Gene Expression in Trans-Generationally Immune Primed Bumblebee Workers Mimics a Primary Immune Response.

    Directory of Open Access Journals (Sweden)

    Seth M Barribeau

    Full Text Available Invertebrates lack the cellular and physiological machinery of the adaptive immune system, but show specificity in their immune response and immune priming. Functionally, immune priming is comparable to immune memory in vertebrates. Individuals that have survived exposure to a given parasite are better protected against subsequent exposures. Protection may be cross-reactive, but demonstrations of persistent and specific protection in invertebrates are increasing. This immune priming can cross generations ("trans-generational" immune priming, preparing offspring for the prevailing parasite environment. While these phenomena gain increasing support, the mechanistic foundations underlying such immune priming, both within and across generations, remain largely unknown. Using a transcriptomic approach, we show that exposing bumblebee queens with an injection of heat-killed bacteria, known to induce trans-generational immune priming, alters daughter (worker gene expression. Daughters, even when unexposed themselves, constitutively express a core set of the genes induced upon direct bacterial exposure, including high expression of antimicrobial peptides, a beta-glucan receptor protein implicated in bacterial recognition and the induction of the toll signaling pathway, and slit-3 which is important in honeybee immunity. Maternal exposure results in a distinct upregulation of their daughters' immune system, with a signature overlapping with the induced individual response to a direct exposure. This will mediate mother-offspring protection, but also associated costs related to reconfiguration of constitutive immune expression. Moreover, identification of conserved immune pathways in memory-like responses has important implications for our understanding of the innate immune system, including the innate components in vertebrates, which share many of these pathways.

  5. pBaSysBioll : an integrative plasmid generating gfp transcriptional fusions for high-throughput analysis of gene expression in Bacillus subtilis

    NARCIS (Netherlands)

    Botella, Eric; Fogg, Mark; Jules, Matthieu; Piersma, Sjouke; Doherty, Geoff; Hansen, Annette; Denham, Emma. L.; Le Chat, Ludovic; Veiga, Patrick; Bailey, Kirra; Lewis, Peter J.; van Dijl, Jan Maarten; Aymerich, Stephane; Wilkinson, Anthony J.; Devine, Kevin M.

    Plasmid pBaSysBioll was constructed for high-throughput analysis of gene expression in Bacillus subtilis. It is an integrative plasmid with a ligation-independent cloning (LIC) site, allowing the generation of transcriptional gfpmut3 fusions with desired promoters. Integration is by a Campbell-type

  6. pBaSysBioll : an integrative plasmid generating gfp transcriptional fusions for high-throughput analysis of gene expression in Bacillus subtilis

    NARCIS (Netherlands)

    Botella, Eric; Fogg, Mark; Jules, Matthieu; Piersma, Sjouke; Doherty, Geoff; Hansen, Annette; Denham, Emma. L.; Le Chat, Ludovic; Veiga, Patrick; Bailey, Kirra; Lewis, Peter J.; van Dijl, Jan Maarten; Aymerich, Stephane; Wilkinson, Anthony J.; Devine, Kevin M.

    2010-01-01

    Plasmid pBaSysBioll was constructed for high-throughput analysis of gene expression in Bacillus subtilis. It is an integrative plasmid with a ligation-independent cloning (LIC) site, allowing the generation of transcriptional gfpmut3 fusions with desired promoters. Integration is by a Campbell-type

  7. Generation of a Transcriptome in a Model Lepidopteran Pest, Heliothis virescens, Using Multiple Sequencing Strategies for Profiling Midgut Gene Expression.

    Science.gov (United States)

    Perera, Omaththage P; Shelby, Kent S; Popham, Holly J R; Gould, Fred; Adang, Michael J; Jurat-Fuentes, Juan Luis

    2015-01-01

    Heliothine pests such as the tobacco budworm, Heliothis virescens (F.), pose a significant threat to production of a variety of crops and ornamental plants and are models for developmental and physiological studies. The efforts to develop new control measures for H. virescens, as well as its use as a relevant biological model, are hampered by a lack of molecular resources. The present work demonstrates the utility of next-generation sequencing technologies for rapid molecular resource generation from this species for which lacks a sequenced genome. In order to amass a de novo transcriptome for this moth, transcript sequences generated from Illumina, Roche 454, and Sanger sequencing platforms were merged into a single de novo transcriptome assembly. This pooling strategy allowed a thorough sampling of transcripts produced under diverse environmental conditions, developmental stages, tissues, and infections with entomopathogens used for biological control, to provide the most complete transcriptome to date for this species. Over 138 million reads from the three platforms were assembled into the final set of 63,648 contigs. Of these, 29,978 had significant BLAST scores indicating orthologous relationships to transcripts of other insect species, with the top-hit species being the monarch butterfly (Danaus plexippus) and silkworm (Bombyx mori). Among identified H. virescens orthologs were immune effectors, signal transduction pathways, olfactory receptors, hormone biosynthetic pathways, peptide hormones and their receptors, digestive enzymes, and insecticide resistance enzymes. As an example, we demonstrate the utility of this transcriptomic resource to study gene expression profiling of larval midguts and detect transcripts of putative Bacillus thuringiensis (Bt) Cry toxin receptors. The substantial molecular resources described in this study will facilitate development of H. virescens as a relevant biological model for functional genomics and for new biological

  8. Generation of a Transcriptome in a Model Lepidopteran Pest, Heliothis virescens, Using Multiple Sequencing Strategies for Profiling Midgut Gene Expression.

    Directory of Open Access Journals (Sweden)

    Omaththage P Perera

    Full Text Available Heliothine pests such as the tobacco budworm, Heliothis virescens (F., pose a significant threat to production of a variety of crops and ornamental plants and are models for developmental and physiological studies. The efforts to develop new control measures for H. virescens, as well as its use as a relevant biological model, are hampered by a lack of molecular resources. The present work demonstrates the utility of next-generation sequencing technologies for rapid molecular resource generation from this species for which lacks a sequenced genome. In order to amass a de novo transcriptome for this moth, transcript sequences generated from Illumina, Roche 454, and Sanger sequencing platforms were merged into a single de novo transcriptome assembly. This pooling strategy allowed a thorough sampling of transcripts produced under diverse environmental conditions, developmental stages, tissues, and infections with entomopathogens used for biological control, to provide the most complete transcriptome to date for this species. Over 138 million reads from the three platforms were assembled into the final set of 63,648 contigs. Of these, 29,978 had significant BLAST scores indicating orthologous relationships to transcripts of other insect species, with the top-hit species being the monarch butterfly (Danaus plexippus and silkworm (Bombyx mori. Among identified H. virescens orthologs were immune effectors, signal transduction pathways, olfactory receptors, hormone biosynthetic pathways, peptide hormones and their receptors, digestive enzymes, and insecticide resistance enzymes. As an example, we demonstrate the utility of this transcriptomic resource to study gene expression profiling of larval midguts and detect transcripts of putative Bacillus thuringiensis (Bt Cry toxin receptors. The substantial molecular resources described in this study will facilitate development of H. virescens as a relevant biological model for functional genomics and for new

  9. Gene expression during the generation and activation of mouse neutrophils: implication of novel functional and regulatory pathways.

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    Jeffrey A Ericson

    Full Text Available As part of the Immunological Genome Project (ImmGen, gene expression was determined in unstimulated (circulating mouse neutrophils and three populations of neutrophils activated in vivo, with comparison among these populations and to other leukocytes. Activation conditions included serum-transfer arthritis (mediated by immune complexes, thioglycollate-induced peritonitis, and uric acid-induced peritonitis. Neutrophils expressed fewer genes than any other leukocyte population studied in ImmGen, and down-regulation of genes related to translation was particularly striking. However, genes with expression relatively specific to neutrophils were also identified, particularly three genes of unknown function: Stfa2l1, Mrgpr2a and Mrgpr2b. Comparison of genes up-regulated in activated neutrophils led to several novel findings: increased expression of genes related to synthesis and use of glutathione and of genes related to uptake and metabolism of modified lipoproteins, particularly in neutrophils elicited by thioglycollate; increased expression of genes for transcription factors in the Nr4a family, only in neutrophils elicited by serum-transfer arthritis; and increased expression of genes important in synthesis of prostaglandins and response to leukotrienes, particularly in neutrophils elicited by uric acid. Up-regulation of genes related to apoptosis, response to microbial products, NFkB family members and their regulators, and MHC class II expression was also seen, in agreement with previous studies. A regulatory model developed from the ImmGen data was used to infer regulatory genes involved in the changes in gene expression during neutrophil activation. Among 64, mostly novel, regulatory genes predicted to influence these changes in gene expression, Irf5 was shown to be important for optimal secretion of IL-10, IP-10, MIP-1α, MIP-1β, and TNF-α by mouse neutrophils in vitro after stimulation through TLR9. This data-set and its analysis using the

  10. A molecular toolbox for rapid generation of viral vectors to up- or down-regulate in vivo neuronal gene expression

    Directory of Open Access Journals (Sweden)

    Melanie D. White

    2011-07-01

    Full Text Available We introduce a molecular toolbox for manipulation of neuronal gene expression in vivo. The toolbox includes promoters, ion channels, optogenetic tools, fluorescent proteins and intronic artificial microRNAs. The components are easily assembled into adeno-associated virus (AAV or lentivirus vectors using recombination cloning. We demonstrate assembly of toolbox components into lentivirus and AAV vectors and use these vectors for in vivo expression of inwardly rectifying potassium channels (Kir2.1, Kir3.1 and Kir3.2 and an artificial microRNA targeted against the ion channel HCN1 (HCN1 miR. We show that AAV assembled to express HCN1 miR produces efficacious and specific in vivo knockdown of HCN1 channels. Comparison of in vivo viral transduction using HCN1 miR with mice containing a germ line deletion of HCN1 reveals similar physiological phenotypes in cerebellar Purkinje cells. The easy assembly and re-usability of the toolbox components, together with the ability to up- or down-regulate neuronal gene expression in vivo, may be useful for applications in many areas of neuroscience.

  11. 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...

  12. 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.

  13. 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.

  14. Comparing machine learning and logistic regression methods for predicting hypertension using a combination of gene expression and next-generation sequencing data.

    Science.gov (United States)

    Held, Elizabeth; Cape, Joshua; Tintle, Nathan

    2016-01-01

    Machine learning methods continue to show promise in the analysis of data from genetic association studies because of the high number of variables relative to the number of observations. However, few best practices exist for the application of these methods. We extend a recently proposed supervised machine learning approach for predicting disease risk by genotypes to be able to incorporate gene expression data and rare variants. We then apply 2 different versions of the approach (radial and linear support vector machines) to simulated data from Genetic Analysis Workshop 19 and compare performance to logistic regression. Method performance was not radically different across the 3 methods, although the linear support vector machine tended to show small gains in predictive ability relative to a radial support vector machine and logistic regression. Importantly, as the number of genes in the models was increased, even when those genes contained causal rare variants, model predictive ability showed a statistically significant decrease in performance for both the radial support vector machine and logistic regression. The linear support vector machine showed more robust performance to the inclusion of additional genes. Further work is needed to evaluate machine learning approaches on larger samples and to evaluate the relative improvement in model prediction from the incorporation of gene expression data.

  15. A Robust Quantum Random Number Generator Based on Bosonic Stimulation

    CERN Document Server

    H, Akshata Shenoy; Srikanth, R; Srinivas, T

    2011-01-01

    We propose a method to realize a robust quantum random number generator based on bosonic stimulation. A particular implementation that employs weak coherent pulses and conventional avalanche photo-diode detectors (APDs) is discussed.

  16. Monocyte derived dendritic cells generated by IFN-α acquire mature dendritic and natural killer cell properties as shown by gene expression analysis

    OpenAIRE

    Czibere Akos; Winter Meike; Diaz Blanco Elena; Papewalis Claudia; Schott Matthias; Maihöfer Dagmar; Kronenwett Ralf; Safaian Nancy; Korthals Mark; Haas Rainer; Kobbe Guido; Fenk Roland

    2007-01-01

    Abstract Background Dendritic cell (DC) vaccines can induce antitumor immune responses in patients with malignant diseases, while the most suitable DC culture conditions have not been established yet. In this study we compared monocyte derived human DC from conventional cultures containing GM-CSF and IL-4/TNF-α (IL-4/TNF-DC) with DC generated by the novel protocol using GM-CSF and IFN-α (IFN-DC). Methods To characterise the molecular differences of both DC preparations, gene expression profil...

  17. Robust entanglement generation by reservoir engineering

    OpenAIRE

    Muschik, Christine A.; Krauter, Hanna; Jensen, Kasper; Petersen, Jonas M.; Cirac, J. Ignacio; Polzik, Eugene S.

    2012-01-01

    Following a recent proposal [C. Muschik et. al., Phys. Rev. A 83, 052312 (2011)], engineered dissipative processes have been used for the generation of stable entanglement between two macroscopic atomic ensembles at room temperature [H. Krauter et. al., Phys. Rev. Lett. 107, 080503 (2011)]. This experiment included the preparation of entangled states which are continuously available during a time interval of one hour. Here, we present additional material, further-reaching data and an extensio...

  18. Ex vivo generated natural killer cells acquire typical natural killer receptors and display a cytotoxic gene expression profile similar to peripheral blood natural killer cells.

    Science.gov (United States)

    Lehmann, Dorit; Spanholtz, Jan; Osl, Markus; Tordoir, Marleen; Lipnik, Karoline; Bilban, Martin; Schlechta, Bernhard; Dolstra, Harry; Hofer, Erhard

    2012-11-01

    Ex vivo differentiation systems of natural killer (NK) cells from CD34+ hematopoietic stem cells are of potential importance for adjuvant immunotherapy of cancer. Here, we analyzed ex vivo differentiation of NK cells from cord blood-derived CD34+ stem cells by gene expression profiling, real-time RT-PCR, flow cytometry, and functional analysis. Additionally, we compared the identified characteristics to peripheral blood (PB) CD56(bright) and CD56(dim) NK cells. The data show sequential expression of CD56 and the CD94 and NKG2 receptor chains during ex vivo NK cell development, resulting finally in the expression of a range of genes with partial characteristics of CD56(bright) and CD56(dim) NK cells from PB. Expression of characteristic NK cell receptors and cytotoxic genes was mainly found within the predominant ex vivo generated population of NKG2A+ NK cells, indicating the importance of NKG2A expression during NK cell differentiation and maturation. Furthermore, despite distinct phenotypic characteristics, the detailed analysis of cytolytic genes expressed within the ex vivo differentiated NK cells revealed a pattern close to CD56(dim) NK cells. In line with this finding, ex vivo generated NK cells displayed potent cytotoxicity. This supports that the ex vivo differentiation system faithfully reproduces major steps of the differentiation of NK cells from their progenitors, constitutes an excellent model to study NK cell differentiation, and is valuable to generate large-scale NK cells appropriate for immunotherapy.

  19. HeatmapGenerator: high performance RNAseq and microarray visualization software suite to examine differential gene expression levels using an R and C++ hybrid computational pipeline.

    Science.gov (United States)

    Khomtchouk, Bohdan B; Van Booven, Derek J; Wahlestedt, Claes

    2014-01-01

    The graphical visualization of gene expression data using heatmaps has become an integral component of modern-day medical research. Heatmaps are used extensively to plot quantitative differences in gene expression levels, such as those measured with RNAseq and microarray experiments, to provide qualitative large-scale views of the transcriptonomic landscape. Creating high-quality heatmaps is a computationally intensive task, often requiring considerable programming experience, particularly for customizing features to a specific dataset at hand. Software to create publication-quality heatmaps is developed with the R programming language, C++ programming language, and OpenGL application programming interface (API) to create industry-grade high performance graphics. We create a graphical user interface (GUI) software package called HeatmapGenerator for Windows OS and Mac OS X as an intuitive, user-friendly alternative to researchers with minimal prior coding experience to allow them to create publication-quality heatmaps using R graphics without sacrificing their desired level of customization. The simplicity of HeatmapGenerator is that it only requires the user to upload a preformatted input file and download the publicly available R software language, among a few other operating system-specific requirements. Advanced features such as color, text labels, scaling, legend construction, and even database storage can be easily customized with no prior programming knowledge. We provide an intuitive and user-friendly software package, HeatmapGenerator, to create high-quality, customizable heatmaps generated using the high-resolution color graphics capabilities of R. The software is available for Microsoft Windows and Apple Mac OS X. HeatmapGenerator is released under the GNU General Public License and publicly available at: http://sourceforge.net/projects/heatmapgenerator/. The Mac OS X direct download is available at: http://sourceforge.net/projects/heatmapgenerator/files/HeatmapGenerator

  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. High-frequency stimulation induces gradual immediate early gene expression in maturing adult-generated hippocampal granule cells.

    Science.gov (United States)

    Jungenitz, Tassilo; Radic, Tijana; Jedlicka, Peter; Schwarzacher, Stephan W

    2014-07-01

    Increasing evidence shows that adult neurogenesis of hippocampal granule cells is advantageous for learning and memory. We examined at which stage of structural maturation and age new granule cells can be activated by strong synaptic stimulation. High-frequency stimulation of the perforant pathway in urethane-anesthetized rats elicited expression of the immediate early genes c-fos, Arc, zif268 and pCREB133 in almost 100% of mature, calbindin-positive granule cells. In contrast, it failed to induce immediate early gene expression in immature doublecortin-positive granule cells. Furthermore, doublecortin-positive neurons did not react with c-fos or Arc expression to mild theta-burst stimulation or novel environment exposure. Endogenous expression of pCREB133 was increasingly present in young cells with more elaborated dendrites, revealing a close correlation to structural maturation. Labeling with bromodeoxyuridine revealed cell age dependence of stimulation-induced c-fos, Arc and zif268 expression, with only a few cells reacting at 21 days, but with up to 75% of cells activated at 35-77 days of cell age. Our results indicate an increasing synaptic integration of maturing granule cells, starting at 21 days of cell age, but suggest a lack of ability to respond to activation with synaptic potentiation on the transcriptional level as long as immature cells express doublecortin. © The Author 2013. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

  2. Learning robust pulses for generating universal quantum gates

    Science.gov (United States)

    Dong, Daoyi; Wu, Chengzhi; Chen, Chunlin; Qi, Bo; Petersen, Ian R.; Nori, Franco

    2016-01-01

    Constructing a set of universal quantum gates is a fundamental task for quantum computation. The existence of noises, disturbances and fluctuations is unavoidable during the process of implementing quantum gates for most practical quantum systems. This paper employs a sampling-based learning method to find robust control pulses for generating a set of universal quantum gates. Numerical results show that the learned robust control fields are insensitive to disturbances, uncertainties and fluctuations during the process of realizing universal quantum gates. PMID:27782219

  3. Robust network topologies for generating switch-like cellular responses.

    Directory of Open Access Journals (Sweden)

    Najaf A Shah

    2011-06-01

    Full Text Available Signaling networks that convert graded stimuli into binary, all-or-none cellular responses are critical in processes ranging from cell-cycle control to lineage commitment. To exhaustively enumerate topologies that exhibit this switch-like behavior, we simulated all possible two- and three-component networks on random parameter sets, and assessed the resulting response profiles for both steepness (ultrasensitivity and extent of memory (bistability. Simulations were used to study purely enzymatic networks, purely transcriptional networks, and hybrid enzymatic/transcriptional networks, and the topologies in each class were rank ordered by parametric robustness (i.e., the percentage of applied parameter sets exhibiting ultrasensitivity or bistability. Results reveal that the distribution of network robustness is highly skewed, with the most robust topologies clustering into a small number of motifs. Hybrid networks are the most robust in generating ultrasensitivity (up to 28% and bistability (up to 18%; strikingly, a purely transcriptional framework is the most fragile in generating either ultrasensitive (up to 3% or bistable (up to 1% responses. The disparity in robustness among the network classes is due in part to zero-order ultrasensitivity, an enzyme-specific phenomenon, which repeatedly emerges as a particularly robust mechanism for generating nonlinearity and can act as a building block for switch-like responses. We also highlight experimentally studied examples of topologies enabling switching behavior, in both native and synthetic systems, that rank highly in our simulations. This unbiased approach for identifying topologies capable of a given response may be useful in discovering new natural motifs and in designing robust synthetic gene networks.

  4. Multi-Agent Flight Simulation with Robust Situation Generation

    Science.gov (United States)

    Johnson, Eric N.; Hansman, R. John, Jr.

    1994-01-01

    A robust situation generation architecture has been developed that generates multi-agent situations for human subjects. An implementation of this architecture was developed to support flight simulation tests of air transport cockpit systems. This system maneuvers pseudo-aircraft relative to the human subject's aircraft, generating specific situations for the subject to respond to. These pseudo-aircraft maneuver within reasonable performance constraints, interact in a realistic manner, and make pre-recorded voice radio communications. Use of this system minimizes the need for human experimenters to control the pseudo-agents and provides consistent interactions between the subject and the pseudo-agents. The achieved robustness of this system to typical variations in the subject's flight path was explored. It was found to successfully generate specific situations within the performance limitations of the subject-aircraft, pseudo-aircraft, and the script used.

  5. 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...

  6. 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.

  7. Generation of Oxtr cDNA(HA)-Ires-Cre Mice for Gene Expression in an Oxytocin Receptor Specific Manner.

    Science.gov (United States)

    Hidema, Shizu; Fukuda, Tomokazu; Hiraoka, Yuichi; Mizukami, Hiroaki; Hayashi, Ryotaro; Otsuka, Ayano; Suzuki, Shingo; Miyazaki, Shinji; Nishimori, Katsuhiko

    2016-05-01

    The neurohypophysial hormone oxytocin (OXT) and its receptor (OXTR) have critical roles in the regulation of pro-social behaviors, including social recognition, pair bonding, parental behavior, and stress-related responses. Supporting this hypothesis, a portion of patients suffering from autism spectrum disorder have mutations, such as single nucleotide polymorphisms, or epigenetic modifications in their OXTR gene. We previously reported that OXTR-deficient mice exhibit pervasive social deficits, indicating the critical role of OXTR in social behaviors. In the present study, we generated Oxtr cDNA(HA)-Ires-Cre knock-in mice, expressing both OXTR and Cre recombinase under the control of the endogenous Oxtr promoter. Knock-in cassette of Oxtr cDNA(HA)-Ires-Cre consisted of Oxtr cDNA tagged with the hemagglutinin epitope at the 3' end (Oxtr cDNA(HA)), internal ribosomal entry site (Ires), and Cre. Cre was expressed in the uterus, mammary gland, kidney, and brain of Oxtr cDNA(HA)-Ires-Cre knock-in mice. Furthermore, the distribution of Cre in the brain was similar to that observed in Oxtr-Venus fluorescent protein expressing mice (Oxtr-Venus), another animal model previously generated by our group. Social behavior of Oxtr cDNA(HA)-Ires-Cre knock-in mice was similar to that of wild-type animals. We demonstrated that this construct is expressed in OXTR-expressing neurons specifically after an infection with the recombinant adeno-associated virus carrying the flip-excision switch vector. Using this system, we showed the transport of the wheat-germ agglutinin tracing molecule from the OXTR-expressing neurons to the innervated neurons in knock-in mice. This study might contribute to the monosynaptic analysis of neuronal circuits and to the optogenetic analysis of neurons expressing OXTR.

  8. Microarray analysis of gene expression patterns of high lycopene tomato generated from seeds after long-term space flight

    Science.gov (United States)

    Lu, Jinying; Ren, Chunxiao; Pan, Yi; Nechitailo, Galina S.; Liu, Min

    Lycopene content is a most vital trait of tomatoes due to the role of lycopene in reducing the risk of some kinds of cancers. In this experiment, we gained a high lycopene (hl) tomato (named HY-2), after seven generations of self-cross selection, from seeds Russian MNP-1 carried in Russia MIR space station for six years. HPLC result showed that the lycopene content was 1.6 times more than that in Russian MNP-1 (the wild type). Microarray analysis presented the general profile of differential expressed genes at the tomato developmental stage of 7DPB (days post breaker). One hundred and forty three differential expression genes were identified according to the following criterion: the average changes were no less than 1.5 folds with q-value (similar to FDR) less than 0.05 or changes were no less than 1.5 folds in all three biological replications. Most of the differential expressed genes were mainly involved in metabolism, response to stimulus, biosynthesis, development and regulation. Particularly, we discussed the genes involved in protein metabolism, response to unfolded protein, carotenoid biosynthesis and photosynthesis that might be related to the fruit development and the accumulation of lycopene. What's more, we conducted QRT-PCR validation of five key genes (Fps, CrtL-b, CrtR-b, Zep and Nxs) in the lycopene biosynthesis pathway through time courses and that provided the direct molecular evidence for the hl phenotype. Our results demonstrate that long-term space flight, as a rarely used tool, can positively cause some beneficial mutations in the seeds and thus to help to generate a high quality variety, combined with ground selections.

  9. Robust Quantum Random Number Generator Based on Avalanche Photodiodes

    Science.gov (United States)

    Wang, Fang-Xiang; Wang, Chao; Chen, Wei; Wang, Shuang; Lv, Fu-Sheng; He, De-Yong; Yin, Zhen-Qiang; Li, Hong-Wei; Guo, Guang-Can; Han, Zheng-Fu

    2015-08-01

    We propose and demonstrate a scheme to realize a high-efficiency truly quantum random number generator (RNG) at room temperature (RT). Using an effective extractor with simple time bin encoding method, the avalanche pulses of avalanche photodiode (APD) are converted into high-quality random numbers (RNs) that are robust to slow varying noise such as fluctuations of pulse intensity and temperature. A light source is compatible but not necessary in this scheme. Therefor the robustness of the system is effective enhanced. The random bits generation rate of this proof-of-principle system is 0.69 Mbps with double APDs and 0.34 Mbps with single APD. The results indicate that a high-speed RNG chip based on the scheme is potentially available with an integrable APD array.

  10. Maternal high fat feeding and gestational dietary restriction: effects on offspring body weight, food intake and hypothalamic gene expression over three generations in mice.

    Science.gov (United States)

    Giraudo, Silvia Q; Della-Fera, Mary Anne; Proctor, Lindsey; Wickwire, Kathie; Ambati, Suresh; Baile, Clifton A

    2010-11-01

    Excessive gestational weight gain and maternal obesity have both been associated with increased incidence of obesity and metabolic disorder in offspring in both humans and animal models. The objectives of this study were to determine (1) whether mild gestational food restriction during the third trimester (GFR) would alter food intake and growth parameters of offspring, (2) whether effects of GFR depended on diet (high fat [HF] vs chow), (3) whether effects of excessive gestational weight gain (WG) would become magnified across generations, and (4) whether diet and GFR would alter hypothalamic gene expression in adult offspring. Three generations of female C57BL/6 mice were fed chow or HF diet, mated at 11 weeks of age and assigned to ad libitum feeding or 25% GFR. Offspring were fed the same diet as their mothers. Results showed (1) maternal gestational WG was positively correlated with offspring WG. (2) HF offspring weighed less (pfood restriction of obese mothers during pregnancy may have beneficial effects in reducing the risk or degree of obesity in offspring. Copyright © 2010 Elsevier Inc. All rights reserved.

  11. Robust Generation of Signed Distance Fields from Triangle Meshes

    DEFF Research Database (Denmark)

    Bærentzen, Jakob Andreas

    2005-01-01

    is then used to convert the binary volume into a distance field. The method is robust and handles holes, spurious triangles and ambiguities. Moreover, the method lends itself to Boolean operations between solids. Since a point cloud as well as a signed distance is generated, it is possible to extract an iso......-surface of the distance field and fit it to the point set. Using this method, one may recover sharp edge information. Examples are given where the method for generating distance fields coupled with mesh fitting is used to perform Boolean and morphological operations on triangle meshes....

  12. Monocyte derived dendritic cells generated by IFN-α acquire mature dendritic and natural killer cell properties as shown by gene expression analysis

    Directory of Open Access Journals (Sweden)

    Czibere Akos

    2007-09-01

    Full Text Available Abstract Background Dendritic cell (DC vaccines can induce antitumor immune responses in patients with malignant diseases, while the most suitable DC culture conditions have not been established yet. In this study we compared monocyte derived human DC from conventional cultures containing GM-CSF and IL-4/TNF-α (IL-4/TNF-DC with DC generated by the novel protocol using GM-CSF and IFN-α (IFN-DC. Methods To characterise the molecular differences of both DC preparations, gene expression profiling was performed using Affymetrix microarrays. The data were conformed on a protein level by immunophenotyping, and functional tests for T cell stimulation, migration and cytolytic activity were performed. Results Both methods resulted in CD11c+ CD86+ HLA-DR+ cells with a typical DC morphology that could efficiently stimulate T cells. But gene expression profiling revealed two distinct DC populations. Whereas IL-4/TNF-DC showed a higher expression of genes envolved in phagocytosis IFN-DC had higher RNA levels for markers of DC maturity and migration to the lymph nodes like DCLAMP, CCR7 and CD49d. This different orientation of both DC populations was confined by a 2.3 fold greater migration in transwell experiments (p = 0.01. Most interestingly, IFN-DC also showed higher RNA levels for markers of NK cells such as TRAIL, granzymes, KLRs and other NK cell receptors. On a protein level, intracytoplasmatic TRAIL and granzyme B were observed in 90% of IFN-DC. This translated into a cytolytic activity against K562 cells with a median specific lysis of 26% at high effector cell numbers as determined by propidium iodide uptake, whereas IL-4/TNF-DC did not induce any tumor cell lysis (p = 0.006. Thus, IFN-DC combined characteristics of mature DC and natural killer cells. Conclusion Our results suggest that IFN-DC not only stimulate adaptive but also mediate innate antitumor immune responses. Therefore, IFN-DC should be evaluated in clinical vaccination trials. In

  13. Identification of gene profiles of CD4~+ and CD8~+ T lymphocyte in systemic lupus erythematosus by generation of longer cDNA fragments from serial analysis of gene expression tags for gene identification

    Institute of Scientific and Technical Information of China (English)

    王惠琳

    2006-01-01

    Objective To identify LongSAGE Tags in systemic lupus erythematosus (SLE) by generation of longer cDNA fragments from serial analysis of gene expression (SAGE) tags for gene identification (GLGI). Methods CD4+ and CD8+ T lymphocytes were collected from the PBMCs of 25 patients with SLE and 10 healthy controls. Then the total RNA was extracted and reversely

  14. Robust Collimation Control of Laser-Generated Ion Beam

    CERN Document Server

    Kawata, S; Kamiyama, D; Nagashima, T; Barada, D; Gu, Y J; Li, X; Yu, Q; Kong, Q; Wang, P X

    2015-01-01

    The robustness of a structured collimation device is discussed for an intense-laser-produced ion beam. In this paper the ion beam collimation is realized by the solid structured collimation device, which produces the transverse electric field; the electric field contributes to reduce the ion beam transverse velocity and collimate the ion beam. Our 2.5 dimensional particle-in cell simulations demonstrate that the collimation device is rather robust against the changes in the laser parameters and the collimation target sizes. The intense short-pulse lasers are now available, and are used to generate an ion beam. The issues in the laser ion acceleration include an ion beam collimation, ion energy spectrum control, ion production efficiency, ion energy control, ion beam bunching, etc. The laser-produced ion beam tends to expand in the transverse and longitudinal directions during the ion beam propagation. The ion beam collimation is focused in this paper.

  15. Robust video watermarking scheme using computer generated holographic technique

    Science.gov (United States)

    Li, Jianzhong

    2013-06-01

    A novel blind video watermarking scheme offering a low computational complexity is presented in which the computer generated holograms are used as the watermarks. In the scheme, the original video is divided into nonoverlapping groups of pictures (GOPs). A quantization method is used to insert the mark hologram into the low frequency wavelet coefficients of every GOP. The extraction procedure does not need the original video. Experimental results demonstrate that the presented scheme is transparent and robust to a variety of attacks, including compression, noise addition, filtering, occlusion, cropping and temporal attacks, etc. One of the most important advantages of the suggested method is its simplicity and practicality.

  16. Transcriptional Profiling of Newly Generated Dentate Granule Cells Using TU Tagging Reveals Pattern Shifts in Gene Expression during Circuit Integration1,2

    Science.gov (United States)

    Chatzi, Christina; Shen, Rongkun; Goodman, Richard H.

    2016-01-01

    Abstract Despite representing only a small fraction of hippocampal granule cells, adult-generated newborn granule cells have been implicated in learning and memory (Aimone et al., 2011). Newborn granule cells undergo functional maturation and circuit integration over a period of weeks. However, it is difficult to assess the accompanying gene expression profiles in vivo with high spatial and temporal resolution using traditional methods. Here we used a novel method [“thiouracil (TU) tagging”] to map the profiles of nascent mRNAs in mouse immature newborn granule cells compared with mature granule cells. We targeted a nonmammalian uracil salvage enzyme, uracil phosphoribosyltransferase, to newborn neurons and mature granule cells using retroviral and lentiviral constructs, respectively. Subsequent injection of 4-TU tagged nascent RNAs for analysis by RNA sequencing. Several hundred genes were significantly enhanced in the retroviral dataset compared with the lentiviral dataset. We compared a selection of the enriched genes with steady-state levels of mRNAs using quantitative PCR. Ontology analysis revealed distinct patterns of nascent mRNA expression, with newly generated immature neurons showing enhanced expression for genes involved in synaptic function, and neural differentiation and development, as well as genes not previously associated with granule cell maturation. Surprisingly, the nascent mRNAs enriched in mature cells were related to energy homeostasis and metabolism, presumably indicative of the increased energy demands of synaptic transmission and their complex dendritic architecture. The high spatial and temporal resolution of our modified TU-tagging method provides a foundation for comparison with steady-state RNA analyses by traditional transcriptomic approaches in defining the functional roles of newborn neurons. PMID:27011954

  17. Toward robust AV conferencing on next-generation networks

    Science.gov (United States)

    Liu, Haining; Cheng, Liang; El Zarki, Magda

    2005-01-01

    In order to enable a truly pervasive computing environment, next generation networks (including B3G and 4G) will merge the broadband wireless and wireline networking infrastructure. However, due to the tremendous complexity in administration and the unreliability of the wireless channel, provision of hard-guarantees for services on such networks will not happen in the foreseeable future. This consequently makes it particularly challenging to offer viable AV conferencing services due to their stringent synchronization, delay and data fidelity requirements. We propose in this paper a robust application-level solution for wireless mobile AV conferencing on B3G/4G networks. Expecting no special treatment from the network, we apply a novel adaptive delay and synchronization control mechanism to maintain the synchronization and reduce the latency as much as possible. We also employ a robust video coding technique that has better error-resilience capability. We investigate the performance of the proposed solution through simulations using a three-state hidden Markov chain as the generic end-to-end transport channel model. The results show that our scheme yields tight synchronization performance, relatively low end-to-end latency and satisfactory presentation quality. The scheme successfully provides a fairly robust AV conferencing service.

  18. Reduce, reuse, recycle, for robust cluster state generation

    CERN Document Server

    Horsman, Clare; Munro, William J; Kendon, Vivien M

    2010-01-01

    Efficient generation of cluster states is crucial for engineering large-scale measurement-based quantum computers. Hybrid matter-optical systems offer a robust, scalable path to this goal. Such systems have an ancilla which acts as a bus connecting the qubits. We show that by generating smaller cluster "Lego blocks", reusing one ancilla per block, the cluster can be produced with maximal efficiency, requiring less than half the operations compared with no bus reuse. Our results are general for all ancilla-based computational schemes; we describe it in detail for the qubus system. By reducing the time required to prepare sections of the cluster, bus reuse more than doubles the size of the computational workspace that can be used before decoherence effects dominate.

  19. Identification of the MUC2 Promoter as a Strong Promoter for Intestinal Gene Expression through Generation of Transgenic Quail Expressing GFP in Gut Epithelial Cells

    Directory of Open Access Journals (Sweden)

    Rachel M. Woodfint

    2017-01-01

    Full Text Available Identification of tissue- and stage-specific gene promoters is valuable for delineating the functional roles of specific genes in genetically engineered animals. Here, through the comparison of gene expression in different tissues by analysis of a microarray database, the intestinal specificity of mucin 2 (MUC2 expression was identified in mice and humans, and further confirmed in chickens by RT-PCR (reverse transcription-PCR analysis. An analysis of cis-acting elements in avian MUC2 gene promoters revealed conservation of binding sites, within a 2.9 kb proximal promoter region, for transcription factors such as caudal type homeobox 2 (CDX2, GATA binding protein 4 (GATA4, hepatocyte nuclear factor 4 α (HNF4A, and transcription factor 4 (TCF4 that are important for maintaining intestinal homeostasis and functional integrity. By generating transgenic quail, we demonstrated that the 2.9 kb chicken MUC2 promoter could drive green fluorescent protein (GFP reporter expression exclusively in the small intestine, large intestine, and ceca. Fluorescence image analysis further revealed GFP expression in intestine epithelial cells. The GFP expression was barely detectable in the embryonic intestine, but increased during post-hatch development. The spatiotemporal expression pattern of the reporter gene confirmed that the 2.9 kb MUC2 promoter could retain the regulatory element to drive expression of target genes in intestinal tissues after hatching. This new transgene expression system, using the MUC2 promoter, will provide a new method of overexpressing target genes to study gene function in the avian intestine.

  20. Identification of the MUC2 Promoter as a Strong Promoter for Intestinal Gene Expression through Generation of Transgenic Quail Expressing GFP in Gut Epithelial Cells

    Science.gov (United States)

    Woodfint, Rachel M.; Chen, Paula R.; Ahn, Jinsoo; Suh, Yeunsu; Hwang, Seongsoo; Lee, Sang Suk; Lee, Kichoon

    2017-01-01

    Identification of tissue- and stage-specific gene promoters is valuable for delineating the functional roles of specific genes in genetically engineered animals. Here, through the comparison of gene expression in different tissues by analysis of a microarray database, the intestinal specificity of mucin 2 (MUC2) expression was identified in mice and humans, and further confirmed in chickens by RT-PCR (reverse transcription-PCR) analysis. An analysis of cis-acting elements in avian MUC2 gene promoters revealed conservation of binding sites, within a 2.9 kb proximal promoter region, for transcription factors such as caudal type homeobox 2 (CDX2), GATA binding protein 4 (GATA4), hepatocyte nuclear factor 4 α (HNF4A), and transcription factor 4 (TCF4) that are important for maintaining intestinal homeostasis and functional integrity. By generating transgenic quail, we demonstrated that the 2.9 kb chicken MUC2 promoter could drive green fluorescent protein (GFP) reporter expression exclusively in the small intestine, large intestine, and ceca. Fluorescence image analysis further revealed GFP expression in intestine epithelial cells. The GFP expression was barely detectable in the embryonic intestine, but increased during post-hatch development. The spatiotemporal expression pattern of the reporter gene confirmed that the 2.9 kb MUC2 promoter could retain the regulatory element to drive expression of target genes in intestinal tissues after hatching. This new transgene expression system, using the MUC2 promoter, will provide a new method of overexpressing target genes to study gene function in the avian intestine. PMID:28106824

  1. Ex vivo generated natural killer cells acquire typical natural killer receptors and display a cytotoxic gene expression profile similar to peripheral blood natural killer cells

    NARCIS (Netherlands)

    Lehmann, D.; Spanholtz, J.; Osl, M.; Tordoir, M.; Lipnik, K.; Bilban, M.; Schlechta, B.; Dolstra, H.; Hofer, E.

    2012-01-01

    Ex vivo differentiation systems of natural killer (NK) cells from CD34+ hematopoietic stem cells are of potential importance for adjuvant immunotherapy of cancer. Here, we analyzed ex vivo differentiation of NK cells from cord blood-derived CD34+ stem cells by gene expression profiling, real-time RT

  2. Ex vivo generated natural killer cells acquire typical natural killer receptors and display a cytotoxic gene expression profile similar to peripheral blood natural killer cells

    NARCIS (Netherlands)

    Lehmann, D.; Spanholtz, J.; Osl, M.; Tordoir, M.; Lipnik, K.; Bilban, M.; Schlechta, B.; Dolstra, H.; Hofer, E.

    2012-01-01

    Ex vivo differentiation systems of natural killer (NK) cells from CD34+ hematopoietic stem cells are of potential importance for adjuvant immunotherapy of cancer. Here, we analyzed ex vivo differentiation of NK cells from cord blood-derived CD34+ stem cells by gene expression profiling, real-time

  3. Robust Adaptive Reactive Power Control for Doubly Fed Induction Generator

    Directory of Open Access Journals (Sweden)

    Huabin Wen

    2014-01-01

    Full Text Available The problem of reactive power control for mains-side inverter (MSI in doubly fed induction generator (DFIG is studied in this paper. To accommodate the modelling nonlinearities and inherent uncertainties, a novel robust adaptive control algorithm for MSI is proposed by utilizing Lyapunov theory that ensures asymptotic stability of the system under unpredictable external disturbances and significant parametric uncertainties. The distinguishing benefit of the aforementioned scheme consists in its capabilities to maintain satisfactory performance under varying operation conditions without the need for manually redesigning or reprogramming the control gains in contrast to the commonly used PI/PID control. Simulations are also built to confirm the correctness and benefits of the control scheme.

  4. Robust Reservoir Generation by Correlation-Based Learning

    Directory of Open Access Journals (Sweden)

    Tadashi Yamazaki

    2009-01-01

    Full Text Available Reservoir computing (RC is a new framework for neural computation. A reservoir is usually a recurrent neural network with fixed random connections. In this article, we propose an RC model in which the connections in the reservoir are modifiable. Specifically, we consider correlation-based learning (CBL, which modifies the connection weight between a given pair of neurons according to the correlation in their activities. We demonstrate that CBL enables the reservoir to reproduce almost the same spatiotemporal activity patterns in response to an identical input stimulus in the presence of noise. This result suggests that CBL enhances the robustness in the generation of the spatiotemporal activity pattern against noise in input signals. We apply our RC model to trace eyeblink conditioning. The reservoir bridged the gap of an interstimulus interval between the conditioned and unconditioned stimuli, and a readout neuron was able to learn and express the timed conditioned response.

  5. Generation and classification of robust remote symmetric Dicke states

    Institute of Scientific and Technical Information of China (English)

    Zhu Yan-Wu; Gao Ke-Lin

    2008-01-01

    In this paper,we present an approach to generating arbitrary symmetric Dicke states with distant trapped ions and linear optics.Distant trapped ions can be prepared in the symmetric Dicke states by using two photon-number-resolving detectors and a polarization beam splitter.The atomic symmetric Dicke states are robust against decoherence,for atoms are in a metastable level.We discuss the experimental feasibility of our scheme with current technology.Finally,we discuss the classification of arbitrary n-qubit symmetric Dicke states under statistical local operation and classical communication and prove the existence of[n/2]inequivalent classes of genuine entanglement of n-qubit symmetric Dicke states.

  6. Next-generation text-mining mediated generation of chemical response-specific gene sets for interpretation of gene expression data

    NARCIS (Netherlands)

    Hettne, K.M.; Boorsma, A.; Dartel, van D.A.M.; Goeman, J.J.; Jong, de E.; Piersma, A.H.; Stierum, R.H.; Kleinjans, J.C.; Kors, J.A.

    2013-01-01

    Background: Availability of chemical response-specific lists of genes (gene sets) for pharmacological and/or toxic effect prediction for compounds is limited. We hypothesize that more gene sets can be created by next-generation text mining (next-gen TM), and that these can be used with gene set

  7. Next-generation text-mining mediated generation of chemical response-specific gene sets for interpretation of gene expression data

    NARCIS (Netherlands)

    K.M. Hettne (Kristina); J. Boorsma (Jeffrey); D.A.M. van Dartel (Dorien A M); J.J. Goeman (Jelle); E.C. de Jong (Esther); A.H. Piersma (Aldert); R.H. Stierum (Rob); J. Kleinjans (Jos); J.A. Kors (Jan)

    2013-01-01

    textabstractBackground: Availability of chemical response-specific lists of genes (gene sets) for pharmacological and/or toxic effect prediction for compounds is limited. We hypothesize that more gene sets can be created by next-generation text mining (next-gen TM), and that these can be used with

  8. Next-generation text-mining mediated generation of chemical response-specific gene sets for interpretation of gene expression data

    NARCIS (Netherlands)

    Hettne, K.M.; Boorsma, A.; Dartel, D.A. van; Goeman, J.J.; Jong, Esther de; Piersma, A.H.; Stierum, R.H.; Kleinjans, J.C.; Kors, J.A.

    2013-01-01

    BACKGROUND: Availability of chemical response-specific lists of genes (gene sets) for pharmacological and/or toxic effect prediction for compounds is limited. We hypothesize that more gene sets can be created by next-generation text mining (next-gen TM), and that these can be used with gene set

  9. Next-generation text-mining mediated generation of chemical response-specific gene sets for interpretation of gene expression data

    NARCIS (Netherlands)

    Hettne, K.M.; Boorsma, A.; Dartel, D.A. van; Goeman, J.J.; Jong, Esther de; Piersma, A.H.; Stierum, R.H.; Kleinjans, J.C.; Kors, J.A.

    2013-01-01

    BACKGROUND: Availability of chemical response-specific lists of genes (gene sets) for pharmacological and/or toxic effect prediction for compounds is limited. We hypothesize that more gene sets can be created by next-generation text mining (next-gen TM), and that these can be used with gene set anal

  10. Next-generation text-mining mediated generation of chemical response-specific gene sets for interpretation of gene expression data

    NARCIS (Netherlands)

    Hettne, K.M.; Boorsma, A.; Dartel, van D.A.M.; Goeman, J.J.; Jong, de E.; Piersma, A.H.; Stierum, R.H.; Kleinjans, J.C.; Kors, J.A.

    2013-01-01

    Background: Availability of chemical response-specific lists of genes (gene sets) for pharmacological and/or toxic effect prediction for compounds is limited. We hypothesize that more gene sets can be created by next-generation text mining (next-gen TM), and that these can be used with gene set anal

  11. Next-generation text-mining mediated generation of chemical response-specific gene sets for interpretation of gene expression data

    NARCIS (Netherlands)

    K.M. Hettne (Kristina); J. Boorsma (Jeffrey); D.A.M. van Dartel (Dorien A M); J.J. Goeman (Jelle); E.C. de Jong (Esther); A.H. Piersma (Aldert); R.H. Stierum (Rob); J. Kleinjans (Jos); J.A. Kors (Jan)

    2013-01-01

    textabstractBackground: Availability of chemical response-specific lists of genes (gene sets) for pharmacological and/or toxic effect prediction for compounds is limited. We hypothesize that more gene sets can be created by next-generation text mining (next-gen TM), and that these can be used with g

  12. Pax4 is not essential for beta-cell differentiation in zebrafish embryos but modulates alpha-cell generation by repressing arx gene expression.

    Science.gov (United States)

    Djiotsa, Joachim; Verbruggen, Vincianne; Giacomotto, Jean; Ishibashi, Minaka; Manning, Elisabeth; Rinkwitz, Silke; Manfroid, Isabelle; Voz, Marianne L; Peers, Bernard

    2012-12-17

    Genetic studies in mouse have demonstrated the crucial function of PAX4 in pancreatic cell differentiation. This transcription factor specifies β- and δ-cell fate at the expense of α-cell identity by repressing Arx gene expression and ectopic expression of PAX4 in α-cells is sufficient to convert them into β-cells. Surprisingly, no Pax4 orthologous gene can be found in chicken and Xenopus tropicalis raising the question of the function of pax4 gene in lower vertebrates such as in fish. In the present study, we have analyzed the expression and the function of the orthologous pax4 gene in zebrafish. pax4 gene is transiently expressed in the pancreas of zebrafish embryos and is mostly restricted to endocrine precursors as well as to some differentiating δ- and ε-cells but was not detected in differentiating β-cells. pax4 knock-down in zebrafish embryos caused a significant increase in α-cells number while having no apparent effect on β- and δ-cell differentiation. This rise of α-cells is due to an up-regulation of the Arx transcription factor. Conversely, knock-down of arx caused to a complete loss of α-cells and a concomitant increase of pax4 expression but had no effect on the number of β- and δ-cells. In addition to the mutual repression between Arx and Pax4, these two transcription factors negatively regulate the transcription of their own gene. Interestingly, disruption of pax4 RNA splicing or of arx RNA splicing by morpholinos targeting exon-intron junction sites caused a blockage of the altered transcripts in cell nuclei allowing an easy characterization of the arx- and pax4-deficient cells. Such analyses demonstrated that arx knock-down in zebrafish does not lead to a switch of cell fate, as reported in mouse, but rather blocks the cells in their differentiation process towards α-cells. In zebrafish, pax4 is not required for the generation of the first β- and δ-cells deriving from the dorsal pancreatic bud, unlike its crucial role in the

  13. 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

  14. 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.

  15. Next-generation text-mining mediated generation of chemical response-specific gene sets for interpretation of gene expression data

    Directory of Open Access Journals (Sweden)

    Hettne Kristina M

    2013-01-01

    Full Text Available Abstract Background Availability of chemical response-specific lists of genes (gene sets for pharmacological and/or toxic effect prediction for compounds is limited. We hypothesize that more gene sets can be created by next-generation text mining (next-gen TM, and that these can be used with gene set analysis (GSA methods for chemical treatment identification, for pharmacological mechanism elucidation, and for comparing compound toxicity profiles. Methods We created 30,211 chemical response-specific gene sets for human and mouse by next-gen TM, and derived 1,189 (human and 588 (mouse gene sets from the Comparative Toxicogenomics Database (CTD. We tested for significant differential expression (SDE (false discovery rate -corrected p-values Results Next-gen TM-derived gene sets matching the chemical treatment were significantly altered in three GE data sets, and the corresponding CTD-derived gene sets were significantly altered in five GE data sets. Six next-gen TM-derived and four CTD-derived fibrate gene sets were significantly altered in the PPARA knock-out GE dataset. None of the fibrate signatures in cMap scored significant against the PPARA GE signature. 33 environmental toxicant gene sets were significantly altered in the triazole GE data sets. 21 of these toxicants had a similar toxicity pattern as the triazoles. We confirmed embryotoxic effects, and discriminated triazoles from other chemicals. Conclusions Gene set analysis with next-gen TM-derived chemical response-specific gene sets is a scalable method for identifying similarities in gene responses to other chemicals, from which one may infer potential mode of action and/or toxic effect.

  16. 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.

  17. 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.

  18. 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...

  19. 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....

  20. 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...

  1. Next Generation Robust Low Noise Seismometer for Nuclear Monitoring

    Energy Technology Data Exchange (ETDEWEB)

    Abramovich, Igor A.

    2013-06-20

    Implementation of the proposed seismometers turned out to be much more challenging than anticipated. The noise levels achieved are indeed well below those ever featured by any electrochemical sensor and just very nearly miss reaching the original objectives. However, while noise-wise the instruments could still prove their usefulness, especially considering their robustness and no-maintenance operation, the implementation of the proposed noise-reduction concept resulted in much larger and heavier devices than originally expected. Moreover, these large dimensions relate only to single-component vertical sensors. While building similar horizontal component is possible, the resulting three-component instrument would be way too large and heavy to be of any practical use. The prototype instruments developed and built retained the inherent advantages of the electrochemical seismometers: no maintenance operation; ability to perform with large installation tilts; and, unfortunately, to a much lesser extent in terms of robustness.

  2. FANSe2: a robust and cost-efficient alignment tool for quantitative next-generation sequencing applications.

    Directory of Open Access Journals (Sweden)

    Chuan-Le Xiao

    Full Text Available Correct and bias-free interpretation of the deep sequencing data is inevitably dependent on the complete mapping of all mappable reads to the reference sequence, especially for quantitative RNA-seq applications. Seed-based algorithms are generally slow but robust, while Burrows-Wheeler Transform (BWT based algorithms are fast but less robust. To have both advantages, we developed an algorithm FANSe2 with iterative mapping strategy based on the statistics of real-world sequencing error distribution to substantially accelerate the mapping without compromising the accuracy. Its sensitivity and accuracy are higher than the BWT-based algorithms in the tests using both prokaryotic and eukaryotic sequencing datasets. The gene identification results of FANSe2 is experimentally validated, while the previous algorithms have false positives and false negatives. FANSe2 showed remarkably better consistency to the microarray than most other algorithms in terms of gene expression quantifications. We implemented a scalable and almost maintenance-free parallelization method that can utilize the computational power of multiple office computers, a novel feature not present in any other mainstream algorithm. With three normal office computers, we demonstrated that FANSe2 mapped an RNA-seq dataset generated from an entire Illunima HiSeq 2000 flowcell (8 lanes, 608 M reads to masked human genome within 4.1 hours with higher sensitivity than Bowtie/Bowtie2. FANSe2 thus provides robust accuracy, full indel sensitivity, fast speed, versatile compatibility and economical computational utilization, making it a useful and practical tool for deep sequencing applications. FANSe2 is freely available at http://bioinformatics.jnu.edu.cn/software/fanse2/.

  3. 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

  4. 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.

  5. Robust controller for synchronous generator with local load via VSC

    Energy Technology Data Exchange (ETDEWEB)

    Cabrera-Vazquez, J. [Universidad de Guadalajara, Centro Universitario de Ciencias Exactas e Ingenierias, Departamento de Electronica, Av. Revolucion No. 1500, Modulo ' ' O' ' , Apdo. Postal 44840, Guadalajara Jalisco (Mexico); Loukianov, Alexander G.; Canedo, Jose M. [Centro de Investigacion y de Estudios Avanzados del IPN, Apdo. Postal 31-438, Plaza La Luna, C. P. 44550, Guadalajara, Jalisco (Mexico); Utkin, Vadim I. [Department of Electrical Engineering, The Ohio-State University, Columbus, OH 43210-1272 (United States)

    2007-05-15

    The objective of this paper is to design a nonlinear observer-based excitation controller for power system comprising a single synchronous generator connected to an infinite bus with local load. The controller proposed is based on the using first singular perturbation systems concepts and then Sliding Mode Control technique combining with Block Control Principle. To reduce ''chattering'' a nonlinear observer with estimation of the mechanical torque and rotor fluxes is designed. This combined approach enables to compensate the inherent nonlinearities of the generator and to reject external disturbances. (author)

  6. Efficient, Robust and Constant-Round Distributed RSA Key Generation

    DEFF Research Database (Denmark)

    Damgård, Ivan Bjerre; Mikkelsen, Gert Læssøe

    2010-01-01

    We present the first protocol for distributed RSA key generation which is constant round, secure against malicious adversaries and has a negligibly small bound on the error probability, even using only one iteration of the underlying primality test on each candidate number.......We present the first protocol for distributed RSA key generation which is constant round, secure against malicious adversaries and has a negligibly small bound on the error probability, even using only one iteration of the underlying primality test on each candidate number....

  7. Smooth Muscle-Like Cells Generated from Human Mesenchymal Stromal Cells Display Marker Gene Expression and Electrophysiological Competence Comparable to Bladder Smooth Muscle Cells.

    Directory of Open Access Journals (Sweden)

    Juliane Brun

    Full Text Available The use of mesenchymal stromal cells (MSCs differentiated toward a smooth muscle cell (SMC phenotype may provide an alternative for investigators interested in regenerating urinary tract organs such as the bladder where autologous smooth muscle cells cannot be used or are unavailable. In this study we measured the effects of good manufacturing practice (GMP-compliant expansion followed by myogenic differentiation of human MSCs on the expression of a range of contractile (from early to late myogenic markers in relation to the electrophysiological parameters to assess the functional role of the differentiated MSCs and found that differentiation of MSCs associated with electrophysiological competence comparable to bladder SMCs. Within 1-2 weeks of myogenic differentiation, differentiating MSCs significantly expressed alpha smooth muscle actin (αSMA; ACTA2, transgelin (TAGLN, calponin (CNN1, and smooth muscle myosin heavy chain (SM-MHC; MYH11 according to qRT-PCR and/or immunofluorescence and Western blot. Voltage-gated Na+ current levels also increased within the same time period following myogenic differentiation. In contrast to undifferentiated MSCs, differentiated MSCs and bladder SMCs exhibited elevated cytosolic Ca2+ transients in response to K+-induced depolarization and contracted in response to K+ indicating functional maturation of differentiated MSCs. Depolarization was suppressed by Cd2+, an inhibitor of voltage-gated Ca2+-channels. The expression of Na+-channels was pharmacologically identified as the Nav1.4 subtype, while the K+ and Ca2+ ion channels were identified by gene expression of KCNMA1, CACNA1C and CACNA1H which encode for the large conductance Ca2+-activated K+ channel BKCa channels, Cav1.2 L-type Ca2+ channels and Cav3.2 T-type Ca2+ channels, respectively. This protocol may be used to differentiate adult MSCs into smooth muscle-like cells with an intermediate-to-late SMC contractile phenotype exhibiting voltage-gated ion

  8. Smooth Muscle-Like Cells Generated from Human Mesenchymal Stromal Cells Display Marker Gene Expression and Electrophysiological Competence Comparable to Bladder Smooth Muscle Cells

    Science.gov (United States)

    Brun, Juliane; Lutz, Katrin A.; Neumayer, Katharina M. H.; Klein, Gerd; Seeger, Tanja; Uynuk-Ool, Tatiana; Wörgötter, Katharina; Schmid, Sandra; Kraushaar, Udo; Guenther, Elke; Rolauffs, Bernd; Aicher, Wilhelm K.; Hart, Melanie L.

    2015-01-01

    The use of mesenchymal stromal cells (MSCs) differentiated toward a smooth muscle cell (SMC) phenotype may provide an alternative for investigators interested in regenerating urinary tract organs such as the bladder where autologous smooth muscle cells cannot be used or are unavailable. In this study we measured the effects of good manufacturing practice (GMP)-compliant expansion followed by myogenic differentiation of human MSCs on the expression of a range of contractile (from early to late) myogenic markers in relation to the electrophysiological parameters to assess the functional role of the differentiated MSCs and found that differentiation of MSCs associated with electrophysiological competence comparable to bladder SMCs. Within 1–2 weeks of myogenic differentiation, differentiating MSCs significantly expressed alpha smooth muscle actin (αSMA; ACTA2), transgelin (TAGLN), calponin (CNN1), and smooth muscle myosin heavy chain (SM-MHC; MYH11) according to qRT-PCR and/or immunofluorescence and Western blot. Voltage-gated Na+ current levels also increased within the same time period following myogenic differentiation. In contrast to undifferentiated MSCs, differentiated MSCs and bladder SMCs exhibited elevated cytosolic Ca2+ transients in response to K+-induced depolarization and contracted in response to K+ indicating functional maturation of differentiated MSCs. Depolarization was suppressed by Cd2+, an inhibitor of voltage-gated Ca2+-channels. The expression of Na+-channels was pharmacologically identified as the Nav1.4 subtype, while the K+ and Ca2+ ion channels were identified by gene expression of KCNMA1, CACNA1C and CACNA1H which encode for the large conductance Ca2+-activated K+ channel BKCa channels, Cav1.2 L-type Ca2+ channels and Cav3.2 T-type Ca2+ channels, respectively. This protocol may be used to differentiate adult MSCs into smooth muscle-like cells with an intermediate-to-late SMC contractile phenotype exhibiting voltage-gated ion channel

  9. In vitro levamisole selection pressure on larval stages of Haemonchus contortus over nine generations gives rise to drug resistance and target site gene expression changes specific to the early larval stages only.

    Science.gov (United States)

    Sarai, Ranbir S; Kopp, Steven R; Knox, Malcolm R; Coleman, Glen T; Kotze, Andrew C

    2015-06-30

    There is some evidence that resistance to levamisole and pyrantel in trichostrongylid nematodes is due to changes in the composition of nicotinic acetylcholine receptors (nAChRs) which represent the drug target site. Altered expression patterns of genes coding for nAChR subunits, as well as the presence of truncated versions of several subunits, have been implicated in observed resistances. The studies have mostly compared target sites in worm isolates of very different genetic background, and hence the ability to associate the molecular changes with drug sensitivity alone have been clouded to some extent. The present study aimed to circumvent this issue by following target site gene expression pattern changes as resistance developed in Haemonchus contortus worms under laboratory selection pressure with levamisole. We applied drug selection pressure to early stage larvae in vitro over nine generations, and monitored changes in larval and adult drug sensitivities and target site gene expression patterns. High level resistance developed in larvae, with resistance factors of 94-fold and 1350-fold at the IC50 and IC95, respectively, in larval development assays after nine generations of selection. There was some cross-resistance to bephenium (70-fold increase in IC95). The expression of all the putative subunit components of levamisole-sensitive nAChRs, as well as a number of ancillary protein genes, particularly Hco-unc-29.1 and -ric-3, were significantly decreased (up to 5.5-fold) in the resistant larvae at generation nine compared to the starting population. However, adult worms did not show any resistance to levamisole, and showed an inverse pattern of gene expression changes, with many target site genes showing increased expression compared to the starting population. A comparison of the larval/adult drug sensitivity data with the known relationships for field-derived isolates indicated that the adults of our selected population should have been highly resistant

  10. 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

    The increased availability and use of DNA microarrays has allowed the characterization of gene expression patterns associated with different toxicants. An important question is whether toxicant induced changes in gene expression in fish are sufficiently diverse to allow for identification of specific modes of action and/or specific contaminants. In theory, each class of toxicant may generate a gene expression profile unique to its mode of toxic action. We exposed isogenic (cloned) rainbow trout Oncorhyncus mykiss, to sublethal levels of a series of model toxicants with varying modes of action, including ethynylestradiol (xeno-estrogen), trenbolone (anabolic steroid; model androgen), 2,2,4,4´tetrabromodiphenyl ether (BDE-47, thyroid active), diquat (oxidant stressor), chromium VI, and benzo[a]pyrene (BaP) for a period of 1-3 weeks. Following exposure, fish were euthanized, livers harvested and RNA extracted. Fluorescently labeled cDNA were generated and hybridized against a commercially available Atlantic Salmon / Trout array (GRASP project, University of Victoria) spotted with 16,000 cDNA’s. The slides were scanned to measure abundance of a given transcript in each sample relative to controls. Data were analyzed via Genespring (Silicon Genetics) to identify a list of up and down regulated genes, as well as to determine gene clustering patterns that can be used as “expression signatures”. Our analysis indicates each toxicant generated specific gene expression profiles. Most genes exhibiting altered expression responded to only one of the toxicants. Relatively few genes are co-expressed in multiple treatments. For example, BaP and Diquat, both of which exert toxicity via oxidative stress, up-regulated 28 of the same genes, of over 100 genes altered by ether treatment. Other genes associated with steroidogenesis, p450 and estrogen responsive genes appear to be useful for selectively identifying toxicant mode of in fish, suggesting a link between gene expression

  11. Lyapunov function gradient generated robust control in the absence of the nominal stabilizing control

    Science.gov (United States)

    Blackwell, C. C.

    1987-01-01

    A relevant facet of the application of Lyapunov gradient-generated robust control to unstable linear autonomous plants is explored. It is demonstrated that if the plant, the output, and the nominal stabilizing control satisfy certain conditions, then the robust component alone stabilizes the nominal plant. An example characterized by two zero eigenvalues and two negative real value poles is presented. These results assure that the robust component will fulfill the role of nominal stabilization successfully so long as the possible magnitude of the robust component can overcome the contribution of the instability to positiveness of the Lyapunov rate.

  12. Lyapunov function gradient generated robust control in the absence of the nominal stabilizing control

    Science.gov (United States)

    Blackwell, C. C.

    1987-01-01

    A relevant facet of the application of Lyapunov gradient-generated robust control to unstable linear autonomous plants is explored. It is demonstrated that if the plant, the output, and the nominal stabilizing control satisfy certain conditions, then the robust component alone stabilizes the nominal plant. An example characterized by two zero eigenvalues and two negative real value poles is presented. These results assure that the robust component will fulfill the role of nominal stabilization successfully so long as the possible magnitude of the robust component can overcome the contribution of the instability to positiveness of the Lyapunov rate.

  13. Regularization strategies for hyperplane classifiers: application to cancer classification with gene expression data.

    Science.gov (United States)

    Andries, Erik; Hagstrom, Thomas; Atlas, Susan R; Willman, Cheryl

    2007-02-01

    Linear discrimination, from the point of view of numerical linear algebra, can be treated as solving an ill-posed system of linear equations. In order to generate a solution that is robust in the presence of noise, these problems require regularization. Here, we examine the ill-posedness involved in the linear discrimination of cancer gene expression data with respect to outcome and tumor subclasses. We show that a filter factor representation, based upon Singular Value Decomposition, yields insight into the numerical ill-posedness of the hyperplane-based separation when applied to gene expression data. We also show that this representation yields useful diagnostic tools for guiding the selection of classifier parameters, thus leading to improved performance.

  14. 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...

  15. Robust infrared target tracking using discriminative and generative approaches

    Science.gov (United States)

    Asha, C. S.; Narasimhadhan, A. V.

    2017-09-01

    The process of designing an efficient tracker for thermal infrared imagery is one of the most challenging tasks in computer vision. Although a lot of advancement has been achieved in RGB videos over the decades, textureless and colorless properties of objects in thermal imagery pose hard constraints in the design of an efficient tracker. Tracking of an object using a single feature or a technique often fails to achieve greater accuracy. Here, we propose an effective method to track an object in infrared imagery based on a combination of discriminative and generative approaches. The discriminative technique makes use of two complementary methods such as kernelized correlation filter with spatial feature and AdaBoost classifier with pixel intesity features to operate in parallel. After obtaining optimized locations through discriminative approaches, the generative technique is applied to determine the best target location using a linear search method. Unlike the baseline algorithms, the proposed method estimates the scale of the target by Lucas-Kanade homography estimation. To evaluate the proposed method, extensive experiments are conducted on 17 challenging infrared image sequences obtained from LTIR dataset and a significant improvement of mean distance precision and mean overlap precision is accomplished as compared with the existing trackers. Further, a quantitative and qualitative assessment of the proposed approach with the state-of-the-art trackers is illustrated to clearly demonstrate an overall increase in performance.

  16. Efficient and Robust Two-Party RSA Key Generation

    Institute of Scientific and Technical Information of China (English)

    YANG Muxiang; HONG Fan; ZHENG Minghui; LI Jun

    2006-01-01

    An efficient two party RSA secret key sharing generation scheme based on a homomorphic encryption, which is semantically secure under the prime residuosity assumption, is proposed in this paper. At the stage of computing RSA modulo N, an initial distributed primality test protocol is used to reduce the computation complexity and increase the probability of N being a two-prime product. On the other aspect, the homomorphic encryption based sharing conversion protocols is devised and adopted in multi-party computing modulus N and secret key d. Comparing to any sharing conversion protocols based on oblivious transfer protocol, the homomorphic encryption based sharing conversion protocols are of high performance. Our scheme resists the passive attack and since a method of verifying the sharing was introduced in, the scheme can resists any cheating behaviors too. Security proof, computation complexity and communication complexity analysis are given at last.

  17. 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

    through stress response processes known as adaptive resistance. Adaptive resistance fosters transient tolerance increases and the emergence of mutations conferring heritable drug resistance. In order to extend the applicable lifetime of new antibiotics, we must seek to hinder the occurrence of bacterial adaptive resistance; however, the regulation of adaptation is difficult to identify due to immense heterogeneity emerging during evolution. This study specifically seeks to generate heterogeneity by adapting bacteria to different stresses and then examines gene expression trends across the disparate populations in order to pinpoint key genes and pathways associated with adaptive resistance. The targets identified here may eventually inform strategies for impeding adaptive resistance and prolonging the effectiveness of antibiotic treatment. PMID:28217741

  18. Effects on circulating steroid hormones and gene expression along the hypothalamus–pituitary–gonadal axis in adult Japanese quail exposed to 17β-trenbolone across multiple generations

    Science.gov (United States)

    Karouna, Natalie; Chen, Yu; Henry, Paula F.; Maddox, Catherine M.; Sprague, Dan

    2017-01-01

    We investigated the effects of the androgenic growth promoter 17β-trenbolone (17βTB) on adult Japanese quail (Coturnix japonica) exposed across three generations. The F0 generation was exposed after sexual maturity to 0, 1, 5, 10, 20, and 40 ppm through feed. The F1 generation was exposed in ovo by maternal transfer and through feed at the same doses as their parents. The F2 generation was exposed in ovo only. Levels of plasma sex steroids, gonadal Cytochrome P450 aromatase (CYP19A1) mRNA and select brain neuroendocrine peptide mRNAs were measured. In males, testosterone levels did not differ in any generation from those in controls. Estradiol was significantly elevated in 17βTB treated F0 and F1 males. In F0 and F1 females, testosterone was suppressed by 17βTB, whereas estradiol was significantly higher at 40 ppm in F0 and at 10 ppm in F1 females. CYP19A1 expression in F1 males and females increased suggesting a compensatory response to the androgenic effects of 17βTB. Few significant effects were observed in the F2 birds indicating that in ovo exposure had limited effects on the monitored endpoints. Overall, our results confirmed endocrine disrupting effects of dietary 17βTB in Japanese quail but the response was dependent on sex, developmental stage at initiation of exposure, and dose.

  19. 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.

  20. 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.

  1. 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...

  2. 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

  3. First study on gene expression of cement proteins and potential adhesion-related genes of a membranous-based barnacle as revealed from Next-Generation Sequencing technology

    KAUST Repository

    Lin, Hsiu Chin

    2013-12-12

    This is the first study applying Next-Generation Sequencing (NGS) technology to survey the kinds, expression location, and pattern of adhesion-related genes in a membranous-based barnacle. A total of 77,528,326 and 59,244,468 raw sequence reads of total RNA were generated from the prosoma and the basis of Tetraclita japonica formosana, respectively. In addition, 55,441 and 67,774 genes were further assembled and analyzed. The combined sequence data from both body parts generates a total of 79,833 genes of which 47.7% were shared. Homologues of barnacle cement proteins - CP-19K, -52K, and -100K - were found and all were dominantly expressed at the basis where the cement gland complex is located. This is the main area where transcripts of cement proteins and other potential adhesion-related genes were detected. The absence of another common barnacle cement protein, CP-20K, in the adult transcriptome suggested a possible life-stage restricted gene function and/or a different mechanism in adhesion between membranous-based and calcareous-based barnacles. © 2013 © 2013 Taylor & Francis.

  4. 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.

  5. 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...

  6. A modular lentiviral and retroviral construction system to rapidly generate vectors for gene expression and gene knockdown in vitro and in vivo.

    Science.gov (United States)

    Geiling, Benjamin; Vandal, Guillaume; Posner, Ada R; de Bruyns, Angeline; Dutchak, Kendall L; Garnett, Samantha; Dankort, David

    2013-01-01

    The ability to express exogenous cDNAs while suppressing endogenous genes via RNAi represents an extremely powerful research tool with the most efficient non-transient approach being accomplished through stable viral vector integration. Unfortunately, since traditional restriction enzyme based methods for constructing such vectors are sequence dependent, their construction is often difficult and not amenable to mass production. Here we describe a non-sequence dependent Gateway recombination cloning system for the rapid production of novel lentiviral (pLEG) and retroviral (pREG) vectors. Using this system to recombine 3 or 4 modular plasmid components it is possible to generate viral vectors expressing cDNAs with or without inhibitory RNAs (shRNAmirs). In addition, we demonstrate a method to rapidly produce and triage novel shRNAmirs for use with this system. Once strong candidate shRNAmirs have been identified they may be linked together in tandem to knockdown expression of multiple targets simultaneously or to improve the knockdown of a single target. Here we demonstrate that these recombinant vectors are able to express cDNA and effectively knockdown protein expression using both cell culture and animal model systems.

  7. 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.

  8. 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

  9. 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.

  10. 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.

  11. Aberrant Behaviours of Reaction Diffusion Self-organisation Models on Growing Domains in the Presence of Gene Expression Time Delays

    KAUST Repository

    Seirin Lee, S.

    2010-03-23

    Turing\\'s pattern formation mechanism exhibits sensitivity to the details of the initial conditions suggesting that, in isolation, it cannot robustly generate pattern within noisy biological environments. Nonetheless, secondary aspects of developmental self-organisation, such as a growing domain, have been shown to ameliorate this aberrant model behaviour. Furthermore, while in-situ hybridisation reveals the presence of gene expression in developmental processes, the influence of such dynamics on Turing\\'s model has received limited attention. Here, we novelly focus on the Gierer-Meinhardt reaction diffusion system considering delays due the time taken for gene expression, while incorporating a number of different domain growth profiles to further explore the influence and interplay of domain growth and gene expression on Turing\\'s mechanism. We find extensive pathological model behaviour, exhibiting one or more of the following: temporal oscillations with no spatial structure, a failure of the Turing instability and an extreme sensitivity to the initial conditions, the growth profile and the duration of gene expression. This deviant behaviour is even more severe than observed in previous studies of Schnakenberg kinetics on exponentially growing domains in the presence of gene expression (Gaffney and Monk in Bull. Math. Biol. 68:99-130, 2006). Our results emphasise that gene expression dynamics induce unrealistic behaviour in Turing\\'s model for multiple choices of kinetics and thus such aberrant modelling predictions are likely to be generic. They also highlight that domain growth can no longer ameliorate the excessive sensitivity of Turing\\'s mechanism in the presence of gene expression time delays. The above, extensive, pathologies suggest that, in the presence of gene expression, Turing\\'s mechanism would generally require a novel and extensive secondary mechanism to control reaction diffusion patterning. © 2010 Society for Mathematical Biology.

  12. Fault-tolerant Algorithms for Tick-Generation in Asynchronous Logic: Robust Pulse Generation

    CERN Document Server

    Dolev, Danny; Lenzen, Christoph; Schmid, Ulrich

    2011-01-01

    Today's hardware technology presents a new challenge in designing robust systems. Deep submicron VLSI technology introduced transient and permanent faults that were never considered in low-level system designs in the past. Still, robustness of that part of the system is crucial and needs to be guaranteed for any successful product. Distributed systems, on the other hand, have been dealing with similar issues for decades. However, neither the basic abstractions nor the complexity of contemporary fault-tolerant distributed algorithms match the peculiarities of hardware implementations. This paper is intended to be part of an attempt striving to overcome this gap between theory and practice for the clock synchronization problem. Solving this task sufficiently well will allow to build a very robust high-precision clocking system for hardware designs like systems-on-chips in critical applications. As our first building block, we describe and prove correct a novel Byzantine fault-tolerant self-stabilizing pulse syn...

  13. Performance of a grid-connected wind generation system with a robust susceptance controller

    Energy Technology Data Exchange (ETDEWEB)

    Rahim, A.H.M.A. [Department of Electrical Engineering, K.F. University of Petroleum and Minerals, KFUPM Box 349, Dhahran 31261 (Saudi Arabia); Nowicki, E.P. [Department of Electrical and Computer Engineering, University of Calgary, Calgary, AB (Canada)

    2011-01-15

    Wind turbine driven induction generators are vulnerable to transient disturbances like wind gusts and low voltages on the system. The fixed capacitor at the generator terminal or the limited support from the grid may not be able to provide the requisite reactive power under these abnormal conditions. This paper presents a susceptance control strategy for a variable speed wound-rotor induction generator which can cater for the reactive power requirement. The susceptance is adjusted through a robust feedback controller included in the terminal voltage driven automatic excitation control circuit. The fixed parameter robust controller design is carried out in frequency domain using multiplicative uncertainty modeling and H{sub {infinity}} norms. The robustness of the controller has been evaluated through optimally tuned PID controllers. Simulation results show that the robust controller can effectively restore normal operation following emergencies like sudden load changes, wind gusts and low voltage conditions. The proposed robust controller has been shown to have adequate fault ride through capabilities in order to be able to meet connection requirements defined by transmission system operators. (author)

  14. Coding and Noncoding Gene Expression Biomarkers in Mood Disorders and Schizophrenia

    Directory of Open Access Journals (Sweden)

    Firoza Mamdani

    2013-01-01

    Full Text Available Mood disorders and schizophrenia are common and complex disorders with consistent evidence of genetic and environmental influences on predisposition. It is generally believed that the consequences of disease, gene expression, and allelic heterogeneity may be partly the explanation for the variability observed in treatment response. Correspondingly, while effective treatments are available for some patients, approximately half of the patients fail to respond to current neuropsychiatric treatments. A number of peripheral gene expression studies have been conducted to understand these brain-based disorders and mechanisms of treatment response with the aim of identifying suitable biomarkers and perhaps subgroups of patients based upon molecular fingerprint. In this review, we summarize the results from blood-derived gene expression studies implemented with the aim of discovering biomarkers for treatment response and classification of disorders. We include data from a biomarker study conducted in first-episode subjects with schizophrenia, where the results provide insight into possible individual biological differences that predict antipsychotic response. It is concluded that, while peripheral studies of expression are generating valuable results in pathways involving immune regulation and response, larger studies are required which hopefully will lead to robust biomarkers for treatment response and perhaps underlying variations relevant to these complex disorders.

  15. 奶牛乳腺上皮细胞不同代数对乳蛋白基因表达的影响%Different Generations of Bovine Mammary Epithelial Cells Impacting on Gene Expression of Milk Protein

    Institute of Scientific and Technical Information of China (English)

    韩亚南; 侯先志; 考桂兰; 王秀美; 杨金丽; 高爱武; 杨银芬; 赵青; 高民

    2012-01-01

    The aim of this study was to research milk protein gene expression—αsl-casein, β-casein, κ-casein of lactating bovine mammary epithelial cells between different generations; Using the real—time PCR method to detect milk protein gene expression of lactating bovine mammary tissue, the cells of primary generation (P0) derived from the bovine mammary tissue, the first generation (Pi), the second generation (P2), the third generation (P3), the fourth generation (P4) and the fifth generation (P3); The results showed that expression of three target-genes was at different levels between the cells of primary generation and passages. The expression in the primary cells was significantly higher than P1-P5 cells (P<0.05). Whereas P1-P5 cells had no significant difference (P>0.05). Moreover, from Po to P5, the expression of αsl-casein, β-casein, K-casein was gradually decreasing. So, P2-P5 BMECs could be used as a trial material.%为了研究泌乳期奶牛乳腺上皮细胞(bovine mammary epithelial cells,BMECs)不同代数乳蛋白基因αs1-casein,β-casein,κ-casein的表达.利用real-time PCR方法分别对泌乳期奶牛乳腺组织,以及由乳腺组织分离得到的细胞原代(P0),1代(P1),2代(P2),3代(P3),4代(P4),5代(P5)中的乳蛋白基因表达状况进行检测.结果表明:αs1-casein,β-casein,κ-casein在泌乳期奶牛乳腺上皮细胞原代及传代细胞中有不同程度的表达.其中,原代中的表达量显著高于P1~P5(P<0.05),而P1~P5之间的表达量无显著差异(P>0.05).并且随着传代次数的增加,基因表达量呈现逐渐下降的趋势.说明P2~P5 BMECs可以作为基础理论问题研究的试验材料而被应用.

  16. IQC-based robust stability analysis for LPV control of doubly-fed induction generators

    NARCIS (Netherlands)

    Tien, H. N.; Scherer, C. W.; Scherpen, J. M. A.

    2008-01-01

    Parameters of electrical machines are usually varying with time in a smooth way due to changing operating conditions, such as variations in the machine temperature and/or the magnetic saturation. This paper is concerned with robust stability analysis of controlled Doubly-Fed Induction Generators (DF

  17. Energy efficient and robust rhythmic limb movement by central pattern generators

    NARCIS (Netherlands)

    Verdaasdonk, B.W.; Koopman, H.F.J.M.; Helm, van der F.C.T.

    2006-01-01

    Humans show great energy efficiency and robustness in rhythmic tasks, such as walking and arm swinging. In this study a mathematical model of rhythmic limb movement is presented, which shows that tight local coupling of Central Pattern Generators (CPGs) to limbs could explain part of this behavior.

  18. 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.

  19. 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.

  20. Microfluidic geometric metering-based multi-reagent mixture generator for robust live cell screening array.

    Science.gov (United States)

    Wang, Han; Kim, Jeongyun; Jayaraman, Arul; Han, Arum

    2014-12-01

    Microfluidic live cell arrays with integrated concentration gradient or mixture generators have been utilized in screening cellular responses to various biomolecular cues. Microfluidic network-based gradient generators that can create concentration gradients by repeatedly splitting and mixing different solutions using networks of serpentine channels are commonly used. However, in this method the generation of concentration gradients relies on the continuous flow of sample solutions at optimized flow rates, which poses challenges in maintaining the pressure and flow stability throughout the entire assay period. Here we present a microfluidic live cell screening array with an on-demand multi-reagent mixture generator where the mixing ratios, thus generated concentrations, are hard-wired into the chip itself through a geometric metering method. This platform showed significantly improved robustness and repeatability in generating concentration gradients of fluorescent dyes (average coefficient of variance C.V. = 9 %) compared to the conventional network-based gradient generators (average C.V. = 21 %). In studying the concentration dependent effects of the environmental toxicant 3-methylcholanthrene (3MC) on the activation of cytochrome P450 1A1 (Cyp 1A1) enzyme in H4IIE rat hepatoma cells, statistical variation of the Cyp 1A1 response was significantly lower (C.V. = 5 %) when using the developed mixture generator compared to that using the conventional gradient generator (C.V. = 12 %). Reduction in reagent consumption by 12-times was also achieved. This robust, accurate, and scalable multi-reagent mixture generator integrated with a cell culture array as a live cell assay platform can be readily implemented into various screening applications where repeatability, robustness, and low reagent consumptions over long periods of assay time are of importance.

  1. 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...

  2. 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...

  3. 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.

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

    Directory of Open Access Journals (Sweden)

    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.

  5. 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.

  6. Dual-loop self-optimizing robust control of wind power generation with Doubly-Fed Induction Generator.

    Science.gov (United States)

    Chen, Quan; Li, Yaoyu; Seem, John E

    2015-09-01

    This paper presents a self-optimizing robust control scheme that can maximize the power generation for a variable speed wind turbine with Doubly-Fed Induction Generator (DFIG) operated in Region 2. A dual-loop control structure is proposed to synergize the conversion from aerodynamic power to rotor power and the conversion from rotor power to the electrical power. The outer loop is an Extremum Seeking Control (ESC) based generator torque regulation via the electric power feedback. The ESC can search for the optimal generator torque constant to maximize the rotor power without wind measurement or accurate knowledge of power map. The inner loop is a vector-control based scheme that can both regulate the generator torque requested by the ESC and also maximize the conversion from the rotor power to grid power. An ℋ(∞) controller is synthesized for maximizing, with performance specifications defined based upon the spectrum of the rotor power obtained by the ESC. Also, the controller is designed to be robust against the variations of some generator parameters. The proposed control strategy is validated via simulation study based on the synergy of several software packages including the TurbSim and FAST developed by NREL, Simulink and SimPowerSystems. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.

  7. 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

  8. 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.

  9. Robust quantum entanglement generation and generation-plus-storage protocols with spin chains

    Science.gov (United States)

    Estarellas, Marta P.; D'Amico, Irene; Spiller, Timothy P.

    2017-04-01

    Reliable quantum communication and/or processing links between modules are a necessary building block for various quantum processing architectures. Here we consider a spin-chain system with alternating strength couplings and containing three defects, which impose three domain walls between topologically distinct regions of the chain. We show that—in addition to its useful, high-fidelity, quantum state transfer properties—an entangling protocol can be implemented in this system, with optional localization and storage of the entangled states. We demonstrate both numerically and analytically that, given a suitable initial product-state injection, the natural dynamics of the system produces a maximally entangled state at a given time. We present detailed investigations of the effects of fabrication errors, analyzing random static disorder both in the diagonal and off-diagonal terms of the system Hamiltonian. Our results show that the entangled state formation is very robust against perturbations of up to ˜10 % the weaker chain coupling, and also robust against timing injection errors. We propose a further protocol, which manipulates the chain in order to localize and store each of the entangled qubits. The engineering of a system with such characteristics would thus provide a useful device for quantum information processing tasks involving the creation and storage of entangled resources.

  10. NetworkAnalyst for statistical, visual and network-based meta-analysis of gene expression data.

    Science.gov (United States)

    Xia, Jianguo; Gill, Erin E; Hancock, Robert E W

    2015-06-01

    Meta-analysis of gene expression data sets is increasingly performed to help identify robust molecular signatures and to gain insights into underlying biological processes. The complicated nature of such analyses requires both advanced statistics and innovative visualization strategies to support efficient data comparison, interpretation and hypothesis generation. NetworkAnalyst (http://www.networkanalyst.ca) is a comprehensive web-based tool designed to allow bench researchers to perform various common and complex meta-analyses of gene expression data via an intuitive web interface. By coupling well-established statistical procedures with state-of-the-art data visualization techniques, NetworkAnalyst allows researchers to easily navigate large complex gene expression data sets to determine important features, patterns, functions and connections, thus leading to the generation of new biological hypotheses. This protocol provides a step-wise description of how to effectively use NetworkAnalyst to perform network analysis and visualization from gene lists; to perform meta-analysis on gene expression data while taking into account multiple metadata parameters; and, finally, to perform a meta-analysis of multiple gene expression data sets. NetworkAnalyst is designed to be accessible to biologists rather than to specialist bioinformaticians. The complete protocol can be executed in ∼1.5 h. Compared with other similar web-based tools, NetworkAnalyst offers a unique visual analytics experience that enables data analysis within the context of protein-protein interaction networks, heatmaps or chord diagrams. All of these analysis methods provide the user with supporting statistical and functional evidence.

  11. Robust image watermarking scheme against geometric attacks using a computer-generated hologram.

    Science.gov (United States)

    Li, Jianzhong

    2010-11-10

    Robustness against geometric attacks is one of the most important issues in digital watermarking. A novel geometric robust watermarking scheme that uses computer-generated holograms as the watermark is presented. To maintain imperceptibility and robustness, a quantization embedding algorithm is adopted to embed the mark hologram into the low-frequency subband of the wavelet-transformed host image. In the detection process, the geometric distorted watermarked images are recovered first by the proposed improved geometric correction method, which is based on the scale invariant feature transform, the invariant centroid, and the pulse coupled neural network. Then the mark holograms are extracted from the recovered images. In comparison with the traditional geometric estimation method, the suggested improved geometric correction method can estimate the geometric distortion parameters more accurately and needs less auxiliary information. Compared with other watermark schemes using digital holograms, the proposed method has the distinct advantage of robustness to geometric attacks. The experimental results demonstrate that the proposed method has good robustness to resist geometric attacks and common attacks including rotation, scaling, translation, image flipping, combined attacks, filtering, occlusion, cropping, and JPEG compression.

  12. Identification and robust water level control of horizontal steam generators using quantitative feedback theory

    Energy Technology Data Exchange (ETDEWEB)

    Safarzadeh, O., E-mail: O_Safarzadeh@sbu.ac.ir [Shahid Beheshti University, P.O. Box: 19839-63113, Tehran (Iran, Islamic Republic of); Khaki-Sedigh, A. [K. N. Toosi University of Technology, Tehran (Iran, Islamic Republic of); Shirani, A.S. [Shahid Beheshti University, P.O. Box: 19839-63113, Tehran (Iran, Islamic Republic of)

    2011-09-15

    Highlights: {yields} A robust water level controller for steam generators (SGs) is designed based on the Quantitative Feedback Theory. {yields} To design the controller, fairly accurate linear models are identified for the SG. {yields} The designed controller is verified using a developed novel global locally linear neuro-fuzzy model of the SG. {yields} Both of the linear and nonlinear models are based on the SG mathematical thermal-hydraulic model developed using the simulation computer code. {yields} The proposed method is easy to apply and guarantees desired closed loop performance. - Abstract: In this paper, a robust water level control system for the horizontal steam generator (SG) using the quantitative feedback theory (QFT) method is presented. To design a robust QFT controller for the nonlinear uncertain SG, control oriented linear models are identified. Then, the nonlinear system is modeled as an uncertain linear time invariant (LTI) system. The robust designed controller is applied to the nonlinear plant model. This nonlinear model is based on a locally linear neuro-fuzzy (LLNF) model. This model is trained using the locally linear model tree (LOLIMOT) algorithm. Finally, simulation results are employed to show the effectiveness of the designed QFT level controller. It is shown that it will ensure the entire designer's water level closed loop specifications.

  13. The Infinity Mirror Test for Analyzing the Robustness of Graph Generators

    CERN Document Server

    Aguinaga, Salvador

    2016-01-01

    Graph generators learn a model from a source graph in order to generate a new graph that has many of the same properties. The learned models each have implicit and explicit biases built in, and its important to understand the assumptions that are made when generating a new graph. Of course, the differences between the new graph and the original graph, as compared by any number of graph properties, are important indicators of the biases inherent in any modelling task. But these critical differences are subtle and not immediately apparent using standard performance metrics. Therefore, we introduce the infinity mirror test for the analysis of graph generator performance and robustness. This stress test operates by repeatedly, recursively fitting a model to itself. A perfect graph generator would have no deviation from the original or ideal graph, however the implicit biases and assumptions that are cooked into the various models are exaggerated by the infinity mirror test allowing for new insights that were not ...

  14. 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...

  15. Efficient and robust generation of maximally entangled states of two atomic ensembles by adiabatic quantum feedback

    CERN Document Server

    Lisi, A D; Illuminati, F; Vitali, D; Lisi, Antonio Di; Siena, Silvio De; Illuminati, Fabrizio; Vitali, David

    2004-01-01

    We introduce an efficient and robust scheme to generate maximally entangled states of two atomic ensembles. The scheme is based on quantum non-demolition measurements of total atomic populations and on quantum feedback conditioned by the measurements outputs. The high efficiency of the scheme is tested and confirmed numerically for photo-detection with ideal efficiency as well as in the presence of losses.

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

    Science.gov (United States)

    Toh, Kazuko; Yoshitomi, Toru; Ikeda, Yutaka; Nagasaki, Yukio

    2011-12-01

    Gene therapy has generated worldwide attention as a new medical technology. While non-viral gene vectors are promising candidates as gene carriers, they have several issues such as toxicity and low transfection efficiency. We have hypothesized that the generation of reactive oxygen species (ROS) affects gene expression in polyplex supported gene delivery systems. The effect of ROS on the gene expression of polyplex was evaluated using a nitroxide radical-containing nanoparticle (RNP) as an ROS scavenger. When polyethyleneimine (PEI)/pGL3 or PEI alone was added to the HeLa cells, ROS levels increased significantly. In contrast, when (PEI)/pGL3 or PEI was added with RNP, the ROS levels were suppressed. The luciferase expression was increased by the treatment with RNP in a dose-dependent manner and the cellular uptake of pDNA was also increased. Inflammatory cytokines play an important role in ROS generation in vivo. In particular, tumor necrosis factor (TNF)-α caused intracellular ROS generation in HeLa cells and decreased gene expression. RNP treatment suppressed ROS production even in the presence of TNF-α and increased gene expression. This anti-inflammatory property of RNP suggests that it may be used as an effective adjuvant for non-viral gene delivery systems.

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

    Directory of Open Access Journals (Sweden)

    Kazuko Toh, Toru Yoshitomi, Yutaka Ikeda and Yukio Nagasaki

    2011-01-01

    Full Text Available Gene therapy has generated worldwide attention as a new medical technology. While non-viral gene vectors are promising candidates as gene carriers, they have several issues such as toxicity and low transfection efficiency. We have hypothesized that the generation of reactive oxygen species (ROS affects gene expression in polyplex supported gene delivery systems. The effect of ROS on the gene expression of polyplex was evaluated using a nitroxide radical-containing nanoparticle (RNP as an ROS scavenger. When polyethyleneimine (PEI/pGL3 or PEI alone was added to the HeLa cells, ROS levels increased significantly. In contrast, when (PEI/pGL3 or PEI was added with RNP, the ROS levels were suppressed. The luciferase expression was increased by the treatment with RNP in a dose-dependent manner and the cellular uptake of pDNA was also increased. Inflammatory cytokines play an important role in ROS generation in vivo. In particular, tumor necrosis factor (TNF-α caused intracellular ROS generation in HeLa cells and decreased gene expression. RNP treatment suppressed ROS production even in the presence of TNF-α and increased gene expression. This anti-inflammatory property of RNP suggests that it may be used as an effective adjuvant for non-viral gene delivery systems.

  18. 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.

  19. 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.

  20. 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.

  1. Robust Generation of Three-Particle W State with Atoms Trapped in Separate Cavities

    Institute of Scientific and Technical Information of China (English)

    辛斌; 贾仁需; 郑亦庄

    2012-01-01

    This paper presents a scheme for generating three-particle W state of remote atoms trapped in leaky cavities.The scheme uses cavity decay to inject photons into a setup of optical devices which consist of a series of beam splitters and photon detectors.Photon detection on the output mode projects the atomic state into the W state.In the condition of “weakly driven approach”,it shows that the scheme is robust and has high fidelity.It also points out that the scheme is scalable to generate multi-atomic W state.

  2. Design of a H∞ Robust Controller with μ-Analysis for Steam Turbine Power Generation Applications

    Directory of Open Access Journals (Sweden)

    Vincenzo Iannino

    2017-07-01

    Full Text Available Concentrated Solar Power plants are complex systems subjected to quite sensitive variations of the steam production profile and external disturbances, thus advanced control techniques that ensure system stability and suitable performance criteria are required. In this work, a multi-objective H∞ robust controller is designed and applied to the power control of a Concentered Solar Power plant composed by two turbines, a gear and a generator. In order to provide robust performance and stability in presence of disturbances, not modeled plant dynamics and plant-parameter variations, the advanced features of the μ-analysis are exploited. A high order controller is obtained from the process of synthesis that makes the implementation of the controller difficult and computational more demanding for a Programmable Logic Controller. Therefore, the controller order is reduced through the Balanced Truncation method and then discretized. The obtained robust control is compared to the current Proportional Integral Derivative-based governing system in order to evaluate its performance, considering unperturbed as well as perturbed scenarios, taking into account variations of steam conditions, sensor measurement delays and power losses. The simulations results show that the proposed controller achieves better robustness and performance compared to the existing Proportional Integral Derivative controller.

  3. Integrated signaling pathway and gene expression regulatory model to dissect dynamics of Escherichia coli challenged mammary epithelial cells.

    Science.gov (United States)

    den Breems, Nicoline Y; Nguyen, Lan K; Kulasiri, Don

    2014-12-01

    Cells transform external stimuli, through the activation of signaling pathways, which in turn activate gene regulatory networks, in gene expression. As more omics data are generated from experiments, eliciting the integrated relationship between the external stimuli, the signaling process in the cell and the subsequent gene expression is a major challenge in systems biology. The complex system of non-linear dynamic protein interactions in signaling pathways and gene networks regulates gene expression. The complexity and non-linear aspects have resulted in the study of the signaling pathway or the gene network regulation in isolation. However, this limits the analysis of the interaction between the two components and the identification of the source of the mechanism differentiating the gene expression profiles. Here, we present a study of a model of the combined signaling pathway and gene network to highlight the importance of integrated modeling. Based on the experimental findings we developed a compartmental model and conducted several simulation experiments. The model simulates the mRNA expression of three different cytokines (RANTES, IL8 and TNFα) regulated by the transcription factor NFκB in mammary epithelial cells challenged with E. coli. The analysis of the gene network regulation identifies a lack of robustness and therefore sensitivity for the transcription factor regulation. However, analysis of the integrated signaling and gene network regulation model reveals distinctly different underlying mechanisms in the signaling pathway responsible for the variation between the three cytokine's mRNA expression levels. Our key findings reveal the importance of integrating the signaling pathway and gene expression dynamics in modeling. Modeling infers valid research questions which need to be verified experimentally and can assist in the design of future biological experiments.

  4. Gene expression data (CEL files) - Open TG-GATEs | LSDB Archive [Life Science Database Archive metadata

    Lifescience Database Archive (English)

    Full Text Available [ Credits ] BLAST Search Image Search Home About Archive Update History Contact us Open TG-GATEs Gene expres...sion data (CEL files) Data detail Data name Gene expression data (CEL files) Descri...Tab Separated Value (TSV) format is included. CEL is one of the file formats that expresses gene expression ...data (raw data) generated from Affymetrix GeneChip®. Data file File name: Gene expression data from rat samp...ze: 12.0GB total File name: Gene expression data from human samples File URL: ftp://ftp.biosciencedbc.jp/arc

  5. H∞ Robust Controller Design for an Induction Generator Driven by a Variable-Speed Wind Turbine

    Directory of Open Access Journals (Sweden)

    Seyed Mohammad Hoseini

    2011-01-01

    Full Text Available This paper presents the modeling and robust controller design design for a wind-driven induction generator system. a  robust controller for the static synchronous compensator (STATCOM and the variable blade pitch in a wind energy conversion system (WECS is designed to be controlled voltage and mechanical power. This controller leading to satisfactory damping characteristics achieved for the closed loop system. Effects of various system disturbances on the dynamic performance have been simulated, and the results comparison with output feedback controller reveal that the proposed controller is effective in regulating the load voltage and stabilizing the generator rotating speed for WECS. The nonlinear simulation was conducted and that comparison with the above linear simulation shows that the simulations carried out for small changes in system inputs is sufficiently accurate. For review performance against large disturbances from a symmetrical three-phase short circuit at infinity bus bar has been used  and the results show robust controller design as well as fluctuations resulting from the short circuit is damped.

  6. Development of a Robust Model-Based Water Level Controller for U-Tube Steam Generator

    Energy Technology Data Exchange (ETDEWEB)

    Basher, A.M.H.

    2001-09-04

    Poor control of steam generator water level of a nuclear power plant may lead to frequent nuclear reactor shutdowns. These shutdowns are more common at low power where the plant exhibits strong non-minimum phase characteristics and flow measurements at low power are unreliable in many instances. There is need to investigate this problem and systematically design a controller for water level regulation. This work is concerned with the study and the design of a suitable controller for a U-Tube Steam Generator (UTSG) of a Pressurized Water Reactor (PWR) which has time varying dynamics. The controller should be suitable for the water level control of UTSG without manual operation from start-up to full load transient condition. Some preliminary simulation results are presented that demonstrate the effectiveness of the proposed controller. The development of the complete control algorithm includes components such as robust output tracking, and adaptively estimating both the system parameters and state variables simultaneously. At the present time all these components are not completed due to time constraints. A robust tracking component of the controller for water level control is developed and its effectiveness on the parameter variations is demonstrated in this study. The results appear encouraging and they are only preliminary. Additional work is warranted to resolve other issues such as robust adaptive estimation.

  7. Generating a robust statistical causal structure over 13 cardiovascular disease risk factors using genomics data.

    Science.gov (United States)

    Yazdani, Azam; Yazdani, Akram; Samiei, Ahmad; Boerwinkle, Eric

    2016-04-01

    Understanding causal relationships among large numbers of variables is a fundamental goal of biomedical sciences and can be facilitated by Directed Acyclic Graphs (DAGs) where directed edges between nodes represent the influence of components of the system on each other. In an observational setting, some of the directions are often unidentifiable because of Markov equivalency. Additional exogenous information, such as expert knowledge or genotype data can help establish directionality among the endogenous variables. In this study, we use the method of principle component analysis to extract information across the genome in order to generate a robust statistical causal network among phenotypes, the variables of primary interest. The method is applied to 590,020 SNP genotypes measured on 1596 individuals to generate the statistical causal network of 13 cardiovascular disease risk factor phenotypes. First, principal component analysis was used to capture information across the genome. The principal components were then used to identify a robust causal network structure, GDAG, among the phenotypes. Analyzing a robust causal network over risk factors reveals the flow of information in direct and alternative paths, as well as determining predictors and good targets for intervention. For example, the analysis identified BMI as influencing multiple other risk factor phenotypes and a good target for intervention to lower disease risk.

  8. 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.

  9. 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.

  10. 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

  11. 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.

  12. Robust thin-film generator based on segmented contact-electrification for harvesting wind energy.

    Science.gov (United States)

    Meng, Xian Song; Zhu, Guang; Wang, Zhong Lin

    2014-06-11

    Collecting and converting energy from ambient air flow promise to be a viable approach in developing self-powered autonomous electronics. Here, we report an effective and robust triboelectric generator that consists of an undulating thin-film membrane and an array of segmented fine-sized electrode pairs on a single substrate. Sequential processes of contact electrification and electrostatic induction generate alternating flows of free electrons when the membrane interacts with ambient air flow. Based on an optimum rational design, the segmented electrodes play an essential role in boosting the output current, leading to an enhancement of over 500% compared to the structure without the segmentation. The thin-film based generator can simultaneously and continuously light up tens of commercial light-emitting diodes. Moreover, it possesses exceptional durability, providing constant electric output after millions of operation cycles. This work offers a truly practical solution that opens the avenue to take advantage of wind energy by using the triboelectric effect.

  13. A robust approach to the generation of high-quality random numbers

    Science.gov (United States)

    Bisadi, Zahra; Fontana, Giorgio; Moser, Enrico; Pucker, Georg; Pavesi, Lorenzo

    2016-10-01

    A random number generation approach comprising a silicon nanocrystals LED (Si-NCs LED), silicon single photon avalanche photodiode (Si SPAD) and a field-programmable gate array (FPGA) is introduced. The Si-NCs LED is the source of entropy with photon emission in the visible range detectable by silicon detectors allowing the fabrication of an all-silicon-based device. The proposed quantum random number generator (QRNG) is robust against variations of the internal and external parameters such as aging of the components, changing temperature, the ambient interferences and the silicon detector artifacts. The raw data show high quality of randomness and passed all the statistical tests in National Institute of Standards and Technology (NIST) tests suite without the application of a post-processing algorithm. The efficiency of random number generation is 4-bits per detected photon.

  14. 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.

  15. Robust Power Management Control for Stand-Alone Hybrid Power Generation System

    Science.gov (United States)

    Kamal, Elkhatib; Adouane, Lounis; Aitouche, Abdel; Mohammed, Walaa

    2017-01-01

    This paper presents a new robust fuzzy control of energy management strategy for the stand-alone hybrid power systems. It consists of two levels named centralized fuzzy supervisory control which generates the power references for each decentralized robust fuzzy control. Hybrid power systems comprises: a photovoltaic panel and wind turbine as renewable sources, a micro turbine generator and a battery storage system. The proposed control strategy is able to satisfy the load requirements based on a fuzzy supervisor controller and manage power flows between the different energy sources and the storage unit by respecting the state of charge and the variation of wind speed and irradiance. Centralized controller is designed based on If-Then fuzzy rules to manage and optimize the hybrid power system production by generating the reference power for photovoltaic panel and wind turbine. Decentralized controller is based on the Takagi-Sugeno fuzzy model and permits us to stabilize each photovoltaic panel and wind turbine in presence of disturbances and parametric uncertainties and to optimize the tracking reference which is given by the centralized controller level. The sufficient conditions stability are formulated in the format of linear matrix inequalities using the Lyapunov stability theory. The effectiveness of the proposed Strategy is finally demonstrated through a SAHPS (stand-alone hybrid power systems) to illustrate the effectiveness of the overall proposed method.

  16. Self-Generated Chemoattractant Gradients: Attractant Depletion Extends the Range and Robustness of Chemotaxis.

    Directory of Open Access Journals (Sweden)

    Luke Tweedy

    2016-03-01

    Full Text Available Chemotaxis is fundamentally important, but the sources of gradients in vivo are rarely well understood. Here, we analyse self-generated chemotaxis, in which cells respond to gradients they have made themselves by breaking down globally available attractants, using both computational simulations and experiments. We show that chemoattractant degradation creates steep local gradients. This leads to surprising results, in particular the existence of a leading population of cells that moves highly directionally, while cells behind this group are undirected. This leading cell population is denser than those following, especially at high attractant concentrations. The local gradient moves with the leading cells as they interact with their surroundings, giving directed movement that is unusually robust and can operate over long distances. Even when gradients are applied from external sources, attractant breakdown greatly changes cells' responses and increases robustness. We also consider alternative mechanisms for directional decision-making and show that they do not predict the features of population migration we observe experimentally. Our findings provide useful diagnostics to allow identification of self-generated gradients and suggest that self-generated chemotaxis is unexpectedly universal in biology and medicine.

  17. Design of the robust synchronous generator stator voltage regulator based on the interval plant model

    Directory of Open Access Journals (Sweden)

    Stojić Đorđe

    2013-01-01

    Full Text Available In this paper a novel method for the stator voltage regulator of a synchronous generator based on the interval plant mode, is presented. Namely, it is shown in the literature that, in order to design a controller for the first-order compensator, the limited number of interval plants needs to be examined. Consequently, the intervals of the plant model parameter variations used to calculate the four extreme interval plants required for the sequential PI controller design are determined. The controller is designed using frequency-domain-based techniques, while its robust performance is examined using simulation tests.

  18. 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.

  19. A robust and rapid algorithm for generating and transmitting multi-resolution three-dimensional models

    Institute of Scientific and Technical Information of China (English)

    2006-01-01

    Recent advances in 3D spatial data capture, such as high resolution satellite images and laser scanning as well as corresponding data processing and modeling technologies, have led to the generation of large amounts of datasets on terrains, buildings, roads and other features. The rapid transmission and visualization of 3D models has become a 'bottleneck' of internet-based applications. This paper proposes a robust algorithm to generate multi-resolution models for rapid visualization and network transmission of 3D models. Experiments were undertaken to evaluate the performance of the proposed algorithm. Experimental results demonstrate that the proposed algorithm achieves good performance in terms of running speed, accuracy, encoding of multi-resolution models, and network transmission.

  20. Minimalist design of a robust real-time quantum random number generator

    Science.gov (United States)

    Kravtsov, K. S.; Radchenko, I. V.; Kulik, S. P.; Molotkov, S. N.

    2015-08-01

    We present a simple and robust construction of a real-time quantum random number generator (QRNG). Our minimalist approach ensures stable operation of the device as well as its simple and straightforward hardware implementation as a stand-alone module. As a source of randomness the device uses measurements of time intervals between clicks of a single-photon detector. The obtained raw sequence is then filtered and processed by a deterministic randomness extractor, which is realized as a look-up table. This enables high speed on-the-fly processing without the need of extensive computations. The overall performance of the device is around 1 random bit per detector click, resulting in 1.2 Mbit/s generation rate in our implementation.

  1. 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

  2. Distribution of population averaged observables in stochastic gene expression

    Science.gov (United States)

    Bhattacharyya, Bhaswati; Kalay, Ziya

    2014-03-01

    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 (pgf) of observables and Large Deviation Theory, we calculate the distribution of population averaged mRNA and protein levels as a function of model parameters and population size. We validate our results using stochastic simulations also report exact results on the asymptotic properties of population averages which show qualitative differences for different models. We calculate the skewness and coefficient of variance for pgfs to estimate the sample size required for population average that contains information about gene expression models. This is relevant to experiments where a large number of data points are unavailable.

  3. Gene-expression signature predicts postoperative recurrence in stage I non-small cell lung cancer patients.

    Science.gov (United States)

    Lu, Yan; Wang, Liang; Liu, Pengyuan; Yang, Ping; You, Ming

    2012-01-01

    About 30% stage I non-small cell lung cancer (NSCLC) patients undergoing resection will recur. Robust prognostic markers are required to better manage therapy options. The purpose of this study is to develop and validate a novel gene-expression signature that can predict tumor recurrence of stage I NSCLC patients. Cox proportional hazards regression analysis was performed to identify recurrence-related genes and a partial Cox regression model was used to generate a gene signature of recurrence in the training dataset -142 stage I lung adenocarcinomas without adjunctive therapy from the Director's Challenge Consortium. Four independent validation datasets, including GSE5843, GSE8894, and two other datasets provided by Mayo Clinic and Washington University, were used to assess the prediction accuracy by calculating the correlation between risk score estimated from gene expression and real recurrence-free survival time and AUC of time-dependent ROC analysis. Pathway-based survival analyses were also performed. 104 probesets correlated with recurrence in the training dataset. They are enriched in cell adhesion, apoptosis and regulation of cell proliferation. A 51-gene expression signature was identified to distinguish patients likely to develop tumor recurrence (Dxy = -0.83, P85%. Multiple pathways including leukocyte transendothelial migration and cell adhesion were highly correlated with recurrence-free survival. The gene signature is highly predictive of recurrence in stage I NSCLC patients, which has important prognostic and therapeutic implications for the future management of these patients.

  4. Gene-expression signature predicts postoperative recurrence in stage I non-small cell lung cancer patients.

    Directory of Open Access Journals (Sweden)

    Yan Lu

    Full Text Available About 30% stage I non-small cell lung cancer (NSCLC patients undergoing resection will recur. Robust prognostic markers are required to better manage therapy options. The purpose of this study is to develop and validate a novel gene-expression signature that can predict tumor recurrence of stage I NSCLC patients. Cox proportional hazards regression analysis was performed to identify recurrence-related genes and a partial Cox regression model was used to generate a gene signature of recurrence in the training dataset -142 stage I lung adenocarcinomas without adjunctive therapy from the Director's Challenge Consortium. Four independent validation datasets, including GSE5843, GSE8894, and two other datasets provided by Mayo Clinic and Washington University, were used to assess the prediction accuracy by calculating the correlation between risk score estimated from gene expression and real recurrence-free survival time and AUC of time-dependent ROC analysis. Pathway-based survival analyses were also performed. 104 probesets correlated with recurrence in the training dataset. They are enriched in cell adhesion, apoptosis and regulation of cell proliferation. A 51-gene expression signature was identified to distinguish patients likely to develop tumor recurrence (Dxy = -0.83, P85%. Multiple pathways including leukocyte transendothelial migration and cell adhesion were highly correlated with recurrence-free survival. The gene signature is highly predictive of recurrence in stage I NSCLC patients, which has important prognostic and therapeutic implications for the future management of these patients.

  5. 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

  6. 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.

  7. 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.

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

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    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

  9. 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

  10. Efficient and robust quantum random number generation by photon number detection

    Science.gov (United States)

    Applegate, M. J.; Thomas, O.; Dynes, J. F.; Yuan, Z. L.; Ritchie, D. A.; Shields, A. J.

    2015-08-01

    We present an efficient and robust quantum random number generator based upon high-rate room temperature photon number detection. We employ an electric field-modulated silicon avalanche photodiode, a type of device particularly suited to high-rate photon number detection with excellent photon number resolution to detect, without an applied dead-time, up to 4 photons from the optical pulses emitted by a laser. By both measuring and modeling the response of the detector to the incident photons, we are able to determine the illumination conditions that achieve an optimal bit rate that we show is robust against variation in the photon flux. We extract random bits from the detected photon numbers with an efficiency of 99% corresponding to 1.97 bits per detected photon number yielding a bit rate of 143 Mbit/s, and verify that the extracted bits pass stringent statistical tests for randomness. Our scheme is highly scalable and has the potential of multi-Gbit/s bit rates.

  11. 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

  12. Robust Sliding Mode Control of Permanent Magnet Synchronous Generator-Based Wind Energy Conversion Systems

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    Guangping Zhuo

    2016-12-01

    Full Text Available The subject of this paper pertains to sliding mode control and its application in nonlinear electrical power systems as seen in wind energy conversion systems. Due to the robustness in dealing with unmodeled system dynamics, sliding mode control has been widely used in electrical power system applications. This paper presents first and high order sliding mode control schemes for permanent magnet synchronous generator-based wind energy conversion systems. The application of these methods for control using dynamic models of the d-axis and q-axis currents, as well as those of the high speed shaft rotational speed show a high level of efficiency in power extraction from a varying wind resource. Computer simulation results have shown the efficacy of the proposed sliding mode control approaches.

  13. Robust network oscillations during mammalian respiratory rhythm generation driven by synaptic dynamics.

    Science.gov (United States)

    Guerrier, Claire; Hayes, John A; Fortin, Gilles; Holcman, David

    2015-08-04

    How might synaptic dynamics generate synchronous oscillations in neuronal networks? We address this question in the preBötzinger complex (preBötC), a brainstem neural network that paces robust, yet labile, inspiration in mammals. The preBötC is composed of a few hundred neurons that alternate bursting activity with silent periods, but the mechanism underlying this vital rhythm remains elusive. Using a computational approach to model a randomly connected neuronal network that relies on short-term synaptic facilitation (SF) and depression (SD), we show that synaptic fluctuations can initiate population activities through recurrent excitation. We also show that a two-step SD process allows activity in the network to synchronize (bursts) and generate a population refractory period (silence). The model was validated against an array of experimental conditions, which recapitulate several processes the preBötC may experience. Consistent with the modeling assumptions, we reveal, by electrophysiological recordings, that SF/SD can occur at preBötC synapses on timescales that influence rhythmic population activity. We conclude that nondeterministic neuronal spiking and dynamic synaptic strengths in a randomly connected network are sufficient to give rise to regular respiratory-like rhythmic network activity and lability, which may play an important role in generating the rhythm for breathing and other coordinated motor activities in mammals.

  14. Generation After Next Propulsor Research: Robust Design for Embedded Engine Systems

    Science.gov (United States)

    Arend, David J.; Tillman, Gregory; O'Brien, Walter F.

    2012-01-01

    The National Aeronautics and Space Administration, United Technologies Research Center and Virginia Polytechnic and State University have contracted to pursue multi-disciplinary research into boundary layer ingesting (BLI) propulsors for generation after next environmentally responsible subsonic fixed wing aircraft. This Robust Design for Embedded Engine Systems project first conducted a high-level vehicle system study based on a large commercial transport class hybrid wing body aircraft, which determined that a 3 to 5 percent reduction in fuel burn could be achieved over a 7,500 nanometer mission. Both pylon-mounted baseline and BLI propulsion systems were based on a low-pressure-ratio fan (1.35) in an ultra-high-bypass ratio engine (16), consistent with the next generation of advanced commercial turbofans. An optimized, coupled BLI inlet and fan system was subsequently designed to achieve performance targets identified in the system study. The resulting system possesses an inlet with total pressure losses less than 0.5%, and a fan stage with an efficiency debit of less than 1.5 percent relative to the pylon-mounted, clean-inflow baseline. The subject research project has identified tools and methodologies necessary for the design of next-generation, highly-airframe-integrated propulsion systems. These tools will be validated in future large-scale testing of the BLI inlet / fan system in NASA's 8 foot x 6 foot transonic wind tunnel. In addition, fan unsteady response to screen-generated total pressure distortion is being characterized experimentally in a JT15D engine test rig. These data will document engine sensitivities to distortion magnitude and spatial distribution, providing early insight into key physical processes that will control BLI propulsor design.

  15. Toward robust phase-locking in Melibe swim central pattern generator models

    Science.gov (United States)

    Jalil, Sajiya; Allen, Dane; Youker, Joseph; Shilnikov, Andrey

    2013-12-01

    Small groups of interneurons, abbreviated by CPG for central pattern generators, are arranged into neural networks to generate a variety of core bursting rhythms with specific phase-locked states, on distinct time scales, which govern vital motor behaviors in invertebrates such as chewing and swimming. These movements in lower level animals mimic motions of organs in higher animals due to evolutionarily conserved mechanisms. Hence, various neurological diseases can be linked to abnormal movement of body parts that are regulated by a malfunctioning CPG. In this paper, we, being inspired by recent experimental studies of neuronal activity patterns recorded from a swimming motion CPG of the sea slug Melibe leonina, examine a mathematical model of a 4-cell network that can plausibly and stably underlie the observed bursting rhythm. We develop a dynamical systems framework for explaining the existence and robustness of phase-locked states in activity patterns produced by the modeled CPGs. The proposed tools can be used for identifying core components for other CPG networks with reliable bursting outcomes and specific phase relationships between the interneurons. Our findings can be employed for identifying or implementing the conditions for normal and pathological functioning of basic CPGs of animals and artificially intelligent prosthetics that can regulate various movements.

  16. Gene expression profiles of mouse spermatogenesis during recovery from irradiation

    DEFF Research Database (Denmark)

    Shah, Fozia J; Tanaka, Masami; Nielsen, John E

    2009-01-01

    BACKGROUND: Irradiation or chemotherapy that suspend normal spermatogenesis is commonly used to treat various cancers. Fortunately, spermatogenesis in many cases can be restored after such treatments but knowledge is limited about the re-initiation process. Earlier studies have described...... the cellular changes that happen during recovery from irradiation by means of histology. We have earlier generated gene expression profiles during induction of spermatogenesis in mouse postnatal developing testes and found a correlation between profiles and the expressing cell types. The aim of the present...... work was to utilize the link between expression profile and cell types to follow the cellular changes that occur during post-irradiation recovery of spermatogenesis in order to describe recovery by means of gene expression. METHODS: Adult mouse testes were subjected to irradiation with 1 Gy...

  17. Scripted drives: A robust protocol for generating exposures to traffic-related air pollution

    Science.gov (United States)

    Patton, Allison P.; Laumbach, Robert; Ohman-Strickland, Pamela; Black, Kathy; Alimokhtari, Shahnaz; Lioy, Paul J.; Kipen, Howard M.

    2016-10-01

    Commuting in automobiles can contribute substantially to total traffic-related air pollution (TRAP) exposure, yet measuring commuting exposures for studies of health outcomes remains challenging. To estimate real-world TRAP exposures, we developed and evaluated the robustness of a scripted drive protocol on the NJ Turnpike and local roads between April 2007 and October 2014. Study participants were driven in a car with closed windows and open vents during morning rush hours on 190 days. Real-time measurements of PM2.5, PNC, CO, and BC, and integrated samples of NO2, were made in the car cabin. Exposure measures included in-vehicle concentrations on the NJ Turnpike and local roads and the differences and ratios of these concentrations. Median in-cabin concentrations were 11 μg/m3 PM2.5, 40 000 particles/cm3, 0.3 ppm CO, 4 μg/m3 BC, and 20.6 ppb NO2. In-cabin concentrations on the NJ Turnpike were higher than in-cabin concentrations on local roads by a factor of 1.4 for PM2.5, 3.5 for PNC, 1.0 for CO, and 4 for BC. Median concentrations of NO2 for full rides were 2.4 times higher than ambient concentrations. Results were generally robust relative to season, traffic congestion, ventilation setting, and study year, except for PNC and PM2.5, which had secular and seasonal trends. Ratios of concentrations were more stable than differences or absolute concentrations. Scripted drives can be used to generate reasonably consistent in-cabin increments of exposure to traffic-related air pollution.

  18. 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.

  19. 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.

  20. 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.

  1. 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.

  2. Non-linear control of variable-speed wind turbines with permanent magnet synchronous generators: a robust backstepping approach

    Science.gov (United States)

    Şeker, Murat; Zergeroğlu, Erkan; Tatlicioğlu, Enver

    2016-01-01

    In this study, a robust backstepping approach for the control problem of the variable-speed wind turbine with a permanent magnet synchronous generator is presented. Specifically, to overcome the negative effects of parametric uncertainties in both mechanical and electrical subsystems, a robust controller with a differentiable compensation term is proposed. The proposed methodology ensures the generator velocity tracking error to uniformly approach a small bound where practical tracking is achieved. Stability of the overall system is ensured by Lyapunov-based arguments. Comparative simulation studies with a standard proportional-integral-type controller are performed to illustrate the effectiveness, feasibility and efficiency of the proposed controller.

  3. Intrinsic bursters increase the robustness of rhythm generation in an excitatory network.

    Science.gov (United States)

    Purvis, L K; Smith, J C; Koizumi, H; Butera, R J

    2007-02-01

    The pre-Botzinger complex (pBC) is a vital subcircuit of the respiratory central pattern generator. Although the existence of neurons with pacemaker-like bursting properties in this network is not questioned, their role in network rhythmogenesis is unresolved. Modeling is ideally suited to address this debate because of the ease with which biophysical parameters of individual cells and network architecture can be manipulated. We modeled the parameter variability of experimental data from pBC bursting pacemaker and nonpacemaker neurons using a modified version of our previously developed pBC neuron and network models. To investigate the role of pacemakers in networkwide rhythmogenesis, we simulated networks of these neurons and varied the fraction of the population made up of pacemakers. For each number of pacemaker neurons, we varied the amount of tonic drive to the network and measured the frequency of synchronous networkwide bursting produced. Both excitatory networks with all-to-all coupling and sparsely connected networks were explored for several levels of synaptic coupling strength. Networks containing only nonpacemakers were able to produce networkwide bursting, but with a low probability of bursting and low input and output ranges. Our results indicate that inclusion of pacemakers in an excitatory network increases robustness of the network by more than tripling the input and output ranges compared with networks containing no pacemakers. The largest increase in dynamic range occurs when the number of pacemakers in the network is greater than 20% of the population. Experimental tests of our model predictions are proposed.

  4. Robust Optimization-Based Generation Self-Scheduling under Uncertain Price

    Directory of Open Access Journals (Sweden)

    Xiao Luo

    2011-01-01

    Full Text Available This paper considers generation self-scheduling in electricity markets under uncertain price. Based on the robust optimization (denoted as RO methodology, a new self-scheduling model, which has a complicated max-min optimization structure, is set up. By using optimal dual theory, the proposed model is reformulated to an ordinary quadratic and quadratic cone programming problems in the cases of box and ellipsoidal uncertainty, respectively. IEEE 30-bus system is used to test the new model. Some comparisons with other methods are done, and the sensitivity with respect to the uncertain set is analyzed. Comparing with the existed uncertain self-scheduling approaches, the new method has twofold characteristics. First, it does not need a prediction of distribution of random variables and just requires an estimated value and the uncertain set of power price. Second, the counterpart of RO corresponding to the self-scheduling is a simple quadratic or quadratic cone programming. This indicates that the reformulated problem can be solved by many ordinary optimization algorithms.

  5. 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.

  6. Imputing Gene Expression in Uncollected Tissues Within and Beyond GTEx

    Science.gov (United States)

    Wang, Jiebiao; Gamazon, Eric R.; Pierce, Brandon L.; Stranger, Barbara E.; Im, Hae Kyung; Gibbons, Robert D.; Cox, Nancy J.; Nicolae, Dan L.; Chen, Lin S.

    2016-01-01

    Gene expression and its regulation can vary substantially across tissue types. In order to generate knowledge about gene expression in human tissues, the Genotype-Tissue Expression (GTEx) program has collected transcriptome data in a wide variety of tissue types from post-mortem donors. However, many tissue types are difficult to access and are not collected in every GTEx individual. Furthermore, in non-GTEx studies, the accessibility of certain tissue types greatly limits the feasibility and scale of studies of multi-tissue expression. In this work, we developed multi-tissue imputation methods to impute gene expression in uncollected or inaccessible tissues. Via simulation studies, we showed that the proposed methods outperform existing imputation methods in multi-tissue expression imputation and that incorporating imputed expression data can improve power to detect phenotype-expression correlations. By analyzing data from nine selected tissue types in the GTEx pilot project, we demonstrated that harnessing expression quantitative trait loci (eQTLs) and tissue-tissue expression-level correlations can aid imputation of transcriptome data from uncollected GTEx tissues. More importantly, we showed that by using GTEx data as a reference, one can impute expression levels in inaccessible tissues in non-GTEx expression studies. PMID:27040689

  7. Robust fractional order sliding mode control of doubly-fed induction generator (DFIG)-based wind turbines.

    Science.gov (United States)

    Ebrahimkhani, Sadegh

    2016-07-01

    Wind power plants have nonlinear dynamics and contain many uncertainties such as unknown nonlinear disturbances and parameter uncertainties. Thus, it is a difficult task to design a robust reliable controller for this system. This paper proposes a novel robust fractional-order sliding mode (FOSM) controller for maximum power point tracking (MPPT) control of doubly fed induction generator (DFIG)-based wind energy conversion system. In order to enhance the robustness of the control system, uncertainties and disturbances are estimated using a fractional order uncertainty estimator. In the proposed method a continuous control strategy is developed to achieve the chattering free fractional order sliding-mode control, and also no knowledge of the uncertainties and disturbances or their bound is assumed. The boundedness and convergence properties of the closed-loop signals are proven using Lyapunov׳s stability theory. Simulation results in the presence of various uncertainties were carried out to evaluate the effectiveness and robustness of the proposed control scheme.

  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. 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.

  10. 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.

  11. 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

  12. 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.

  13. 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

  14. 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.

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

    DEFF Research Database (Denmark)

    Manijak, Mieszko P.; Nielsen, Henrik Bjørn

    2011-01-01

    BACKGROUND: Although, systematic analysis of gene annotation is a powerful tool for interpreting gene expression data, it sometimes is blurred by incomplete gene annotation, missing expression response of key genes and secondary gene expression responses. These shortcomings may be partially...... circumvented by instead matching gene expression signatures to signatures of other experiments. FINDINGS: To facilitate this we present the Functional Association Response by Overlap (FARO) server, that match input signatures to a compendium of 242 gene expression signatures, extracted from more than 1700...

  16. Microarray data integration for genome-wide analysis of human tissue-selective gene expression

    OpenAIRE

    Wang, Liangjiang; Srivastava, Anand K; Schwartz, Charles E

    2010-01-01

    Background Microarray gene expression data are accumulating in public databases. The expression profiles contain valuable information for understanding human gene expression patterns. However, the effective use of public microarray data requires integrating the expression profiles from heterogeneous sources. Results In this study, we have compiled a compendium of microarray expression profiles of various human tissue samples. The microarray raw data generated in different research laboratorie...

  17. 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

  18. 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.

  19. 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.

  20. Robust modelling of heat-induced reactions in an industrial food production process exemplified by acrylamide generation in breakfast cereals

    DEFF Research Database (Denmark)

    Jensen, Bo Boye Busk; Lennox, Martin; Granby, Kit

    2008-01-01

    Data from an industrial case study of breakfast cereal production indicated that the generated amounts of acrylamide are greatly dependent upon the combined effects of temperature and heating time in a roasting step process. Two approaches to obtain process models for acrylamide generation were...... the importance of robustness in the developed models. The correlations obtained for predicting acrylamide generation in the case study present a useful tool for food processing industry to minimize acrylamide generation. In the present case it was possible by lowering process temperature and prolonging residence...

  1. 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.

  2. 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.

  3. Identification of stable reference genes for gene expression analysis of three-dimensional cultivated human bone marrow-derived mesenchymal stromal cells for bone tissue engineering.

    Science.gov (United States)

    Rauh, Juliane; Jacobi, Angela; Stiehler, Maik

    2015-02-01

    The principles of tissue engineering (TE) are widely used for bone regeneration concepts. Three-dimensional (3D) cultivation of autologous human mesenchymal stromal cells (MSCs) on porous scaffolds is the basic prerequisite to generate newly formed bone tissue. Quantitative reverse transcription polymerase chain reaction (qRT-PCR) is a specific and sensitive analytical tool for the measurement of mRNA-levels in cells or tissues. For an accurate quantification of gene expression levels, stably expressed reference genes (RGs) are essential to obtain reliable results. Since the 3D environment can affect a cell's morphology, proliferation, and gene expression profile compared with two-dimensional (2D) cultivation, there is a need to identify robust RGs for the quantification of gene expression. So far, this issue has not been adequately investigated. The aim of this study was to identify the most stably expressed RGs for gene expression analysis of 3D-cultivated human bone marrow-derived MSCs (BM-MSCs). For this, we analyzed the gene expression levels of n=31 RGs in 3D-cultivated human BM-MSCs from six different donors compared with conventional 2D cultivation using qRT-PCR. MSCs isolated from bone marrow aspirates were cultivated on human cancellous bone cube scaffolds for 14 days. Osteogenic differentiation was assessed by cell-specific alkaline phosphatase (ALP) activity and expression of osteogenic marker genes. Expression levels of potential reference and target genes were quantified using commercially available TaqMan(®) assays. mRNA expression stability of RGs was determined by calculating the coefficient of variation (CV) and using the algorithms of geNorm and NormFinder. Using both algorithms, we identified TATA box binding protein (TBP), transferrin receptor (p90, CD71) (TFRC), and hypoxanthine phosphoribosyltransferase 1 (HPRT1) as the most stably expressed RGs in 3D-cultivated BM-MSCs. Notably, genes that are routinely used as RGs, for example, beta actin

  4. Generating Fuzzy Rule-based Systems from Examples Based on Robust Support Vector Machine

    Institute of Scientific and Technical Information of China (English)

    JIA Jiong; ZHANG Hao-ran

    2006-01-01

    This paper firstly proposes a new support vector machine regression (SVR) with a robust loss function, and designs a gradient based algorithm for implementation of the SVR,then uses the SVR to extract fuzzy rules and designs fuzzy rule-based system. Simulations show that fuzzy rule-based system technique based on robust SVR achieves superior performance to the conventional fuzzy inference method, the proposed method provides satisfactory performance with excellent approximation and generalization property than the existing algorithm.

  5. Regulation of cell-to-cell variability in divergent gene expression

    Science.gov (United States)

    Yan, Chao; Wu, Shuyang; Pocetti, Christopher; Bai, Lu

    2016-03-01

    Cell-to-cell variability (noise) is an important feature of gene expression that impacts cell fitness and development. The regulatory mechanism of this variability is not fully understood. Here we investigate the effect on gene expression noise in divergent gene pairs (DGPs). We generated reporters driven by divergent promoters, rearranged their gene order, and probed their expressions using time-lapse fluorescence microscopy and single-molecule fluorescence in situ hybridization (smFISH). We show that two genes in a co-regulated DGP have higher expression covariance compared with the separate, tandem and convergent configurations, and this higher covariance is caused by more synchronized firing of the divergent transcriptions. For differentially regulated DGPs, the regulatory signal of one gene can stochastically `leak' to the other, causing increased gene expression noise. We propose that the DGPs' function in limiting or promoting gene expression noise may enhance or compromise cell fitness, providing an explanation for the conservation pattern of DGPs.

  6. 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

  7. 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.

  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 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.

  10. 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.

  11. 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

  12. 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.

  13. 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.

  14. 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.

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

    Directory of Open Access Journals (Sweden)

    Leckie Christopher

    2010-09-01

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

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

    Science.gov (United States)

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

    2010-09-23

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

  17. A hierarchy of ECM-mediated signalling tissue-specific gene expression regulates tissue-specific gene expression

    Energy Technology Data Exchange (ETDEWEB)

    Roskelley, Calvin D; Srebrow, Anabella; Bissell, Mina J

    1995-10-07

    A dynamic and reciprocal flow of information between cells and the extracellular matrix contributes significantly to the regulation of form and function in developing systems. Signals generated by the extracellular matrix do not act in isolation. Instead, they are processed within the context of global signalling hierarchies whose constituent inputs and outputs are constantly modulated by all the factors present in the cell's surrounding microenvironment. This is particularly evident in the mammary gland, where the construction and subsequent destruction of such a hierarchy regulates changes in tissue-specific gene expression, morphogenesis and apoptosis during each developmental cycle of pregnancy, lactation and involution.

  18. 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

  19. Integrated Microfluidic Devices for Automated Microarray-Based Gene Expression and Genotyping Analysis

    Science.gov (United States)

    Liu, Robin H.; Lodes, Mike; Fuji, H. Sho; Danley, David; McShea, Andrew

    Microarray assays typically involve multistage sample processing and fluidic handling, which are generally labor-intensive and time-consuming. Automation of these processes would improve robustness, reduce run-to-run and operator-to-operator variation, and reduce costs. In this chapter, a fully integrated and self-contained microfluidic biochip device that has been developed to automate the fluidic handling steps for microarray-based gene expression or genotyping analysis is presented. The device consists of a semiconductor-based CustomArray® chip with 12,000 features and a microfluidic cartridge. The CustomArray was manufactured using a semiconductor-based in situ synthesis technology. The micro-fluidic cartridge consists of microfluidic pumps, mixers, valves, fluid channels, and reagent storage chambers. Microarray hybridization and subsequent fluidic handling and reactions (including a number of washing and labeling steps) were performed in this fully automated and miniature device before fluorescent image scanning of the microarray chip. Electrochemical micropumps were integrated in the cartridge to provide pumping of liquid solutions. A micromixing technique based on gas bubbling generated by electrochemical micropumps was developed. Low-cost check valves were implemented in the cartridge to prevent cross-talk of the stored reagents. Gene expression study of the human leukemia cell line (K562) and genotyping detection and sequencing of influenza A subtypes have been demonstrated using this integrated biochip platform. For gene expression assays, the microfluidic CustomArray device detected sample RNAs with a concentration as low as 0.375 pM. Detection was quantitative over more than three orders of magnitude. Experiment also showed that chip-to-chip variability was low indicating that the integrated microfluidic devices eliminate manual fluidic handling steps that can be a significant source of variability in genomic analysis. The genotyping results showed

  20. 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...

  1. 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.

  2. Gene expression profiling of chicken primordial germ cell ESTs

    Directory of Open Access Journals (Sweden)

    Lim Dajeong

    2006-08-01

    Full Text Available Abstract Background Germ cells are the only cell type that can penetrate from one generation to next generation. At the early embryonic developmental stages, germ cells originally stem from primordial germ cells, and finally differentiate into functional gametes, sperm in male or oocyte in female, after sexual maturity. This study was conducted to investigate a large-scale expressed sequence tag (EST analysis in chicken PGCs and compare the expression of the PGC ESTs with that of embryonic gonad. Results We constructed 10,851 ESTs from a chicken cDNA library of a collection of highly separated embryonic PGCs. After chimeric and problematic sequences were filtered out using the chicken genomic sequences, there were 5,093 resulting unique sequences consisting of 156 contigs and 4,937 singlets. Pearson chi-square tests of gene ontology terms in the 2nd level between PGC and embryonic gonad set showed no significance. However, digital gene expression profiling using the Audic's test showed that there were 2 genes expressed significantly with higher number of transcripts in PGCs compared with the embryonic gonads set. On the other hand, 17 genes in embryonic gonads were up-regulated higher than those in the PGC set. Conclusion Our results in this study contribute to knowledge of mining novel transcripts and genes involved in germline cell proliferation and differentiation at the early embryonic stages.

  3. Robust stabilization via computer-generated Lyapunov functions: An application to a magnetic levitation system

    Energy Technology Data Exchange (ETDEWEB)

    Blanchini, F. [Universita di Udine (Italy); Carabelli, S. [Politecnico di Torino (Italy)

    1994-12-31

    We apply a technique recently proposed in literature for the robust stabilization of linear systems with time-varying uncertain parameters to a magnetic levitation system. This technique allows the construction of a polyhedral Lyapunov function and a linear variable-structure stabilizing controller.

  4. Visual exploration of three-dimensional gene expression using physical views and linked abstract views.

    Science.gov (United States)

    Weber, Gunther H; Rübel, Oliver; Huang, Min-Yu; DePace, Angela H; Fowlkes, Charless C; Keränen, Soile V E; Luengo Hendriks, Cris L; Hagen, Hans; Knowles, David W; Malik, Jitendra; Biggin, Mark D; Hamann, Bernd

    2009-01-01

    During animal development, complex patterns of gene expression provide positional information within the embryo. To better understand the underlying gene regulatory networks, the Berkeley Drosophila Transcription Network Project (BDTNP) has developed methods that support quantitative computational analysis of three-dimensional (3D) gene expression in early Drosophila embryos at cellular resolution. We introduce PointCloudXplore (PCX), an interactive visualization tool that supports visual exploration of relationships between different genes' expression using a combination of established visualization techniques. Two aspects of gene expression are of particular interest: 1) gene expression patterns defined by the spatial locations of cells expressing a gene and 2) relationships between the expression levels of multiple genes. PCX provides users with two corresponding classes of data views: 1) Physical Views based on the spatial relationships of cells in the embryo and 2) Abstract Views that discard spatial information and plot expression levels of multiple genes with respect to each other. Cell Selectors highlight data associated with subsets of embryo cells within a View. Using linking, these selected cells can be viewed in multiple representations. We describe PCX as a 3D gene expression visualization tool and provide examples of how it has been used by BDTNP biologists to generate new hypotheses.

  5. Acoustic Model Training Using Pseudo-Speaker Features Generated by MLLR Transformations for Robust Speaker-Independent Speech Recognition

    OpenAIRE

    Arata Itoh; Sunao Hara; Norihide Kitaoka; Kazuya Takeda

    2012-01-01

    A novel speech feature generation-based acoustic model training method for robust speaker-independent speech recognition is proposed. For decades, speaker adaptation methods have been widely used. All of these adaptation methods need adaptation data. However, our proposed method aims to create speaker-independent acoustic models that cover not only known but also unknown speakers. We achieve this by adopting inverse maximum likelihood linear regression (MLLR) transformation-based feature gene...

  6. The Effects of High-Fat Diet Exposure In Utero on the Obesogenic and Diabetogenic Traits Through Epigenetic Changes in Adiponectin and Leptin Gene Expression for Multiple Generations in Female Mice.

    Science.gov (United States)

    Masuyama, Hisashi; Mitsui, Takashi; Nobumoto, Etsuko; Hiramatsu, Yuji

    2015-07-01

    Recent studies demonstrate that epigenetic changes under malnutrition in utero might play important roles in transgenerational links with metabolic diseases. We have previously shown that exposure to a high-fat diet (HFD) in utero may cause a metabolic syndrome-like phenomenon through epigenetic modifications of Adiponectin and Leptin genes. Because an association of obesity between mother and offspring endured in multiple generations, we examined whether HFD exposure in utero might affect the metabolic status of female offspring through multigenerational epigenetic changes of Adiponectin and Leptin genes and whether a normal diet in utero for multiple generations might abolish such epigenetic changes after exposure to a HFD in utero using ICR mice. We observed that the effect of maternal HFD on offspring over multiple generations in metabolic syndrome-like phenomenon such as weight and fat mass gain, glucose intolerance, hypertriglyceridemia, abnormal adiponectin and leptin levels, and hypertension, were accumulated with expression and epigenetic changes in Adiponectin and Leptin genes. A normal diet in utero in the subsequent generations after HFD exposure in utero diminished, and a normal diet in utero for 3 generations completely abolished, the effect of HFD in utero on weight and fat mass gain, insulin resistance, serum triglyceride, adiponectin, and leptin levels, with epigenetic changes of Adiponectin and Leptin genes. Exposure to a HFD in utero might affect glucose and lipid metabolism of female offspring through epigenetic modifications to Adiponectin and Leptin genes for multiple generations. Obesogenic and diabetogenic traits were abolished after a maternal normal diet for 3 generations.

  7. Meta Analysis of Gene Expression Data within and Across Species.

    Science.gov (United States)

    Fierro, Ana C; Vandenbussche, Filip; Engelen, Kristof; Van de Peer, Yves; Marchal, Kathleen

    2008-12-01

    Since the second half of the 1990s, a large number of genome-wide analyses have been described that study gene expression at the transcript level. To this end, two major strategies have been adopted, a first one relying on hybridization techniques such as microarrays, and a second one based on sequencing techniques such as serial analysis of gene expression (SAGE), cDNA-AFLP, and analysis based on expressed sequence tags (ESTs). Despite both types of profiling experiments becoming routine techniques in many research groups, their application remains costly and laborious. As a result, the number of conditions profiled in individual studies is still relatively small and usually varies from only two to few hundreds of samples for the largest experiments. More and more, scientific journals require the deposit of these high throughput experiments in public databases upon publication. Mining the information present in these databases offers molecular biologists the possibility to view their own small-scale analysis in the light of what is already available. However, so far, the richness of the public information remains largely unexploited. Several obstacles such as the correct association between ESTs and microarray probes with the corresponding gene transcript, the incompleteness and inconsistency in the annotation of experimental conditions, and the lack of standardized experimental protocols to generate gene expression data, all impede the successful mining of these data. Here, we review the potential and difficulties of combining publicly available expression data from respectively EST analyses and microarray experiments. With examples from literature, we show how meta-analysis of expression profiling experiments can be used to study expression behavior in a single organism or between organisms, across a wide range of experimental conditions. We also provide an overview of the methods and tools that can aid molecular biologists in exploiting these public data.

  8. Gene expression in cortex and hippocampus during acute pneumococcal meningitis

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    Wittwer Matthias

    2006-06-01

    Full Text Available Abstract Background Pneumococcal meningitis is associated with high mortality (~30% and morbidity. Up to 50% of survivors are affected by neurological sequelae due to a wide spectrum of brain injury mainly affecting the cortex and hippocampus. Despite this significant disease burden, the genetic program that regulates the host response leading to brain damage as a consequence of bacterial meningitis is largely unknown. We used an infant rat model of pneumococcal meningitis to assess gene expression profiles in cortex and hippocampus at 22 and 44 hours after infection and in controls at 22 h after mock-infection with saline. To analyze the biological significance of the data generated by Affymetrix DNA microarrays, a bioinformatics pipeline was used combining (i a literature-profiling algorithm to cluster genes based on the vocabulary of abstracts indexed in MEDLINE (NCBI and (ii the self-organizing map (SOM, a clustering technique based on covariance in gene expression kinetics. Results Among 598 genes differentially regulated (change factor ≥ 1.5; p ≤ 0.05, 77% were automatically assigned to one of 11 functional groups with 94% accuracy. SOM disclosed six patterns of expression kinetics. Genes associated with growth control/neuroplasticity, signal transduction, cell death/survival, cytoskeleton, and immunity were generally upregulated. In contrast, genes related to neurotransmission and lipid metabolism were transiently downregulated on the whole. The majority of the genes associated with ionic homeostasis, neurotransmission, signal transduction and lipid metabolism were differentially regulated specifically in the hippocampus. Of the cell death/survival genes found to be continuously upregulated only in hippocampus, the majority are pro-apoptotic, while those continuously upregulated only in cortex are anti-apoptotic. Conclusion Temporal and spatial analysis of gene expression in experimental pneumococcal meningitis identified potential

  9. 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.

  10. 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.

  11. 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.

  12. LMI-Based Generation of Feedback Laws for a Robust Model Predictive Control Algorithm

    Science.gov (United States)

    Acikmese, Behcet; Carson, John M., III

    2007-01-01

    This technical note provides a mathematical proof of Corollary 1 from the paper 'A Nonlinear Model Predictive Control Algorithm with Proven Robustness and Resolvability' that appeared in the 2006 Proceedings of the American Control Conference. The proof was omitted for brevity in the publication. The paper was based on algorithms developed for the FY2005 R&TD (Research and Technology Development) project for Small-body Guidance, Navigation, and Control [2].The framework established by the Corollary is for a robustly stabilizing MPC (model predictive control) algorithm for uncertain nonlinear systems that guarantees the resolvability of the associated nite-horizon optimal control problem in a receding-horizon implementation. Additional details of the framework are available in the publication.

  13. 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.

  14. Construction and use of gene expression covariation matrix

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    Bellis Michel

    2009-07-01

    Full Text Available Abstract Background One essential step in the massive analysis of transcriptomic profiles is the calculation of the correlation coefficient, a value used to select pairs of genes with similar or inverse transcriptional profiles across a large fraction of the biological conditions examined. Until now, the choice between the two available methods for calculating the coefficient has been dictated mainly by technological considerations. Specifically, in analyses based on double-channel techniques, researchers have been required to use covariation correlation, i.e. the correlation between gene expression changes measured between several pairs of biological conditions, expressed for example as fold-change. In contrast, in analyses of single-channel techniques scientists have been restricted to the use of coexpression correlation, i.e. correlation between gene expression levels. To our knowledge, nobody has ever examined the possible benefits of using covariation instead of coexpression in massive analyses of single channel microarray results. Results We describe here how single-channel techniques can be treated like double-channel techniques and used to generate both gene expression changes and covariation measures. We also present a new method that allows the calculation of both positive and negative correlation coefficients between genes. First, we perform systematic comparisons between two given biological conditions and classify, for each comparison, genes as increased (I, decreased (D, or not changed (N. As a result, the original series of n gene expression level measures assigned to each gene is replaced by an ordered string of n(n-1/2 symbols, e.g. IDDNNIDID....DNNNNNNID, with the length of the string corresponding to the number of comparisons. In a second step, positive and negative covariation matrices (CVM are constructed by calculating statistically significant positive or negative correlation scores for any pair of genes by comparing their

  15. Comparison of a spiking neural network and an MLP for robust identification of generator dynamics in a multimachine power system.

    Science.gov (United States)

    Johnson, Cameron; Venayagamoorthy, Ganesh Kumar; Mitra, Pinaki

    2009-01-01

    The application of a spiking neural network (SNN) and a multi-layer perceptron (MLP) for online identification of generator dynamics in a multimachine power system are compared in this paper. An integrate-and-fire model of an SNN which communicates information via the inter-spike interval is applied. The neural network identifiers are used to predict the speed and terminal voltage deviations one time-step ahead of generators in a multimachine power system. The SNN is developed in two steps: (i) neuron centers determined by offline k-means clustering and (ii) output weights obtained by online training. The sensitivity of the SNN to the neuron centers determined in the first step is evaluated on generators of different ratings and parameters. Performances of the SNN and MLP are compared to evaluate robustness on the identification of generator dynamics under small and large disturbances, and to illustrate that SNNs are capable of learning nonlinear dynamics of complex systems.

  16. GENE EXPRESSION PROFILING IN THE LIVER OF CD-1 MICE TO CHARACTERIZE THE HEPATOTOXICITY OF TRIAZOLE FUNGICIDES

    Science.gov (United States)

    Four triazole fungicides used in agricultural or pharmaceutical applications were examined for hepatotoxic effects in mouse liver. Besides organ weight, histopathology, and cytochrome P450 (CYP) enzyme induction, DNA microarrays were used to generate gene expression profiles and ...

  17. 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.

  18. The Low Noise Limit in Gene Expression.

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    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.

  19. 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.

  20. 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.

  1. 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

  2. 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.

  3. 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.

  4. 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.

  5. 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.

  6. Analysis of gene expression in rabbit muscle

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    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.

  7. Evaluation of Plaid Models in Biclustering of Gene Expression Data

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    Hamid Alavi Majd

    2016-01-01

    Full Text Available Background. Biclustering algorithms for the analysis of high-dimensional gene expression data were proposed. Among them, the plaid model is arguably one of the most flexible biclustering models up to now. Objective. The main goal of this study is to provide an evaluation of plaid models. To that end, we will investigate this model on both simulation data and real gene expression datasets. Methods. Two simulated matrices with different degrees of overlap and noise are generated and then the intrinsic structure of these data is compared with biclusters result. Also, we have searched biologically significant discovered biclusters by GO analysis. Results. When there is no noise the algorithm almost discovered all of the biclusters but when there is moderate noise in the dataset, this algorithm cannot perform very well in finding overlapping biclusters and if noise is big, the result of biclustering is not reliable. Conclusion. The plaid model needs to be modified because when there is a moderate or big noise in the data, it cannot find good biclusters. This is a statistical model and is a quite flexible one. In summary, in order to reduce the errors, model can be manipulated and distribution of error can be changed.

  8. Sleep Deprivation Influences Circadian Gene Expression in the Lateral Habenula.

    Science.gov (United States)

    Zhang, Beilin; Gao, Yanxia; Li, Yang; Yang, Jing; Zhao, Hua

    2016-01-01

    Sleep is governed by homeostasis and the circadian clock. Clock genes play an important role in the generation and maintenance of circadian rhythms but are also involved in regulating sleep homeostasis. The lateral habenular nucleus (LHb) has been implicated in sleep-wake regulation, since LHb gene expression demonstrates circadian oscillation characteristics. This study focuses on the participation of LHb clock genes in regulating sleep homeostasis, as the nature of their involvement is unclear. In this study, we observed changes in sleep pattern following sleep deprivation in LHb-lesioned rats using EEG recording techniques. And then the changes of clock gene expression (Per1, Per2, and Bmal1) in the LHb after 6 hours of sleep deprivation were detected by using real-time quantitative PCR (qPCR). We found that sleep deprivation increased the length of Non-Rapid Eye Movement Sleep (NREMS) and decreased wakefulness. LHb-lesioning decreased the amplitude of reduced wake time and increased NREMS following sleep deprivation in rats. qPCR results demonstrated that Per2 expression was elevated after sleep deprivation, while the other two genes were unaffected. Following sleep recovery, Per2 expression was comparable to the control group. This study provides the basis for further research on the role of LHb Per2 gene in the regulation of sleep homeostasis.

  9. Sleep Deprivation Influences Circadian Gene Expression in the Lateral Habenula

    Directory of Open Access Journals (Sweden)

    Beilin Zhang

    2016-01-01

    Full Text Available Sleep is governed by homeostasis and the circadian clock. Clock genes play an important role in the generation and maintenance of circadian rhythms but are also involved in regulating sleep homeostasis. The lateral habenular nucleus (LHb has been implicated in sleep-wake regulation, since LHb gene expression demonstrates circadian oscillation characteristics. This study focuses on the participation of LHb clock genes in regulating sleep homeostasis, as the nature of their involvement is unclear. In this study, we observed changes in sleep pattern following sleep deprivation in LHb-lesioned rats using EEG recording techniques. And then the changes of clock gene expression (Per1, Per2, and Bmal1 in the LHb after 6 hours of sleep deprivation were detected by using real-time quantitative PCR (qPCR. We found that sleep deprivation increased the length of Non-Rapid Eye Movement Sleep (NREMS and decreased wakefulness. LHb-lesioning decreased the amplitude of reduced wake time and increased NREMS following sleep deprivation in rats. qPCR results demonstrated that Per2 expression was elevated after sleep deprivation, while the other two genes were unaffected. Following sleep recovery, Per2 expression was comparable to the control group. This study provides the basis for further research on the role of LHb Per2 gene in the regulation of sleep homeostasis.

  10. 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

  11. A primer on molecular biology for imagers: II. Transcription and gene expression.

    Science.gov (United States)

    Pandit, Sunil D; Li, King C P

    2004-03-01

    The process of gene expression is complex and highly regulated to ensure that the right gene is expressed at the right place, at the right time, and in regulated amounts. The cell has multiple levels at which it controls the expression of a transcript including gene expression, alternate splicing, and stability of the transcript. Alternate splicing to generate different RNA species from a given gene and DNA rearrangements where genes are rearranged during cellular differentiation (eg, immunoglobulin genes) are additional mechanisms used to generate diversity in complex organisms. Epigenetic mechanisms such as methylation where CpG-rich islands in the promoter region depending on their methylation status can also modulate gene expression. The reader is requested to refer to the books, review articles, and web sites for additional information.

  12. 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.

  13. 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.

  14. Efficient conditional gene expression following transplantation of retrovirally transduced bone marrow stem cells.

    Science.gov (United States)

    Chung, Jie-Yu; Mackay, Fabienne; Alderuccio, Frank

    2015-01-01

    Retroviral gene therapy combined with bone marrow stem cell transplantation can be used to generate mice with ectopic gene expression in the bone marrow compartment in a quick and cost effective manner when compared to generating and maintaining transgenic mouse lines. However a limitation of this procedure is the lack of cell specificity in gene expression that is associated with the use of endogenous retroviral promoters. Restricting gene expression to specific cell subsets utilising tissue-specific promoter driven retroviral vectors is a challenge. Here we describe the generation of conditional expression of retrovirally encoded genes in specific bone marrow derived cell lineages utilising a Cre-dependent retroviral vector. By utilising Lck and CD19 restricted Cre transgenic bone marrow stem cells, we generate chimeric animals with T or B lymphocyte restricted gene expression respectively. The design of the Cre-dependent retroviral vector enables expression of encoded MOG and GFP genes only in association with Cre mediated DNA inversion. Importantly this strategy does not significantly increase the size of the retroviral vector; as such we are able to generate bone marrow chimeric animals with significantly higher chimerism levels than previous studies utilising Cre-dependent retroviral vectors and Cre transgenic bone marrow stem cells. This demonstrates that the use of Cre-dependent retroviral vectors is able to yield high chimerism levels for experimental use and represent a viable alternative to generating transgenic animals.

  15. Sensitivity and fidelity of DNA microarray improved with integration of Amplified Differential Gene Expression (ADGE

    Directory of Open Access Journals (Sweden)

    Ile Kristina E

    2003-07-01

    Full Text Available Abstract Background The ADGE technique is a method designed to magnify the ratios of gene expression before detection. It improves the detection sensitivity to small change of gene expression and requires small amount of starting material. However, the throughput of ADGE is low. We integrated ADGE with DNA microarray (ADGE microarray and compared it with regular microarray. Results When ADGE was integrated with DNA microarray, a quantitative relationship of a power function between detected and input ratios was found. Because of ratio magnification, ADGE microarray was better able to detect small changes in gene expression in a drug resistant model cell line system. The PCR amplification of templates and efficient labeling reduced the requirement of starting material to as little as 125 ng of total RNA for one slide hybridization and enhanced the signal intensity. Integration of ratio magnification, template amplification and efficient labeling in ADGE microarray reduced artifacts in microarray data and improved detection fidelity. The results of ADGE microarray were less variable and more reproducible than those of regular microarray. A gene expression profile generated with ADGE microarray characterized the drug resistant phenotype, particularly with reference to glutathione, proliferation and kinase pathways. Conclusion ADGE microarray magnified the ratios of differential gene expression in a power function, improved the detection sensitivity and fidelity and reduced the requirement for starting material while maintaining high throughput. ADGE microarray generated a more informative expression pattern than regular microarray.

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

    Science.gov (United States)

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

    2016-03-01

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

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

    Directory of Open Access Journals (Sweden)

    Nevin Belder

    2016-03-01

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

  18. 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...

  19. 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.

  20. 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.

  1. 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...

  2. 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.

  3. 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.

  4. 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.

  5. 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.

  6. Determining the effect of DNA methylation on gene expression in cancer cells.

    Science.gov (United States)

    Lee, Chai-Jin; Evans, Jared; Kim, Kwangsoo; Chae, Heejoon; Kim, Sun

    2014-01-01

    DNA methylation, a DNA modification by adding methyl group to cytosine, has an important role in the regulation of gene expression. DNA methylation is known to be associated with gene transcription by interfering with DNA-binding proteins, such as transcription factors. DNA methylation is closely related to tumorigenesis, and the methylation state of some genes can be used as a biomarker for tumorigenesis. Aberrant DNA methylation of genomic regions, including CpG islands, CpG shores, and first exons, is related to the altered gene expression pattern characteristics of all human cancers. Subheading 1 surveys recent developments on DNA methylation and gene expressions in cancer. Then we provide analysis of DNA methylation and gene expression in 30 breast cancer cell lines representing different tumor phenotypes. This study conducted an integrated analysis to identify the relationship between DNA methylation in various genomic regions and expression levels of downstream genes, using MethylCapseq data (affinity purification followed by next-generation sequencing of eluted DNA) and Affymetrix gene expression microarray data. The goal of this study was to assess genome-wide methylation profiles associated with different molecular subtypes of human breast cancer (luminal, basal A, and basal B) and to comprehensively investigate the effect of DNA methylation on gene expression in breast cancer phenotypes. This showed that methylation of genomic regions near transcription start sites, CpG island, CpG shore, and first exon was strongly associated with gene repression, and the effects of the regions on gene expression patterns were different for different molecular subtypes of breast cancer. The results further indicated that aberrant methylation of specific genomic regions was significantly associated with different breast cancer subtypes.

  7. Optimal Control for Fast and Robust Generation of Entangled States in Anisotropic Heisenberg Chains

    Science.gov (United States)

    Zhang, Xiong-Peng; Shao, Bin; Zou, Jian

    2017-05-01

    Motivated by some recent results of the optimal control (OC) theory, we study anisotropic XXZ Heisenberg spin-1/2 chains with control fields acting on a single spin, with the aim of exploring how maximally entangled state can be prepared. To achieve the goal, we use a numerical optimization algorithm (e.g., the Krotov algorithm, which was shown to be capable of reaching the quantum speed limit) to search an optimal set of control parameters, and then obtain OC pulses corresponding to the target fidelity. We find that the minimum time for implementing our target state depending on the anisotropy parameter Δ of the model. Finally, we analyze the robustness of the obtained results for the optimal fidelities and the effectiveness of the Krotov method under some realistic conditions.

  8. Optimal Control for Fast and Robust Generation of Entangled States in Anisotropic Heisenberg Chains

    Science.gov (United States)

    Zhang, Xiong-Peng; Shao, Bin; Zou, Jian

    2017-02-01

    Motivated by some recent results of the optimal control (OC) theory, we study anisotropic XXZ Heisenberg spin-1/2 chains with control fields acting on a single spin, with the aim of exploring how maximally entangled state can be prepared. To achieve the goal, we use a numerical optimization algorithm (e.g., the Krotov algorithm, which was shown to be capable of reaching the quantum speed limit) to search an optimal set of control parameters, and then obtain OC pulses corresponding to the target fidelity. We find that the minimum time for implementing our target state depending on the anisotropy parameter Δ of the model. Finally, we analyze the robustness of the obtained results for the optimal fidelities and the effectiveness of the Krotov method under some realistic conditions.

  9. 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.

  10. On the Generation of a Robust Residual for Closed-loopControl systems that Exhibit Sensor Faults

    DEFF Research Database (Denmark)

    Alavi, Seyed Mohammad Mahdi; Izadi-Zamanabadi, Roozbeh; Hayes, Martin J.

    2007-01-01

    This paper presents a novel design methodology, based on shaping the system frequency response, for the generation of an appropriate residual signal that is sensitive to sensor faults in the presence of model uncertainty and exogenous unknown (unmeasured) disturbances. An integrated feedback...... controller design and robust frequency-based fault detection approach is proposed for Single-Input/Single-Output systems. The effciency of the proposed method is demonstrated on a Single Machine Innite Bus (SMIB) power system that achieves a coordinate power system stabilizer with satisfactory sensor fault...

  11. Robust alignment of chromatograms by statistically analyzing the shifts matrix generated by moving window fast Fourier transform cross-correlation.

    Science.gov (United States)

    Zhang, Mingjing; Wen, Ming; Zhang, Zhi-Min; Lu, Hongmei; Liang, Yizeng; Zhan, Dejian

    2015-03-01

    Retention time shift is one of the most challenging problems during the preprocessing of massive chromatographic datasets. Here, an improved version of the moving window fast Fourier transform cross-correlation algorithm is presented to perform nonlinear and robust alignment of chromatograms by analyzing the shifts matrix generated by moving window procedure. The shifts matrix in retention time can be estimated by fast Fourier transform cross-correlation with a moving window procedure. The refined shift of each scan point can be obtained by calculating the mode of corresponding column of the shifts matrix. This version is simple, but more effective and robust than the previously published moving window fast Fourier transform cross-correlation method. It can handle nonlinear retention time shift robustly if proper window size has been selected. The window size is the only one parameter needed to adjust and optimize. The properties of the proposed method are investigated by comparison with the previous moving window fast Fourier transform cross-correlation and recursive alignment by fast Fourier transform using chromatographic datasets. The pattern recognition results of a gas chromatography mass spectrometry dataset of metabolic syndrome can be improved significantly after preprocessing by this method. Furthermore, the proposed method is available as an open source package at https://github.com/zmzhang/MWFFT2.

  12. Quantitative PCR for glucose transporter and tristetraprolin family gene expression in cultured mouse adipocytes and macrophages.

    Science.gov (United States)

    Cao, Heping; Cao, Fangping; Roussel, Anne-Marie; Anderson, Richard A

    2013-12-01

    Quantitative real-time PCR (qPCR) such as TaqMan and SYBR Green qPCR are widely used for gene expression analysis. The drawbacks of SYBR Green assay are that the dye binds to any double-stranded DNA which can generate false-positive signals and that the length of the amplicon affects the intensity of the amplification. Previous results demonstrate that TaqMan assay is more sensitive but generates lower calculated expression levels than SYBR Green assay in quantifying seven mRNAs in tung tree tissues. The objective of this study is to expand the analysis using animal cells. We compared both qPCR assays for quantifying 24 mRNAs including those coding for glucose transporter (Glut) and mRNA-binding protein tristetraprolin (TTP) in mouse 3T3-L1 adipocytes and RAW264.7 macrophages. The results showed that SYBR Green and TaqMan qPCR were reliable for quantitative gene expression in animal cells. This result was supported by validation analysis of Glut and TTP family gene expression. However, SYBR Green qPCR overestimated the expression levels in most of the genes tested. Finally, both qPCR instruments (Bio-Rad's CFX96 real-time system and Applied Biosystems' Prism 7700 real-time PCR instrument) generated similar gene expression profiles in the mouse cells. These results support the conclusion that both qPCR assays (TaqMan and SYBR Green qPCR) and both qPCR instruments (Bio-Rad's CFX96 real-time system and Applied Biosystems' Prism 7700 real-time PCR instrument) are reliable for quantitative gene expression analyses in animal cells but SYBR Green qPCR generally overestimates gene expression levels than TaqMan qPCR.

  13. Robustness of muscle synergies underlying three-dimensional force generation at the hand in healthy humans

    Science.gov (United States)

    Rymer, William Z.; Beer, Randall F.

    2012-01-01

    Previous studies using advanced matrix factorization techniques have shown that the coordination of human voluntary limb movements may be accomplished using combinations of a small number of intermuscular coordination patterns, or muscle synergies. However, the potential use of muscle synergies for isometric force generation has been evaluated mostly using correlational methods. The results of such studies suggest that fixed relationships between the activations of pairs of muscles are relatively rare. There is also emerging evidence that the nervous system uses independent strategies to control movement and force generation, which suggests that one cannot conclude a priori that isometric force generation is accomplished by combining muscle synergies, as shown in movement control. In this study, we used non-negative matrix factorization to evaluate the ability of a few muscle synergies to reconstruct the activation patterns of human arm muscles underlying the generation of three-dimensional (3-D) isometric forces at the hand. Surface electromyographic (EMG) data were recorded from eight key elbow and shoulder muscles during 3-D force target-matching protocols performed across a range of load levels and hand positions. Four synergies were sufficient to explain, on average, 95% of the variance in EMG datasets. Furthermore, we found that muscle synergy composition was conserved across biomechanical task conditions, experimental protocols, and subjects. Our findings are consistent with the view that the nervous system can generate isometric forces by assembling a combination of a small number of muscle synergies, differentially weighted according to task constraints. PMID:22279190

  14. Dynamic Post-Transcriptional Regulation of HIV-1 Gene Expression

    Science.gov (United States)

    Kula, Anna; Marcello, Alessandro

    2012-01-01

    Gene expression of the human immunodeficiency virus type 1 (HIV-1) is a highly regulated process. Basal transcription of the integrated provirus generates early transcripts that encode for the viral products Tat and Rev. Tat promotes the elongation of RNA polymerase while Rev mediates the nuclear export of viral RNAs that contain the Rev-responsive RNA element (RRE). These RNAs are exported from the nucleus to allow expression of Gag-Pol and Env proteins and for the production of full-length genomic RNAs. A balance exists between completely processed mRNAs and RRE-containing RNAs. Rev functions as an adaptor that recruits cellular factors to re-direct singly spliced and unspliced viral RNAs to nuclear export. The aim of this review is to address the dynamic regulation of this post-transcriptional pathway in light of recent findings that implicate several novel cellular cofactors of Rev function. PMID:24832221

  15. Dynamic Post-Transcriptional Regulation of HIV-1 Gene Expression

    Directory of Open Access Journals (Sweden)

    Alessandro Marcello

    2012-07-01

    Full Text Available Gene expression of the human immunodeficiency virus type 1 (HIV-1 is a highly regulated process. Basal transcription of the integrated provirus generates early transcripts that encode for the viral products Tat and Rev. Tat promotes the elongation of RNA polymerase while Rev mediates the nuclear export of viral RNAs that contain the Rev-responsive RNA element (RRE. These RNAs are exported from the nucleus to allow expression of Gag-Pol and Env proteins and for the production of full-length genomic RNAs. A balance exists between completely processed mRNAs and RRE-containing RNAs. Rev functions as an adaptor that recruits cellular factors to re-direct singly spliced and unspliced viral RNAs to nuclear export. The aim of this review is to address the dynamic regulation of this post-transcriptional pathway in light of recent findings that implicate several novel cellular cofactors of Rev function.

  16. Data Preprocessing in Cluster Analysis of Gene Expression

    Institute of Scientific and Technical Information of China (English)

    杨春梅; 万柏坤; 高晓峰

    2003-01-01

    Considering that the DNA microarray technology has generated explosive gene expression data and that it is urgent to analyse and to visualize such massive datasets with efficient methods, we investigate the data preprocessing methods used in cluster analysis, normalization or logarithm of the matrix, by using hierarchical clustering, principal component analysis (PCA) and self-organizing maps (SOMs). The results illustrate that when using the Euclidean distance as measuring metrics, logarithm of relative expression level is the best preprocessing method, while data preprocessed by normalization cannot attain the expected results because the data structure is ruined. If there are only a few principal components, the PCA is an effective method to extract the frame structure, while SOMs are more suitable for a specific structure.

  17. 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.

  18. Robust generation of high-fidelity entangled states for multiple atoms

    Institute of Scientific and Technical Information of China (English)

    Lin Li-Hua

    2009-01-01

    A scheme is presented for generating entangled states of multiple atoms in a cavity. In the scheme the atoms simultaneously interact with a cavity mode, with the first atom driven by two classical fields and the other atoms driven by a classical field. Our scheme is valid even if the cavity decay rate is larger than the effective coupling strength, which is important for experiment. The generation of entangled states is conditional on the detection of a photon decaying from the cavity and thus the fidelity of the entangled state is insensitive to the detection inefficiency. Furthermore, the scheme can be applied to the case with any number of atoms in principle.

  19. Stochastic fluctuations and distributed control of gene expression impact cellular memory.

    Directory of Open Access Journals (Sweden)

    Guillaume Corre

    Full Text Available Despite the stochastic noise that characterizes all cellular processes the cells are able to maintain and transmit to their daughter cells the stable level of gene expression. In order to better understand this phenomenon, we investigated the temporal dynamics of gene expression variation using a double reporter gene model. We compared cell clones with transgenes coding for highly stable mRNA and fluorescent proteins with clones expressing destabilized mRNA-s and proteins. Both types of clones displayed strong heterogeneity of reporter gene expression levels. However, cells expressing stable gene products produced daughter cells with similar level of reporter proteins, while in cell clones with short mRNA and protein half-lives the epigenetic memory of the gene expression level was completely suppressed. Computer simulations also confirmed the role of mRNA and protein stability in the conservation of constant gene expression levels over several cell generations. These data indicate that the conservation of a stable phenotype in a cellular lineage may largely depend on the slow turnover of mRNA-s and proteins.

  20. The diagnosis of inherited metabolic diseases by microarray gene expression profiling

    Directory of Open Access Journals (Sweden)

    Taanman Jan-Willem

    2010-12-01

    Full Text Available Abstract Background Inherited metabolic diseases (IMDs comprise a diverse group of generally progressive genetic metabolic disorders of variable clinical presentations and severity. We have undertaken a study using microarray gene expression profiling of cultured fibroblasts to investigate 68 patients with a broad range of suspected metabolic disorders, including defects of lysosomal, mitochondrial, peroxisomal, fatty acid, carbohydrate, amino acid, molybdenum cofactor, and purine and pyrimidine metabolism. We aimed to define gene expression signatures characteristic of defective metabolic pathways. Methods Total mRNA extracted from cultured fibroblast cell lines was hybridized to Affymetrix U133 Plus 2.0 arrays. Expression data was analyzed for the presence of a gene expression signature characteristic of an inherited metabolic disorder and for genes expressing significantly decreased levels of mRNA. Results No characteristic signatures were found. However, in 16% of cases, disease-associated nonsense and frameshift mutations generating premature termination codons resulted in significantly decreased mRNA expression of the defective gene. The microarray assay detected these changes with high sensitivity and specificity. Conclusion In patients with a suspected familial metabolic disorder where initial screening tests have proven uninformative, microarray gene expression profiling may contribute significantly to the identification of the genetic defect, shortcutting the diagnostic cascade.

  1. 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...

  2. Gene expression analysis of dendritic/Langerhans cells and Langerhans cell histiocytosis

    NARCIS (Netherlands)

    Rust, Renata; Kluiver, J.; Visser, Lydia; Harms, G.; Blokzijl, T.; Kamps, W.A.; Poppema, Sibrand; van den Berg, Anke

    2006-01-01

    Langerhans cell histiocytosis (LCH) is a neoplastic disorder that results in clonal proliferation of cells with a Langerhans cell (LQ phenotype. The pathogenesis of LCH is still poorly understood. In the present study, serial analysis of gene expression (SAGE) was applied to LCs generated from umbil

  3. Pregnancy-induced gene expression changes in vivo among women with rheumatoid arthritis

    DEFF Research Database (Denmark)

    Goin, Dana E; Smed, Mette Kiel; Pachter, Lior

    2017-01-01

    observed among women with RA who worsen during pregnancy (pregDASworse). METHODS: Global gene expression profiles were generated by RNA sequencing (RNA-seq) from 11 women with RA and 5 healthy women before pregnancy (T0) and at the third trimester (T3). Among the women with RA, eight showed an improvement...

  4. Fast and Robust pointing and tracking using a second-generation star tracker

    DEFF Research Database (Denmark)

    Jørgensen, John Leif; Pickles, Andrew

    1998-01-01

    Second generation star trackers work by taking wide-angle optical pictures of star fields, correlating the image against a star catalogue in ROM, centroiding many stars to derive an accurate position and orientation. This paper describes a miniature instrument(10cm cube), fast and lightweight (85...

  5. 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.

  6. 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.

  7. 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.

  8. Computation of a Reference Model for Robust Fault Detection and Isolation Residual Generation

    Directory of Open Access Journals (Sweden)

    Emmanuel Mazars

    2008-01-01

    Full Text Available This paper considers matrix inequality procedures to address the robust fault detection and isolation (FDI problem for linear time-invariant systems subject to disturbances, faults, and polytopic or norm-bounded uncertainties. We propose a design procedure for an FDI filter that aims to minimize a weighted combination of the sensitivity of the residual signal to disturbances and modeling errors, and the deviation of the faults to residual dynamics from a fault to residual reference model, using the ℋ∞-norm as a measure. A key step in our procedure is the design of an optimal fault reference model. We show that the optimal design requires the solution of a quadratic matrix inequality (QMI optimization problem. Since the solution of the optimal problem is intractable, we propose a linearization technique to derive a numerically tractable suboptimal design procedure that requires the solution of a linear matrix inequality (LMI optimization. A jet engine example is employed to demonstrate the effectiveness of the proposed approach.

  9. Can Targeted Intervention Mitigate Early Emotional and Behavioral Problems?: Generating Robust Evidence within Randomized Controlled Trials.

    Directory of Open Access Journals (Sweden)

    Orla Doyle

    Full Text Available This study examined the impact of a targeted Irish early intervention program on children's emotional and behavioral development using multiple methods to test the robustness of the results. Data on 164 Preparing for Life participants who were randomly assigned into an intervention group, involving home visits from pregnancy onwards, or a control group, was used to test the impact of the intervention on Child Behavior Checklist scores at 24-months. Using inverse probability weighting to account for differential attrition, permutation testing to address small sample size, and quantile regression to characterize the distributional impact of the intervention, we found that the few treatment effects were largely concentrated among boys most at risk of developing emotional and behavioral problems. The average treatment effect identified a 13% reduction in the likelihood of falling into the borderline clinical threshold for Total Problems. The interaction and subgroup analysis found that this main effect was driven by boys. The distributional analysis identified a 10-point reduction in the Externalizing Problems score for boys at the 90th percentile. No effects were observed for girls or for the continuous measures of Total, Internalizing, and Externalizing problems. These findings suggest that the impact of this prenatally commencing home visiting program may be limited to boys experiencing the most difficulties. Further adoption of the statistical methods applied here may help to improve the internal validity of randomized controlled trials and contribute to the field of evaluation science more generally.ISRCTN Registry ISRCTN04631728.

  10. Gene expression in honey bee (Apis mellifera) larvae exposed to pesticides and Varroa mites (Varroa destructor).

    Science.gov (United States)

    Gregorc, Aleš; Evans, Jay D; Scharf, Mike; Ellis, James D

    2012-08-01

    Honey bee (Apis mellifera) larvae reared in vitro were exposed to one of nine pesticides and/or were challenged with the parasitic mite, Varroa destructor. Total RNA was extracted from individual larvae and first strand cDNAs were generated. Gene-expression changes in larvae were measured using quantitative PCR (qPCR) targeting transcripts for pathogens and genes involved in physiological processes, bee health, immunity, and/or xenobiotic detoxification. Transcript levels for Peptidoglycan Recognition Protein (PGRPSC), a pathogen recognition gene, increased in larvae exposed to Varroa mites (Ppesticide treated larvae. As expected, Varroa-parasitized brood had higher transcripts of Deformed Wing Virus than did control larvae (Ppesticides and Varroa parasitism on honey bee larval gene expression were demonstrated. Interactions between larval treatments and gene expression for the targeted genes are discussed.

  11. Visualization of the Dynamics of Gene Expression in the Living Mouse

    Directory of Open Access Journals (Sweden)

    Amy Ryan

    2004-01-01

    Full Text Available Reporter genes can monitor the status and activity of recombinant genomes in a diverse array of organisms, from bacteria and yeast to plants and animals. We have combined luciferase reporter genes with a conditional gene expression system based on regulatory elements from the lac Operon of Escherichia coli to visualize the dynamics of gene expression in realtime in the living mouse. Using this technology, we have determined the rate of gene induction and repression, the level of target gene activity in response to different doses of inducer, and the schedule of induction during early embryogenesis of both the endogenous and the experimentally manipulated programs of mammalian gene expression associated with the HD/Hdh locus. The combination of in vivo imaging and lac regulation is a powerful tool for generating conditional transgenic mice that can be screened rapidly for optimal regulation and expression patterns, and for monitoring the induction and repression of regulated genes noninvasively in the living animal.

  12. A Bistable Switch and Anatomical Site Control Vibrio cholerae Virulence Gene Expression in the Intestine

    DEFF Research Database (Denmark)

    Nielsen, Alex Toftgaard; Dolganov, N. A.; Rasmussen, Thomas

    2010-01-01

    A fundamental, but unanswered question in host-pathogen interactions is the timing, localization and population distribution of virulence gene expression during infection. Here, microarray and in situ single cell expression methods were used to study Vibrio cholerae growth and virulence gene...... expression during infection of the rabbit ligated ileal loop model of cholera. Genes encoding the toxin-coregulated pilus (TCP) and cholera toxin (CT) were powerfully expressed early in the infectious process in bacteria adjacent to epithelial surfaces. Increased growth was found to co...... into artificial seawater, bacterial aggregates continued to express tcpA for prolonged periods of time. The bistable control of virulence gene expression points to a mechanism that could generate a subpopulation of V. cholerae that continues to produce TCP and CT in the rice water stools of cholera patients....

  13. Gene expression profiling during intensive cardiovascular lifestyle modification: Relationships with vascular function and weight loss

    Directory of Open Access Journals (Sweden)

    Heather L. Blackburn

    2015-06-01

    Full Text Available Heart disease and related sequelae are a leading cause of death and healthcare expenditure throughout the world. Although many patients opt for surgical interventions, lifestyle modification programs focusing on nutrition and exercise have shown substantial health benefits and are becoming increasing popular. We conducted a year-long lifestyle modification program to mediate cardiovascular risk through traditional risk factors and to investigate how molecular changes, if present, may contribute to long-term risk reduction. Here we describe the lifestyle intervention, including clinical and molecular data collected, and provide details of the experimental methods and quality control parameters for the gene expression data generated from participants and non-intervention controls. Our findings suggest successful and sustained modulation of gene expression through healthy lifestyle changes may have beneficial effects on vascular health that cannot be discerned from traditional risk factor profiles. The data are deposited in the Gene Expression Omnibus, series GSE46097 and GSE66175.

  14. 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.

  15. Cross-talk between signaling pathways can generate robust oscillations in calcium and cAMP.

    Directory of Open Access Journals (Sweden)

    Fernando Siso-Nadal

    Full Text Available BACKGROUND: To control and manipulate cellular signaling, we need to understand cellular strategies for information transfer, integration, and decision-making. A key feature of signal transduction is the generation of only a few intracellular messengers by many extracellular stimuli. METHODOLOGY/PRINCIPAL FINDINGS: Here we model molecular cross-talk between two classic second messengers, cyclic AMP (cAMP and calcium, and show that the dynamical complexity of the response of both messengers increases substantially through their interaction. In our model of a non-excitable cell, both cAMP and calcium concentrations can oscillate. If mutually inhibitory, cross-talk between the two second messengers can increase the range of agonist concentrations for which oscillations occur. If mutually activating, cross-talk decreases the oscillation range, but can generate 'bursting' oscillations of calcium and may enable better filtering of noise. CONCLUSION: We postulate that this increased dynamical complexity allows the cell to encode more information, particularly if both second messengers encode signals. In their native environments, it is unlikely that cells are exposed to one stimulus at a time, and cross-talk may help generate sufficiently complex responses to allow the cell to discriminate between different combinations and concentrations of extracellular agonists.

  16. 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

  17. 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

  18. 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

  19. Differential gene expression before and after ionizing radiation of subcutaneous fibroblasts identifies breast cancer patients resistant to radiation-induced fibrosis

    DEFF Research Database (Denmark)

    Alsner, Jan; Rødningen, Olaug K.; Overgaard, Jens

    2007-01-01

    -induced changes in gene expression in fibroblasts, whether differential expression is more pronounced when looking at the fold induction levels, taking into account the differences in background expression levels between patients, and whether there is a linear correlation between individual risk of RIF...... and changes in radiation-induced gene expression in fibroblasts. MATERIAL AND METHODS: Gene expression was analysed by quantitative real-time PCR before and after a fractionated scheme with 3x3.5Gy/3 days in fibroblasts derived from 26 patients with breast cancer treated with post-mastectomy radiotherapy....... RESULTS: Robust radiation-induced changes in gene expression were observed, with differential gene expression between low and high risk patients being most pronounced for the fold induction level ('after' value divided by 'before' value for each patient). When including patients with intermediate risk...

  20. Differential gene expression before and after ionizing radiation of subcutaneous fibroblasts identifies breast cancer patients resistant to radiation-induced fibrosis

    DEFF Research Database (Denmark)

    Alsner, Jan; Rødningen, Olaug K.; Overgaard, Jens

    2007-01-01

    -induced changes in gene expression in fibroblasts, whether differential expression is more pronounced when looking at the fold induction levels, taking into account the differences in background expression levels between patients, and whether there is a linear correlation between individual risk of RIF...... and changes in radiation-induced gene expression in fibroblasts. MATERIAL AND METHODS: Gene expression was analysed by quantitative real-time PCR before and after a fractionated scheme with 3x3.5Gy/3 days in fibroblasts derived from 26 patients with breast cancer treated with post-mastectomy radiotherapy....... RESULTS: Robust radiation-induced changes in gene expression were observed, with differential gene expression between low and high risk patients being most pronounced for the fold induction level ('after' value divided by 'before' value for each patient). When including patients with intermediate risk...

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

    Directory of Open Access Journals (Sweden)

    Vanderburg Charles R

    2009-01-01

    Full Text Available Abstract Background Gene microarray technology is an effective tool to investigate the simultaneous activity of multiple cellular pathways from hundreds to thousands of genes. However, because data in the colossal amounts generated by DNA microarray technology are usually complex, noisy, high-dimensional, and often hindered by low statistical power, their exploitation is difficult. To overcome these problems, two kinds of unsupervised analysis methods for microarray data: principal component analysis (PCA and independent component analysis (ICA have been developed to accomplish the task. PCA projects the data into a new space spanned by the principal components that are mutually orthonormal to each other. The constraint of mutual orthogonality and second-order statistics technique within PCA algorithms, however, may not be applied to the biological systems studied. Extracting and characterizing the most informative features of the biological signals, however, require higher-order statistics. Results ICA is one of the unsupervised algorithms that can extract higher-order statistical structures from data and has been applied to DNA microarray gene expression data analysis. We performed FastICA method on DNA microarray gene expression data from Alzheimer's disease (AD hippocampal tissue samples and consequential gene clustering. Experimental results showed that the ICA method can improve the clustering results of AD samples and identify significant genes. More than 50 significant genes with high expression levels in severe AD were extracted, representing immunity-related protein, metal-related protein, membrane protein, lipoprotein, neuropeptide, cytoskeleton protein, cellular binding protein, and ribosomal protein. Within the aforementioned categories, our method also found 37 significant genes with low expression levels. Moreover, it is worth noting that some oncogenes and phosphorylation-related proteins are expressed in low levels. In

  2. 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.

  3. Robust Current Control of Doubly Fed Wind Turbine Generator under Unbalanced Grid Voltage Conditions

    DEFF Research Database (Denmark)

    Wang, Yun; Gong, Wenming; Wu, Qiuwei

    2014-01-01

    This paper presents the design of a H ∞ current controller for doubly fed induction generators (DFIGs) in order to maintain stable operation under unbalanced voltage conditions. The H ∞ current controller has a multi-input and multi-output (MIMO) structure and is designed using the loop shaping...... method. Case studies have been carried out in order to verify the efficacy of the proposed H ∞ current controller for DFIGs. The case study results show that the proposed H ∞ current controller can realize different control objectives, i.e. stable stator current, stable stator active power and stable...

  4. 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.

  5. 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.

  6. 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.

  7. 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.

  8. 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)

  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. 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%.

  11. Differential gene expression during Trypanosoma cruzi metacyclogenesis

    Directory of Open Access Journals (Sweden)

    Marco Aurelio Krieger

    1999-09-01

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

  12. Flexible and Robust Thermoelectric Generators Based on All-Carbon Nanotube Yarn without Metal Electrodes.

    Science.gov (United States)

    Choi, Jaeyoo; Jung, Yeonsu; Yang, Seung Jae; Oh, Jun Young; Oh, Jinwoo; Jo, Kiyoung; Son, Jeong Gon; Moon, Seung Eon; Park, Chong Rae; Kim, Heesuk

    2017-08-22

    As practical interest in flexible/or wearable power-conversion devices increases, the demand for high-performance alternatives to thermoelectric (TE) generators based on brittle inorganic materials is growing. Herein, we propose a flexible and ultralight TE generator (TEG) based on carbon nanotube yarn (CNTY) with excellent TE performance. The as-prepared CNTY shows a superior electrical conductivity of 3147 S/cm due to increased longitudinal carrier mobility derived from a highly aligned structure. Our TEG is innovative in that the CNTY acts as multifunctions in the same device. The CNTY is alternatively doped into n- and p-types using polyethylenimine and FeCl3, respectively. The highly conductive CNTY between the doped regions is used as electrodes to minimize the circuit resistance, thereby forming an all-carbon TEG without additional metal deposition. A flexible TEG based on 60 pairs of n- and p-doped CNTY shows the maximum power density of 10.85 and 697 μW/g at temperature differences of 5 and 40 K, respectively, which are the highest values among reported TEGs based on flexible materials. We believe that the strategy proposed here to improve the power density of flexible TEG by introducing highly aligned CNTY and designing a device without metal electrodes shows great potential for the flexible/or wearable power-conversion devices.

  13. Next-generation libraries for robust RNA interference-based genome-wide screens.

    Science.gov (United States)

    Kampmann, Martin; Horlbeck, Max A; Chen, Yuwen; Tsai, Jordan C; Bassik, Michael C; Gilbert, Luke A; Villalta, Jacqueline E; Kwon, S Chul; Chang, Hyeshik; Kim, V Narry; Weissman, Jonathan S

    2015-06-30

    Genetic screening based on loss-of-function phenotypes is a powerful discovery tool in biology. Although the recent development of clustered regularly interspaced short palindromic repeats (CRISPR)-based screening approaches in mammalian cell culture has enormous potential, RNA interference (RNAi)-based screening remains the method of choice in several biological contexts. We previously demonstrated that ultracomplex pooled short-hairpin RNA (shRNA) libraries can largely overcome the problem of RNAi off-target effects in genome-wide screens. Here, we systematically optimize several aspects of our shRNA library, including the promoter and microRNA context for shRNA expression, selection of guide strands, and features relevant for postscreen sample preparation for deep sequencing. We present next-generation high-complexity libraries targeting human and mouse protein-coding genes, which we grouped into 12 sublibraries based on biological function. A pilot screen suggests that our next-generation RNAi library performs comparably to current CRISPR interference (CRISPRi)-based approaches and can yield complementary results with high sensitivity and high specificity.

  14. A robust high throughput platform to generate functional recombinant monoclonal antibodies using rabbit B cells from peripheral blood.

    Directory of Open Access Journals (Sweden)

    Stefan Seeber

    Full Text Available We have developed a robust platform to generate and functionally characterize rabbit-derived antibodies using B cells from peripheral blood. The rapid high throughput procedure generates a diverse set of antibodies, yet requires only few animals to be immunized without the need to sacrifice them. The workflow includes (i the identification and isolation of single B cells from rabbit blood expressing IgG antibodies, (ii an elaborate short term B-cell cultivation to produce sufficient monoclonal antigen specific IgG for comprehensive phenotype screens, (iii the isolation of VH and VL coding regions via PCR from B-cell clones producing antigen specific and functional antibodies followed by the sequence determination, and (iv the recombinant expression and purification of IgG antibodies. The fully integrated and to a large degree automated platform (demonstrated in this paper using IL1RL1 immunized rabbits yielded clonal and very diverse IL1RL1-specific and functional IL1RL1-inhibiting rabbit antibodies. These functional IgGs from individual animals were obtained at a short time range after immunization and could be identified already during primary screening, thus substantially lowering the workload for the subsequent B-cell PCR workflow. Early availability of sequence information permits one to select early-on function- and sequence-diverse antibodies for further characterization. In summary, this powerful technology platform has proven to be an efficient and robust method for the rapid generation of antigen specific and functional monoclonal rabbit antibodies without sacrificing the immunized animal.

  15. A robust high throughput platform to generate functional recombinant monoclonal antibodies using rabbit B cells from peripheral blood.

    Science.gov (United States)

    Seeber, Stefan; Ros, Francesca; Thorey, Irmgard; Tiefenthaler, Georg; Kaluza, Klaus; Lifke, Valeria; Fischer, Jens André Alexander; Klostermann, Stefan; Endl, Josef; Kopetzki, Erhard; Pashine, Achal; Siewe, Basile; Kaluza, Brigitte; Platzer, Josef; Offner, Sonja

    2014-01-01

    We have developed a robust platform to generate and functionally characterize rabbit-derived antibodies using B cells from peripheral blood. The rapid high throughput procedure generates a diverse set of antibodies, yet requires only few animals to be immunized without the need to sacrifice them. The workflow includes (i) the identification and isolation of single B cells from rabbit blood expressing IgG antibodies, (ii) an elaborate short term B-cell cultivation to produce sufficient monoclonal antigen specific IgG for comprehensive phenotype screens, (iii) the isolation of VH and VL coding regions via PCR from B-cell clones producing antigen specific and functional antibodies followed by the sequence determination, and (iv) the recombinant expression and purification of IgG antibodies. The fully integrated and to a large degree automated platform (demonstrated in this paper using IL1RL1 immunized rabbits) yielded clonal and very diverse IL1RL1-specific and functional IL1RL1-inhibiting rabbit antibodies. These functional IgGs from individual animals were obtained at a short time range after immunization and could be identified already during primary screening, thus substantially lowering the workload for the subsequent B-cell PCR workflow. Early availability of sequence information permits one to select early-on function- and sequence-diverse antibodies for further characterization. In summary, this powerful technology platform has proven to be an efficient and robust method for the rapid generation of antigen specific and functional monoclonal rabbit antibodies without sacrificing the immunized animal.

  16. A destabilized bacterial luciferase for dynamic gene expression studies

    Science.gov (United States)

    Allen, Michael S.; Wilgus, John R.; Chewning, Christopher S.; Sayler, Gary S.

    2006-01-01

    Fusions of genetic regulatory elements with reporter genes have long been used as tools for monitoring gene expression and have become a major component in synthetic gene circuit implementation. A major limitation of many of these systems is the relatively long half-life of the reporter protein(s), which prevents monitoring both the initiation and the termination of transcription in real-time. Furthermore, when used as components in synthetic gene circuits, the long time constants associated with reporter protein decay may significantly degrade circuit performance. In this study, short half-life variants of LuxA and LuxB from Photorhabdus luminescens were constructed in Escherichia coli by inclusion of an 11-amino acid carboxy-terminal tag that is recognized by endogenous tail-specific proteases. Results indicated that the addition of the C-terminal tag affected the functional half-life of the holoenzyme when the tag was added to luxA or to both luxA and luxB, but modification of luxB alone did not have a significant effect. In addition, it was also found that alteration of the terminal three amino acid residues of the carboxy-terminal tag fused to LuxA generated variants with half-lives of intermediate length in a manner similar to that reported for GFP. This report is the first instance of the C-terminal tagging approach for the regulation of protein half-life to be applied to an enzyme or monomer of a multi-subunit enzyme complex and will extend the utility of the bacterial luciferase reporter genes for the monitoring of dynamic changes in gene expression. PMID:19003433

  17. Transcriptome database resource and gene expression atlas for the rose

    Directory of Open Access Journals (Sweden)

    Dubois Annick

    2012-11-01

    Full Text Available Abstract Background For centuries roses have been selected based on a number of traits. Little information exists on the genetic and molecular basis that contributes to these traits, mainly because information on expressed genes for this economically important ornamental plant is scarce. Results Here, we used a combination of Illumina and 454 sequencing technologies to generate information on Rosa sp. transcripts using RNA from various tissues and in response to biotic and abiotic stresses. A total of 80714 transcript clusters were identified and 76611 peptides have been predicted among which 20997 have been clustered into 13900 protein families. BLASTp hits in closely related Rosaceae species revealed that about half of the predicted peptides in the strawberry and peach genomes have orthologs in Rosa dataset. Digital expression was obtained using RNA samples from organs at different development stages and under different stress conditions. qPCR validated the digital expression data for a selection of 23 genes with high or low expression levels. Comparative gene expression analyses between the different tissues and organs allowed the identification of clusters that are highly enriched in given tissues or under particular conditions, demonstrating the usefulness of the digital gene expression analysis. A web interface ROSAseq was created that allows data interrogation by BLAST, subsequent analysis of DNA clusters and access to thorough transcript annotation including best BLAST matches on Fragaria vesca, Prunus persica and Arabidopsis. The rose peptides dataset was used to create the ROSAcyc resource pathway database that allows access to the putative genes and enzymatic pathways. Conclusions The study provides useful information on Rosa expressed genes, with thorough annotation and an overview of expression patterns for transcripts with good accuracy.

  18. Evolution of robust circadian clocks in Drosophila melanogaster populations reared in constant dark for over 330 generations

    Science.gov (United States)

    Shindey, Radhika; Varma, Vishwanath; Nikhil, K. L.; Sharma, Vijay Kumar

    2016-10-01

    Robustness is considered to be an important feature of biological systems which may evolve when the functionality of a trait is associated with higher fitness across multiple environmental conditions. Thus, the ability to maintain stable biological phenotypes across environments is thought to be of adaptive value. Previously, we have reported higher intrinsic activity levels (activity levels of free-running rhythm in constant darkness) and power of rhythm (as assessed by amplitude of the periodogram) in Drosophila melanogaster populations (stocks) reared in constant darkness (DD stocks) as compared to those reared in constant light (LL stocks) and 12:12-h light-dark cycles (LD stocks) for over 19 years (˜330 generations). In the current study, we intended to examine whether the enhanced levels of activity observed in DD stocks persist under various environments such as photoperiods, ambient temperatures, non-24-h light-dark (LD) cycles, and semi-natural conditions (SN). We found that DD stocks largely retain their phenotype of enhanced activity levels across most of the above-mentioned environments suggesting the evolution of robust circadian clocks in DD stocks. Furthermore, we compared the peak activity levels of the three stocks across different environmental conditions relative to their peaks in constant darkness and found that the change in peak activity levels upon entrainment was not significantly different across the three stocks for any of the examined environmental conditions. This suggests that the enhancement of activity levels in DD stocks is not due to differential sensitivity to environment. Thus, these results suggest that rearing in constant darkness (DD) leads to evolution of robust circadian clocks suggesting a possible adaptive value of possessing such rhythms under constant dark environments.

  19. 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

  20. 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

  1. 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...

  2. 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

  3. 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

  4. 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

  5. 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

  6. Building prognostic models for breast cancer patients using clinical variables and hundreds of gene expression signatures

    Directory of Open Access Journals (Sweden)

    Liu Yufeng

    2011-01-01

    Full Text Available Abstract Background Multiple breast cancer gene expression profiles have been developed that appear to provide similar abilities to predict outcome and may outperform clinical-pathologic criteria; however, the extent to which seemingly disparate profiles provide additive prognostic information is not known, nor do we know whether prognostic profiles perform equally across clinically defined breast cancer subtypes. We evaluated whether combining the prognostic powers of standard breast cancer clinical variables with a large set of gene expression signatures could improve on our ability to predict patient outcomes. Methods Using clinical-pathological variables and a collection of 323 gene expression "modules", including 115 previously published signatures, we build multivariate Cox proportional hazards models using a dataset of 550 node-negative systemically untreated breast cancer patients. Models predictive of pathological complete response (pCR to neoadjuvant chemotherapy were also built using this approach. Results We identified statistically significant prognostic models for relapse-free survival (RFS at 7 years for the entire population, and for the subgroups of patients with ER-positive, or Luminal tumors. Furthermore, we found that combined models that included both clinical and genomic parameters improved prognostication compared with models with either clinical or genomic variables alone. Finally, we were able to build statistically significant combined models for pathological complete response (pCR predictions for the entire population. Conclusions Integration of gene expression signatures and clinical-pathological factors is an improved method over either variable type alone. Highly prognostic models could be created when using all patients, and for the subset of patients with lymph node-negative and ER-positive breast cancers. Other variables beyond gene expression and clinical-pathological variables, like gene mutation status or DNA

  7. Neighbourhood continuity is not required for correct testis gene expression in Drosophila.

    Directory of Open Access Journals (Sweden)

    Lisa A Meadows

    Full Text Available It is now widely accepted that gene organisation in eukaryotic genomes is non-random and it is proposed that such organisation may be important for gene expression and genome evolution. In particular, the results of several large-scale gene expression analyses in a range of organisms from yeast to human indicate that sets of genes with similar tissue-specific or temporal expression profiles are clustered within the genome in gene expression neighbourhoods. While the existence of neighbourhoods is clearly established, the underlying reason for this facet of genome organisation is currently unclear and there is little experimental evidence that addresses the genomic requisites for neighbourhood organisation. We report the targeted disruption of three well-defined male-specific gene expression neighbourhoods in the Drosophila genome by the synthesis of precisely mapped chromosomal inversions. We compare gene expression in individuals carrying inverted chromosomes with their non-inverted but otherwise identical progenitors using whole-transcriptome microarray analysis, validating these data with specific quantitative real-time PCR assays. For each neighbourhood we generate and examine multiple inversions. We find no significant differences in the expression of genes that define each of the neighbourhoods. We further show that the inversions spatially separate both halves of a neighbourhood in the nucleus. Thus, models explaining neighbourhood organisation in terms of local sequence interactions, enhancer crosstalk, or short-range chromatin effects are unlikely to account for this facet of genome organisation. Our study challenges the notion that, at least in the case of the testis, expression neighbourhoods are a feature of eukaryotic genome organisation necessary for correct gene expression.

  8. A role for gene duplication and natural variation of gene expression in the evolution of metabolism.

    Directory of Open Access Journals (Sweden)

    Daniel J Kliebenstein

    Full Text Available BACKGROUND: Most eukaryotic genomes have undergone whole genome duplications during their evolutionary history. Recent studies have shown that the function of these duplicated genes can diverge from the ancestral gene via neo- or sub-functionalization within single genotypes. An additional possibility is that gene duplicates may also undergo partitioning of function among different genotypes of a species leading to genetic differentiation. Finally, the ability of gene duplicates to diverge may be limited by their biological function. METHODOLOGY/PRINCIPAL FINDINGS: To test these hypotheses, I estimated the impact of gene duplication and metabolic function upon intraspecific gene expression variation of segmental and tandem duplicated genes within Arabidopsis thaliana. In all instances, the younger tandem duplicated genes showed higher intraspecific gene expression variation than the average Arabidopsis gene. Surprisingly, the older segmental duplicates also showed evidence of elevated intraspecific gene expression variation albeit typically lower than for the tandem duplicates. The specific biological function of the gene as defined by metabolic pathway also modulated the level of intraspecific gene expression variation. The major energy metabolism and biosynthetic pathways showed decreased variation, suggesting that they are constrained in their ability to accumulate gene expression variation. In contrast, a major herbivory defense pathway showed significantly elevated intraspecific variation suggesting that it may be under pressure to maintain and/or generate diversity in response to fluctuating insect herbivory pressures. CONCLUSION: These data show that intraspecific variation in gene expression is facilitated by an interaction of gene duplication and biological activity. Further, this plays a role in controlling diversity of plant metabolism.

  9. The impact of gene expression analysis on evolving views of avian brain organization.

    Science.gov (United States)

    Montiel, Juan F; Molnár, Zoltán

    2013-11-01

    Recent studies have presented data on adult and developing avian brain organization. Jarvis et al. ([2013] J Comp Neurol. 521:3614-3665) identify four pallial and two subpallial gene expression domains and demonstrate that the mesopallium and adjoining divisions of the hyperpallium (hyperpallium intercalatum and hyperpallium densocellulare), have very similar gene expression profiles to each other, distinct from those of the nidopallium, the arcopallium, and the more distant divisions of the hyperpallium (hyperpallium apicale). The study proposes an update of the current nomenclature (Jarvis et al. [2005] Nat Rev Neurosci. 6:151-159). The authors perform densitometric quantifications of the in situ expression of 50 selected genes, use correlations of distances between vectors that represent these gene expression patterns within the 23 avian brain regions of their study, and group them according to similarity in their expression profiles. The generated cluster tree further supports their argument for a new terminology. The authors hypothesize that the mesopallium and adjoining divisions of the hyperpallium have a common developmental origin, and in the accompanying paper (Chen et al. [2013] J Comp Neurol. 521:3666-3701) show that these structures/subdivisions initially form continuous gene expression domains. With subsequent development these domains fold into distinct subdivisions in the dorsal and ventral avian pallium, forming mirror images to each other. Jarvis et al. ([2013] J Comp Neurol. 521:3614-3665) also demonstrate interesting principles of the functional organization of the avian brain by showing that specific sensory stimulation or motor behavior elicits gene expression in functional units perpendicular to the axis of the gene expression reversal and compare their arrangements and cell types with mammalian cortical columns.

  10. 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.

  11. Gene expression during development of fetal and adult Leydig cells.

    Science.gov (United States)

    Dong, Lei; Jelinsky, Scott A; Finger, Joshua N; Johnston, Daniel S; Kopf, Gregory S; Sottas, Chantal M; Hardy, Matthew P; Ge, Ren-Shan

    2007-12-01

    In rats and mice, Leydig cells are formed as two morphologically and functionally different generations. The first generation develops in utero, from undifferentiated stem Leydig cells (SLCs) that differentiate into fetal Leydig cells (FLCs). After birth, SLCs that may differ from the fetal SLCs undergo lineage-specific commitment and give rise to adult Leydig cells (ALCs). The intermediates of ALCs first become apparent by day 11 postpartum. These first-appearing intermediates, progenitor Leydig cells (PLCs), are spindle shaped and identifiable as steroidogenic because they express luteinizing hormone receptor (LHR) and 3beta-hydroxysteroid dehydrogenase (3betaHSD). The next step in the transition of PLCs to ALCs is the appearance of the immature Leydig cells (ILCs), most commonly seen in the testis during days 28 to 56 postpartum. ILCs have a more abundant smooth endoplasm reticulum (SER), the network of membranes providing a scaffold for steroidogenic enzyme localization, compared to PLCs, but are considered immature because they secrete higher levels of 5alpha-reduced androgen than testosterone. ILCs undergo a final division before ALC steroidogenic function matures by postnatal day 56. ALCs mark the point of maximum differentiation, and at this stage, the Leydig cell secretes testosterone at the highest rate. In this review, trends of gene expression during development of the two Leydig-cell generations, and recent information from gene profiling by microarray, are evaluated. The expression profiles are distinct, indicating that FLCs and ALCs may originate from separate pools of stem cells.

  12. 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

  13. 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

  14. 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.

  15. 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.

  16. 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

  17. Application of multidisciplinary analysis to gene expression.

    Energy Technology Data Exchange (ETDEWEB)

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

    2004-01-01

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

  18. Phenotypic plasticity and divergence in gene expression.

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    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?

  19. Modified PCR methods for 3' end amplification from serial analysis of gene expression (SAGE) tags.

    Science.gov (United States)

    Xu, Wang-Jie; Wang, Zhao-Xia; Qiao, Zhong-Dong

    2009-05-01

    Serial analysis of gene expression (SAGE) is a powerful technique to study gene expression at the genome level. However, a disadvantage of the shortness of SAGE tags is that it prevents further study of SAGE library data, thus limiting extensive application of the SAGE method in gene expression studies. However, this problem can be solved by extension of the SAGE tags to 3' cDNAs. Therefore, several methods based on PCR have been developed to generate a 3' longer fragment cDNA corresponding to a SAGE tag. The list of modified methods is extensive, and includes rapid RT-PCR analysis of unknown SAGE tags (RAST-PCR), generation of longer cDNA fragments from SAGE tags for gene identification (GLGI), a high-throughput GLGI procedure, reverse SAGE (rSAGE), two-step analysis of unknown SAGE tags (TSAT-PCR), etc. These procedures are constantly being updated because they have characteristics and advantages that can be shared. Development of these methods has promoted the widespread use of the SAGE technique, and has accelerated the speed of studies of large-scale gene expression.

  20. 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

  1. 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

  2. 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

  3. Extracting expression modules from perturbational gene expression compendia

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    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

  4. Robust algorithm to generate a diverse class of dense disordered and ordered sphere packings via linear programming.

    Science.gov (United States)

    Torquato, S; Jiao, Y

    2010-12-01

    We have formulated the problem of generating dense packings of nonoverlapping, nontiling nonspherical particles within an adaptive fundamental cell subject to periodic boundary conditions as an optimization problem called the adaptive-shrinking cell (ASC) formulation [S. Torquato and Y. Jiao, Phys. Rev. E 80, 041104 (2009)]. Because the objective function and impenetrability constraints can be exactly linearized for sphere packings with a size distribution in d-dimensional Euclidean space R(d), it is most suitable and natural to solve the corresponding ASC optimization problem using sequential-linear-programming (SLP) techniques. We implement an SLP solution to produce robustly a wide spectrum of jammed sphere packings in R(d) for d=2, 3, 4, 5, and 6 with a diversity of disorder and densities up to the respective maximal densities. A novel feature of this deterministic algorithm is that it can produce a broad range of inherent structures (locally maximally dense and mechanically stable packings), besides the usual disordered ones (such as the maximally random jammed state), with very small computational cost compared to that of the best known packing algorithms by tuning the radius of the influence sphere. For example, in three dimensions, we show that it can produce with high probability a variety of strictly jammed packings with a packing density anywhere in the wide range [0.6, 0.7408...], where π/√18 = 0.7408... corresponds to the density of the densest packing. We also apply the algorithm to generate various disordered packings as well as the maximally dense packings for d=2, 4, 5, and 6. Our jammed sphere packings are characterized and compared to the corresponding packings generated by the well-known Lubachevsky-Stillinger (LS) molecular-dynamics packing algorithm. Compared to the LS procedure, our SLP protocol is able to ensure that the final packings are truly jammed, produces disordered jammed packings with anomalously low densities, and is appreciably

  5. Identification of a potential ovarian cancer stem cell gene expression profile from advanced stage papillary serous ovarian cancer.

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    Vinod Vathipadiekal

    Full Text Available Identification of gene expression profiles of cancer stem cells may have significant implications in the understanding of tumor biology and for the design of novel treatments targeted toward these cells. Here we report a potential ovarian cancer stem cell gene expression profile from isolated side population of fresh ascites obtained from women with high-grade advanced stage papillary serous ovarian adenocarcinoma. Affymetrix U133 Plus 2.0 microarrays were used to interrogate the differentially expressed genes between side population (SP and main population (MP, and the results were analyzed by paired T-test using BRB-ArrayTools. We identified 138 up-regulated and 302 down-regulated genes that were differentially expressed between all 10 SP/MP pairs. Microarray data was validated using qRT-PCR and17/19 (89.5% genes showed robust correlations between microarray and qRT-PCR expression data. The Pathway Studio analysis identified several genes involved in cell survival, differentiation, proliferation, and apoptosis which are unique to SP cells and a mechanism for the activation of Notch signaling is identified. To validate these findings, we have identified and isolated SP cells enriched for cancer stem cells from human ovarian cancer cell lines. The SP populations were having a higher colony forming efficiency in comparison to its MP counterpart and also capable of sustained expansion and differentiation in to SP and MP phenotypes. 50,000 SP cells produced tumor in nude mice whereas the same number of MP cells failed to give any tumor at 8 weeks after injection. The SP cells demonstrated a dose dependent sensitivity to specific γ-secretase inhibitors implicating the role of Notch signaling pathway in SP cell survival. Further the generated SP gene list was found to be enriched in recurrent ovarian cancer tumors.

  6. 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

  7. 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

  8. Gene expression in Pseudomonas aeruginosa swarming motility

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    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

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

    Directory of Open Access Journals (Sweden)

    Cheung Leo

    2007-02-01

    Bayesian inferences. Simulation studies showed that, even without any knowledge of the underlying generative model, the KIGP performed very close to the theoretical Bayesian bound not only in the case with a linear Bayesian classifier but also in the case with a very non-linear Bayesian classifier. This sheds light on its broader usability to microarray data analysis problems, especially to those that linear methods work awkwardly. The KIGP was also applied to four published microarray datasets, and the results showed that the KIGP performed better than or at least as well as any of the referred state-of-the-art methods did in all of these cases. Conclusion Mathematically built on the kernel-induced feature space concept under a Bayesian framework, the KIGP method presented in this paper provides a unified machine learning approach to explore both the linear and the possibly non-linear underlying relationship between the target features of a given binary disease classification problem and the related explanatory gene expression data. More importantly, it incorporates the model parameter tuning into the framework. The model selection problem is addressed in the form of selecting a proper kernel type. The KIGP method also gives Bayesian probabilistic predictions for disease classification. These properties and features are beneficial to most real-world applications. The algorithm is naturally robust in numerical computation. The simulation studies and the published data studies demonstrated that the proposed KIGP performs satisfactorily and consistently.

  10. Modulation of R-gene expression across environments.

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    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.

  11. State-related alterations of gene expression in bipolar disorder

    DEFF Research Database (Denmark)

    Munkholm, Klaus; Vinberg, Maj; Berk, Michael

    2012-01-01

    Munkholm K, Vinberg M, Berk M, Kessing LV. State-related alterations of gene expression in bipolar disorder: a systematic review. Bipolar Disord 2012: 14: 684-696. © 2012 The Authors. Journal compilation © 2012 John Wiley & Sons A/S. Objective:  Alterations in gene expression in bipolar disorder...... on comprehensive database searches for studies on gene expression in patients with bipolar disorder in specific mood states, was conducted. We searched Medline, Embase, PsycINFO, and The Cochrane Library, supplemented by manually searching reference lists from retrieved publications. Results:  A total of 17...

  12. 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.

  13. Minimization of biosynthetic costs in adaptive gene expression responses of yeast to environmental changes.

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    Ester Vilaprinyo

    2010-02-01

    Full Text Available Yeast successfully adapts to an environmental stress by altering physiology and fine-tuning metabolism. This fine-tuning is achieved through regulation of both gene expression and protein activity, and it is shaped by various physiological requirements. Such requirements impose a sustained evolutionary pressure that ultimately selects a specific gene expression profile, generating a suitable adaptive response to each environmental change. Although some of the requirements are stress specific, it is likely that others are common to various situations. We hypothesize that an evolutionary pressure for minimizing biosynthetic costs might have left signatures in the physicochemical properties of proteins whose gene expression is fine-tuned during adaptive responses. To test this hypothesis we analyze existing yeast transcriptomic data for such responses and investigate how several properties of proteins correlate to changes in gene expression. Our results reveal signatures that are consistent with a selective pressure for economy in protein synthesis during adaptive response of yeast to various types of stress. These signatures differentiate two groups of adaptive responses with respect to how cells manage expenditure in protein biosynthesis. In one group, significant trends towards downregulation of large proteins and upregulation of small ones are observed. In the other group we find no such trends. These results are consistent with resource limitation being important in the evolution of the first group of stress responses.

  14. Identification of reference genes in human myelomonocytic cells for gene expression studies in altered gravity.

    Science.gov (United States)

    Thiel, Cora S; Hauschild, Swantje; Tauber, Svantje; Paulsen, Katrin; Raig, Christiane; Raem, Arnold; Biskup, Josefine; Gutewort, Annett; Hürlimann, Eva; Unverdorben, Felix; Buttron, Isabell; Lauber, Beatrice; Philpot, Claudia; Lier, Hartwin; Engelmann, Frank; Layer, Liliana E; Ullrich, Oliver

    2015-01-01

    Gene expression studies are indispensable for investigation and elucidation of molecular mechanisms. For the process of normalization, reference genes ("housekeeping genes") are essential to verify gene expression analysis. Thus, it is assumed that these reference genes demonstrate similar expression levels over all experimental conditions. However, common recommendations about reference genes were established during 1 g conditions and therefore their applicability in studies with altered gravity has not been demonstrated yet. The microarray technology is frequently used to generate expression profiles under defined conditions and to determine the relative difference in expression levels between two or more different states. In our study, we searched for potential reference genes with stable expression during different gravitational conditions (microgravity, normogravity, and hypergravity) which are additionally not altered in different hardware systems. We were able to identify eight genes (ALB, B4GALT6, GAPDH, HMBS, YWHAZ, ABCA5, ABCA9, and ABCC1) which demonstrated no altered gene expression levels in all tested conditions and therefore represent good candidates for the standardization of gene expression studies in altered gravity.

  15. Identification of Reference Genes in Human Myelomonocytic Cells for Gene Expression Studies in Altered Gravity

    Directory of Open Access Journals (Sweden)

    Cora S. Thiel

    2015-01-01

    Full Text Available Gene expression studies are indispensable for investigation and elucidation of molecular mechanisms. For the process of normalization, reference genes (“housekeeping genes” are essential to verify gene expression analysis. Thus, it is assumed that these reference genes demonstrate similar expression levels over all experimental conditions. However, common recommendations about reference genes were established during 1 g conditions and therefore their applicability in studies with altered gravity has not been demonstrated yet. The microarray technology is frequently used to generate expression profiles under defined conditions and to determine the relative difference in expression levels between two or more different states. In our study, we searched for potential reference genes with stable expression during different gravitational conditions (microgravity, normogravity, and hypergravity which are additionally not altered in different hardware systems. We were able to identify eight genes (ALB, B4GALT6, GAPDH, HMBS, YWHAZ, ABCA5, ABCA9, and ABCC1 which demonstrated no altered gene expression levels in all tested conditions and therefore represent good candidates for the standardization of gene expression studies in altered gravity.

  16. MidExDB: A database of Drosophila CNS midline cell gene expression

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    Crews Stephen T

    2009-11-01

    Full Text Available Abstract Background The Drosophila CNS midline cells are an excellent model system to study neuronal and glial development because of their diversity of cell types and the relative ease in identifying and studying the function of midline-expressed genes. In situ hybridization experiments generated a large dataset of midline gene expression patterns. To help synthesize these data and make them available to the scientific community, we developed a web-accessible database. Description MidExDB (Drosophila CNS Midline Gene Expression Database is comprised of images and data from our in situ hybridization experiments that examined midline gene expression. Multiple search tools are available to allow each type of data to be viewed and compared. Descriptions of each midline cell type and their development are included as background information. Conclusion MidExDB integrates large-scale gene expression data with the ability to identify individual cell types providing the foundation for detailed genetic, molecular, and biochemical studies of CNS midline cell neuronal and glial development and function. This information has general relevance for the study of nervous system development in other organisms, and also provides insight into transcriptional regulation.

  17. Single muscle fiber gene expression with run taper.

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    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.

  18. Fetal mesenchymal stromal cells differentiating towards chondrocytes acquire a gene expression profile resembling human growth plate cartilage.

    Directory of Open Access Journals (Sweden)

    Sandy A van Gool

    Full Text Available We used human fetal bone marrow-derived mesenchymal stromal cells (hfMSCs differentiating towards chondrocytes as an alternative model for the human growth plate (GP. Our aims were to study gene expression patterns associated with chondrogenic differentiation to assess whether chondrocytes derived from hfMSCs are a suitable model for studying the development and maturation of the GP. hfMSCs efficiently formed hyaline cartilage in a pellet culture in the presence of TGFβ3 and BMP6. Microarray and principal component analysis were applied to study gene expression profiles during chondrogenic differentiation. A set of 232 genes was found to correlate with in vitro cartilage formation. Several identified genes are known to be involved in cartilage formation and validate the robustness of the differentiating hfMSC model. KEGG pathway analysis using the 232 genes revealed 9 significant signaling pathways correlated with cartilage formation. To determine the progression of growth plate cartilage formation, we compared the gene expression profile of differentiating hfMSCs with previously established expression profiles of epiphyseal GP cartilage. As differentiation towards chondrocytes proceeds, hfMSCs gradually obtain a gene expression profile resembling epiphyseal GP cartilage. We visualized the differences in gene expression profiles as protein interaction clusters and identified many protein clusters that are activated during the early chondrogenic differentiation of hfMSCs showing the potential of this system to study GP development.

  19. Gene expression profiling of RNA extracted from FFPE tissues: NuGEN technologies' whole-transcriptome amplification system.

    Science.gov (United States)

    Turner, Leah; Heath, Joe Don; Kurn, Nurith

    2011-01-01

    Gene expression profiling of RNA isolated from formalin fixed, paraffin-embedded (FFPE) tissue samples has been historically challenging. Yet FFPE samples are sought-after because of the in-depth retrospective records typically associated with them rendering these samples a valuable resource for translational medicine studies. Extensive degradation, chemical modifications, and cross-linking have made it difficult to isolate RNA of sufficient quality required for large-scale gene expression profiling studies. NuGEN Technologies' WT-Ovation™ FFPE System linearly amplifies RNA from FFPE samples through a robust and simple whole-transcriptome approach using as little as 50 ng total RNA isolated from FFPE samples. The amplified material may be labeled with validated kits and/or protocols from NuGEN for analysis on any of the major gene expression microarray platforms, including: Affymetrix, Agilent, and Illumina gene expression arrays. Results compare well with those obtained using RNA from fresh-frozen samples. RNA quality from FFPE samples varies significantly and neither sample age nor sample size analysis via gel electrophoresis or the Agilent Bioanalyzer system accurately predict materials suitable for amplification. Therefore, NuGEN has validated a correlative qPCR-based analytical method for the RNA derived from FFPE samples which effectively predicts array results. The NuGEN approach enables fast and successful analysis of samples previously thought to be too degraded for gene expression analysis.

  20. 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

  1. Application of a Scalable Plant Transient Gene Expression Platform for Malaria Vaccine Development

    Science.gov (United States)

    Spiegel, Holger; Boes, Alexander; Voepel, Nadja; Beiss, Veronique; Edgue, Gueven; Rademacher, Thomas; Sack, Markus; Schillberg, Stefan; Reimann, Andreas; Fischer, Rainer

    2015-01-01

    Despite decades of intensive research efforts there is currently no vaccine that provides sustained sterile immunity against malaria. In this context, a large number of targets from the different stages of the Plasmodium falciparum life cycle have been evaluated as vaccine candidates. None of these candidates has fulfilled expectations, and as long as we lack a single target that induces strain-transcending protective immune responses, combining key antigens from different life cycle stages seems to be the most promising route toward the development of efficacious malaria vaccines. After the identification of potential targets using approaches such as omics-based technology and reverse immunology, the rapid expression, purification, and characterization of these proteins, as well as the generation and analysis of fusion constructs combining different promising antigens or antigen domains before committing to expensive and time consuming clinical development, represents one of the bottlenecks in the vaccine development pipeline. The production of recombinant proteins by transient gene expression in plants is a robust and versatile alternative to cell-based microbial and eukaryotic production platforms. The transfection of plant tissues and/or whole plants using Agrobacterium tumefaciens offers a low technical entry barrier, low costs, and a high degree of flexibility embedded within a rapid and scalable workflow. Recombinant proteins can easily be targeted to different subcellular compartments according to their physicochemical requirements, including post-translational modifications, to ensure optimal yields of high quality product, and to support simple and economical downstream processing. Here, we demonstrate the use of a plant transient expression platform based on transfection with A. tumefaciens as essential component of a malaria vaccine development workflow involving screens for expression, solubility, and stability using fluorescent fusion proteins. Our

  2. Application of a Scalable Plant Transient Gene Expression Platform for Malaria Vaccine Development.

    Science.gov (United States)

    Spiegel, Holger; Boes, Alexander; Voepel, Nadja; Beiss, Veronique; Edgue, Gueven; Rademacher, Thomas; Sack, Markus; Schillberg, Stefan; Reimann, Andreas; Fischer, Rainer

    2015-01-01

    Despite decades of intensive research efforts there is currently no vaccine that provides sustained sterile immunity against malaria. In this context, a large number of targets from the different stages of the Plasmodium falciparum life cycle have been evaluated as vaccine candidates. None of these candidates has fulfilled expectations, and as long as we lack a single target that induces strain-transcending protective immune responses, combining key antigens from different life cycle stages seems to be the most promising route toward the development of efficacious malaria vaccines. After the identification of potential targets using approaches such as omics-based technology and reverse immunology, the rapid expression, purification, and characterization of these proteins, as well as the generation and analysis of fusion constructs combining different promising antigens or antigen domains before committing to expensive and time consuming clinical development, represents one of the bottlenecks in the vaccine development pipeline. The production of recombinant proteins by transient gene expression in plants is a robust and versatile alternative to cell-based microbial and eukaryotic production platforms. The transfection of plant tissues and/or whole plants using Agrobacterium tumefaciens offers a low technical entry barrier, low costs, and a high degree of flexibility embedded within a rapid and scalable workflow. Recombinant proteins can easily be targeted to different subcellular compartments according to their physicochemical requirements, including post-translational modifications, to ensure optimal yields of high quality product, and to support simple and economical downstream processing. Here, we demonstrate the use of a plant transient expression platform based on transfection with A. tumefaciens as essential component of a malaria vaccine development workflow involving screens for expression, solubility, and stability using fluorescent fusion proteins. Our

  3. Application of a scalable plant transient gene expression platform for malaria vaccine development

    Directory of Open Access Journals (Sweden)

    Holger eSpiegel

    2015-12-01

    Full Text Available Despite decades of intensive research efforts there is currently no vaccine that provides sustained sterile immunity against malaria. In this context, a large number of targets from the different stages of the Plasmodium falciparum life cycle have been evaluated as vaccine candidates. None of these candidates has fulfilled expectations, and as long as we lack a single target that induces strain-transcending protective immune responses, combining key antigens from different life cycle stages seems to be the most promising route towards the development of efficacious malaria vaccines. After the identification of potential targets using approaches such as omics-based technology and reverse immunology, the rapid expression, purification and characterization of these proteins, as well as the generation and analysis of fusion constructs combining different promising antigens or antigen domains before committing to expensive and time consuming clinical development, represents one of the bottlenecks in the vaccine development pipeline. The production of recombinant proteins by transient gene expression in plants is a robust and versatile alternative to cell-based microbial and eukaryotic production platforms. The transfection of plant tissues and/or whole plants using Agrobacterium tumefaciens offers a low technical entry barrier, low costs and a high degree of flexibility embedded within a rapid and scalable workflow. Recombinant proteins can easily be targeted to different subcellular compartments according to their physicochemical requirements, including post-translational modifications, to ensure optimal yields of high quality product, and to support simple and economical downstream processing. Here we demonstrate the use of a plant transient expression platform based on transfection with A. tumefaciens as essential component of a malaria vaccine development workflow involving screens for expression, solubility and stability using fluorescent fusion

  4. 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...

  5. 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...

  6. Applications of Little's Law to stochastic models of gene expression

    CERN Document Server

    Elgart, Vlad; Kulkarni, Rahul V

    2010-01-01

    The intrinsic stochasticity of gene expression can lead to large variations in protein levels across a population of cells. To explain this variability, different sources of mRNA fluctuations ('Poisson' and 'Telegraph' processes) have been proposed in stochastic models of gene expression. Both Poisson and Telegraph scenario models explain experimental observations of noise in protein levels in terms of 'bursts' of protein expression. Correspondingly, there is considerable interest in establishing relations between burst and steady-state protein distributions for general stochastic models of gene expression. In this work, we address this issue by considering a mapping between stochastic models of gene expression and problems of interest in queueing theory. By applying a general theorem from queueing theory, Little's Law, we derive exact relations which connect burst and steady-state distribution means for models with arbitrary waiting-time distributions for arrival and degradation of mRNAs and proteins. The de...

  7. Gene expression in three stages of ripening tomato fruit

    NARCIS (Netherlands)

    Maagd, de R.A.; Bovy, A.G.

    2013-01-01

    Gene expression in three stages of ripening tomato fruit (variety Ailsa Craig) was determined with the EUTOM3 Affymetrix array in order to compare with degradrome sequencing data from study GSE42661, treated as RNAseq.

  8. 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.

  9. 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.

  10. Gene expression profiling of benign and malignant pheochromocytoma.

    NARCIS (Netherlands)

    Brouwers, F.M.; Elkahloun, A.G.; Munson, P.J.; Eisenhofer, G.; Barb, J.; Linehan, W.M.; Lenders, J.W.M.; Krijger, R.R. de; Mannelli, M.; Udelsman, R.; Ocal, I.T.; Shulkin, B.L.; Bornstein, S.R.; Breza, J.; Ksinantova, L.; Pacak, K.

    2006-01-01

    There are currently no reliable diagnostic and prognostic markers or effective treatments for malignant pheochromocytoma. This study used oligonucleotide microarrays to examine gene expression profiles in pheochromocytomas from 90 patients, including 20 with malignant tumors, the latter including

  11. The evolution of gene expression levels in mammalian organs

    DEFF Research Database (Denmark)

    Brawand, David; Soumillon, Magali; Necsulea, Anamaria

    2011-01-01

    and chromosomes, owing to differences in selective pressures: transcriptome change was slow in nervous tissues and rapid in testes, slower in rodents than in apes and monotremes, and rapid for the X chromosome right after its formation. Although gene expression evolution in mammals was strongly shaped......Changes in gene expression are thought to underlie many of the phenotypic differences between species. However, large-scale analyses of gene expression evolution were until recently prevented by technological limitations. Here we report the sequencing of polyadenylated RNA from six organs across...... ten species that represent all major mammalian lineages (placentals, marsupials and monotremes) and birds (the evolutionary outgroup), with the goal of understanding the dynamics of mammalian transcriptome evolution. We show that the rate of gene expression evolution varies among organs, lineages...

  12. Effect of normalization on statistical and biological interpretation of gene expression profiles.

    Science.gov (United States)

    Qin, Shaopu; Kim, Jinhee; Arafat, Dalia; Gibson, Greg

    2012-01-01

    An under-appreciated aspect of the genetic analysis of gene expression is the impact of post-probe level normalization on biological inference. Here we contrast nine different methods for normalization of an Illumina bead-array gene expression profiling dataset consisting of peripheral blood samples from 189 individual participants in the Center for Health Discovery and Well Being study in Atlanta, quantifying differences in the inference of global variance components and covariance of gene expression, as well as the detection of variants that affect transcript abundance (eSNPs). The normalization strategies, all relative to raw log2 measures, include simple mean centering, two modes of transcript-level linear adjustment for technical factors, and for differential immune cell counts, variance normalization by interquartile range and by quantile, fitting the first 16 Principal Components, and supervised normalization using the SNM procedure with adjustment for cell counts. Robustness of genetic associations as a consequence of Pearson and Spearman rank correlation is also reported for each method, and it is shown that the normalization strategy has a far greater impact than correlation method. We describe similarities among methods, discuss the impact on biological interpretation, and make recommendations regarding appropriate strategies.

  13. Effect of Normalization on Statistical and Biological Interpretation of Gene Expression Profiles

    Directory of Open Access Journals (Sweden)

    Shaopu Peter Qin

    2013-05-01

    Full Text Available A neglected aspect of the genetic analysis of gene expression is the impact of normalization on biological inference. Here we contrast nine different methods for normalization of an Illumina bead-array gene expression profiling dataset consisting of peripheral blood samples from 189 individual participants in the Center for Health Discovery and Well-Being (CHDWB study in Atlanta, quantifying differences in the inference of global variance components and covariance of gene expression, as well as the detection of eSNPs. The normalization strategies, all relative to raw log2 measures, include simple mean centering, two modes of transcript-level linear adjustment for technical factors, and for differential immune cell counts, variance normalization by inter-quartile range and by quantile, fitting the first 16 Principal Components, and supervised normalization using the SNM procedure with adjustment for cell counts. Robustness of genetic associations as a consequence of Pearson and Spearman rank correlation is also reported for each method, and it shown that the normalization strategy has a far greater impact than correlation method. We describe similarities among methods, discuss the impact on biological interpretation, and make recommendations regarding appropriate strategies.

  14. Extracting biologically significant patterns from short time series gene expression data

    Directory of Open Access Journals (Sweden)

    McGinnis Thomas

    2009-08-01

    Full Text Available Abstract Background Time series gene expression data analysis is used widely to study the dynamics of various cell processes. Most of the time series data available today consist of few time points only, thus making the application of standard clustering techniques difficult. Results We developed two new algorithms that are capable of extracting biological patterns from short time point series gene expression data. The two algorithms, ASTRO and MiMeSR, are inspired by the rank order preserving framework and the minimum mean squared residue approach, respectively. However, ASTRO and MiMeSR differ from previous approaches in that they take advantage of the relatively few number of time points in order to reduce the problem from NP-hard to linear. Tested on well-defined short time expression data, we found that our approaches are robust to noise, as well as to random patterns, and that they can correctly detect the temporal expression profile of relevant functional categories. Evaluation of our methods was performed using Gene Ontology (GO annotations and chromatin immunoprecipitation (ChIP-chip data. Conclusion Our approaches generally outperform both standard clustering algorithms and algorithms designed specifically for clustering of short time series gene expression data. Both algorithms are available at http://www.benoslab.pitt.edu/astro/.

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

    Directory of Open Access Journals (Sweden)

    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. 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.

  17. Gene expression platform for synthetic biology in the human pathogen Streptococcus pneumoniae.

    Science.gov (United States)

    Sorg, Robin A; Kuipers, Oscar P; Veening, Jan-Willem

    2015-03-20

    The human pathogen Streptococcus pneumoniae (pneumococcus) is a bacterium that owes its success to complex gene expression regulation patterns on both the cellular and the population level. Expression of virulence factors enables a mostly hazard-free presence of the commensal, in balance with the host and niche competitors. Under specific circumstances, changes in this expression can result in a more aggressive behavior and the reversion to the invasive form as pathogen. These triggering conditions are very difficult to study due to the fact that environmental cues are often unknown or barely possible to simulate outside the host (in vitro). An alternative way of investigating expression patterns is found in synthetic biology approaches of reconstructing regulatory networks that mimic an observed behavior with orthogonal components. Here, we created a genetic platform suitable for synthetic biology approaches in S. pneumoniae and characterized a set of standardized promoters and reporters. We show that our system allows for fast and easy cloning with the BglBrick system and that reliable and robust gene expression after integration into the S. pneumoniae genome is achieved. In addition, the cloning system was extended to allow for direct linker-based assembly of ribosome binding sites, peptide tags, and fusion proteins, and we called this new generally applicable standard "BglFusion". The gene expression platform and the methods described in this study pave the way for employing synthetic biology approaches in S. pneumoniae.

  18. 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

  19. 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.

  20. Molecular subsets in the gene expression signatures of scleroderma skin.

    Directory of Open Access Journals (Sweden)

    Ausra Milano

    Full Text Available BACKGROUND: Scleroderma is a clinically heterogeneous disease with a complex phenotype. The disease is characterized by vascular dysfunction, tissue fibrosis, internal organ dysfunction, and immune dysfunction resulting in autoantibody production. METHODOLOGY AND FINDINGS: We analyzed the genome-wide patterns of gene expression with DNA microarrays in skin biopsies from distinct scleroderma subsets including 17 patients with systemic sclerosis (SSc with diffuse scleroderma (dSSc, 7 patients with SSc with limited scleroderma (lSSc, 3 patients with morphea, and 6 healthy controls. 61 skin biopsies were analyzed in a total of 75 microarray hybridizations. Analysis by hierarchical clustering demonstrates nearly identical patterns of gene expression in 17 out of 22 of the forearm and back skin pairs of SSc patients. Using this property of the gene expression, we selected a set of 'intrinsic' genes and analyzed the inherent data-driven groupings. Distinct patterns of gene expression separate patients with dSSc from those with lSSc and both are easily distinguished from normal controls. Our data show three distinct patient groups among the patients with dSSc and two groups among patients with lSSc. Each group can be distinguished by unique gene expression signatures indicative of proliferating cells, immune infiltrates and a fibrotic program. The intrinsic groups are statistically significant (p<0.001 and each has been mapped to clinical covariates of modified Rodnan skin score, interstitial lung disease, gastrointestinal involvement, digital ulcers, Raynaud's phenomenon and disease duration. We report a 177-gene signature that is associated with severity of skin disease in dSSc. CONCLUSIONS AND SIGNIFICANCE: Genome-wide gene expression profiling of skin biopsies demonstrates that the heterogeneity in scleroderma can be measured quantitatively with DNA microarrays. The diversity in gene expression demonstrates multiple distinct gene expression programs

  1. A Compendium of Canine Normal Tissue Gene Expression

    OpenAIRE

    Joseph Briggs; Melissa Paoloni; Qing-Rong Chen; Xinyu Wen; Javed Khan; Chand Khanna

    2011-01-01

    BACKGROUND: Our understanding of disease is increasingly informed by changes in gene expression between normal and abnormal tissues. The release of the canine genome sequence in 2005 provided an opportunity to better understand human health and disease using the dog as clinically relevant model. Accordingly, we now present the first genome-wide, canine normal tissue gene expression compendium with corresponding human cross-species analysis. METHODOLOGY/PRINCIPAL FINDINGS: The Affymetrix platf...

  2. Genetic Algorithms Applied to Multi-Class Clustering for Gene Expression Data

    Institute of Scientific and Technical Information of China (English)

    Haiyan Pan; Jun Zhu; Danfu Han

    2003-01-01

    A hybrid GA (genetic algorithm)-based clustering (HGACLUS) schema, combining merits of the Simulated Annealing, was described for finding an optimal or near-optimal set of medoids. This schema maximized the clustering success by achieving internal cluster cohesion and external cluster isolation. The performance of HGACLUS and other methods was compared by using simulated data and open microarray gene-expression datasets. HGACLUS was generally found to be more accurate and robust than other methods discussed in this paper by the exact validation strategy and the explicit cluster number.

  3. Unsupervised Bayesian linear unmixing of gene expression microarrays.

    Science.gov (United States)

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

    2013-03-19

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

  4. Gene expression variation between distinct areas of breast cancer measured from paraffin-embedded tissue cores

    Directory of Open Access Journals (Sweden)

    Gugger Mathias

    2008-11-01

    Full Text Available Abstract Background Diagnosis and prognosis in breast cancer are mainly based on histology and immunohistochemistry of formalin-fixed, paraffin-embedded (FFPE material. Recently, gene expression analysis was shown to elucidate the biological variance between tumors and molecular markers were identified that led to new classification systems that provided better prognostic and predictive parameters. Archived FFPE samples represent an ideal source of tissue for translational research, as millions of tissue blocks exist from routine diagnostics and from clinical studies. These should be exploited to provide clinicians with more accurate prognostic and predictive information. Unfortunately, RNA derived from FFPE material is partially degraded and chemically modified and reliable gene expression measurement has only become successful after implementing novel and optimized procedures for RNA isolation, demodification and detection. Methods In this study we used tissue cylinders as known from the construction of tissue microarrays. RNA was isolated with a robust protocol recently developed for RNA derived from FFPE material. Gene expression was measured by quantitative reverse transcription PCR. Results Sixteen tissue blocks from 7 patients diagnosed with multiple histological subtypes of breast cancer were available for this study. After verification of appropriate localization, sufficient RNA yield and quality, 30 tissue cores were available for gene expression measurement on TaqMan® Low Density Arrays (16 invasive ductal carcinoma (IDC, 8 ductal carcinoma in situ (DCIS and 6 normal tissue, and 14 tissue cores were lost. Gene expression values were used to calculate scores representing the proliferation status (PRO, the estrogen receptor status and the HER2 status. The PRO scores measured from entire sections were similar to PRO scores determined from IDC tissue cores. Scores determined from normal tissue cores consistently revealed lower PRO scores

  5. Intrinsic and extrinsic contributions to stochasticity in gene expression

    Science.gov (United States)

    Swain, Peter S.; Elowitz, Michael B.; Siggia, Eric D.

    2002-10-01

    Gene expression is a stochastic, or "noisy," process. This noise comes about in two ways. The inherent stochasticity of biochemical processes such as transcription and translation generates "intrinsic" noise. In addition, fluctuations in the amounts or states of other cellular components lead indirectly to variation in the expression of a particular gene and thus represent "extrinsic" noise. Here, we show how the total variation in the level of expression of a given gene can be decomposed into its intrinsic and extrinsic components. We demonstrate theoretically that simultaneous measurement of two identical genes per cell enables discrimination of these two types of noise. Analytic expressions for intrinsic noise are given for a model that involves all the major steps in transcription and translation. These expressions give the sensitivity to various parameters, quantify the deviation from Poisson statistics, and provide a way of fitting experiment. Transcription dominates the intrinsic noise when the average number of proteins made per mRNA transcript is greater than 2. Below this number, translational effects also become important. Gene replication and cell division, included in the model, cause protein numbers to tend to a limit cycle. We calculate a general form for the extrinsic noise and illustrate it with the particular case of a single fluctuating extrinsic variablea repressor protein, which acts on the gene of interest. All results are confirmed by stochastic simulation using plausible parameters for Escherichia coli.

  6. Root exudate impact on gene expression of Sporisorium reilianum.

    Science.gov (United States)

    Sabbagh, S K; Panjakeh, N; Salary, M

    2009-01-01

    Sporisorium reilianum f.sp zeae, a basidiomycetous fungus belonging to Ustilaginaceae, is the causal agent of the maize head smut disease. This soilborne pathogen infects the host plant at the seedling stage by penetrating roots. The infection is systemic, and disease symptoms become apparent only after the onset of flower development when the fungal sori replace male or female inflorescences. In order to investigate the mechanism of infection, we analysed the transcriptome of the fungus in response to root exudates during the previous phase of infection. A suppression subtractive hybridization (SSH) was used to generate cDNA libraries representing genes differentially expressed in haploid cell forms of the fungus exposed to root exudates Leading to 960 ESTs. By using cDNA macroarray hybridization, we identified 36 ESTs which were differentially expressed in response to exudates application. In this first transcriptomic analysis realized on S. reilianum, we show that maize root exudates may affect gene expression of the fungus involved in cell respiration, cell wall development, metabolism and hypothetical proteins during the previous step of infection and could play an important role in fungi growth promotion and plant pathogenesis.

  7. Controlling gene expression by DNA mechanics: emerging insights and challenges.

    Science.gov (United States)

    Levens, David; Baranello, Laura; Kouzine, Fedor

    2016-11-01

    Transcription initiation is a major control point for the precise regulation of gene expression. Our knowledge of this process has been mainly derived from protein-centric studies wherein cis-regulatory DNA sequences play a passive role, mainly in arranging the protein machinery to coalesce at the transcription start sites of genes in a spatial and temporal-specific manner. However, this is a highly dynamic process in which molecular motors such as RNA polymerase II (RNAPII), helicases, and other transcription factors, alter the level of mechanical force in DNA, rather than simply a set of static DNA-protein interactions. The double helix is a fiber that responds to flexural and torsional stress, which if accumulated, can affect promoter output as well as change DNA and chromatin structure. The relationship between DNA mechanics and the control of early transcription initiation events has been under-investigated. Genomic techniques to display topological stress and conformational variation in DNA across the mammalian genome provide an exciting new insight on the role of DNA mechanics in the early stages of the transcription cycle. Without understanding how torsional and flexural stresses are generated, transmitted, and dissipated, no model of transcription will be complete and accurate.

  8. Improving metabolic flux predictions using absolute gene expression data

    Directory of Open Access Journals (Sweden)

    Lee Dave

    2012-06-01

    Full Text Available Abstract Background Constraint-based analysis of genome-scale metabolic models typically relies upon maximisation of a cellular objective function such as the rate or efficiency of biomass production. Whilst this assumption may be valid in the case of microorganisms growing under certain conditions, it is likely invalid in general, and especially for multicellular organisms, where cellular objectives differ greatly both between and within cell types. Moreover, for the purposes of biotechnological applications, it is normally the flux to a specific metabolite or product that is of interest rather than the rate of production of biomass per se. Results An alternative objective function is presented, that is based upon maximising the correlation between experimentally measured absolute gene expression data and predicted internal reaction fluxes. Using quantitative transcriptomics data acquired from Saccharomyces cerevisiae cultures under two growth conditions, the method outperforms traditional approaches for predicting experimentally measured exometabolic flux that are reliant upon maximisation of the rate of biomass production. Conclusion Due to its improved prediction of experimentally measured metabolic fluxes, and of its lack of a requirement for knowledge of the biomass composition of the organism under the conditions of interest, the approach is likely to be of rather general utility. The method has been shown to predict fluxes reliably in single cellular systems. Subsequent work will investigate the method’s ability to generate condition- and tissue-specific flux predictions in multicellular organisms.

  9. A modified consumer inkjet for spatiotemporal control of gene expression.

    Directory of Open Access Journals (Sweden)

    Daniel J Cohen

    Full Text Available This paper presents a low-cost inkjet dosing system capable of continuous, two-dimensional spatiotemporal regulation of gene expression via delivery of diffusible regulators to a custom-mounted gel culture of E. coli. A consumer-grade, inkjet printer was adapted for chemical printing; E. coli cultures were grown on 750 microm thick agar embedded in micro-wells machined into commercial compact discs. Spatio-temporal regulation of the lac operon was demonstrated via the printing of patterns of lactose and glucose directly into the cultures; X-Gal blue patterns were used for visual feedback. We demonstrate how the bistable nature of the lac operon's feedback, when perturbed by patterning lactose (inducer and glucose (inhibitor, can lead to coordination of cell expression patterns across a field in ways that mimic motifs seen in developmental biology. Examples of this include sharp boundaries and the generation of traveling waves of mRNA expression. To our knowledge, this is the first demonstration of reaction-diffusion effects in the well-studied lac operon. A finite element reaction-diffusion model of the lac operon is also presented which predicts pattern formation with good fidelity.

  10. Width of gene expression profile drives alternative splicing.

    Directory of Open Access Journals (Sweden)

    Daniel Wegmann

    Full Text Available Alternative splicing generates an enormous amount of functional and proteomic diversity in metazoan organisms. This process is probably central to the macromolecular and cellular complexity of higher eukaryotes. While most studies have focused on the molecular mechanism triggering and controlling alternative splicing, as well as on its incidence in different species, its maintenance and evolution within populations has been little investigated. Here, we propose to address these questions by comparing the structural characteristics as well as the functional and transcriptional profiles of genes with monomorphic or polymorphic splicing, referred to as MS and PS genes, respectively. We find that MS and PS genes differ particularly in the number of tissues and cell types where they are expressed.We find a striking deficit of PS genes on the sex chromosomes, particularly on the Y chromosome where it is shown not to be due to the observed lower breadth of expression of genes on that chromosome. The development of a simple model of evolution of cis-regulated alternative splicing leads to predictions in agreement with these observations. It further predicts the conditions for the emergence and the maintenance of cis-regulated alternative splicing, which are both favored by the tissue specific expression of splicing variants. We finally propose that the width of the gene expression profile is an essential factor for the acquisition of new transcript isoforms that could later be maintained by a new form of balancing selection.

  11. Bitumen fume-induced gene expression profile in rat lung.

    Science.gov (United States)

    Gate, Laurent; Langlais, Cristina; Micillino, Jean-Claude; Nunge, Hervé; Bottin, Marie-Claire; Wrobel, Richard; Binet, Stéphane

    2006-08-15

    Exposure to bitumen fumes during paving and roofing activities may represent an occupational health risk. To date, most of the studies performed on the biological effect of asphalt fumes have been done with regard to their content in carcinogenic polycyclic aromatic hydrocarbons (PAH). In order to gain an additional insight into the mechanisms of action of bitumen fumes, we studied their pulmonary effects in rodents following inhalation using the microarray technology. Fisher 344 rats were exposed for 5 days, 6 h/day to bitumen fumes generated at road paving temperature (170 degrees C) using a nose-only exposition device. With the intention of studying the early transcriptional events induced by asphalt fumes, lung tissues were collected immediately following exposure and gene expression profiles in control and exposed rats were determined by using oligonucleotide microarrays. Data analysis revealed that genes involved in lung inflammatory response as well as genes associated with PAH metabolization and detoxification were highly expressed in bitumen-exposed animals. In addition, the expression of genes related to elastase activity and its inhibition which are associated with emphysema was also modulated. More interestingly genes coding for monoamine oxidases A and B involved in the metabolism of neurotransmitters and xenobiotics were downregulated in exposed rats. Altogether, these data give additional information concerning the bitumen fumes biological effects and would allow to better review the health effects of occupational asphalt fumes exposure.

  12. Precise integration of inducible transcriptional elements (PrIITE) enables absolute control of gene expression

    DEFF Research Database (Denmark)

    Pinto, Rita; Hansen, Lars; Hintze, John Birger Hjalmar

    2017-01-01

    Tetracycline-based inducible systems provide powerful methods for functional studies where gene expression can be controlled. However, the lack of tight control of the inducible system, leading to leakiness and adverse effects caused by undesirable tetracycline dosage requirements, has proven...... to be a limitation. Here, we report that the combined use of genome editing tools and last generation Tet-On systems can resolve these issues. Our principle is based on precise integration of inducible transcriptional elements (coined PrIITE) targeted to: (i) exons of an endogenous gene of interest (GOI) and (ii......) a safe harbor locus. Using PrIITE cells harboring a GFP reporter or CDX2 transcription factor, we demonstrate discrete inducibility of gene expression with complete abrogation of leakiness. CDX2 PrIITE cells generated by this approach uncovered novel CDX2 downstream effector genes. Our results provide...

  13. 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.

  14. 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.

  15. 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

  16. 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

  17. Global analysis of transcriptome responses and gene expression profiles to cold stress of Jatropha curcas L.

    Directory of Open Access Journals (Sweden)

    Haibo Wang

    Full Text Available BACKGROUND: Jatropha curcas L., also called the Physic nut, is an oil-rich shrub with multiple uses, including biodiesel production, and is currently exploited as a renewable energy resource in many countries. Nevertheless, because of its origin from the tropical MidAmerican zone, J. curcas confers an inherent but undesirable characteristic (low cold resistance that may seriously restrict its large-scale popularization. This adaptive flaw can be genetically improved by elucidating the mechanisms underlying plant tolerance to cold temperatures. The newly developed Illumina Hiseq™ 2000 RNA-seq and Digital Gene Expression (DGE are deep high-throughput approaches for gene expression analysis at the transcriptome level, using which we carefully investigated the gene expression profiles in response to cold stress to gain insight into the molecular mechanisms of cold response in J. curcas. RESULTS: In total, 45,251 unigenes were obtained by assembly of clean data generated by RNA-seq analysis of the J. curcas transcriptome. A total of 33,363 and 912 complete or partial coding sequences (CDSs were determined by protein database alignments and ESTScan prediction, respectively. Among these unigenes, more than 41.52% were involved in approximately 128 known metabolic or signaling pathways, and 4,185 were possibly associated with cold resistance. DGE analysis was used to assess the changes in gene expression when exposed to cold condition (12°C for 12, 24, and 48 h. The results showed that 3,178 genes were significantly upregulated and 1,244 were downregulated under cold stress. These genes were then functionally annotated based on the transcriptome data from RNA-seq analysis. CONCLUSIONS: This study provides a global view of transcriptome response and gene expression profiling of J. curcas in response to cold stress. The results can help improve our current understanding of the mechanisms underlying plant cold resistance and favor the screening of

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

    OpenAIRE

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

    2008-01-01

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

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

    OpenAIRE

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

    2008-01-01

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

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

    OpenAIRE

    Martínez-Godoy, M. Ángeles; Mauri, Nuria; Juárez, José; Marqués, M. Carmen; Santiago, Julia; Forment, Javier; Gadea Vacas, José

    2008-01-01

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

  1. 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...

  2. Modular Analysis of Peripheral Blood Gene Expression in Rheumatoid Arthritis Captures Reproducible Gene Expression Changes in TNF Responders

    Science.gov (United States)

    Oswald, Michaela; Curran, Mark; Lamberth, Sarah; Townsend, Robert; Hamilton, Jennifer D.; Chernoff, David N.; Carulli, John; Townsend, Michael; Weinblatt, Michael; Kern, Marlena; Pond, Cassandra; Lee, Annette; Gregersen, Peter K.

    2015-01-01

    Objective To establish whether the analysis of whole blood gene expression can be useful in predicting or monitoring response to anti-TNF therapy in RA. Methods Whole blood RNA (PAXgene) was obtained at baseline and 14 weeks on three independent cohorts with a combined total of 250 patients with rheumatoid arthritis beginning anti-TNF therapy. We employed an approach to gene expression analysis that is based on gene expression “modules”. Results Good and Moderate Responders by EULAR criteria exhibited highly significant and consistent changes in multiple gene expression modules using a hyper geometric analysis after 14 weeks of therapy. Strikingly, non responders exhibited very little change in any modules, despite exposure to TNF blockade. These patterns of change were highly consistent across all three cohorts, indicating that immunological changes after TNF treatment are specific to the combination of both drug exposure and responder status. In contrast, modular patterns of gene expression did not exhibit consistent differences between responders and non-responders at baseline in the three cohorts. Conclusions These data provide evidence that using gene expression modules related to inflammatory disease may provide a valuable method for objective monitoring of the response of RA patients who are treated with TNF inhibitors. PMID:25371395

  3. Gene Expression Measurement Module (GEMM) - A Fully Automated, Miniaturized Instrument for Measuring Gene Expression in Space

    Science.gov (United States)

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

    2012-01-01

    The capability to measure gene expression on board spacecraft opens the door to a large number of high-value experiments on the influence of the space environment on biological systems. For example, 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, and determine the metabolic bases of microbial pathogenicity and drug resistance. These and other applications hold significant potential for discoveries in space biology, biotechnology, and medicine. 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 measurement of expression of several hundreds of microbial genes from multiple samples. The instrument will be capable of (1) lysing cell walls of bacteria sampled from cultures grown in space, (2) extracting and purifying RNA released from cells, (3) hybridizing the RNA on a microarray and (4) providing readout of the microarray signal, all in a single microfluidics cartridge. The device is suitable for deployment on nanosatellite platforms developed by NASA Ames' Small Spacecraft Division. To meet space and other technical constraints imposed by these platforms, a number of technical innovations are being implemented. The integration and end-to-end technological and biological validation of the instrument are carried out using as a model the photosynthetic bacterium Synechococcus elongatus, known for its remarkable metabolic diversity and resilience to adverse conditions. Each step in the measurement process-lysis, nucleic acid extraction, purification, and hybridization to an array-is assessed through comparison of the results obtained using the instrument with

  4. 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.

  5. Analysis of gene expression in resynthesized Brassica napus Allopolyploids using arabidopsis 70mer oligo microarrays.

    Directory of Open Access Journals (Sweden)

    Robert T Gaeta

    Full Text Available BACKGROUND: Studies in resynthesized Brassica napus allopolyploids indicate that homoeologous chromosome exchanges in advanced generations (S(5ratio6 alter gene expression through the loss and doubling of homoeologous genes within the rearrangements. Rearrangements may also indirectly affect global gene expression if homoeologous copies of gene regulators within rearrangements have differential affects on the transcription of genes in networks. METHODOLOGY/PRINCIPAL FINDINGS: We utilized Arabidopsis 70mer oligonucleotide microarrays for exploring gene expression in three resynthesized B. napus lineages at the S(0ratio1 and S(5ratio6 generations as well as their diploid progenitors B. rapa and B. oleracea. Differential gene expression between the progenitors and additive (midparent expression in the allopolyploids were tested. The S(5ratio6 lines differed in the number of genetic rearrangements, allowing us to test if the number of genes displaying nonadditive expression was related to the number of rearrangements. Estimates using per-gene and common variance ANOVA models indicated that 6-15% of 26,107 genes were differentially expressed between the progenitors. Individual allopolyploids showed nonadditive expression for 1.6-32% of all genes. Less than 0.3% of genes displayed nonadditive expression in all S(0ratio1 lines and 0.1-0.2% were nonadditive among all S(5ratio6 lines. Differentially expressed genes in the polyploids were over-represented by genes differential between the progenitors. The total number of differentially expressed genes was correlated with the number of genetic changes in S(5ratio6 lines under the common variance model; however, there was no relationship using a per-gene variance model, and many genes showed nonadditive expression in S(0ratio1 lines. CONCLUSIONS/SIGNIFICANCE: Few genes reproducibly demonstrated nonadditive expression among lineages, suggesting few changes resulted from a general response to polyploidization

  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. PhysioSpace: relating gene expression experiments from heterogeneous sources using shared physiological processes.

    Directory of Open Access Journals (Sweden)

    Michael Lenz

    Full Text Available Relating expression signatures from different sources such as cell lines, in vitro cultures from primary cells and biopsy material is an important task in drug development and translational medicine as well as for tracking of cell fate and disease progression. Especially the comparison of large scale gene expression changes to tissue or cell type specific signatures is of high interest for the tracking of cell fate in (trans- differentiation experiments and for cancer research, which increasingly focuses on shared processes and the involvement of the microenvironment. These signature relation approaches require robust statistical methods to account for the high biological heterogeneity in clinical data and must cope with small sample sizes in lab experiments and common patterns of co-expression in ubiquitous cellular processes. We describe a novel method, called PhysioSpace, to position dynamics of time series data derived from cellular differentiation and disease progression in a genome-wide expression space. The PhysioSpace is defined by a compendium of publicly available gene expression signatures representing a large set of biological phenotypes. The mapping of gene expression changes onto the PhysioSpace leads to a robust ranking of physiologically relevant signatures, as rigorously evaluated via sample-label permutations. A spherical transformation of the data improves the performance, leading to stable results even in case of small sample sizes. Using PhysioSpace with clinical cancer datasets reveals that such data exhibits large heterogeneity in the number of significant signature associations. This behavior was closely associated with the classification endpoint and cancer type under consideration, indicating shared biological functionalities in disease associated processes. Even though the time series data of cell line differentiation exhibited responses in larger clusters covering several biologically related patterns, top scoring

  8. 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

  9. High-performance integrated virtual environment (HIVE): a robust infrastructure for next-generation sequence data analysis.

    Science.gov (United States)

    Simonyan, Vahan; Chumakov, Konstantin; Dingerdissen, Hayley; Faison, William; Goldweber, Scott; Golikov, Anton; Gulzar, Naila; Karagiannis, Konstantinos; Vinh Nguyen Lam, Phuc; Maudru, Thomas; Muravitskaja, Olesja; Osipova, Ekaterina; Pan, Yang; Pschenichnov, Alexey; Rostovtsev, Alexandre; Santana-Quintero, Luis; Smith, Krista; Thompson, Elaine E; Tkachenko, Valery; Torcivia-Rodriguez, John; Voskanian, Alin; Wan, Quan; Wang, Jing; Wu, Tsung-Jung; Wilson, Carolyn; Mazumder, Raja

    2016-01-01

    The High-performance Integrated Virtual Environment (HIVE) is a distributed storage and compute environment designed primarily to handle next-generation sequencing (NGS) data. This multicomponent cloud infrastructure provides secure web access for authorized users to deposit, retrieve, annotate and compute on NGS data, and to analyse the outcomes using web interface visual environments appropriately built in collaboration with research and regulatory scientists and other end users. Unlike many massively parallel computing environments, HIVE uses a cloud control server which virtualizes services, not processes. It is both very robust and flexible due to the abstraction layer introduced between computational requests and operating system processes. The novel paradigm of moving computations to the data, instead of moving data to computational nodes, has proven to be significantly less taxing for both hardware and network infrastructure.The honeycomb data model developed for HIVE integrates metadata into an object-oriented model. Its distinction from other object-oriented databases is in the additional implementation of a unified application program interface to search, view and manipulate data of all types. This model simplifies the introduction of new data types, thereby minimizing the need for database restructuring and streamlining the development of new integrated information systems. The honeycomb model employs a highly secure hierarchical access control and permission system, allowing determination of data access privileges in a finely granular manner without flooding the security subsystem with a multiplicity of rules. HIVE infrastructure will allow engineers and scientists to perform NGS analysis in a manner that is both efficient and secure. HIVE is actively supported in public and private domains, and project collaborations are welcomed. Database URL: https://hive.biochemistry.gwu.edu.

  10. 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

  11. Sparse Representation for Classification of Tumors Using Gene Expression Data

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    Xiyi Hang

    2009-01-01

    Full Text Available Personalized drug design requires the classification of cancer patients as accurate as possible. With advances in genome sequencing and microarray technology, a large amount of gene expression data has been and will continuously be produced from various cancerous patients. Such cancer-alerted gene expression data allows us to classify tumors at the genomewide level. However, cancer-alerted gene expression datasets typically have much more number of genes (features than that of samples (patients, which imposes a challenge for classification of tumors. In this paper, a new method is proposed for cancer diagnosis using gene expression data by casting the classification problem as finding sparse representations of test samples with respect to training samples. The sparse representation is computed by the l1-regularized least square method. To investigate its performance, the proposed method is applied to six tumor gene expression datasets and compared with various support vector machine (SVM methods. The experimental results have shown that the performance of the proposed method is comparable with or better than those of SVMs. In addition, the proposed method is more efficient than SVMs as it has no need of model selection.

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

    Science.gov (United States)

    Saintigny, Pierre; Zhang, Li; Fan, You-Hong; El-Naggar, Adel K; Papadimitrakopoulou, Vassiliki A; Feng, Lei; Lee, J Jack; Kim, Edward S; Ki Hong, Waun; Mao, Li

    2011-02-01

    Patients with oral premalignant lesion (OPL) have a high risk of developing oral cancer. Although certain risk factors, such as smoking status and histology, are known, our ability to predict oral cancer risk remains poor. The study objective was to determine the value of gene expression profiling in predicting oral cancer development. Gene expression profile was measured in 86 of 162 OPL patients who were enrolled in a clinical chemoprevention trial that used the incidence of oral cancer development as a prespecified endpoint. The median follow-up time was 6.08 years and 35 of the 86 patients developed oral cancer over the course. Gene expression profiles were associated with oral cancer-free survival and used to develop multivariate predictive models for oral cancer prediction. We developed a 29-transcript predictive model which showed marked improvement in terms of prediction accuracy (with 8% predicting error rate) over the models using previously known clinicopathologic risk factors. On the basis of the gene expression profile data, we also identified 2,182 transcripts significantly associated with oral cancer risk-associated genes (P value oral cancer risk. In multiple independent data sets, the expression profiles of the genes can differentiate head and neck cancer from normal mucosa. Our results show that gene expression profiles may improve the prediction of oral cancer risk in OPL patients and the significant genes identified may serve as potential targets for oral cancer chemoprevention. ©2011 AACR.

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

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    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.

  14. Garlic Influences Gene Expression In Vivo and In Vitro.

    Science.gov (United States)

    Charron, Craig S; Dawson, Harry D; Novotny, Janet A

    2016-02-01

    There is a large body of preclinical research aimed at understanding the roles of garlic and garlic-derived preparations in the promotion of human health. Most of this research has targeted the possible functions of garlic in maintaining cardiovascular health and in preventing and treating cancer. A wide range of outcome variables has been used to investigate the bioactivity of garlic, ranging from direct measures of health status such as cholesterol concentrations, blood pressure, and changes in tumor size and number, to molecular and biochemical measures such as mRNA gene expression, protein concentration, enzyme activity, and histone acetylation status. Determination of how garlic influences mRNA gene expression has proven to be a valuable approach to elucidating the mechanisms of garlic bioactivity. Preclinical studies investigating the health benefits of garlic far outnumber human studies and have made frequent use of mRNA gene expression measurement. There is an immediate need to understand mRNA gene expression in humans as well. Although safety and ethical constraints limit the types of available human tissue, peripheral whole blood is readily accessible, and measuring mRNA gene expression in whole blood may provide a unique window to understanding how garlic intake affects human health.

  15. Variations in Phase and Amplitude of Rhythmic Clock Gene Expression across Prefrontal Cortex, Hippocampus, Amygdala, and Hypothalamic Paraventricular and Suprachiasmatic Nuclei of Male and Female Rats.

    Science.gov (United States)

    Chun, Lauren E; Woodruff, Elizabeth R; Morton, Sarah; Hinds, Laura R; Spencer, Robert L

    2015-10-01

    The molecular circadian clock is a self-regulating transcription/translation cycle of positive (Bmal1, Clock/Npas2) and negative (Per1,2,3, Cry1,2) regulatory components. While the molecular clock has been well characterized in the body's master circadian pacemaker, the hypothalamic suprachiasmatic nucleus (SCN), only a few studies have examined both the positive and negative clock components in extra-SCN brain tissue. Furthermore, there has yet to be a direct comparison of male and female clock gene expression in the brain. This comparison is warranted, as there are sex differences in circadian functioning and disorders associated with disrupted clock gene expression. This study examined basal clock gene expression (Per1, Per2, Bmal1 mRNA) in the SCN, prefrontal cortex (PFC), rostral agranular insula, hypothalamic paraventricular nucleus (PVN), amygdala, and hippocampus of male and female rats at 4-h intervals throughout a 12:12 h light:dark cycle. There was a significant rhythm of Per1, Per2, and Bmal1 in the SCN, PFC, insula, PVN, subregions of the hippocampus, and amygdala with a 24-h period, suggesting the importance of an oscillating molecular clock in extra-SCN brain regions. There were 3 distinct clock gene expression profiles across the brain regions, indicative of diversity among brain clocks. Although, generally, the clock gene expression profiles were similar between male and female rats, there were some sex differences in the robustness of clock gene expression (e.g., females had fewer robust rhythms in the medial PFC, more robust rhythms in the hippocampus, and a greater mesor in the medial amygdala). Furthermore, females with a regular estrous cycle had attenuated aggregate rhythms in clock gene expression in the PFC compared with noncycling females. This suggests that gonadal hormones may modulate the expression of the molecular clock.

  16. In Vivo Imaging of Local Gene Expression Induced by Magnetic Hyperthermia

    Science.gov (United States)

    Sandre, Olivier; Genevois, Coralie; Garaio, Eneko; Adumeau, Laurent; Mornet, Stéphane; Couillaud, Franck

    2017-01-01

    The present work aims to demonstrate that colloidal dispersions of magnetic iron oxide nanoparticles stabilized with dextran macromolecules placed in an alternating magnetic field can not only produce heat, but also that these particles could be used in vivo for local and noninvasive deposition of a thermal dose sufficient to trigger thermo-induced gene expression. Iron oxide nanoparticles were first characterized in vitro on a bio-inspired setup, and then they were assayed in vivo using a transgenic mouse strain expressing the luciferase reporter gene under transcriptional control of a thermosensitive promoter. Iron oxide nanoparticles dispersions were applied topically on the mouse skin or injected subcutaneously with Matrigel™ to generate so-called pseudotumors. Temperature was monitored continuously with a feedback loop to control the power of the magnetic field generator and to avoid overheating. Thermo-induced luciferase expression was followed by bioluminescence imaging 6 h after heating. We showed that dextran-coated magnetic iron oxide nanoparticle dispersions were able to induce in vivo mild hyperthermia compatible with thermo-induced gene expression in surrounding tissues and without impairing cell viability. These data open new therapeutic perspectives for using mild magnetic hyperthermia as noninvasive modulation of tumor microenvironment by local thermo-induced gene expression or drug release. PMID:28208731

  17. In Vivo Imaging of Local Gene Expression Induced by Magnetic Hyperthermia

    Directory of Open Access Journals (Sweden)

    Olivier Sandre

    2017-02-01

    Full Text Available The present work aims to demonstrate that colloidal dispersions of magnetic iron oxide nanoparticles stabilized with dextran macromolecules placed in an alternating magnetic field can not only produce heat, but also that these particles could be used in vivo for local and noninvasive deposition of a thermal dose sufficient to trigger thermo-induced gene expression. Iron oxide nanoparticles were first characterized in vitro on a bio-inspired setup, and then they were assayed in vivo using a transgenic mouse strain expressing the luciferase reporter gene under transcriptional control of a thermosensitive promoter. Iron oxide nanoparticles dispersions were applied topically on the mouse skin or injected subcutaneously with Matrigel™ to generate so-called pseudotumors. Temperature was monitored continuously with a feedback loop to control the power of the magnetic field generator and to avoid overheating. Thermo-induced luciferase expression was followed by bioluminescence imaging 6 h after heating. We showed that dextran-coated magnetic iron oxide nanoparticle dispersions were able to induce in vivo mild hyperthermia compatible with thermo-induced gene expression in surrounding tissues and without impairing cell viability. These data open new therapeutic perspectives for using mild magnetic hyperthermia as noninvasive modulation of tumor microenvironment by local thermo-induced gene expression or drug release.

  18. Gene expression, signal transduction pathways and functional networks associated with growth of sporadic vestibular schwannomas

    DEFF Research Database (Denmark)

    Sass, Hjalte Christian Reeberg; Borup, Rehannah; Alanin, Mikkel

    2017-01-01

    The objective of this study was to determine global gene expression in relation to Vestibular schwannomas (VS) growth rate and to identify signal transduction pathways and functional molecular networks associated with growth. Repeated magnetic resonance imaging (MRI) prior to surgery determined...... of signal transduction pathways and functional molecular networks associated with tumor growth. In total 109 genes were deregulated in relation to tumor growth rate. Genes associated with apoptosis, growth and cell proliferation were deregulated. Gene ontology included regulation of the cell cycle, cell...... differentiation and proliferation, among other functions. Fourteen pathways were associated with tumor growth. Five functional molecular networks were generated. This first study on global gene expression in relation to vestibular schwannoma growth rate identified several genes, signal transduction pathways...

  19. Integrated pathway-based transcription regulation network mining and visualization based on gene expression profiles.

    Science.gov (United States)

    Kibinge, Nelson; Ono, Naoaki; Horie, Masafumi; Sato, Tetsuo; Sugiura, Tadao; Altaf-Ul-Amin, Md; Saito, Akira; Kanaya, Shigehiko

    2016-06-01

    Conventionally, workflows examining transcription regulation networks from gene expression data involve distinct analytical steps. There is a need for pipelines that unify data mining and inference deduction into a singular framework to enhance interpretation and hypotheses generation. We propose a workflow that merges network construction with gene expression data mining focusing on regulation processes in the context of transcription factor driven gene regulation. The pipeline implements pathway-based modularization of expression profiles into functional units to improve biological interpretation. The integrated workflow was implemented as a web application software (TransReguloNet) with functions that enable pathway visualization and comparison of transcription factor activity between sample conditions defined in the experimental design. The pipeline merges differential expression, network construction, pathway-based abstraction, clustering and visualization. The framework was applied in analysis of actual expression datasets related to lung, breast and prostrate cancer. Copyright © 2016 Elsevier Inc. All rights reserved.

  20. Turnour necrosis factor stimulates endothelin-1 gene expression in cultured bovine endothelial cells

    Directory of Open Access Journals (Sweden)

    Silvia Orisio

    1992-01-01

    Full Text Available We have studied the effect of human recombinant tumour necrosis factor-α (TNF-α on gene expression and production of endothelin-1 in cultured bovine aortic endothelial cells. TNF-α (10 and 100 ng ml−1 increased in a time dependent manner the preproendothelin-1 mRNA levels in respect to unstimulated endothelial cells. TNF-α induced endothelin-1 gene expression was associated with a parallel increase in the release of the corresponding peptide in the culture medium. These findings suggest that the enhanced synthesis and release of endothelin-1 occurring in conditions of increased generation of TNF, may act as a modulatory factor that counteracts the hypotensive effect and the excessive platelet aggregation and adhesion induced by TNF.

  1. The influence of bovine milk high or low in isoflavones on hepatic gene expression in mice

    DEFF Research Database (Denmark)

    Skaanild, Mette Tingleff; Nielsen, Tina Skau

    2012-01-01

    in hepatic gene expression after dietary intake of milk high and low in isoflavones. In addition to pelleted feed female NMRI mice were offered water, water added either 17β-estradiol, equol, Tween 80, and milk high and low in isoflavone content for a week. Gene expression was analyzed using an array q......Isoflavones have generated much attention due to their potential positive effects in various diseases. Phytoestrogens especially equol can be found in bovine milk, as feed ration for dairy cows is comprised of plants containing phytoestrogens. The aim of this study was to analyze the changes......PCR kit. It was revealed that Tween 80 and 17β-estradiol upregulated both phase I and phase II genes to the same extent whereas equol alone, high and low isoflavone milk did not alter the expression of phase I genes but decreased the expression of phase II genes. This study shows that dietary isoflavones...

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

    Institute of Scientific and Technical Information of China (English)

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

    2005-01-01

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

  3. Integrative Analysis of DCE-MRI and Gene Expression Profiles in Construction of a Gene Classifier for Assessment of Hypoxia-Related Risk of Chemoradiotherapy Failure in Cervical Cancer

    DEFF Research Database (Denmark)

    Fjeldbo, Christina S; Julin, Cathinka H; Lando, Malin

    2016-01-01

    classification threshold that separated cervical cancer patients into a more and less hypoxic group with different outcome to chemoradiotherapy. EXPERIMENTAL DESIGN: A training cohort of 42 patients and two independent cohorts of 108 and 131 patients were included. Gene expression data were generated from tumor...... biopsies by two Illumina array generations (WG-6, HT-12). Technical transfer of the classifier to a reverse transcription quantitative PCR (RT-qPCR) platform was performed for 74 patients. The amplitude ABrix in the Brix pharmacokinetic model was extracted from DCE-MR images of 64 patients and used......-gene classifier was identified. The classifier separated the patients into two groups with different progression-free survival probability. The robustness of the classifier was demonstrated by successful validation of hypoxia association and prognostic value across cohorts, array generations, and assay...

  4. Selective gene expression by postnatal electroporation during olfactory interneuron neurogenesis.

    Directory of Open Access Journals (Sweden)

    Alexander T Chesler

    Full Text Available Neurogenesis persists in the olfactory system throughout life. The mechanisms of how new neurons are generated, how they integrate into circuits, and their role in coding remain mysteries. Here we report a technique that will greatly facilitate research into these questions. We found that electroporation can be used to robustly and selectively label progenitors in the Subventicular Zone. The approach was performed postnatally, without surgery, and with near 100% success rates. Labeling was found in all classes of interneurons in the olfactory bulb, persisted to adulthood and had no adverse effects. The broad utility of electroporation was demonstrated by encoding a calcium sensor and markers of intracellular organelles. The approach was found to be effective in wildtype and transgenic mice as well as rats. Given its versatility, robustness, and both time and cost effectiveness, this method offers a powerful new way to use genetic manipulation to understand adult neurogenesis.

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

    Science.gov (United States)

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

    2008-07-03

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

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

    Directory of Open Access Journals (Sweden)

    Gadea Jose

    2008-07-01

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

  7. ROUGH SET BASED CLUSTERING OF GENE EXPRESSION DATA: A SURVEY

    Directory of Open Access Journals (Sweden)

    J.JEBA EMILYN

    2010-12-01

    Full Text Available Microarray technology has now made it possible to simultaneously monitor the expression levels of thousands of genes during important biological processes and across collections of related samples. But the high dimensionality property of gene expression data makes it difficult to be analyzed. Lot of clustering algorithms are available for clustering. In this paper we first briefly introduce the concepts of microarray technology and discuss the basic elements of clustering on gene expression data. Then we introduce rough clustering and itsadvantage over strict and fuzzy clustering is explored. We also explain why rough clustering is preferred over other conventional methods by presenting a survey on few clustering algorithms based on rough set theory for gene expression data. We conclude by stating that this area proves to be potential research field for the researchcommunity.

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

    DEFF Research Database (Denmark)

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

    2010-01-01

    by carotid endarterectomy. The gene expression of markers of vulnerability - CD68, IL-18, matrix metalloproteinase 9, cathepsin K, GLUT-1, and hexokinase type II (HK2) - were measured in plaques by quantitative PCR. RESULTS: In a multivariate linear regression model, GLUT-1, CD68, cathepsin K, and HK2 gene...... expression remained in the final model as predictive variables of FDG accumulation calculated as SUVmean (R=0.26, PGLUT-1, CD68, cathepsin K, and HK2 gene expression as independent predictive variables of FDG accumulation calculated...... as SUVmax (R=0.30, PGLUT-1, HK2, CD68, and cathepsin K remained in both multivariate models and thus provided independent information regarding FDG uptake. We suggest that FDG uptake is a composite indicator of macrophage load, overall inflammatory activity and collagenolytic plaque...

  9. Study of human dopamine sulfotransferases based on gene expression programming.

    Science.gov (United States)

    Si, Hongzong; Zhao, Jiangang; Cui, Lianhua; Lian, Ning; Feng, Hanlin; Duan, Yun-Bo; Hu, Zhide

    2011-09-01

    A quantitative model is developed to predict the Km of 47 human dopamine sulfotransferases by gene expression programming. Each kind of compound is represented by several calculated structural descriptors of moment of inertia A, average electrophilic reactivity index for a C atom, relative number of triple bonds, RNCG relative negative charge, HA-dependent HDSA-1, and HBCA H-bonding charged surface area. Eight fitness functions of the gene expression programming method are used to find the best nonlinear model. The best quantitative model with squared standard error and square of correlation coefficient are 0.096 and 0.91 for training data set, and 0.102 and 0.88 for test set, respectively. It is shown that the gene expression programming-predicted results with fitness function are in good agreement with experimental ones.

  10. The core promoter: At the heart of gene expression.

    Science.gov (United States)

    Danino, Yehuda M; Even, Dan; Ideses, Diana; Juven-Gershon, Tamar

    2015-08-01

    The identities of different cells and tissues in multicellular organisms are determined by tightly controlled transcriptional programs that enable accurate gene expression. The mechanisms that regulate gene expression comprise diverse multiplayer molecular circuits of multiple dedicated components. The RNA polymerase II (Pol II) core promoter establishes the center of this spatiotemporally orchestrated molecular machine. Here, we discuss transcription initiation, diversity in core promoter composition, interactions of the basal transcription machinery with the core promoter, enhancer-promoter specificity, core promoter-preferential activation, enhancer RNAs, Pol II pausing, transcription termination, Pol II recycling and translation. We further discuss recent findings indicating that promoters and enhancers share similar features and may not substantially differ from each other, as previously assumed. Taken together, we review a broad spectrum of studies that highlight the importance of the core promoter and its pivotal role in the regulation of metazoan gene expression and suggest future research directions and challenges.

  11. New feature extraction in gene expression data for tumor classification

    Institute of Scientific and Technical Information of China (English)

    HE Renya; CHENG Qiansheng; WU Lianwen; YUAN Kehong

    2005-01-01

    Using gene expression data to discriminate tumor from the normal ones is a powerful method. However, it is sometimes difficult because the gene expression data are in high dimension and the object number of the data sets is very small. The key technique is to find a new gene expression profiling that can provide understanding and insight into tumor related cellular processes. In this paper, we propose a new feature extraction method based on variance to the center of the class and employ the support vector machine to recognize the gene data either normal or tumor. Two tumor data sets are used to demonstrate the effectiveness of our methods. The results show that the performance has been significantly improved.

  12. 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.

  13. Lab-specific gene expression signatures in pluripotent stem cells.

    Science.gov (United States)

    Newman, Aaron M; Cooper, James B

    2010-08-06

    Pluripotent stem cells derived from both embryonic and reprogrammed somatic cells have significant potential for human regenerative medicine. Despite similarities in developmental potential, however, several groups have found fundamental differences between embryonic stem cell (ESC) and induced-pluripotent stem cell (iPSC) lines that may have important implications for iPSC-based medical therapies. Using an unsupervised clustering algorithm, we further studied the genetic homogeneity of iPSC and ESC lines by reanalyzing microarray gene expression data from seven different laboratories. Unexpectedly, this analysis revealed a strong correlation between gene expression signatures and specific laboratories in both ESC and iPSC lines. Nearly one-third of the genes with lab-specific expression signatures are also differentially expressed between ESCs and iPSCs. These data are consistent with the hypothesis that in vitro microenvironmental context differentially impacts the gene expression signatures of both iPSCs and ESCs.

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

    CERN Document Server

    H, Swathi

    2010-01-01

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

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

    Science.gov (United States)

    Shaw, Harry C.

    2016-01-01

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

  16. Meta-analysis based variable selection for gene expression data.

    Science.gov (United States)

    Li, Quefeng; Wang, Sijian; Huang, Chiang-Ching; Yu, Menggang; Shao, Jun

    2014-12-01

    Recent advance in biotechnology and its wide applications have led to the generation of many high-dimensional gene expression data sets that can be used to address similar biological questions. Meta-analysis plays an important role in summarizing and synthesizing scientific evidence from multiple studies. When the dimensions of datasets are high, it is desirable to incorporate variable selection into meta-analysis to improve model interpretation and prediction. According to our knowledge, all existing methods conduct variable selection with meta-analyzed data in an "all-in-or-all-out" fashion, that is, a gene is either selected in all of studies or not selected in any study. However, due to data heterogeneity commonly exist in meta-analyzed data, including choices of biospecimens, study population, and measurement sensitivity, it is possible that a gene is important in some studies while unimportant in others. In this article, we propose a novel method called meta-lasso for variable selection with high-dimensional meta-analyzed data. Through a hierarchical decomposition on regression coefficients, our method not only borrows strength across multiple data sets to boost the power to identify important genes, but also keeps the selection flexibility among data sets to take into account data heterogeneity. We show that our method possesses the gene selection consistency, that is, when sample size of each data set is large, with high probability, our method can identify all important genes and remove all unimportant genes. Simulation studies demonstrate a good performance of our method. We applied our meta-lasso method to a meta-analysis of five cardiovascular studies. The analysis results are clinically meaningful.

  17. Production of cloned pigs with targeted attenuation of gene expression.

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    Vilceu Bordignon

    Full Text Available The objective of this study was to demonstrate that RNA interference (RNAi and somatic cell nuclear transfer (SCNT technologies can be used to attenuate the expression of specific genes in tissues of swine, a large animal species. Apolipoprotein E (apoE, a secreted glycoprotein known for its major role in lipid and lipoprotein metabolism and transport, was selected as the target gene for this study. Three synthetic small interfering RNAs (siRNA targeting the porcine apoE mRNA were tested in porcine granulosa cells in primary culture and reduced apoE mRNA abundance ranging from 45-82% compared to control cells. The most effective sequence was selected for cloning into a short hairpin RNA (shRNA expression vector under the control of RNA polymerase III (U6 promoter. Stably transfected fetal porcine fibroblast cells were generated and used to produce embryos with in vitro matured porcine oocytes, which were then transferred into the uterus of surrogate gilts. Seven live and one stillborn piglet were born from three gilts that became pregnant. Integration of the shRNA expression vector into the genome of clone piglets was confirmed by PCR and expression of the GFP transgene linked to the expression vector. Analysis showed that apoE protein levels in the liver and plasma of the clone pigs bearing the shRNA expression vector targeting the apoE mRNA was significantly reduced compared to control pigs cloned from non-transfected fibroblasts of the same cell line. These results demonstrate the feasibility of applying RNAi and SCNT technologies for introducing stable genetic modifications in somatic cells for eventual attenuation of gene expression in vivo in large animal species.

  18. Gene expression profile of renal cell carcinoma clear cell type

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    Marcos F. Dall’Oglio

    2010-08-01

    Full Text Available PURPOSE: The determination of prognosis in patients with renal cell carcinoma (RCC is based, classically, on stage and histopathological aspects. The metastatic disease develops in one third of patients after surgery, even in localized tumors. There are few options for treating those patients, and even the new target designed drugs have shown low rates of success in controlling disease progression. Few studies used high throughput genomic analysis in renal cell carcinoma for determination of prognosis. This study is focused on the identification of gene expression signatures in tissues of low-risk, high-risk and metastatic RCC clear cell type (RCC-CCT. MATERIALS AND METHODS: We analyzed the expression of approximately 55,000 distinct transcripts using the Whole Genome microarray platform hybridized with RNA extracted from 19 patients submitted to surgery to treat RCC-CCT with different clinical outcomes. They were divided into three groups (1 low risk, characterized by pT1, Fuhrman grade 1 or 2, no microvascular invasion RCC; (2 high risk, pT2-3, Fuhrman grade 3 or 4 with, necrosis and microvascular invasion present and (3 metastatic RCC-CCT. Normal renal tissue was used as control. RESULTS: After comparison of differentially expressed genes among low-risk, high-risk and metastatic groups, we identified a group of common genes characterizing metastatic disease. Among them Interleukin-8 and Heat shock protein 70 were over-expressed in metastasis and validated by real-time polymerase chain reaction. CONCLUSION: These findings can be used as a starting point to generate molecular markers of RCC-CCT as well as a target for the development of innovative therapies.

  19. Hybrid dysfunction and physiological compensation in gene expression.

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    Barreto, Felipe S; Pereira, Ricardo J; Burton, Ronald S

    2015-03-01

    The formation of new species is often a consequence of genetic incompatibilities accumulated between populations during allopatric divergence. When divergent taxa interbreed, these incompatibilities impact physiology and have a direct cost resulting in reduced hybrid fitness. Recent surveys of gene regulation in interspecific hybrids have revealed anomalous expression across large proportions of the genome, with 30-70% of all genes exhibiting transgressive expression (i.e., higher or lower levels compared with both parental taxa), and these were mostly in the direction of downregulation. However, as most of these studies have focused on pairs of species exhibiting high degrees of reproductive isolation, the association between regulatory disruption and reduced hybrid fitness prior to species formation remains unclear. Within the copepod species Tigriopus californicus, interpopulation hybrids at F2 or later generations show reduced fitness associated with mitochondrial dysfunction. Here we show that in contrast to studies of interspecific hybrids, only 1.2% of the transcriptome is transgressively expressed in F3+ interpopulation hybrids of T. californicus, and nearly 80% of these genes are overexpressed rather than underexpressed; remarkably, none of these genes are among those showing divergent expression between parentals, nor is magnitude of transgressive gene expression in hybrids dependent on levels of protein sequence divergence. Moreover, many genes with transgressive expression are components of functional pathways impacted by mitonuclear incompatibilities in hybrid T. californicus (e.g., oxidative phosphorylation and antioxidant response). Our results suggest that hybrid breakdown at early stages of speciation may result from initial incompatibilities amplified by the cost of compensatory physiological responses.

  20. Gene expression dosage regulation in an allopolyploid fish.

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    I Matos

    Full Text Available How allopolyploids are able not only to cope but profit from their condition is a question that remains elusive, but is of great importance within the context of successful allopolyploid evolution. One outstanding example of successful allopolyploidy is the endemic Iberian cyprinid Squalius alburnoides. Previously, based on the evaluation of a few genes, it was reported that the transcription levels between diploid and triploid S. alburnoides were similar. If this phenomenon occurs on a full genomic scale, a wide functional ''diploidization'' could be related to the success of these polyploids. We generated RNA-seq data from whole juvenile fish and from adult livers, to perform the first comparative quantitative transcriptomic analysis between diploid and triploid individuals of a vertebrate allopolyploid. Together with an assay to estimate relative expression per cell, it was possible to infer the relative sizes of transcriptomes. This showed that diploid and triploid S. alburnoides hybrids have similar liver transcriptome sizes. This in turn made it valid to directly compare the S. alburnoides RNA-seq transcript data sets and obtain a profile of dosage responses across the S. alburnoides transcriptome. We found that 64% of transcripts in juveniles' samples and 44% in liver samples differed less than twofold between diploid and triploid hybrids (similar expression. Yet, respectively 29% and 15% of transcripts presented accurate dosage compensation (PAA/PA expression ratio of 1 instead of 1.5. Therefore, an exact functional diploidization of the triploid genome does not occur, but a significant down regulation of gene expression in triploids was observed. However, for those genes with similar expression levels between diploids and triploids, expression is not globally strictly proportional to gene dosage nor is it set to a perfect diploid level. This quantitative expression flexibility may be a strong contributor to overcome the genomic shock

  1. A gene expression atlas of the domestic pig

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    Freeman Tom C

    2012-11-01

    Full Text Available Abstract Background This work describes the first genome-wide analysis of the transcriptional landscape of the pig. A new porcine Affymetrix expression array was designed in order to provide comprehensive coverage of the known pig transcriptome. The new array was used to generate a genome-wide expression atlas of pig tissues derived from 62 tissue/cell types. These data were subjected to network correlation analysis and clustering. Results The analysis presented here provides a detailed functional clustering of the pig transcriptome where transcripts are grouped according to their expression pattern, so one can infer the function of an uncharacterized gene from the company it keeps and the locations in which it is expressed. We describe the overall transcriptional signatures present in the tissue atlas, where possible assigning those signatures to specific cell populations or pathways. In particular, we discuss the expression signatures associated with the gastrointestinal tract, an organ that was sampled at 15 sites along its length and whose biology in the pig is similar to human. We identify sets of genes that define specialized cellular compartments and region-specific digestive functions. Finally, we performed a network analysis of the transcription factors expressed in the gastrointestinal tract and demonstrate how they sub-divide into functional groups that may control cellular gastrointestinal development. Conclusions As an important livestock animal with a physiology that is more similar than mouse to man, we provide a major new resource for understanding gene expression with respect to the known physiology of mammalian tissues and cells. The data and analyses are available on the websites http://biogps.org and http://www.macrophages.com/pig-atlas.

  2. Gene expression profiling in uveal melanoma: technical reliability and correlation of molecular class with pathologic characteristics.

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    Plasseraud, Kristen M; Wilkinson, Jeff K; Oelschlager, Kristen M; Poteet, Trisha M; Cook, Robert W; Stone, John F; Monzon, Federico A

    2017-08-04

    A 15-gene expression profile test has been clinically validated and is widely utilized in newly diagnosed uveal melanoma (UM) patients to assess metastatic potential of the tumor. As most patients are treated with eye-sparing radiotherapy, there is limited tumor tissue available for testing, and technical reliability and success of prognostic testing are critical. This study assessed the analytical performance of the 15-gene expression test for UM and the correlation of molecular class with pathologic characteristics. Inter-assay, intra-assay, inter-instrument/operator, and inter-site experiments were conducted, and concordance of the 15-gene expression profile test results and associated discriminant scores for matched tumor samples were evaluated. Technical success was determined from de-identified clinical reports from January 2010 - May 2016. Pathologic characteristics of enucleated tumors were correlated with molecular class results. Inter-assay concordance on 16 samples run on 3 consecutive days was 100%, and matched discriminant scores were strongly correlated (R(2) = 0.9944). Inter-assay concordance of 46 samples assayed within a one year period was 100%, with an R(2) value of 0.9747 for the discriminant scores. Intra-assay concordance of 12 samples run concurrently in duplicates was 100%; discriminant score correlation yielded an R(2) of 0.9934. Concordance between two sites assessing the same tumors was 100% with an R(2) of 0.9818 between discriminant scores. Inter-operator/instrument concordance was 96% for Class 1/2 calls and 90% for Class 1A/1B calls, and the discriminant scores had a correlation R(2) of 0.9636. Technical success was 96.3% on 5516 samples tested since 2010. Increased largest basal diameter and thickness were significantly associated with Class 1B and Class 2 vs. Class 1A signatures. These results show that the 15-gene expression profile test for UM has robust, reproducible performance characteristics. The technical success rate

  3. Faster-X Evolution of Gene Expression in Drosophila

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    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

  4. A Compendium of Canine Normal Tissue Gene Expression

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    Chen, Qing-Rong; Wen, Xinyu; Khan, Javed; Khanna, Chand

    2011-01-01

    Background Our understanding of disease is increasingly informed by changes in gene expression between normal and abnormal tissues. The release of the canine genome sequence in 2005 provided an opportunity to better understand human health and disease using the dog as clinically relevant model. Accordingly, we now present the first genome-wide, canine normal tissue gene expression compendium with corresponding human cross-species analysis. Methodology/Principal Findings The Affymetrix platform was utilized to catalogue gene expression signatures of 10 normal canine tissues including: liver, kidney, heart, lung, cerebrum, lymph node, spleen, jejunum, pancreas and skeletal muscle. The quality of the database was assessed in several ways. Organ defining gene sets were identified for each tissue and functional enrichment analysis revealed themes consistent with known physio-anatomic functions for each organ. In addition, a comparison of orthologous gene expression between matched canine and human normal tissues uncovered remarkable similarity. To demonstrate the utility of this dataset, novel canine gene annotations were established based on comparative analysis of dog and human tissue selective gene expression and manual curation of canine probeset mapping. Public access, using infrastructure identical to that currently in use for human normal tissues, has been established and allows for additional comparisons across species. Conclusions/Significance These data advance our understanding of the canine genome through a comprehensive analysis of gene expression in a diverse set of tissues, contributing to improved functional annotation that has been lacking. Importantly, it will be used to inform future studies of disease in the dog as a model for human translational research and provides a novel resource to the community at large. PMID:21655323

  5. Gene expression profiling reveals multiple toxicity endpoints induced by hepatotoxicants

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    Huang Qihong; Jin Xidong; Gaillard, Elias T.; Knight, Brian L.; Pack, Franklin D.; Stoltz, James H.; Jayadev, Supriya; Blanchard, Kerry T

    2004-05-18

    Microarray technology continues to gain increased acceptance in the drug development process, particularly at the stage of toxicology and safety assessment. In the current study, microarrays were used to investigate gene expression changes associated with hepatotoxicity, the most commonly reported clinical liability with pharmaceutical agents. Acetaminophen, methotrexate, methapyrilene, furan and phenytoin were used as benchmark compounds capable of inducing specific but different types of hepatotoxicity. The goal of the work was to define gene expression profiles capable of distinguishing the different subtypes of hepatotoxicity. Sprague-Dawley rats were orally dosed with acetaminophen (single dose, 4500 mg/kg for 6, 24 and 72 h), methotrexate (1 mg/kg per day for 1, 7 and 14 days), methapyrilene (100 mg/kg per day for 3 and 7 days), furan (40 mg/kg per day for 1, 3, 7 and 14 days) or phenytoin (300 mg/kg per day for 14 days). Hepatic gene expression was assessed using toxicology-specific gene arrays containing 684 target genes or expressed sequence tags (ESTs). Principal component analysis (PCA) of gene expression data was able to provide a clear distinction of each compound, suggesting that gene expression data can be used to discern different hepatotoxic agents and toxicity endpoints. Gene expression data were applied to the multiplicity-adjusted permutation test and significantly changed genes were categorized and correlated to hepatotoxic endpoints. Repression of enzymes involved in lipid oxidation (acyl-CoA dehydrogenase, medium chain, enoyl CoA hydratase, very long-chain acyl-CoA synthetase) were associated with microvesicular lipidosis. Likewise, subsets of genes associated with hepatotocellular necrosis, inflammation, hepatitis, bile duct hyperplasia and fibrosis have been identified. The current study illustrates that expression profiling can be used to: (1) distinguish different hepatotoxic endpoints; (2) predict the development of toxic endpoints; and

  6. Salmonella induces prominent gene expression in the rat colon

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    Roosing Susanne

    2007-09-01

    Full Text Available Abstract Background Salmonella enteritidis is suggested to translocate in the small intestine. In vivo it induces gene expression changes in the ileal mucosa and Peyer's patches. Stimulation of Salmonella translocation by dietary prebiotics fermented in colon suggests involvement of the colon as well. However, effects of Salmonella on colonic gene expression in vivo are largely unknown. We aimed to characterize time dependent Salmonella-induced changes of colonic mucosal gene expression in rats using whole genome microarrays. For this, rats were orally infected with Salmonella enteritidis to mimic a foodborne infection and colonic gene expression was determined at days 1, 3 and 6 post-infection (n = 8 rats per time-point. As fructo-oligosaccharides (FOS affect colonic physiology, we analyzed colonic mucosal gene expression of FOS-fed versus cellulose-fed rats infected with Salmonella in a separate experiment. Colonic mucosal samples were isolated at day 2 post-infection. Results Salmonella affected transport (e.g. Chloride channel calcium activated 6, H+/K+ transporting Atp-ase, antimicrobial defense (e.g. Lipopolysaccharide binding protein, Defensin 5 and phospholipase A2, inflammation (e.g. calprotectin, oxidative stress related genes (e.g. Dual oxidase 2 and Glutathione peroxidase 2 and Proteolysis (e.g. Ubiquitin D and Proteosome subunit beta type 9. Furthermore, Salmonella translocation increased serum IFNγ and many interferon-related genes in colonic mucosa. The gene most strongly induced by Salmonella infection was Pancreatitis Associated Protein (Pap, showing >100-fold induction at day 6 after oral infection. Results were confirmed by Q-PCR in individual rats. Stimulation of Salmonella translocation by dietary FOS was accompanied by enhancement of the Salmonella-induced mucosal processes, not by induction of other processes. Conclusion We conclude that the colon is a target tissue for Salmonella, considering the abundant changes in

  7. 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.

  8. A compendium of canine normal tissue gene expression.

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    Joseph Briggs

    Full Text Available BACKGROUND: Our understanding of disease is increasingly informed by changes in gene expression between normal and abnormal tissues. The release of the canine genome sequence in 2005 provided an opportunity to better understand human health and disease using the dog as clinically relevant model. Accordingly, we now present the first genome-wide, canine normal tissue gene expression compendium with corresponding human cross-species analysis. METHODOLOGY/PRINCIPAL FINDINGS: The Affymetrix platform was utilized to catalogue gene expression signatures of 10 normal canine tissues including: liver, kidney, heart, lung, cerebrum, lymph node, spleen, jejunum, pancreas and skeletal muscle. The quality of the database was assessed in several ways. Organ defining gene sets were iden