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Sample records for based gene expression

  1. GOBO: gene expression-based outcome for breast cancer online.

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    Markus Ringnér

    Full Text Available Microarray-based gene expression analysis holds promise of improving prognostication and treatment decisions for breast cancer patients. However, the heterogeneity of breast cancer emphasizes the need for validation of prognostic gene signatures in larger sample sets stratified into relevant subgroups. Here, we describe a multifunctional user-friendly online tool, GOBO (http://co.bmc.lu.se/gobo, allowing a range of different analyses to be performed in an 1881-sample breast tumor data set, and a 51-sample breast cancer cell line set, both generated on Affymetrix U133A microarrays. GOBO supports a wide range of applications including: 1 rapid assessment of gene expression levels in subgroups of breast tumors and cell lines, 2 identification of co-expressed genes for creation of potential metagenes, 3 association with outcome for gene expression levels of single genes, sets of genes, or gene signatures in multiple subgroups of the 1881-sample breast cancer data set. The design and implementation of GOBO facilitate easy incorporation of additional query functions and applications, as well as additional data sets irrespective of tumor type and array platform.

  2. Gene expression

    International Nuclear Information System (INIS)

    Hildebrand, C.E.; Crawford, B.D.; Walters, R.A.; Enger, M.D.

    1983-01-01

    We prepared probes for isolating functional pieces of the metallothionein locus. The probes enabled a variety of experiments, eventually revealing two mechanisms for metallothionein gene expression, the order of the DNA coding units at the locus, and the location of the gene site in its chromosome. Once the switch regulating metallothionein synthesis was located, it could be joined by recombinant DNA methods to other, unrelated genes, then reintroduced into cells by gene-transfer techniques. The expression of these recombinant genes could then be induced by exposing the cells to Zn 2+ or Cd 2+ . We would thus take advantage of the clearly defined switching properties of the metallothionein gene to manipulate the expression of other, perhaps normally constitutive, genes. Already, despite an incomplete understanding of how the regulatory switch of the metallothionein locus operates, such experiments have been performed successfully

  3. Ranking candidate disease genes from gene expression and protein interaction: a Katz-centrality based approach.

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    Jing Zhao

    Full Text Available Many diseases have complex genetic causes, where a set of alleles can affect the propensity of getting the disease. The identification of such disease genes is important to understand the mechanistic and evolutionary aspects of pathogenesis, improve diagnosis and treatment of the disease, and aid in drug discovery. Current genetic studies typically identify chromosomal regions associated specific diseases. But picking out an unknown disease gene from hundreds of candidates located on the same genomic interval is still challenging. In this study, we propose an approach to prioritize candidate genes by integrating data of gene expression level, protein-protein interaction strength and known disease genes. Our method is based only on two, simple, biologically motivated assumptions--that a gene is a good disease-gene candidate if it is differentially expressed in cases and controls, or that it is close to other disease-gene candidates in its protein interaction network. We tested our method on 40 diseases in 58 gene expression datasets of the NCBI Gene Expression Omnibus database. On these datasets our method is able to predict unknown disease genes as well as identifying pleiotropic genes involved in the physiological cellular processes of many diseases. Our study not only provides an effective algorithm for prioritizing candidate disease genes but is also a way to discover phenotypic interdependency, cooccurrence and shared pathophysiology between different disorders.

  4. A Fisheye Viewer for microarray-based gene expression data.

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    Wu, Min; Thao, Cheng; Mu, Xiangming; Munson, Ethan V

    2006-10-13

    Microarray has been widely used to measure the relative amounts of every mRNA transcript from the genome in a single scan. Biologists have been accustomed to reading their experimental data directly from tables. However, microarray data are quite large and are stored in a series of files in a machine-readable format, so direct reading of the full data set is not feasible. The challenge is to design a user interface that allows biologists to usefully view large tables of raw microarray-based gene expression data. This paper presents one such interface--an electronic table (E-table) that uses fisheye distortion technology. The Fisheye Viewer for microarray-based gene expression data has been successfully developed to view MIAME data stored in the MAGE-ML format. The viewer can be downloaded from the project web site http://polaris.imt.uwm.edu:7777/fisheye/. The fisheye viewer was implemented in Java so that it could run on multiple platforms. We implemented the E-table by adapting JTable, a default table implementation in the Java Swing user interface library. Fisheye views use variable magnification to balance magnification for easy viewing and compression for maximizing the amount of data on the screen. This Fisheye Viewer is a lightweight but useful tool for biologists to quickly overview the raw microarray-based gene expression data in an E-table.

  5. A fisheye viewer for microarray-based gene expression data

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    Munson Ethan V

    2006-10-01

    Full Text Available Abstract Background Microarray has been widely used to measure the relative amounts of every mRNA transcript from the genome in a single scan. Biologists have been accustomed to reading their experimental data directly from tables. However, microarray data are quite large and are stored in a series of files in a machine-readable format, so direct reading of the full data set is not feasible. The challenge is to design a user interface that allows biologists to usefully view large tables of raw microarray-based gene expression data. This paper presents one such interface – an electronic table (E-table that uses fisheye distortion technology. Results The Fisheye Viewer for microarray-based gene expression data has been successfully developed to view MIAME data stored in the MAGE-ML format. The viewer can be downloaded from the project web site http://polaris.imt.uwm.edu:7777/fisheye/. The fisheye viewer was implemented in Java so that it could run on multiple platforms. We implemented the E-table by adapting JTable, a default table implementation in the Java Swing user interface library. Fisheye views use variable magnification to balance magnification for easy viewing and compression for maximizing the amount of data on the screen. Conclusion This Fisheye Viewer is a lightweight but useful tool for biologists to quickly overview the raw microarray-based gene expression data in an E-table.

  6. Nearest Neighbor Networks: clustering expression data based on gene neighborhoods

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    Olszewski Kellen L

    2007-07-01

    Full Text Available Abstract Background The availability of microarrays measuring thousands of genes simultaneously across hundreds of biological conditions represents an opportunity to understand both individual biological pathways and the integrated workings of the cell. However, translating this amount of data into biological insight remains a daunting task. An important initial step in the analysis of microarray data is clustering of genes with similar behavior. A number of classical techniques are commonly used to perform this task, particularly hierarchical and K-means clustering, and many novel approaches have been suggested recently. While these approaches are useful, they are not without drawbacks; these methods can find clusters in purely random data, and even clusters enriched for biological functions can be skewed towards a small number of processes (e.g. ribosomes. Results We developed Nearest Neighbor Networks (NNN, a graph-based algorithm to generate clusters of genes with similar expression profiles. This method produces clusters based on overlapping cliques within an interaction network generated from mutual nearest neighborhoods. This focus on nearest neighbors rather than on absolute distance measures allows us to capture clusters with high connectivity even when they are spatially separated, and requiring mutual nearest neighbors allows genes with no sufficiently similar partners to remain unclustered. We compared the clusters generated by NNN with those generated by eight other clustering methods. NNN was particularly successful at generating functionally coherent clusters with high precision, and these clusters generally represented a much broader selection of biological processes than those recovered by other methods. Conclusion The Nearest Neighbor Networks algorithm is a valuable clustering method that effectively groups genes that are likely to be functionally related. It is particularly attractive due to its simplicity, its success in the

  7. Finding gene regulatory network candidates using the gene expression knowledge base.

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    Venkatesan, Aravind; Tripathi, Sushil; Sanz de Galdeano, Alejandro; Blondé, Ward; Lægreid, Astrid; Mironov, Vladimir; Kuiper, Martin

    2014-12-10

    Network-based approaches for the analysis of large-scale genomics data have become well established. Biological networks provide a knowledge scaffold against which the patterns and dynamics of 'omics' data can be interpreted. The background information required for the construction of such networks is often dispersed across a multitude of knowledge bases in a variety of formats. The seamless integration of this information is one of the main challenges in bioinformatics. The Semantic Web offers powerful technologies for the assembly of integrated knowledge bases that are computationally comprehensible, thereby providing a potentially powerful resource for constructing biological networks and network-based analysis. We have developed the Gene eXpression Knowledge Base (GeXKB), a semantic web technology based resource that contains integrated knowledge about gene expression regulation. To affirm the utility of GeXKB we demonstrate how this resource can be exploited for the identification of candidate regulatory network proteins. We present four use cases that were designed from a biological perspective in order to find candidate members relevant for the gastrin hormone signaling network model. We show how a combination of specific query definitions and additional selection criteria derived from gene expression data and prior knowledge concerning candidate proteins can be used to retrieve a set of proteins that constitute valid candidates for regulatory network extensions. Semantic web technologies provide the means for processing and integrating various heterogeneous information sources. The GeXKB offers biologists such an integrated knowledge resource, allowing them to address complex biological questions pertaining to gene expression. This work illustrates how GeXKB can be used in combination with gene expression results and literature information to identify new potential candidates that may be considered for extending a gene regulatory network.

  8. Embryo quality predictive models based on cumulus cells gene expression

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    Devjak R

    2016-06-01

    Full Text Available Since the introduction of in vitro fertilization (IVF in clinical practice of infertility treatment, the indicators for high quality embryos were investigated. Cumulus cells (CC have a specific gene expression profile according to the developmental potential of the oocyte they are surrounding, and therefore, specific gene expression could be used as a biomarker. The aim of our study was to combine more than one biomarker to observe improvement in prediction value of embryo development. In this study, 58 CC samples from 17 IVF patients were analyzed. This study was approved by the Republic of Slovenia National Medical Ethics Committee. Gene expression analysis [quantitative real time polymerase chain reaction (qPCR] for five genes, analyzed according to embryo quality level, was performed. Two prediction models were tested for embryo quality prediction: a binary logistic and a decision tree model. As the main outcome, gene expression levels for five genes were taken and the area under the curve (AUC for two prediction models were calculated. Among tested genes, AMHR2 and LIF showed significant expression difference between high quality and low quality embryos. These two genes were used for the construction of two prediction models: the binary logistic model yielded an AUC of 0.72 ± 0.08 and the decision tree model yielded an AUC of 0.73 ± 0.03. Two different prediction models yielded similar predictive power to differentiate high and low quality embryos. In terms of eventual clinical decision making, the decision tree model resulted in easy-to-interpret rules that are highly applicable in clinical practice.

  9. Density based pruning for identification of differentially expressed genes from microarray data

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    Xu Jia

    2010-11-01

    Full Text Available Abstract Motivation Identification of differentially expressed genes from microarray datasets is one of the most important analyses for microarray data mining. Popular algorithms such as statistical t-test rank genes based on a single statistics. The false positive rate of these methods can be improved by considering other features of differentially expressed genes. Results We proposed a pattern recognition strategy for identifying differentially expressed genes. Genes are mapped to a two dimension feature space composed of average difference of gene expression and average expression levels. A density based pruning algorithm (DB Pruning is developed to screen out potential differentially expressed genes usually located in the sparse boundary region. Biases of popular algorithms for identifying differentially expressed genes are visually characterized. Experiments on 17 datasets from Gene Omnibus Database (GEO with experimentally verified differentially expressed genes showed that DB pruning can significantly improve the prediction accuracy of popular identification algorithms such as t-test, rank product, and fold change. Conclusions Density based pruning of non-differentially expressed genes is an effective method for enhancing statistical testing based algorithms for identifying differentially expressed genes. It improves t-test, rank product, and fold change by 11% to 50% in the numbers of identified true differentially expressed genes. The source code of DB pruning is freely available on our website http://mleg.cse.sc.edu/degprune

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

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    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.

  11. A Model-Based Joint Identification of Differentially Expressed Genes and Phenotype-Associated Genes.

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    Samuel Sunghwan Cho

    Full Text Available Over the last decade, many analytical methods and tools have been developed for microarray data. The detection of differentially expressed genes (DEGs among different treatment groups is often a primary purpose of microarray data analysis. In addition, association studies investigating the relationship between genes and a phenotype of interest such as survival time are also popular in microarray data analysis. Phenotype association analysis provides a list of phenotype-associated genes (PAGs. However, it is sometimes necessary to identify genes that are both DEGs and PAGs. We consider the joint identification of DEGs and PAGs in microarray data analyses. The first approach we used was a naïve approach that detects DEGs and PAGs separately and then identifies the genes in an intersection of the list of PAGs and DEGs. The second approach we considered was a hierarchical approach that detects DEGs first and then chooses PAGs from among the DEGs or vice versa. In this study, we propose a new model-based approach for the joint identification of DEGs and PAGs. Unlike the previous two-step approaches, the proposed method identifies genes simultaneously that are DEGs and PAGs. This method uses standard regression models but adopts different null hypothesis from ordinary regression models, which allows us to perform joint identification in one-step. The proposed model-based methods were evaluated using experimental data and simulation studies. The proposed methods were used to analyze a microarray experiment in which the main interest lies in detecting genes that are both DEGs and PAGs, where DEGs are identified between two diet groups and PAGs are associated with four phenotypes reflecting the expression of leptin, adiponectin, insulin-like growth factor 1, and insulin. Model-based approaches provided a larger number of genes, which are both DEGs and PAGs, than other methods. Simulation studies showed that they have more power than other methods

  12. A Model-Based Joint Identification of Differentially Expressed Genes and Phenotype-Associated Genes

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    Seo, Minseok; Shin, Su-kyung; Kwon, Eun-Young; Kim, Sung-Eun; Bae, Yun-Jung; Lee, Seungyeoun; Sung, Mi-Kyung; Choi, Myung-Sook; Park, Taesung

    2016-01-01

    Over the last decade, many analytical methods and tools have been developed for microarray data. The detection of differentially expressed genes (DEGs) among different treatment groups is often a primary purpose of microarray data analysis. In addition, association studies investigating the relationship between genes and a phenotype of interest such as survival time are also popular in microarray data analysis. Phenotype association analysis provides a list of phenotype-associated genes (PAGs). However, it is sometimes necessary to identify genes that are both DEGs and PAGs. We consider the joint identification of DEGs and PAGs in microarray data analyses. The first approach we used was a naïve approach that detects DEGs and PAGs separately and then identifies the genes in an intersection of the list of PAGs and DEGs. The second approach we considered was a hierarchical approach that detects DEGs first and then chooses PAGs from among the DEGs or vice versa. In this study, we propose a new model-based approach for the joint identification of DEGs and PAGs. Unlike the previous two-step approaches, the proposed method identifies genes simultaneously that are DEGs and PAGs. This method uses standard regression models but adopts different null hypothesis from ordinary regression models, which allows us to perform joint identification in one-step. The proposed model-based methods were evaluated using experimental data and simulation studies. The proposed methods were used to analyze a microarray experiment in which the main interest lies in detecting genes that are both DEGs and PAGs, where DEGs are identified between two diet groups and PAGs are associated with four phenotypes reflecting the expression of leptin, adiponectin, insulin-like growth factor 1, and insulin. Model-based approaches provided a larger number of genes, which are both DEGs and PAGs, than other methods. Simulation studies showed that they have more power than other methods. Through analysis of

  13. Gene Expression Omnibus (GEO)

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    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...

  14. Design-Based Learning for Biology: Genetic Engineering Experience Improves Understanding of Gene Expression

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    Ellefson, Michelle R.; Brinker, Rebecca A.; Vernacchio, Vincent J.; Schunn, Christian D.

    2008-01-01

    Gene expression is a difficult topic for students to learn and comprehend, at least partially because it involves various biochemical structures and processes occurring at the microscopic level. Designer Bacteria, a design-based learning (DBL) unit for high-school students, applies principles of DBL to the teaching of gene expression. Throughout…

  15. dictyExpress: a Dictyostelium discoideum gene expression database with an explorative data analysis web-based interface

    Science.gov (United States)

    Rot, Gregor; Parikh, Anup; Curk, Tomaz; Kuspa, Adam; Shaulsky, Gad; Zupan, Blaz

    2009-01-01

    Background Bioinformatics often leverages on recent advancements in computer science to support biologists in their scientific discovery process. Such efforts include the development of easy-to-use web interfaces to biomedical databases. Recent advancements in interactive web technologies require us to rethink the standard submit-and-wait paradigm, and craft bioinformatics web applications that share analytical and interactive power with their desktop relatives, while retaining simplicity and availability. Results We have developed dictyExpress, a web application that features a graphical, highly interactive explorative interface to our database that consists of more than 1000 Dictyostelium discoideum gene expression experiments. In dictyExpress, the user can select experiments and genes, perform gene clustering, view gene expression profiles across time, view gene co-expression networks, perform analyses of Gene Ontology term enrichment, and simultaneously display expression profiles for a selected gene in various experiments. Most importantly, these tasks are achieved through web applications whose components are seamlessly interlinked and immediately respond to events triggered by the user, thus providing a powerful explorative data analysis environment. Conclusion dictyExpress is a precursor for a new generation of web-based bioinformatics applications with simple but powerful interactive interfaces that resemble that of the modern desktop. While dictyExpress serves mainly the Dictyostelium research community, it is relatively easy to adapt it to other datasets. We propose that the design ideas behind dictyExpress will influence the development of similar applications for other model organisms. PMID:19706156

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

    KAUST Repository

    Abusamra, Heba

    2016-07-20

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

  17. Inferring nonlinear gene regulatory networks from gene expression data based on distance correlation.

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    Xiaobo Guo

    Full Text Available Nonlinear dependence is general in regulation mechanism of gene regulatory networks (GRNs. It is vital to properly measure or test nonlinear dependence from real data for reconstructing GRNs and understanding the complex regulatory mechanisms within the cellular system. A recently developed measurement called the distance correlation (DC has been shown powerful and computationally effective in nonlinear dependence for many situations. In this work, we incorporate the DC into inferring GRNs from the gene expression data without any underling distribution assumptions. We propose three DC-based GRNs inference algorithms: CLR-DC, MRNET-DC and REL-DC, and then compare them with the mutual information (MI-based algorithms by analyzing two simulated data: benchmark GRNs from the DREAM challenge and GRNs generated by SynTReN network generator, and an experimentally determined SOS DNA repair network in Escherichia coli. According to both the receiver operator characteristic (ROC curve and the precision-recall (PR curve, our proposed algorithms significantly outperform the MI-based algorithms in GRNs inference.

  18. Inferring gene dependency network specific to phenotypic alteration based on gene expression data and clinical information of breast cancer.

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    Zhou, Xionghui; Liu, Juan

    2014-01-01

    Although many methods have been proposed to reconstruct gene regulatory network, most of them, when applied in the sample-based data, can not reveal the gene regulatory relations underlying the phenotypic change (e.g. normal versus cancer). In this paper, we adopt phenotype as a variable when constructing the gene regulatory network, while former researches either neglected it or only used it to select the differentially expressed genes as the inputs to construct the gene regulatory network. To be specific, we integrate phenotype information with gene expression data to identify the gene dependency pairs by using the method of conditional mutual information. A gene dependency pair (A,B) means that the influence of gene A on the phenotype depends on gene B. All identified gene dependency pairs constitute a directed network underlying the phenotype, namely gene dependency network. By this way, we have constructed gene dependency network of breast cancer from gene expression data along with two different phenotype states (metastasis and non-metastasis). Moreover, we have found the network scale free, indicating that its hub genes with high out-degrees may play critical roles in the network. After functional investigation, these hub genes are found to be biologically significant and specially related to breast cancer, which suggests that our gene dependency network is meaningful. The validity has also been justified by literature investigation. From the network, we have selected 43 discriminative hubs as signature to build the classification model for distinguishing the distant metastasis risks of breast cancer patients, and the result outperforms those classification models with published signatures. In conclusion, we have proposed a promising way to construct the gene regulatory network by using sample-based data, which has been shown to be effective and accurate in uncovering the hidden mechanism of the biological process and identifying the gene signature for

  19. Screening key genes for abdominal aortic aneurysm based on gene expression omnibus dataset.

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    Wan, Li; Huang, Jingyong; Ni, Haizhen; Yu, Guanfeng

    2018-02-13

    Abdominal aortic aneurysm (AAA) is a common cardiovascular system disease with high mortality. The aim of this study was to identify potential genes for diagnosis and therapy in AAA. We searched and downloaded mRNA expression data from the Gene Expression Omnibus (GEO) database to identify differentially expressed genes (DEGs) from AAA and normal individuals. Then, Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway analysis, transcriptional factors (TFs) network and protein-protein interaction (PPI) network were used to explore the function of genes. Additionally, immunohistochemical (IHC) staining was used to validate the expression of identified genes. Finally, the diagnostic value of identified genes was accessed by receiver operating characteristic (ROC) analysis in GEO database. A total of 1199 DEGs (188 up-regulated and 1011 down-regulated) were identified between AAA and normal individual. KEGG pathway analysis displayed that vascular smooth muscle contraction and pathways in cancer were significantly enriched signal pathway. The top 10 up-regulated and top 10 down-regulated DEGs were used to construct TFs and PPI networks. Some genes with high degrees such as NELL2, CCR7, MGAM, HBB, CSNK2A2, ZBTB16 and FOXO1 were identified to be related to AAA. The consequences of IHC staining showed that CCR7 and PDGFA were up-regulated in tissue samples of AAA. ROC analysis showed that NELL2, CCR7, MGAM, HBB, CSNK2A2, ZBTB16, FOXO1 and PDGFA had the potential diagnostic value for AAA. The identified genes including NELL2, CCR7, MGAM, HBB, CSNK2A2, ZBTB16, FOXO1 and PDGFA might be involved in the pathology of AAA.

  20. Partial least squares based gene expression analysis in estrogen receptor positive and negative breast tumors.

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    Ma, W; Zhang, T-F; Lu, P; Lu, S H

    2014-01-01

    Breast cancer is categorized into two broad groups: estrogen receptor positive (ER+) and ER negative (ER-) groups. Previous study proposed that under trastuzumab-based neoadjuvant chemotherapy, tumor initiating cell (TIC) featured ER- tumors response better than ER+ tumors. Exploration of the molecular difference of these two groups may help developing new therapeutic strategies, especially for ER- patients. With gene expression profile from the Gene Expression Omnibus (GEO) database, we performed partial least squares (PLS) based analysis, which is more sensitive than common variance/regression analysis. We acquired 512 differentially expressed genes. Four pathways were found to be enriched with differentially expressed genes, involving immune system, metabolism and genetic information processing process. Network analysis identified five hub genes with degrees higher than 10, including APP, ESR1, SMAD3, HDAC2, and PRKAA1. Our findings provide new understanding for the molecular difference between TIC featured ER- and ER+ breast tumors with the hope offer supports for therapeutic studies.

  1. Towards precise classification of cancers based on robust gene functional expression profiles

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    Zhu Jing

    2005-03-01

    Full Text Available Abstract Background Development of robust and efficient methods for analyzing and interpreting high dimension gene expression profiles continues to be a focus in computational biology. The accumulated experiment evidence supports the assumption that genes express and perform their functions in modular fashions in cells. Therefore, there is an open space for development of the timely and relevant computational algorithms that use robust functional expression profiles towards precise classification of complex human diseases at the modular level. Results Inspired by the insight that genes act as a module to carry out a highly integrated cellular function, we thus define a low dimension functional expression profile for data reduction. After annotating each individual gene to functional categories defined in a proper gene function classification system such as Gene Ontology applied in this study, we identify those functional categories enriched with differentially expressed genes. For each functional category or functional module, we compute a summary measure (s for the raw expression values of the annotated genes to capture the overall activity level of the module. In this way, we can treat the gene expressions within a functional module as an integrative data point to replace the multiple values of individual genes. We compare the classification performance of decision trees based on functional expression profiles with the conventional gene expression profiles using four publicly available datasets, which indicates that precise classification of tumour types and improved interpretation can be achieved with the reduced functional expression profiles. Conclusion This modular approach is demonstrated to be a powerful alternative approach to analyzing high dimension microarray data and is robust to high measurement noise and intrinsic biological variance inherent in microarray data. Furthermore, efficient integration with current biological knowledge

  2. Gene expression and gene therapy imaging

    International Nuclear Information System (INIS)

    Rome, Claire; Couillaud, Franck; Moonen, Chrit T.W.

    2007-01-01

    The fast growing field of molecular imaging has achieved major advances in imaging gene expression, an important element of gene therapy. Gene expression imaging is based on specific probes or contrast agents that allow either direct or indirect spatio-temporal evaluation of gene expression. Direct evaluation is possible with, for example, contrast agents that bind directly to a specific target (e.g., receptor). Indirect evaluation may be achieved by using specific substrate probes for a target enzyme. The use of marker genes, also called reporter genes, is an essential element of MI approaches for gene expression in gene therapy. The marker gene may not have a therapeutic role itself, but by coupling the marker gene to a therapeutic gene, expression of the marker gene reports on the expression of the therapeutic gene. Nuclear medicine and optical approaches are highly sensitive (detection of probes in the picomolar range), whereas MRI and ultrasound imaging are less sensitive and require amplification techniques and/or accumulation of contrast agents in enlarged contrast particles. Recently developed MI techniques are particularly relevant for gene therapy. Amongst these are the possibility to track gene therapy vectors such as stem cells, and the techniques that allow spatiotemporal control of gene expression by non-invasive heating (with MRI guided focused ultrasound) and the use of temperature sensitive promoters. (orig.)

  3. The Arabidopsis co-expression tool (act): a WWW-based tool and database for microarray-based gene expression analysis

    DEFF Research Database (Denmark)

    Jen, C. H.; Manfield, I. W.; Michalopoulos, D. W.

    2006-01-01

    be examined using the novel clique finder tool to determine the sets of genes most likely to be regulated in a similar manner. In combination, these tools offer three levels of analysis: creation of correlation lists of co-expressed genes, refinement of these lists using two-dimensional scatter plots......We present a new WWW-based tool for plant gene analysis, the Arabidopsis Co-Expression Tool (act) , based on a large Arabidopsis thaliana microarray data set obtained from the Nottingham Arabidopsis Stock Centre. The co-expression analysis tool allows users to identify genes whose expression...

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

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    Guo Zheng

    2006-01-01

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

  5. 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

    2016-01-01

    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. 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. 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. Gene and pathway level models performed similarly to each other and to a model based on demographic information only. 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.

  6. Prediction of highly expressed genes in microbes based on chromatin accessibility

    Directory of Open Access Journals (Sweden)

    Ussery David W

    2007-02-01

    Full Text Available Abstract Background It is well known that gene expression is dependent on chromatin structure in eukaryotes and it is likely that chromatin can play a role in bacterial gene expression as well. Here, we use a nucleosomal position preference measure of anisotropic DNA flexibility to predict highly expressed genes in microbial genomes. We compare these predictions with those based on codon adaptation index (CAI values, and also with experimental data for 6 different microbial genomes, with a particular interest in experimental data from Escherichia coli. Moreover, position preference is examined further in 328 sequenced microbial genomes. Results We find that absolute gene expression levels are correlated with the position preference in many microbial genomes. It is postulated that in these regions, the DNA may be more accessible to the transcriptional machinery. Moreover, ribosomal proteins and ribosomal RNA are encoded by DNA having significantly lower position preference values than other genes in fast-replicating microbes. Conclusion This insight into DNA structure-dependent gene expression in microbes may be exploited for predicting the expression of non-translated genes such as non-coding RNAs that may not be predicted by any of the conventional codon usage bias approaches.

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

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    Gong Binsheng

    2011-05-01

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

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

    Science.gov (United States)

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

    2015-05-01

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

  9. Cytomegalovirus replicon-based regulation of gene expression in vitro and in vivo.

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    Hermine Mohr

    Full Text Available There is increasing evidence for a connection between DNA replication and the expression of adjacent genes. Therefore, this study addressed the question of whether a herpesvirus origin of replication can be used to activate or increase the expression of adjacent genes. Cell lines carrying an episomal vector, in which reporter genes are linked to the murine cytomegalovirus (MCMV origin of lytic replication (oriLyt, were constructed. Reporter gene expression was silenced by a histone-deacetylase-dependent mechanism, but was resolved upon lytic infection with MCMV. Replication of the episome was observed subsequent to infection, leading to the induction of gene expression by more than 1000-fold. oriLyt-based regulation thus provided a unique opportunity for virus-induced conditional gene expression without the need for an additional induction mechanism. This principle was exploited to show effective late trans-complementation of the toxic viral protein M50 and the glycoprotein gO of MCMV. Moreover, the application of this principle for intracellular immunization against herpesvirus infection was demonstrated. The results of the present study show that viral infection specifically activated the expression of a dominant-negative transgene, which inhibited viral growth. This conditional system was operative in explant cultures of transgenic mice, but not in vivo. Several applications are discussed.

  10. Analyzing Plasmodium falciparum erythrocyte membrane protein 1 gene expression by a next generation sequencing based method

    DEFF Research Database (Denmark)

    Jespersen, Jakob S.; Petersen, Bent; Seguin-Orlando, Andaine

    2013-01-01

    at identifying PfEMP1 features associated with high virulence. Here we present the first effective method for sequence analysis of var genes expressed in field samples: a sequential PCR and next generation sequencing based technique applied on expressed var sequence tags and subsequently on long range PCR......, encoded by ~60 highly variable 'var' genes per haploid genome. PfEMP1 is exported to the surface of infected erythrocytes and is thought to be fundamental to immune evasion by adhesion to host and parasite factors. The highly variable nature has constituted a roadblock in var expression studies aimed...

  11. A network-based gene expression signature informs prognosis and treatment for colorectal cancer patients.

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    Mingguang Shi

    Full Text Available Several studies have reported gene expression signatures that predict recurrence risk in stage II and III colorectal cancer (CRC patients with minimal gene membership overlap and undefined biological relevance. The goal of this study was to investigate biological themes underlying these signatures, to infer genes of potential mechanistic importance to the CRC recurrence phenotype and to test whether accurate prognostic models can be developed using mechanistically important genes.We investigated eight published CRC gene expression signatures and found no functional convergence in Gene Ontology enrichment analysis. Using a random walk-based approach, we integrated these signatures and publicly available somatic mutation data on a protein-protein interaction network and inferred 487 genes that were plausible candidate molecular underpinnings for the CRC recurrence phenotype. We named the list of 487 genes a NEM signature because it integrated information from Network, Expression, and Mutation. The signature showed significant enrichment in four biological processes closely related to cancer pathophysiology and provided good coverage of known oncogenes, tumor suppressors, and CRC-related signaling pathways. A NEM signature-based Survival Support Vector Machine prognostic model was trained using a microarray gene expression dataset and tested on an independent dataset. The model-based scores showed a 75.7% concordance with the real survival data and separated patients into two groups with significantly different relapse-free survival (p = 0.002. Similar results were obtained with reversed training and testing datasets (p = 0.007. Furthermore, adjuvant chemotherapy was significantly associated with prolonged survival of the high-risk patients (p = 0.006, but not beneficial to the low-risk patients (p = 0.491.The NEM signature not only reflects CRC biology but also informs patient prognosis and treatment response. Thus, the network-based

  12. Hessian regularization based non-negative matrix factorization for gene expression data clustering.

    Science.gov (United States)

    Liu, Xiao; Shi, Jun; Wang, Congzhi

    2015-01-01

    Since a key step in the analysis of gene expression data is to detect groups of genes that have similar expression patterns, clustering technique is then commonly used to analyze gene expression data. Data representation plays an important role in clustering analysis. The non-negative matrix factorization (NMF) is a widely used data representation method with great success in machine learning. Although the traditional manifold regularization method, Laplacian regularization (LR), can improve the performance of NMF, LR still suffers from the problem of its weak extrapolating power. Hessian regularization (HR) is a newly developed manifold regularization method, whose natural properties make it more extrapolating, especially for small sample data. In this work, we propose the HR-based NMF (HR-NMF) algorithm, and then apply it to represent gene expression data for further clustering task. The clustering experiments are conducted on five commonly used gene datasets, and the results indicate that the proposed HR-NMF outperforms LR-based NMM and original NMF, which suggests the potential application of HR-NMF for gene expression data.

  13. Accurate Gene Expression-Based Biodosimetry Using a Minimal Set of Human Gene Transcripts

    Energy Technology Data Exchange (ETDEWEB)

    Tucker, James D., E-mail: jtucker@biology.biosci.wayne.edu [Department of Biological Sciences, Wayne State University, Detroit, Michigan (United States); Joiner, Michael C. [Department of Radiation Oncology, Wayne State University, Detroit, Michigan (United States); Thomas, Robert A.; Grever, William E.; Bakhmutsky, Marina V. [Department of Biological Sciences, Wayne State University, Detroit, Michigan (United States); Chinkhota, Chantelle N.; Smolinski, Joseph M. [Department of Electrical and Computer Engineering, Wayne State University, Detroit, Michigan (United States); Divine, George W. [Department of Public Health Sciences, Henry Ford Hospital, Detroit, Michigan (United States); Auner, Gregory W. [Department of Electrical and Computer Engineering, Wayne State University, Detroit, Michigan (United States)

    2014-03-15

    Purpose: Rapid and reliable methods for conducting biological dosimetry are a necessity in the event of a large-scale nuclear event. Conventional biodosimetry methods lack the speed, portability, ease of use, and low cost required for triaging numerous victims. Here we address this need by showing that polymerase chain reaction (PCR) on a small number of gene transcripts can provide accurate and rapid dosimetry. The low cost and relative ease of PCR compared with existing dosimetry methods suggest that this approach may be useful in mass-casualty triage situations. Methods and Materials: Human peripheral blood from 60 adult donors was acutely exposed to cobalt-60 gamma rays at doses of 0 (control) to 10 Gy. mRNA expression levels of 121 selected genes were obtained 0.5, 1, and 2 days after exposure by reverse-transcriptase real-time PCR. Optimal dosimetry at each time point was obtained by stepwise regression of dose received against individual gene transcript expression levels. Results: Only 3 to 4 different gene transcripts, ASTN2, CDKN1A, GDF15, and ATM, are needed to explain ≥0.87 of the variance (R{sup 2}). Receiver-operator characteristics, a measure of sensitivity and specificity, of 0.98 for these statistical models were achieved at each time point. Conclusions: The actual and predicted radiation doses agree very closely up to 6 Gy. Dosimetry at 8 and 10 Gy shows some effect of saturation, thereby slightly diminishing the ability to quantify higher exposures. Analyses of these gene transcripts may be advantageous for use in a field-portable device designed to assess exposures in mass casualty situations or in clinical radiation emergencies.

  14. Allen Brain Atlas-Driven Visualizations: a web-based gene expression energy visualization tool.

    Science.gov (United States)

    Zaldivar, Andrew; Krichmar, Jeffrey L

    2014-01-01

    The Allen Brain Atlas-Driven Visualizations (ABADV) is a publicly accessible web-based tool created to retrieve and visualize expression energy data from the Allen Brain Atlas (ABA) across multiple genes and brain structures. Though the ABA offers their own search engine and software for researchers to view their growing collection of online public data sets, including extensive gene expression and neuroanatomical data from human and mouse brain, many of their tools limit the amount of genes and brain structures researchers can view at once. To complement their work, ABADV generates multiple pie charts, bar charts and heat maps of expression energy values for any given set of genes and brain structures. Such a suite of free and easy-to-understand visualizations allows for easy comparison of gene expression across multiple brain areas. In addition, each visualization links back to the ABA so researchers may view a summary of the experimental detail. ABADV is currently supported on modern web browsers and is compatible with expression energy data from the Allen Mouse Brain Atlas in situ hybridization data. By creating this web application, researchers can immediately obtain and survey numerous amounts of expression energy data from the ABA, which they can then use to supplement their work or perform meta-analysis. In the future, we hope to enable ABADV across multiple data resources.

  15. Allen Brain Atlas-Driven Visualizations: A Web-Based Gene Expression Energy Visualization Tool

    Directory of Open Access Journals (Sweden)

    Andrew eZaldivar

    2014-05-01

    Full Text Available The Allen Brain Atlas-Driven Visualizations (ABADV is a publicly accessible web-based tool created to retrieve and visualize expression energy data from the Allen Brain Atlas (ABA across multiple genes and brain structures. Though the ABA offers their own search engine and software for researchers to view their growing collection of online public data sets, including extensive gene expression and neuroanatomical data from human and mouse brain, many of their tools limit the amount of genes and brain structures researchers can view at once. To complement their work, ABADV generates multiple pie charts, bar charts and heat maps of expression energy values for any given set of genes and brain structures. Such a suite of free and easy-to-understand visualizations allows for easy comparison of gene expression across multiple brain areas. In addition, each visualization links back to the ABA so researchers may view a summary of the experimental detail. ABADV is currently supported on modern web browsers and is compatible with expression energy data from the Allen Mouse Brain Atlas in situ hybridization data. By creating this web application, researchers can immediately obtain and survey numerous amounts of expression energy data from the ABA, which they can then use to supplement their work or perform meta-analysis. In the future, we hope to enable ABADV across multiple data resources.

  16. A resampling-based meta-analysis for detection of differential gene expression in breast cancer

    International Nuclear Information System (INIS)

    Gur-Dedeoglu, Bala; Konu, Ozlen; Kir, Serkan; Ozturk, Ahmet Rasit; Bozkurt, Betul; Ergul, Gulusan; Yulug, Isik G

    2008-01-01

    Accuracy in the diagnosis of breast cancer and classification of cancer subtypes has improved over the years with the development of well-established immunohistopathological criteria. More recently, diagnostic gene-sets at the mRNA expression level have been tested as better predictors of disease state. However, breast cancer is heterogeneous in nature; thus extraction of differentially expressed gene-sets that stably distinguish normal tissue from various pathologies poses challenges. Meta-analysis of high-throughput expression data using a collection of statistical methodologies leads to the identification of robust tumor gene expression signatures. A resampling-based meta-analysis strategy, which involves the use of resampling and application of distribution statistics in combination to assess the degree of significance in differential expression between sample classes, was developed. Two independent microarray datasets that contain normal breast, invasive ductal carcinoma (IDC), and invasive lobular carcinoma (ILC) samples were used for the meta-analysis. Expression of the genes, selected from the gene list for classification of normal breast samples and breast tumors encompassing both the ILC and IDC subtypes were tested on 10 independent primary IDC samples and matched non-tumor controls by real-time qRT-PCR. Other existing breast cancer microarray datasets were used in support of the resampling-based meta-analysis. The two independent microarray studies were found to be comparable, although differing in their experimental methodologies (Pearson correlation coefficient, R = 0.9389 and R = 0.8465 for ductal and lobular samples, respectively). The resampling-based meta-analysis has led to the identification of a highly stable set of genes for classification of normal breast samples and breast tumors encompassing both the ILC and IDC subtypes. The expression results of the selected genes obtained through real-time qRT-PCR supported the meta-analysis results. The

  17. A resampling-based meta-analysis for detection of differential gene expression in breast cancer

    Directory of Open Access Journals (Sweden)

    Ergul Gulusan

    2008-12-01

    Full Text Available Abstract Background Accuracy in the diagnosis of breast cancer and classification of cancer subtypes has improved over the years with the development of well-established immunohistopathological criteria. More recently, diagnostic gene-sets at the mRNA expression level have been tested as better predictors of disease state. However, breast cancer is heterogeneous in nature; thus extraction of differentially expressed gene-sets that stably distinguish normal tissue from various pathologies poses challenges. Meta-analysis of high-throughput expression data using a collection of statistical methodologies leads to the identification of robust tumor gene expression signatures. Methods A resampling-based meta-analysis strategy, which involves the use of resampling and application of distribution statistics in combination to assess the degree of significance in differential expression between sample classes, was developed. Two independent microarray datasets that contain normal breast, invasive ductal carcinoma (IDC, and invasive lobular carcinoma (ILC samples were used for the meta-analysis. Expression of the genes, selected from the gene list for classification of normal breast samples and breast tumors encompassing both the ILC and IDC subtypes were tested on 10 independent primary IDC samples and matched non-tumor controls by real-time qRT-PCR. Other existing breast cancer microarray datasets were used in support of the resampling-based meta-analysis. Results The two independent microarray studies were found to be comparable, although differing in their experimental methodologies (Pearson correlation coefficient, R = 0.9389 and R = 0.8465 for ductal and lobular samples, respectively. The resampling-based meta-analysis has led to the identification of a highly stable set of genes for classification of normal breast samples and breast tumors encompassing both the ILC and IDC subtypes. The expression results of the selected genes obtained through real

  18. Machine learning approaches to supporting the identification of photoreceptor-enriched genes based on expression data

    Directory of Open Access Journals (Sweden)

    Simpson David

    2006-03-01

    Full Text Available Abstract Background Retinal photoreceptors are highly specialised cells, which detect light and are central to mammalian vision. Many retinal diseases occur as a result of inherited dysfunction of the rod and cone photoreceptor cells. Development and maintenance of photoreceptors requires appropriate regulation of the many genes specifically or highly expressed in these cells. Over the last decades, different experimental approaches have been developed to identify photoreceptor enriched genes. Recent progress in RNA analysis technology has generated large amounts of gene expression data relevant to retinal development. This paper assesses a machine learning methodology for supporting the identification of photoreceptor enriched genes based on expression data. Results Based on the analysis of publicly-available gene expression data from the developing mouse retina generated by serial analysis of gene expression (SAGE, this paper presents a predictive methodology comprising several in silico models for detecting key complex features and relationships encoded in the data, which may be useful to distinguish genes in terms of their functional roles. In order to understand temporal patterns of photoreceptor gene expression during retinal development, a two-way cluster analysis was firstly performed. By clustering SAGE libraries, a hierarchical tree reflecting relationships between developmental stages was obtained. By clustering SAGE tags, a more comprehensive expression profile for photoreceptor cells was revealed. To demonstrate the usefulness of machine learning-based models in predicting functional associations from the SAGE data, three supervised classification models were compared. The results indicated that a relatively simple instance-based model (KStar model performed significantly better than relatively more complex algorithms, e.g. neural networks. To deal with the problem of functional class imbalance occurring in the dataset, two data re

  19. Cancer Outlier Analysis Based on Mixture Modeling of Gene Expression Data

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    Keita Mori

    2013-01-01

    Full Text Available Molecular heterogeneity of cancer, partially caused by various chromosomal aberrations or gene mutations, can yield substantial heterogeneity in gene expression profile in cancer samples. To detect cancer-related genes which are active only in a subset of cancer samples or cancer outliers, several methods have been proposed in the context of multiple testing. Such cancer outlier analyses will generally suffer from a serious lack of power, compared with the standard multiple testing setting where common activation of genes across all cancer samples is supposed. In this paper, we consider information sharing across genes and cancer samples, via a parametric normal mixture modeling of gene expression levels of cancer samples across genes after a standardization using the reference, normal sample data. A gene-based statistic for gene selection is developed on the basis of a posterior probability of cancer outlier for each cancer sample. Some efficiency improvement by using our method was demonstrated, even under settings with misspecified, heavy-tailed t-distributions. An application to a real dataset from hematologic malignancies is provided.

  20. Clustering gene expression data based on predicted differential effects of GV interaction.

    Science.gov (United States)

    Pan, Hai-Yan; Zhu, Jun; Han, Dan-Fu

    2005-02-01

    Microarray has become a popular biotechnology in biological and medical research. However, systematic and stochastic variabilities in microarray data are expected and unavoidable, resulting in the problem that the raw measurements have inherent "noise" within microarray experiments. Currently, logarithmic ratios are usually analyzed by various clustering methods directly, which may introduce bias interpretation in identifying groups of genes or samples. In this paper, a statistical method based on mixed model approaches was proposed for microarray data cluster analysis. The underlying rationale of this method is to partition the observed total gene expression level into various variations caused by different factors using an ANOVA model, and to predict the differential effects of GV (gene by variety) interaction using the adjusted unbiased prediction (AUP) method. The predicted GV interaction effects can then be used as the inputs of cluster analysis. We illustrated the application of our method with a gene expression dataset and elucidated the utility of our approach using an external validation.

  1. PINTA: a web server for network-based gene prioritization from expression data

    DEFF Research Database (Denmark)

    Nitsch, Daniela; Tranchevent, Léon-Charles; Goncalves, Joana P.

    2011-01-01

    PINTA (available at http://www.esat.kuleuven.be/ pinta/; this web site is free and open to all users and there is no login requirement) is a web resource for the prioritization of candidate genes based on the differential expression of their neighborhood in a genome-wide protein–protein interaction...

  2. Minimal gene selection for classification and diagnosis prediction based on gene expression profile

    Directory of Open Access Journals (Sweden)

    Alireza Mehridehnavi

    2013-01-01

    Conclusion: We have shown that the use of two most significant genes based on their S/N ratios and selection of suitable training samples can lead to classify DLBCL patients with a rather good result. Actually with the aid of mentioned methods we could compensate lack of enough number of patients, improve accuracy of classifying and reduce complication of computations and so running time.

  3. Identification of potential crucial genes associated with steroid-induced necrosis of femoral head based on gene expression profile.

    Science.gov (United States)

    Lin, Zhe; Lin, Yongsheng

    2017-09-05

    The aim of this study was to explore potential crucial genes associated with the steroid-induced necrosis of femoral head (SINFH) and to provide valid biological information for further investigation of SINFH. Gene expression profile of GSE26316, generated from 3 SINFH rat samples and 3 normal rat samples were downloaded from Gene Expression Omnibus (GEO) database. The differentially expressed genes (DEGs) were identified using LIMMA package. After functional enrichment analyses of DEGs, protein-protein interaction (PPI) network and sub-PPI network analyses were conducted based on the STRING database and cytoscape. In total, 59 up-regulated DEGs and 156 downregulated DEGs were identified. The up-regulated DEGs were mainly involved in functions about immunity (e.g. Fcer1A and Il7R), and the downregulated DEGs were mainly enriched in muscle system process (e.g. Tnni2, Mylpf and Myl1). The PPI network of DEGs consisted of 123 nodes and 300 interactions. Tnni2, Mylpf, and Myl1 were the top 3 outstanding genes based on both subgraph centrality and degree centrality evaluation. These three genes interacted with each other in the network. Furthermore, the significant network module was composed of 22 downregulated genes (e.g. Tnni2, Mylpf and Myl1). These genes were mainly enriched in functions like muscle system process. The DEGs related to the regulation of immune system process (e.g. Fcer1A and Il7R), and DEGs correlated with muscle system process (e.g. Tnni2, Mylpf and Myl1) may be closely associated with the progress of SINFH, which is still needed to be confirmed by experiments. Copyright © 2017 Elsevier B.V. All rights reserved.

  4. Monoterpenoid-based preparations in beehives affect learning, memory, and gene expression in the bee brain.

    Science.gov (United States)

    Bonnafé, Elsa; Alayrangues, Julie; Hotier, Lucie; Massou, Isabelle; Renom, Allan; Souesme, Guillaume; Marty, Pierre; Allaoua, Marion; Treilhou, Michel; Armengaud, Catherine

    2017-02-01

    Bees are exposed in their environment to contaminants that can weaken the colony and contribute to bee declines. Monoterpenoid-based preparations can be introduced into hives to control the parasitic mite Varroa destructor. The long-term effects of monoterpenoids are poorly investigated. Olfactory conditioning of the proboscis extension reflex (PER) has been used to evaluate the impact of stressors on cognitive functions of the honeybee such as learning and memory. The authors tested the PER to odorants on bees after exposure to monoterpenoids in hives. Octopamine receptors, transient receptor potential-like (TRPL), and γ-aminobutyric acid channels are thought to play a critical role in the memory of food experience. Gene expression levels of Amoa1, Rdl, and trpl were evaluated in parallel in the bee brain because these genes code for the cellular targets of monoterpenoids and some pesticides and neural circuits of memory require their expression. The miticide impaired the PER to odors in the 3 wk following treatment. Short-term and long-term olfactory memories were improved months after introduction of the monoterpenoids into the beehives. Chronic exposure to the miticide had significant effects on Amoa1, Rdl, and trpl gene expressions and modified seasonal changes in the expression of these genes in the brain. The decrease of expression of these genes in winter could partly explain the improvement of memory. The present study has led to new insights into alternative treatments, especially on their effects on memory and expression of selected genes involved in this cognitive function. Environ Toxicol Chem 2017;36:337-345. © 2016 SETAC. © 2016 SETAC.

  5. Expression-based clustering of CAZyme-encoding genes of Aspergillus niger.

    Science.gov (United States)

    Gruben, Birgit S; Mäkelä, Miia R; Kowalczyk, Joanna E; Zhou, Miaomiao; Benoit-Gelber, Isabelle; De Vries, Ronald P

    2017-11-23

    The Aspergillus niger genome contains a large repertoire of genes encoding carbohydrate active enzymes (CAZymes) that are targeted to plant polysaccharide degradation enabling A. niger to grow on a wide range of plant biomass substrates. Which genes need to be activated in certain environmental conditions depends on the composition of the available substrate. Previous studies have demonstrated the involvement of a number of transcriptional regulators in plant biomass degradation and have identified sets of target genes for each regulator. In this study, a broad transcriptional analysis was performed of the A. niger genes encoding (putative) plant polysaccharide degrading enzymes. Microarray data focusing on the initial response of A. niger to the presence of plant biomass related carbon sources were analyzed of a wild-type strain N402 that was grown on a large range of carbon sources and of the regulatory mutant strains ΔxlnR, ΔaraR, ΔamyR, ΔrhaR and ΔgalX that were grown on their specific inducing compounds. The cluster analysis of the expression data revealed several groups of co-regulated genes, which goes beyond the traditionally described co-regulated gene sets. Additional putative target genes of the selected regulators were identified, based on their expression profile. Notably, in several cases the expression profile puts questions on the function assignment of uncharacterized genes that was based on homology searches, highlighting the need for more extensive biochemical studies into the substrate specificity of enzymes encoded by these non-characterized genes. The data also revealed sets of genes that were upregulated in the regulatory mutants, suggesting interaction between the regulatory systems and a therefore even more complex overall regulatory network than has been reported so far. Expression profiling on a large number of substrates provides better insight in the complex regulatory systems that drive the conversion of plant biomass by fungi. In

  6. Frequency-based time-series gene expression recomposition using PRIISM

    Directory of Open Access Journals (Sweden)

    Rosa Bruce A

    2012-06-01

    Full Text Available Abstract Background Circadian rhythm pathways influence the expression patterns of as much as 31% of the Arabidopsis genome through complicated interaction pathways, and have been found to be significantly disrupted by biotic and abiotic stress treatments, complicating treatment-response gene discovery methods due to clock pattern mismatches in the fold change-based statistics. The PRIISM (Pattern Recomposition for the Isolation of Independent Signals in Microarray data algorithm outlined in this paper is designed to separate pattern changes induced by different forces, including treatment-response pathways and circadian clock rhythm disruptions. Results Using the Fourier transform, high-resolution time-series microarray data is projected to the frequency domain. By identifying the clock frequency range from the core circadian clock genes, we separate the frequency spectrum to different sections containing treatment-frequency (representing up- or down-regulation by an adaptive treatment response, clock-frequency (representing the circadian clock-disruption response and noise-frequency components. Then, we project the components’ spectra back to the expression domain to reconstruct isolated, independent gene expression patterns representing the effects of the different influences. By applying PRIISM on a high-resolution time-series Arabidopsis microarray dataset under a cold treatment, we systematically evaluated our method using maximum fold change and principal component analyses. The results of this study showed that the ranked treatment-frequency fold change results produce fewer false positives than the original methodology, and the 26-hour timepoint in our dataset was the best statistic for distinguishing the most known cold-response genes. In addition, six novel cold-response genes were discovered. PRIISM also provides gene expression data which represents only circadian clock influences, and may be useful for circadian clock studies

  7. GeneTrailExpress: a web-based pipeline for the statistical evaluation of microarray experiments

    Directory of Open Access Journals (Sweden)

    Kohlbacher Oliver

    2008-12-01

    Full Text Available Abstract Background High-throughput methods that allow for measuring the expression of thousands of genes or proteins simultaneously have opened new avenues for studying biochemical processes. While the noisiness of the data necessitates an extensive pre-processing of the raw data, the high dimensionality requires effective statistical analysis methods that facilitate the identification of crucial biological features and relations. For these reasons, the evaluation and interpretation of expression data is a complex, labor-intensive multi-step process. While a variety of tools for normalizing, analysing, or visualizing expression profiles has been developed in the last years, most of these tools offer only functionality for accomplishing certain steps of the evaluation pipeline. Results Here, we present a web-based toolbox that provides rich functionality for all steps of the evaluation pipeline. Our tool GeneTrailExpress offers besides standard normalization procedures powerful statistical analysis methods for studying a large variety of biological categories and pathways. Furthermore, an integrated graph visualization tool, BiNA, enables the user to draw the relevant biological pathways applying cutting-edge graph-layout algorithms. Conclusion Our gene expression toolbox with its interactive visualization of the pathways and the expression values projected onto the nodes will simplify the analysis and interpretation of biochemical pathways considerably.

  8. Accurate, model-based tuning of synthetic gene expression using introns in S. cerevisiae.

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    Ido Yofe

    2014-06-01

    Full Text Available Introns are key regulators of eukaryotic gene expression and present a potentially powerful tool for the design of synthetic eukaryotic gene expression systems. However, intronic control over gene expression is governed by a multitude of complex, incompletely understood, regulatory mechanisms. Despite this lack of detailed mechanistic understanding, here we show how a relatively simple model enables accurate and predictable tuning of synthetic gene expression system in yeast using several predictive intron features such as transcript folding and sequence motifs. Using only natural Saccharomyces cerevisiae introns as regulators, we demonstrate fine and accurate control over gene expression spanning a 100 fold expression range. These results broaden the engineering toolbox of synthetic gene expression systems and provide a framework in which precise and robust tuning of gene expression is accomplished.

  9. Imaging gene expression in gene therapy

    International Nuclear Information System (INIS)

    Wiebe, Leonard I.

    1997-01-01

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

  10. Imaging gene expression in gene therapy

    Energy Technology Data Exchange (ETDEWEB)

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

    1997-12-31

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

  11. Time warping of evolutionary distant temporal gene expression data based on noise suppression

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    Papatsenko Dmitri

    2009-10-01

    Full Text Available Abstract Background Comparative analysis of genome wide temporal gene expression data has a broad potential area of application, including evolutionary biology, developmental biology, and medicine. However, at large evolutionary distances, the construction of global alignments and the consequent comparison of the time-series data are difficult. The main reason is the accumulation of variability in expression profiles of orthologous genes, in the course of evolution. Results We applied Pearson distance matrices, in combination with other noise-suppression techniques and data filtering to improve alignments. This novel framework enhanced the capacity to capture the similarities between the temporal gene expression datasets separated by large evolutionary distances. We aligned and compared the temporal gene expression data in budding (Saccharomyces cerevisiae and fission (Schizosaccharomyces pombe yeast, which are separated by more then ~400 myr of evolution. We found that the global alignment (time warping properly matched the duration of cell cycle phases in these distant organisms, which was measured in prior studies. At the same time, when applied to individual ortholog pairs, this alignment procedure revealed groups of genes with distinct alignments, different from the global alignment. Conclusion Our alignment-based predictions of differences in the cell cycle phases between the two yeast species were in a good agreement with the existing data, thus supporting the computational strategy adopted in this study. We propose that the existence of the alternative alignments, specific to distinct groups of genes, suggests presence of different synchronization modes between the two organisms and possible functional decoupling of particular physiological gene networks in the course of evolution.

  12. Lineage relationship of prostate cancer cell types based on gene expression

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    Ware Carol B

    2011-05-01

    Full Text Available Abstract Background Prostate tumor heterogeneity is a major factor in disease management. Heterogeneity could be due to multiple cancer cell types with distinct gene expression. Of clinical importance is the so-called cancer stem cell type. Cell type-specific transcriptomes are used to examine lineage relationship among cancer cell types and their expression similarity to normal cell types including stem/progenitor cells. Methods Transcriptomes were determined by Affymetrix DNA array analysis for the following cell types. Putative prostate progenitor cell populations were characterized and isolated by expression of the membrane transporter ABCG2. Stem cells were represented by embryonic stem and embryonal carcinoma cells. The cancer cell types were Gleason pattern 3 (glandular histomorphology and pattern 4 (aglandular sorted from primary tumors, cultured prostate cancer cell lines originally established from metastatic lesions, xenografts LuCaP 35 (adenocarcinoma phenotype and LuCaP 49 (neuroendocrine/small cell carcinoma grown in mice. No detectable gene expression differences were detected among serial passages of the LuCaP xenografts. Results Based on transcriptomes, the different cancer cell types could be clustered into a luminal-like grouping and a non-luminal-like (also not basal-like grouping. The non-luminal-like types showed expression more similar to that of stem/progenitor cells than the luminal-like types. However, none showed expression of stem cell genes known to maintain stemness. Conclusions Non-luminal-like types are all representatives of aggressive disease, and this could be attributed to the similarity in overall gene expression to stem and progenitor cell types.

  13. Gene expression-based molecular diagnostic system for malignant gliomas is superior to histological diagnosis.

    Science.gov (United States)

    Shirahata, Mitsuaki; Iwao-Koizumi, Kyoko; Saito, Sakae; Ueno, Noriko; Oda, Masashi; Hashimoto, Nobuo; Takahashi, Jun A; Kato, Kikuya

    2007-12-15

    Current morphology-based glioma classification methods do not adequately reflect the complex biology of gliomas, thus limiting their prognostic ability. In this study, we focused on anaplastic oligodendroglioma and glioblastoma, which typically follow distinct clinical courses. Our goal was to construct a clinically useful molecular diagnostic system based on gene expression profiling. The expression of 3,456 genes in 32 patients, 12 and 20 of whom had prognostically distinct anaplastic oligodendroglioma and glioblastoma, respectively, was measured by PCR array. Next to unsupervised methods, we did supervised analysis using a weighted voting algorithm to construct a diagnostic system discriminating anaplastic oligodendroglioma from glioblastoma. The diagnostic accuracy of this system was evaluated by leave-one-out cross-validation. The clinical utility was tested on a microarray-based data set of 50 malignant gliomas from a previous study. Unsupervised analysis showed divergent global gene expression patterns between the two tumor classes. A supervised binary classification model showed 100% (95% confidence interval, 89.4-100%) diagnostic accuracy by leave-one-out cross-validation using 168 diagnostic genes. Applied to a gene expression data set from a previous study, our model correlated better with outcome than histologic diagnosis, and also displayed 96.6% (28 of 29) consistency with the molecular classification scheme used for these histologically controversial gliomas in the original article. Furthermore, we observed that histologically diagnosed glioblastoma samples that shared anaplastic oligodendroglioma molecular characteristics tended to be associated with longer survival. Our molecular diagnostic system showed reproducible clinical utility and prognostic ability superior to traditional histopathologic diagnosis for malignant glioma.

  14. Characteristics and Validation Techniques for PCA-Based Gene-Expression Signatures

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    Anders E. Berglund

    2017-01-01

    Full Text Available Background. Many gene-expression signatures exist for describing the biological state of profiled tumors. Principal Component Analysis (PCA can be used to summarize a gene signature into a single score. Our hypothesis is that gene signatures can be validated when applied to new datasets, using inherent properties of PCA. Results. This validation is based on four key concepts. Coherence: elements of a gene signature should be correlated beyond chance. Uniqueness: the general direction of the data being examined can drive most of the observed signal. Robustness: if a gene signature is designed to measure a single biological effect, then this signal should be sufficiently strong and distinct compared to other signals within the signature. Transferability: the derived PCA gene signature score should describe the same biology in the target dataset as it does in the training dataset. Conclusions. The proposed validation procedure ensures that PCA-based gene signatures perform as expected when applied to datasets other than those that the signatures were trained upon. Complex signatures, describing multiple independent biological components, are also easily identified.

  15. A contribution to the study of plant development evolution based on gene co-expression networks

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    Francisco J. Romero-Campero

    2013-08-01

    Full Text Available Phototrophic eukaryotes are among the most successful organisms on Earth due to their unparalleled efficiency at capturing light energy and fixing carbon dioxide to produce organic molecules. A conserved and efficient network of light-dependent regulatory modules could be at the bases of this success. This regulatory system conferred early advantages to phototrophic eukaryotes that allowed for specialization, complex developmental processes and modern plant characteristics. We have studied light-dependent gene regulatory modules from algae to plants employing integrative-omics approaches based on gene co-expression networks. Our study reveals some remarkably conserved ways in which eukaryotic phototrophs deal with day length and light signaling. Here we describe how a family of Arabidopsis transcription factors involved in photoperiod response has evolved from a single algal gene according to the innovation, amplification and divergence theory of gene evolution by duplication. These modifications of the gene co-expression networks from the ancient unicellular green algae Chlamydomonas reinhardtii to the modern brassica Arabidopsis thaliana may hint on the evolution and specialization of plants and other organisms.

  16. Candidate genes and pathogenesis investigation for sepsis-related acute respiratory distress syndrome based on gene expression profile.

    Science.gov (United States)

    Wang, Min; Yan, Jingjun; He, Xingxing; Zhong, Qiang; Zhan, Chengye; Li, Shusheng

    2016-04-18

    Acute respiratory distress syndrome (ARDS) is a potentially devastating form of acute inflammatory lung injury as well as a major cause of acute respiratory failure. Although researchers have made significant progresses in elucidating the pathophysiology of this complex syndrome over the years, the absence of a universal detail disease mechanism up until now has led to a series of practical problems for a definitive treatment. This study aimed to predict some genes or pathways associated with sepsis-related ARDS based on a public microarray dataset and to further explore the molecular mechanism of ARDS. A total of 122 up-regulated DEGs and 91 down-regulated differentially expressed genes (DEGs) were obtained. The up- and down-regulated DEGs were mainly involved in functions like mitotic cell cycle and pathway like cell cycle. Protein-protein interaction network of ARDS analysis revealed 20 hub genes including cyclin B1 (CCNB1), cyclin B2 (CCNB2) and topoisomerase II alpha (TOP2A). A total of seven transcription factors including forkhead box protein M1 (FOXM1) and 30 target genes were revealed in the transcription factor-target gene regulation network. Furthermore, co-cited genes including CCNB2-CCNB1 were revealed in literature mining for the relations ARDS related genes. Pathways like mitotic cell cycle were closed related with the development of ARDS. Genes including CCNB1, CCNB2 and TOP2A, as well as transcription factors like FOXM1 might be used as the novel gene therapy targets for sepsis related ARDS.

  17. RNA-based, transient modulation of gene expression in human haematopoietic stem and progenitor cells

    Science.gov (United States)

    Diener, Yvonne; Jurk, Marion; Kandil, Britta; Choi, Yeong-Hoon; Wild, Stefan; Bissels, Ute; Bosio, Andreas

    2015-01-01

    Modulation of gene expression is a useful tool to study the biology of haematopoietic stem and progenitor cells (HSPCs) and might also be instrumental to expand these cells for therapeutic approaches. Most of the studies so far have employed stable gene modification by viral vectors that are burdensome when translating protocols into clinical settings. Our study aimed at exploring new ways to transiently modify HSPC gene expression using non-integrating, RNA-based molecules. First, we tested different methods to deliver these molecules into HSPCs. The delivery of siRNAs with chemical transfection methods such as lipofection or cationic polymers did not lead to target knockdown, although we observed more than 90% fluorescent cells using a fluorochrome-coupled siRNA. Confocal microscopic analysis revealed that despite extensive washing, siRNA stuck to or in the cell surface, thereby mimicking a transfection event. In contrast, electroporation resulted in efficient, siRNA-mediated protein knockdown. For transient overexpression of proteins, we used optimised mRNA molecules with modified 5′- and 3′-UTRs. Electroporation of mRNA encoding GFP resulted in fast, efficient and persistent protein expression for at least seven days. Our data provide a broad-ranging comparison of transfection methods for hard-to-transfect cells and offer new opportunities for DNA-free, non-integrating gene modulation in HSPCs. PMID:26599627

  18. Prediction of highly expressed genes in microbes based on chromatin accessibility

    DEFF Research Database (Denmark)

    Willenbrock, Hanni; Ussery, David

    2007-01-01

    BACKGROUND: It is well known that gene expression is dependent on chromatin structure in eukaryotes and it is likely that chromatin can play a role in bacterial gene expression as well. Here, we use a nucleosomal position preference measure of anisotropic DNA flexibility to predict highly expressed...

  19. Microarray-Based Gene Expression Profiling to Elucidate Effectiveness of Fermented Codonopsis lanceolata in Mice

    Directory of Open Access Journals (Sweden)

    Woon Yong Choi

    2014-04-01

    Full Text Available In this study, the effect of Codonopsis lanceolata fermented by lactic acid on controlling gene expression levels related to obesity was observed in an oligonucleotide chip microarray. Among 8170 genes, 393 genes were up regulated and 760 genes were down regulated in feeding the fermented C. lanceolata (FCL. Another 374 genes were up regulated and 527 genes down regulated without feeding the sample. The genes were not affected by the FCL sample. It was interesting that among those genes, Chytochrome P450, Dmbt1, LOC76487, and thyroid hormones, etc., were mostly up or down regulated. These genes are more related to lipid synthesis. We could conclude that the FCL possibly controlled the gene expression levels related to lipid synthesis, which resulted in reducing obesity. However, more detailed protein expression experiments should be carried out.

  20. Genomic DNA-based absolute quantification of gene expression in Vitis.

    Science.gov (United States)

    Gambetta, Gregory A; McElrone, Andrew J; Matthews, Mark A

    2013-07-01

    Many studies in which gene expression is quantified by polymerase chain reaction represent the expression of a gene of interest (GOI) relative to that of a reference gene (RG). Relative expression is founded on the assumptions that RG expression is stable across samples, treatments, organs, etc., and that reaction efficiencies of the GOI and RG are equal; assumptions which are often faulty. The true variability in RG expression and actual reaction efficiencies are seldom determined experimentally. Here we present a rapid and robust method for absolute quantification of expression in Vitis where varying concentrations of genomic DNA were used to construct GOI standard curves. This methodology was utilized to absolutely quantify and determine the variability of the previously validated RG ubiquitin (VvUbi) across three test studies in three different tissues (roots, leaves and berries). In addition, in each study a GOI was absolutely quantified. Data sets resulting from relative and absolute methods of quantification were compared and the differences were striking. VvUbi expression was significantly different in magnitude between test studies and variable among individual samples. Absolute quantification consistently reduced the coefficients of variation of the GOIs by more than half, often resulting in differences in statistical significance and in some cases even changing the fundamental nature of the result. Utilizing genomic DNA-based absolute quantification is fast and efficient. Through eliminating error introduced by assuming RG stability and equal reaction efficiencies between the RG and GOI this methodology produces less variation, increased accuracy and greater statistical power. © 2012 Scandinavian Plant Physiology Society.

  1. Customized oligonucleotide microarray gene expression-based classification of neuroblastoma patients outperforms current clinical risk stratification.

    Science.gov (United States)

    Oberthuer, André; Berthold, Frank; Warnat, Patrick; Hero, Barbara; Kahlert, Yvonne; Spitz, Rüdiger; Ernestus, Karen; König, Rainer; Haas, Stefan; Eils, Roland; Schwab, Manfred; Brors, Benedikt; Westermann, Frank; Fischer, Matthias

    2006-11-01

    To develop a gene expression-based classifier for neuroblastoma patients that reliably predicts courses of the disease. Two hundred fifty-one neuroblastoma specimens were analyzed using a customized oligonucleotide microarray comprising 10,163 probes for transcripts with differential expression in clinical subgroups of the disease. Subsequently, the prediction analysis for microarrays (PAM) was applied to a first set of patients with maximally divergent clinical courses (n = 77). The classification accuracy was estimated by a complete 10-times-repeated 10-fold cross validation, and a 144-gene predictor was constructed from this set. This classifier's predictive power was evaluated in an independent second set (n = 174) by comparing results of the gene expression-based classification with those of risk stratification systems of current trials from Germany, Japan, and the United States. The first set of patients was accurately predicted by PAM (cross-validated accuracy, 99%). Within the second set, the PAM classifier significantly separated cohorts with distinct courses (3-year event-free survival [EFS] 0.86 +/- 0.03 [favorable; n = 115] v 0.52 +/- 0.07 [unfavorable; n = 59] and 3-year overall survival 0.99 +/- 0.01 v 0.84 +/- 0.05; both P model, the PAM predictor classified patients of the second set more accurately than risk stratification of current trials from Germany, Japan, and the United States (P < .001; hazard ratio, 4.756 [95% CI, 2.544 to 8.893]). Integration of gene expression-based class prediction of neuroblastoma patients may improve risk estimation of current neuroblastoma trials.

  2. Microarray-based analysis of differential gene expression between infective and noninfective larvae of Strongyloides stercoralis.

    Directory of Open Access Journals (Sweden)

    Roshan Ramanathan

    2011-05-01

    Full Text Available Differences between noninfective first-stage (L1 and infective third-stage (L3i larvae of parasitic nematode Strongyloides stercoralis at the molecular level are relatively uncharacterized. DNA microarrays were developed and utilized for this purpose.Oligonucleotide hybridization probes for the array were designed to bind 3,571 putative mRNA transcripts predicted by analysis of 11,335 expressed sequence tags (ESTs obtained as part of the Nematode EST project. RNA obtained from S. stercoralis L3i and L1 was co-hybridized to each array after labeling the individual samples with different fluorescent tags. Bioinformatic predictions of gene function were developed using a novel cDNA Annotation System software. We identified 935 differentially expressed genes (469 L3i-biased; 466 L1-biased having two-fold expression differences or greater and microarray signals with a p value<0.01. Based on a functional analysis, L1 larvae have a larger number of genes putatively involved in transcription (p = 0.004, and L3i larvae have biased expression of putative heat shock proteins (such as hsp-90. Genes with products known to be immunoreactive in S. stercoralis-infected humans (such as SsIR and NIE had L3i biased expression. Abundantly expressed L3i contigs of interest included S. stercoralis orthologs of cytochrome oxidase ucr 2.1 and hsp-90, which may be potential chemotherapeutic targets. The S. stercoralis ortholog of fatty acid and retinol binding protein-1, successfully used in a vaccine against Ancylostoma ceylanicum, was identified among the 25 most highly expressed L3i genes. The sperm-containing glycoprotein domain, utilized in a vaccine against the nematode Cooperia punctata, was exclusively found in L3i biased genes and may be a valuable S. stercoralis target of interest.A new DNA microarray tool for the examination of S. stercoralis biology has been developed and provides new and valuable insights regarding differences between infective and

  3. Gene expression based evidence of innate immune response activation in the epithelium with oral lichen planus

    Science.gov (United States)

    Adami, Guy R.; Yeung, Alexander C.F.; Stucki, Grant; Kolokythas, Antonia; Sroussi, Herve Y.; Cabay, Robert J.; Kuzin, Igor; Schwartz, Joel L.

    2014-01-01

    Objective Oral lichen planus (OLP) is a disease of the oral mucosa of unknown cause producing lesions with an intense band-like inflammatory infiltrate of T cells to the subepithelium and keratinocyte cell death. We performed gene expression analysis of the oral epithelium of lesions in subjects with OLP and its sister disease, oral lichenoid reaction (OLR), in order to better understand the role of the keratinocytes in these diseases. Design Fourteen patients with OLP or OLR were included in the study, along with a control group of 23 subjects with a variety of oral diseases and a normal group of 17 subjects with no clinically visible mucosal abnormalities. Various proteins have been associated with OLP, based on detection of secreted proteins or changes in RNA levels in tissue samples consisting of epithelium, stroma, and immune cells. The mRNA level of twelve of these genes expressed in the epithelium was tested in the three groups. Results Four genes showed increased expression in the epithelium of OLP patients: CD14, CXCL1, IL8, and TLR1, and at least two of these proteins, TLR1 and CXCL1, were expressed at substantial levels in oral keratinocytes. Conclusions Because of the large accumulation of T cells in lesions of OLP it has long been thought to be an adaptive immunity malfunction. We provide evidence that there is increased expression of innate immune genes in the epithelium with this illness, suggesting a role for this process in the disease and a possible target for treatment. PMID:24581860

  4. A reference gene set for sex pheromone biosynthesis and degradation genes from the diamondback moth, Plutella xylostella, based on genome and transcriptome digital gene expression analyses.

    Science.gov (United States)

    He, Peng; Zhang, Yun-Fei; Hong, Duan-Yang; Wang, Jun; Wang, Xing-Liang; Zuo, Ling-Hua; Tang, Xian-Fu; Xu, Wei-Ming; He, Ming

    2017-03-01

    comprehensive gene data set of sex pheromone biosynthesis and degradation enzyme related genes in DBM created by genome- and transcriptome-wide identification, characterization and expression profiling. Our findings provide a basis to better understand the function of genes with tissue enriched expression. The results also provide information on the genes involved in sex pheromone biosynthesis and degradation, and may be useful to identify potential gene targets for pest control strategies by disrupting the insect-insect communication using pheromone-based behavioral antagonists.

  5. Blood-based gene-expression predictors of PTSD risk and resilience among deployed marines: a pilot study.

    Science.gov (United States)

    Glatt, Stephen J; Tylee, Daniel S; Chandler, Sharon D; Pazol, Joel; Nievergelt, Caroline M; Woelk, Christopher H; Baker, Dewleen G; Lohr, James B; Kremen, William S; Litz, Brett T; Tsuang, Ming T

    2013-06-01

    Susceptibility to PTSD is determined by both genes and environment. Similarly, gene-expression levels in peripheral blood are influenced by both genes and environment, and expression levels of many genes show good correspondence between peripheral blood and brain. Therefore, our objectives were to test the following hypotheses: (1) pre-trauma expression levels of a gene subset (particularly immune-system genes) in peripheral blood would differ between trauma-exposed Marines who later developed PTSD and those who did not; (2) a predictive biomarker panel of the eventual emergence of PTSD among high-risk individuals could be developed based on gene expression in readily assessable peripheral blood cells; and (3) a predictive panel based on expression of individual exons would surpass the accuracy of a model based on expression of full-length gene transcripts. Gene-expression levels were assayed in peripheral blood samples from 50 U.S. Marines (25 eventual PTSD cases and 25 non-PTSD comparison subjects) prior to their deployment overseas to war-zones in Iraq or Afghanistan. The panel of biomarkers dysregulated in peripheral blood cells of eventual PTSD cases prior to deployment was significantly enriched for immune genes, achieved 70% prediction accuracy in an independent sample based on the expression of 23 full-length transcripts, and attained 80% accuracy in an independent sample based on the expression of one exon from each of five genes. If the observed profiles of pre-deployment mRNA-expression in eventual PTSD cases can be further refined and replicated, they could suggest avenues for early intervention and prevention among individuals at high risk for trauma exposure. Copyright © 2013 Wiley Periodicals, Inc.

  6. RANWAR: rank-based weighted association rule mining from gene expression and methylation data.

    Science.gov (United States)

    Mallik, Saurav; Mukhopadhyay, Anirban; Maulik, Ujjwal

    2015-01-01

    Ranking of association rules is currently an interesting topic in data mining and bioinformatics. The huge number of evolved rules of items (or, genes) by association rule mining (ARM) algorithms makes confusion to the decision maker. In this article, we propose a weighted rule-mining technique (say, RANWAR or rank-based weighted association rule-mining) to rank the rules using two novel rule-interestingness measures, viz., rank-based weighted condensed support (wcs) and weighted condensed confidence (wcc) measures to bypass the problem. These measures are basically depended on the rank of items (genes). Using the rank, we assign weight to each item. RANWAR generates much less number of frequent itemsets than the state-of-the-art association rule mining algorithms. Thus, it saves time of execution of the algorithm. We run RANWAR on gene expression and methylation datasets. The genes of the top rules are biologically validated by Gene Ontologies (GOs) and KEGG pathway analyses. Many top ranked rules extracted from RANWAR that hold poor ranks in traditional Apriori, are highly biologically significant to the related diseases. Finally, the top rules evolved from RANWAR, that are not in Apriori, are reported.

  7. A cell-based in vitro alternative to identify skin sensitizers by gene expression

    International Nuclear Information System (INIS)

    Hooyberghs, Jef; Schoeters, Elke; Lambrechts, Nathalie; Nelissen, Inge; Witters, Hilda; Schoeters, Greet; Heuvel, Rosette van den

    2008-01-01

    The ethical and economic burden associated with animal testing for assessment of skin sensitization has triggered intensive research effort towards development and validation of alternative methods. In addition, new legislation on the registration and use of cosmetics and chemicals promote the use of suitable alternatives for hazard assessment. Our previous studies demonstrated that human CD34 + progenitor-derived dendritic cells from cord blood express specific gene profiles upon exposure to low molecular weight sensitizing chemicals. This paper presents a classification model based on this cell type which is successful in discriminating sensitizing chemicals from non-sensitizing chemicals based on transcriptome analysis of 13 genes. Expression profiles of a set of 10 sensitizers and 11 non-sensitizers were analyzed by RT-PCR using 9 different exposure conditions and a total of 73 donor samples. Based on these data a predictive dichotomous classifier for skin sensitizers has been constructed, which is referred to as . In a first step the dimensionality of the input data was reduced by selectively rejecting a number of exposure conditions and genes. Next, the generalization of a linear classifier was evaluated by a cross-validation which resulted in a prediction performance with a concordance of 89%, a specificity of 97% and a sensitivity of 82%. These results show that the present model may be a useful human in vitro alternative for further use in a test strategy towards the reduction of animal use for skin sensitization

  8. Multiclass classification for skin cancer profiling based on the integration of heterogeneous gene expression series.

    Science.gov (United States)

    Gálvez, Juan Manuel; Castillo, Daniel; Herrera, Luis Javier; San Román, Belén; Valenzuela, Olga; Ortuño, Francisco Manuel; Rojas, Ignacio

    2018-01-01

    Most of the research studies developed applying microarray technology to the characterization of different pathological states of any disease may fail in reaching statistically significant results. This is largely due to the small repertoire of analysed samples, and to the limitation in the number of states or pathologies usually addressed. Moreover, the influence of potential deviations on the gene expression quantification is usually disregarded. In spite of the continuous changes in omic sciences, reflected for instance in the emergence of new Next-Generation Sequencing-related technologies, the existing availability of a vast amount of gene expression microarray datasets should be properly exploited. Therefore, this work proposes a novel methodological approach involving the integration of several heterogeneous skin cancer series, and a later multiclass classifier design. This approach is thus a way to provide the clinicians with an intelligent diagnosis support tool based on the use of a robust set of selected biomarkers, which simultaneously distinguishes among different cancer-related skin states. To achieve this, a multi-platform combination of microarray datasets from Affymetrix and Illumina manufacturers was carried out. This integration is expected to strengthen the statistical robustness of the study as well as the finding of highly-reliable skin cancer biomarkers. Specifically, the designed operation pipeline has allowed the identification of a small subset of 17 differentially expressed genes (DEGs) from which to distinguish among 7 involved skin states. These genes were obtained from the assessment of a number of potential batch effects on the gene expression data. The biological interpretation of these genes was inspected in the specific literature to understand their underlying information in relation to skin cancer. Finally, in order to assess their possible effectiveness in cancer diagnosis, a cross-validation Support Vector Machines (SVM)-based

  9. Sex-based differences in gene expression in hippocampus following postnatal lead exposure

    International Nuclear Information System (INIS)

    Schneider, J.S.; Anderson, D.W.; Sonnenahalli, H.; Vadigepalli, R.

    2011-01-01

    The influence of sex as an effect modifier of childhood lead poisoning has received little systematic attention. Considering the paucity of information available concerning the interactive effects of lead and sex on the brain, the current study examined the interactive effects of lead and sex on gene expression patterns in the hippocampus, a structure involved in learning and memory. Male or female rats were fed either 1500 ppm lead-containing chow or control chow for 30 days beginning at weaning.Blood lead levels were 26.7 ± 2.1 μg/dl and 27.1 ± 1.7 μg/dl for females and males, respectively. The expression of 175 unique genes was differentially regulated between control male and female rats. A total of 167 unique genes were differentially expressed in response to lead in either males or females. Lead exposure had a significant effect without a significant difference between male and female responses in 77 of these genes. In another set of 71 genes, there were significant differences in male vs. female response. A third set of 30 genes was differentially expressed in opposite directions in males vs. females, with the majority of genes expressed at a lower level in females than in males. Highly differentially expressed genes in males and females following lead exposure were associated with diverse biological pathways and functions. These results show that a brief exposure to lead produced significant changes in expression of a variety of genes in the hippocampus and that the response of the brain to a given lead exposure may vary depending on sex. - Highlights: → Postnatal lead exposure has a significant effect on hippocampal gene expression patterns. → At least one set of genes was affected in opposite directions in males and females. → Differentially expressed genes were associated with diverse biological pathways.

  10. Training ANFIS structure using genetic algorithm for liver cancer classification based on microarray gene expression data

    Directory of Open Access Journals (Sweden)

    Bülent Haznedar

    2017-02-01

    Full Text Available Classification is an important data mining technique, which is used in many fields mostly exemplified as medicine, genetics and biomedical engineering. The number of studies about classification of the datum on DNA microarray gene expression is specifically increased in recent years. However, because of the reasons as the abundance of gene numbers in the datum as microarray gene expressions and the nonlinear relations mostly across those datum, the success of conventional classification algorithms can be limited. Because of these reasons, the interest on classification methods which are based on artificial intelligence to solve the problem on classification has been gradually increased in recent times. In this study, a hybrid approach which is based on Adaptive Neuro-Fuzzy Inference System (ANFIS and Genetic Algorithm (GA are suggested in order to classify liver microarray cancer data set. Simulation results are compared with the results of other methods. According to the results obtained, it is seen that the recommended method is better than the other methods.

  11. Cross-platform analysis of cancer microarray data improves gene expression based classification of phenotypes

    Directory of Open Access Journals (Sweden)

    Eils Roland

    2005-11-01

    Full Text Available Abstract Background The extensive use of DNA microarray technology in the characterization of the cell transcriptome is leading to an ever increasing amount of microarray data from cancer studies. Although similar questions for the same type of cancer are addressed in these different studies, a comparative analysis of their results is hampered by the use of heterogeneous microarray platforms and analysis methods. Results In contrast to a meta-analysis approach where results of different studies are combined on an interpretative level, we investigate here how to directly integrate raw microarray data from different studies for the purpose of supervised classification analysis. We use median rank scores and quantile discretization to derive numerically comparable measures of gene expression from different platforms. These transformed data are then used for training of classifiers based on support vector machines. We apply this approach to six publicly available cancer microarray gene expression data sets, which consist of three pairs of studies, each examining the same type of cancer, i.e. breast cancer, prostate cancer or acute myeloid leukemia. For each pair, one study was performed by means of cDNA microarrays and the other by means of oligonucleotide microarrays. In each pair, high classification accuracies (> 85% were achieved with training and testing on data instances randomly chosen from both data sets in a cross-validation analysis. To exemplify the potential of this cross-platform classification analysis, we use two leukemia microarray data sets to show that important genes with regard to the biology of leukemia are selected in an integrated analysis, which are missed in either single-set analysis. Conclusion Cross-platform classification of multiple cancer microarray data sets yields discriminative gene expression signatures that are found and validated on a large number of microarray samples, generated by different laboratories and

  12. Cancer classification through filtering progressive transductive support vector machine based on gene expression data

    Science.gov (United States)

    Lu, Xinguo; Chen, Dan

    2017-08-01

    Traditional supervised classifiers neglect a large amount of data which not have sufficient follow-up information, only work with labeled data. Consequently, the small sample size limits the advancement of design appropriate classifier. In this paper, a transductive learning method which combined with the filtering strategy in transductive framework and progressive labeling strategy is addressed. The progressive labeling strategy does not need to consider the distribution of labeled samples to evaluate the distribution of unlabeled samples, can effective solve the problem of evaluate the proportion of positive and negative samples in work set. Our experiment result demonstrate that the proposed technique have great potential in cancer prediction based on gene expression.

  13. A Cas9-based toolkit to program gene expression in Saccharomyces cerevisiae

    DEFF Research Database (Denmark)

    Apel, Amanda Reider; d'Espaux, Leo; Wehrs, Maren

    2017-01-01

    of these parts via a web-based tool, that automates the generation of DNA fragments for integration. Our system builds upon existing gene editing methods in the thoroughness with which the parts are standardized and characterized, the types and number of parts available and the ease with which our methodology...... can be used to perform genetic edits in yeast. We demonstrated the applicability of this toolkit by optimizing the expression of a challenging but industrially important enzyme, taxadiene synthase (TXS). This approach enabled us to diagnose an issue with TXS solubility, the resolution of which yielded...

  14. Finding differentially expressed genes in high dimensional data: Rank based test statistic via a distance measure.

    Science.gov (United States)

    Mathur, Sunil; Sadana, Ajit

    2015-12-01

    We present a rank-based test statistic for the identification of differentially expressed genes using a distance measure. The proposed test statistic is highly robust against extreme values and does not assume the distribution of parent population. Simulation studies show that the proposed test is more powerful than some of the commonly used methods, such as paired t-test, Wilcoxon signed rank test, and significance analysis of microarray (SAM) under certain non-normal distributions. The asymptotic distribution of the test statistic, and the p-value function are discussed. The application of proposed method is shown using a real-life data set. © The Author(s) 2011.

  15. Ecdysone Receptor-based Singular Gene Switches for Regulated Transgene Expression in Cells and Adult Rodent Tissues

    Directory of Open Access Journals (Sweden)

    Seoghyun Lee

    2016-01-01

    Full Text Available Controlled gene expression is an indispensable technique in biomedical research. Here, we report a convenient, straightforward, and reliable way to induce expression of a gene of interest with negligible background expression compared to the most widely used tetracycline (Tet-regulated system. Exploiting a Drosophila ecdysone receptor (EcR-based gene regulatory system, we generated nonviral and adenoviral singular vectors designated as pEUI(+ and pENTR-EUI, respectively, which contain all the required elements to guarantee regulated transgene expression (GAL4-miniVP16-EcR, termed GvEcR hereafter, and 10 tandem repeats of an upstream activation sequence promoter followed by a multiple cloning site. Through the transient and stable transfection of mammalian cell lines with reporter genes, we validated that tebufenozide, an ecdysone agonist, reversibly induced gene expression, in a dose- and time-dependent manner, with negligible background expression. In addition, we created an adenovirus derived from the pENTR-EUI vector that readily infected not only cultured cells but also rodent tissues and was sensitive to tebufenozide treatment for regulated transgene expression. These results suggest that EcR-based singular gene regulatory switches would be convenient tools for the induction of gene expression in cells and tissues in a tightly controlled fashion.

  16. 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...... 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...

  17. Correction of gene expression data

    DEFF Research Database (Denmark)

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

    2014-01-01

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

  18. Development of new USER-based cloning vectors for multiple genes expression in Saccharomyces cerevisiae

    DEFF Research Database (Denmark)

    Kildegaard, Kanchana Rueksomtawin; Jensen, Niels Bjerg; Maury, Jerome

    2013-01-01

    auxotrophic and dominant markers for convenience of use. Our vector set also contains both integrating and multicopy vectors for stability of protein expression and high expression level. We will make the new vector system available to the yeast community and provide a comprehensive protocol for cloning...... the production strain with the proper phenotype and product yield. However, the sequential number of metabolic engineering is time-consuming. Furthermore, the number of available selectable markers is also limiting the number of genetic modifications. To overcome these limitations, we have developed a new set...... of shuttle vectors for convenience of use for high-throughput cloning and selectable marker recycling. The new USER-based cloning vectors consist of a unique USER site and a CRE-loxP-mediated marker recycling system. The USER site allows insertion of genes of interest along with a bidirectional promoter...

  19. Classification between normal and tumor tissues based on the pair-wise gene expression ratio

    International Nuclear Information System (INIS)

    Yap, YeeLeng; Zhang, XueWu; Ling, MT; Wang, XiangHong; Wong, YC; Danchin, Antoine

    2004-01-01

    Precise classification of cancer types is critically important for early cancer diagnosis and treatment. Numerous efforts have been made to use gene expression profiles to improve precision of tumor classification. However, reliable cancer-related signals are generally lacking. Using recent datasets on colon and prostate cancer, a data transformation procedure from single gene expression to pair-wise gene expression ratio is proposed. Making use of the internal consistency of each expression profiling dataset this transformation improves the signal to noise ratio of the dataset and uncovers new relevant cancer-related signals (features). The efficiency in using the transformed dataset to perform normal/tumor classification was investigated using feature partitioning with informative features (gene annotation) as discriminating axes (single gene expression or pair-wise gene expression ratio). Classification results were compared to the original datasets for up to 10-feature model classifiers. 82 and 262 genes that have high correlation to tissue phenotype were selected from the colon and prostate datasets respectively. Remarkably, data transformation of the highly noisy expression data successfully led to lower the coefficient of variation (CV) for the within-class samples as well as improved the correlation with tissue phenotypes. The transformed dataset exhibited lower CV when compared to that of single gene expression. In the colon cancer set, the minimum CV decreased from 45.3% to 16.5%. In prostate cancer, comparable CV was achieved with and without transformation. This improvement in CV, coupled with the improved correlation between the pair-wise gene expression ratio and tissue phenotypes, yielded higher classification efficiency, especially with the colon dataset – from 87.1% to 93.5%. Over 90% of the top ten discriminating axes in both datasets showed significant improvement after data transformation. The high classification efficiency achieved suggested

  20. Prediction of operon-like gene clusters in the Arabidopsis thaliana genome based on co-expression analysis of neighboring genes.

    Science.gov (United States)

    Wada, Masayoshi; Takahashi, Hiroki; Altaf-Ul-Amin, Md; Nakamura, Kensuke; Hirai, Masami Y; Ohta, Daisaku; Kanaya, Shigehiko

    2012-07-15

    Operon-like arrangements of genes occur in eukaryotes ranging from yeasts and filamentous fungi to nematodes, plants, and mammals. In plants, several examples of operon-like gene clusters involved in metabolic pathways have recently been characterized, e.g. the cyclic hydroxamic acid pathways in maize, the avenacin biosynthesis gene clusters in oat, the thalianol pathway in Arabidopsis thaliana, and the diterpenoid momilactone cluster in rice. Such operon-like gene clusters are defined by their co-regulation or neighboring positions within immediate vicinity of chromosomal regions. A comprehensive analysis of the expression of neighboring genes therefore accounts a crucial step to reveal the complete set of operon-like gene clusters within a genome. Genome-wide prediction of operon-like gene clusters should contribute to functional annotation efforts and provide novel insight into evolutionary aspects acquiring certain biological functions as well. We predicted co-expressed gene clusters by comparing the Pearson correlation coefficient of neighboring genes and randomly selected gene pairs, based on a statistical method that takes false discovery rate (FDR) into consideration for 1469 microarray gene expression datasets of A. thaliana. We estimated that A. thaliana contains 100 operon-like gene clusters in total. We predicted 34 statistically significant gene clusters consisting of 3 to 22 genes each, based on a stringent FDR threshold of 0.1. Functional relationships among genes in individual clusters were estimated by sequence similarity and functional annotation of genes. Duplicated gene pairs (determined based on BLAST with a cutoff of EOperon-like clusters tend to include genes encoding bio-machinery associated with ribosomes, the ubiquitin/proteasome system, secondary metabolic pathways, lipid and fatty-acid metabolism, and the lipid transfer system. Copyright © 2012 Elsevier B.V. All rights reserved.

  1. An Individual-Based Diploid Model Predicts Limited Conditions Under Which Stochastic Gene Expression Becomes Advantageous

    KAUST Repository

    Matsumoto, Tomotaka; Mineta, Katsuhiko; Osada, Naoki; Araki, Hitoshi

    2015-01-01

    Recent studies suggest the existence of a stochasticity in gene expression (SGE) in many organisms, and its non-negligible effect on their phenotype and fitness. To date, however, how SGE affects the key parameters of population genetics

  2. Identification of human circadian genes based on time course gene expression profiles by using a deep learning method.

    Science.gov (United States)

    Cui, Peng; Zhong, Tingyan; Wang, Zhuo; Wang, Tao; Zhao, Hongyu; Liu, Chenglin; Lu, Hui

    2018-06-01

    Circadian genes express periodically in an approximate 24-h period and the identification and study of these genes can provide deep understanding of the circadian control which plays significant roles in human health. Although many circadian gene identification algorithms have been developed, large numbers of false positives and low coverage are still major problems in this field. In this study we constructed a novel computational framework for circadian gene identification using deep neural networks (DNN) - a deep learning algorithm which can represent the raw form of data patterns without imposing assumptions on the expression distribution. Firstly, we transformed time-course gene expression data into categorical-state data to denote the changing trend of gene expression. Two distinct expression patterns emerged after clustering of the state data for circadian genes from our manually created learning dataset. DNN was then applied to discriminate the aperiodic genes and the two subtypes of periodic genes. In order to assess the performance of DNN, four commonly used machine learning methods including k-nearest neighbors, logistic regression, naïve Bayes, and support vector machines were used for comparison. The results show that the DNN model achieves the best balanced precision and recall. Next, we conducted large scale circadian gene detection using the trained DNN model for the remaining transcription profiles. Comparing with JTK_CYCLE and a study performed by Möller-Levet et al. (doi: https://doi.org/10.1073/pnas.1217154110), we identified 1132 novel periodic genes. Through the functional analysis of these novel circadian genes, we found that the GTPase superfamily exhibits distinct circadian expression patterns and may provide a molecular switch of circadian control of the functioning of the immune system in human blood. Our study provides novel insights into both the circadian gene identification field and the study of complex circadian-driven biological

  3. Argudas: lessons for argumentation in biology based on a gene expression use case

    OpenAIRE

    McLeod, Kenneth; Ferguson, Gus; Burger, Albert

    2012-01-01

    Background In situ hybridisation gene expression information helps biologists identify where a gene is expressed. However, the databases that republish the experimental information online are often both incomplete and inconsistent. Non-monotonic reasoning can help resolve such difficulties - one such form of reasoning is computational argumentation. Essentially this involves asking a computer to debate (i.e. reason about) the validity of a particular statement. Arguments are produced for both...

  4. A model of gene expression based on random dynamical systems reveals modularity properties of gene regulatory networks.

    Science.gov (United States)

    Antoneli, Fernando; Ferreira, Renata C; Briones, Marcelo R S

    2016-06-01

    Here we propose a new approach to modeling gene expression based on the theory of random dynamical systems (RDS) that provides a general coupling prescription between the nodes of any given regulatory network given the dynamics of each node is modeled by a RDS. The main virtues of this approach are the following: (i) it provides a natural way to obtain arbitrarily large networks by coupling together simple basic pieces, thus revealing the modularity of regulatory networks; (ii) the assumptions about the stochastic processes used in the modeling are fairly general, in the sense that the only requirement is stationarity; (iii) there is a well developed mathematical theory, which is a blend of smooth dynamical systems theory, ergodic theory and stochastic analysis that allows one to extract relevant dynamical and statistical information without solving the system; (iv) one may obtain the classical rate equations form the corresponding stochastic version by averaging the dynamic random variables (small noise limit). It is important to emphasize that unlike the deterministic case, where coupling two equations is a trivial matter, coupling two RDS is non-trivial, specially in our case, where the coupling is performed between a state variable of one gene and the switching stochastic process of another gene and, hence, it is not a priori true that the resulting coupled system will satisfy the definition of a random dynamical system. We shall provide the necessary arguments that ensure that our coupling prescription does indeed furnish a coupled regulatory network of random dynamical systems. Finally, the fact that classical rate equations are the small noise limit of our stochastic model ensures that any validation or prediction made on the basis of the classical theory is also a validation or prediction of our model. We illustrate our framework with some simple examples of single-gene system and network motifs. Copyright © 2016 Elsevier Inc. All rights reserved.

  5. An Individual-Based Diploid Model Predicts Limited Conditions Under Which Stochastic Gene Expression Becomes Advantageous

    KAUST Repository

    Matsumoto, Tomotaka

    2015-11-24

    Recent studies suggest the existence of a stochasticity in gene expression (SGE) in many organisms, and its non-negligible effect on their phenotype and fitness. To date, however, how SGE affects the key parameters of population genetics are not well understood. SGE can increase the phenotypic variation and act as a load for individuals, if they are at the adaptive optimum in a stable environment. On the other hand, part of the phenotypic variation caused by SGE might become advantageous if individuals at the adaptive optimum become genetically less-adaptive, for example due to an environmental change. Furthermore, SGE of unimportant genes might have little or no fitness consequences. Thus, SGE can be advantageous, disadvantageous, or selectively neutral depending on its context. In addition, there might be a genetic basis that regulates magnitude of SGE, which is often referred to as “modifier genes,” but little is known about the conditions under which such an SGE-modifier gene evolves. In the present study, we conducted individual-based computer simulations to examine these conditions in a diploid model. In the simulations, we considered a single locus that determines organismal fitness for simplicity, and that SGE on the locus creates fitness variation in a stochastic manner. We also considered another locus that modifies the magnitude of SGE. Our results suggested that SGE was always deleterious in stable environments and increased the fixation probability of deleterious mutations in this model. Even under frequently changing environmental conditions, only very strong natural selection made SGE adaptive. These results suggest that the evolution of SGE-modifier genes requires strict balance among the strength of natural selection, magnitude of SGE, and frequency of environmental changes. However, the degree of dominance affected the condition under which SGE becomes advantageous, indicating a better opportunity for the evolution of SGE in different genetic

  6. Citrus plastid-related gene profiling based on expressed sequence tag analyses

    Directory of Open Access Journals (Sweden)

    Tercilio Calsa Jr.

    2007-01-01

    Full Text Available Plastid-related sequences, derived from putative nuclear or plastome genes, were searched in a large collection of expressed sequence tags (ESTs and genomic sequences from the Citrus Biotechnology initiative in Brazil. The identified putative Citrus chloroplast gene sequences were compared to those from Arabidopsis, Eucalyptus and Pinus. Differential expression profiling for plastid-directed nuclear-encoded proteins and photosynthesis-related gene expression variation between Citrus sinensis and Citrus reticulata, when inoculated or not with Xylella fastidiosa, were also analyzed. Presumed Citrus plastome regions were more similar to Eucalyptus. Some putative genes appeared to be preferentially expressed in vegetative tissues (leaves and bark or in reproductive organs (flowers and fruits. Genes preferentially expressed in fruit and flower may be associated with hypothetical physiological functions. Expression pattern clustering analysis suggested that photosynthesis- and carbon fixation-related genes appeared to be up- or down-regulated in a resistant or susceptible Citrus species after Xylella inoculation in comparison to non-infected controls, generating novel information which may be helpful to develop novel genetic manipulation strategies to control Citrus variegated chlorosis (CVC.

  7. Unveiling network-based functional features through integration of gene expression into protein networks.

    Science.gov (United States)

    Jalili, Mahdi; Gebhardt, Tom; Wolkenhauer, Olaf; Salehzadeh-Yazdi, Ali

    2018-06-01

    Decoding health and disease phenotypes is one of the fundamental objectives in biomedicine. Whereas high-throughput omics approaches are available, it is evident that any single omics approach might not be adequate to capture the complexity of phenotypes. Therefore, integrated multi-omics approaches have been used to unravel genotype-phenotype relationships such as global regulatory mechanisms and complex metabolic networks in different eukaryotic organisms. Some of the progress and challenges associated with integrated omics studies have been reviewed previously in comprehensive studies. In this work, we highlight and review the progress, challenges and advantages associated with emerging approaches, integrating gene expression and protein-protein interaction networks to unravel network-based functional features. This includes identifying disease related genes, gene prioritization, clustering protein interactions, developing the modules, extract active subnetworks and static protein complexes or dynamic/temporal protein complexes. We also discuss how these approaches contribute to our understanding of the biology of complex traits and diseases. This article is part of a Special Issue entitled: Cardiac adaptations to obesity, diabetes and insulin resistance, edited by Professors Jan F.C. Glatz, Jason R.B. Dyck and Christine Des Rosiers. Copyright © 2018 Elsevier B.V. All rights reserved.

  8. Characterizing embryonic gene expression patterns in the mouse using nonredundant sequence-based selection

    DEFF Research Database (Denmark)

    Sousa-Nunes, Rita; Rana, Amer Ahmed; Kettleborough, Ross

    2003-01-01

    This article investigates the expression patterns of 160 genes that are expressed during early mouse development. The cDNAs were isolated from 7.5 d postcoitum (dpc) endoderm, a region that comprises visceral endoderm (VE), definitive endoderm, and the node-tissues that are required for the initi...

  9. Differential peripheral blood gene expression profile based on Her2 expression on primary tumors of breast cancer patients.

    Directory of Open Access Journals (Sweden)

    Oana Tudoran

    Full Text Available Breast cancer prognosis and treatment is highly dependent on the molecular features of the primary tumors. These tumors release specific molecules into the environment that trigger characteristic responses into the circulatory cells. In this study we investigated the expression pattern of 84 genes known to be involved in breast cancer signaling in the peripheral blood of breast cancer patients with ER-, PR- primary tumors. The patients were grouped according to Her2 expression on the primary tumors in Her2+ and Her2- cohorts. Transcriptional analysis revealed 15 genes to be differentially expressed between the two groups highlighting that Her2 signaling in primary tumors could be associated with specific blood gene expression. We found CCNA1 to be up-regulated, while ERBB2, RASSF1, CDH1, MKI67, GATA3, GLI1, SFN, PTGS2, JUN, NOTCH1, CTNNB1, KRT8, SRC, and HIC1 genes were down-regulated in the blood of triple negative breast cancer patients compared to Her2+ cohort. IPA network analysis predicts that the identified genes are interconnected and regulate each other. These genes code for cell cycle regulators, cell adhesion molecules, transcription factors or signal transducers that modulate immune signaling, several genes being also associated with cancer progression and treatment response. These results indicate an altered immune signaling in the peripheral blood of triple negative breast cancer patients. The involvement of the immune system is necessary in favorable treatment response, therefore these results could explain the low response rates observed for triple negative breast cancer patients.

  10. Genome-Wide Constitutively Expressed Gene Analysis and New Reference Gene Selection Based on Transcriptome Data: A Case Study from Poplar/Canker Disease Interaction

    Directory of Open Access Journals (Sweden)

    Jiaping Zhao

    2017-10-01

    Full Text Available A number of transcriptome datasets for differential expression (DE genes have been widely used for understanding organismal biology, but these datasets also contain untapped information that can be used to develop more precise analytical tools. With the use of transcriptome data generated from poplar/canker disease interaction system, we describe a methodology to identify candidate reference genes from high-throughput sequencing data. This methodology will improve the accuracy of RT-qPCR and will lead to better standards for the normalization of expression data. Expression stability analysis from xylem and phloem of Populus bejingensis inoculated with the fungal canker pathogen Botryosphaeria dothidea revealed that 729 poplar transcripts (1.11% were stably expressed, at a threshold level of coefficient of variance (CV of FPKM < 20% and maximum fold change (MFC of FPKM < 2.0. Expression stability and bioinformatics analysis suggested that commonly used house-keeping (HK genes were not the most appropriate internal controls: 70 of the 72 commonly used HK genes were not stably expressed, 45 of the 72 produced multiple isoform transcripts, and some of their reported primers produced unspecific amplicons in PCR amplification. RT-qPCR analysis to compare and evaluate the expression stability of 10 commonly used poplar HK genes and 20 of the 729 newly-identified stably expressed transcripts showed that some of the newly-identified genes (such as SSU_S8e, LSU_L5e, and 20S_PSU had higher stability ranking than most of commonly used HK genes. Based on these results, we recommend a pipeline for deriving reference genes from transcriptome data. An appropriate candidate gene should have a unique transcript, constitutive expression, CV value of expression < 20% (or possibly 30% and MFC value of expression <2, and an expression level of 50–1,000 units. Lastly, when four of the newly identified HK genes were used in the normalization of expression data for 20

  11. A new measure for gene expression biclustering based on non-parametric correlation.

    Science.gov (United States)

    Flores, Jose L; Inza, Iñaki; Larrañaga, Pedro; Calvo, Borja

    2013-12-01

    One of the emerging techniques for performing the analysis of the DNA microarray data known as biclustering is the search of subsets of genes and conditions which are coherently expressed. These subgroups provide clues about the main biological processes. Until now, different approaches to this problem have been proposed. Most of them use the mean squared residue as quality measure but relevant and interesting patterns can not be detected such as shifting, or scaling patterns. Furthermore, recent papers show that there exist new coherence patterns involved in different kinds of cancer and tumors such as inverse relationships between genes which can not be captured. The proposed measure is called Spearman's biclustering measure (SBM) which performs an estimation of the quality of a bicluster based on the non-linear correlation among genes and conditions simultaneously. The search of biclusters is performed by using a evolutionary technique called estimation of distribution algorithms which uses the SBM measure as fitness function. This approach has been examined from different points of view by using artificial and real microarrays. The assessment process has involved the use of quality indexes, a set of bicluster patterns of reference including new patterns and a set of statistical tests. It has been also examined the performance using real microarrays and comparing to different algorithmic approaches such as Bimax, CC, OPSM, Plaid and xMotifs. SBM shows several advantages such as the ability to recognize more complex coherence patterns such as shifting, scaling and inversion and the capability to selectively marginalize genes and conditions depending on the statistical significance. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

  12. Partial Least Squares Based Gene Expression Analysis in EBV- Positive and EBV-Negative Posttransplant Lymphoproliferative Disorders.

    Science.gov (United States)

    Wu, Sa; Zhang, Xin; Li, Zhi-Ming; Shi, Yan-Xia; Huang, Jia-Jia; Xia, Yi; Yang, Hang; Jiang, Wen-Qi

    2013-01-01

    Post-transplant lymphoproliferative disorder (PTLD) is a common complication of therapeutic immunosuppression after organ transplantation. Gene expression profile facilitates the identification of biological difference between Epstein-Barr virus (EBV) positive and negative PTLDs. Previous studies mainly implemented variance/regression analysis without considering unaccounted array specific factors. The aim of this study is to investigate the gene expression difference between EBV positive and negative PTLDs through partial least squares (PLS) based analysis. With a microarray data set from the Gene Expression Omnibus database, we performed PLS based analysis. We acquired 1188 differentially expressed genes. Pathway and Gene Ontology enrichment analysis identified significantly over-representation of dysregulated genes in immune response and cancer related biological processes. Network analysis identified three hub genes with degrees higher than 15, including CREBBP, ATXN1, and PML. Proteins encoded by CREBBP and PML have been reported to be interact with EBV before. Our findings shed light on expression distinction of EBV positive and negative PTLDs with the hope to offer theoretical support for future therapeutic study.

  13. ConGEMs: Condensed Gene Co-Expression Module Discovery Through Rule-Based Clustering and Its Application to Carcinogenesis

    Directory of Open Access Journals (Sweden)

    Saurav Mallik

    2017-12-01

    Full Text Available For transcriptomic analysis, there are numerous microarray-based genomic data, especially those generated for cancer research. The typical analysis measures the difference between a cancer sample-group and a matched control group for each transcript or gene. Association rule mining is used to discover interesting item sets through rule-based methodology. Thus, it has advantages to find causal effect relationships between the transcripts. In this work, we introduce two new rule-based similarity measures—weighted rank-based Jaccard and Cosine measures—and then propose a novel computational framework to detect condensed gene co-expression modules ( C o n G E M s through the association rule-based learning system and the weighted similarity scores. In practice, the list of evolved condensed markers that consists of both singular and complex markers in nature depends on the corresponding condensed gene sets in either antecedent or consequent of the rules of the resultant modules. In our evaluation, these markers could be supported by literature evidence, KEGG (Kyoto Encyclopedia of Genes and Genomes pathway and Gene Ontology annotations. Specifically, we preliminarily identified differentially expressed genes using an empirical Bayes test. A recently developed algorithm—RANWAR—was then utilized to determine the association rules from these genes. Based on that, we computed the integrated similarity scores of these rule-based similarity measures between each rule-pair, and the resultant scores were used for clustering to identify the co-expressed rule-modules. We applied our method to a gene expression dataset for lung squamous cell carcinoma and a genome methylation dataset for uterine cervical carcinogenesis. Our proposed module discovery method produced better results than the traditional gene-module discovery measures. In summary, our proposed rule-based method is useful for exploring biomarker modules from transcriptomic data.

  14. ConGEMs: Condensed Gene Co-Expression Module Discovery Through Rule-Based Clustering and Its Application to Carcinogenesis.

    Science.gov (United States)

    Mallik, Saurav; Zhao, Zhongming

    2017-12-28

    For transcriptomic analysis, there are numerous microarray-based genomic data, especially those generated for cancer research. The typical analysis measures the difference between a cancer sample-group and a matched control group for each transcript or gene. Association rule mining is used to discover interesting item sets through rule-based methodology. Thus, it has advantages to find causal effect relationships between the transcripts. In this work, we introduce two new rule-based similarity measures-weighted rank-based Jaccard and Cosine measures-and then propose a novel computational framework to detect condensed gene co-expression modules ( C o n G E M s) through the association rule-based learning system and the weighted similarity scores. In practice, the list of evolved condensed markers that consists of both singular and complex markers in nature depends on the corresponding condensed gene sets in either antecedent or consequent of the rules of the resultant modules. In our evaluation, these markers could be supported by literature evidence, KEGG (Kyoto Encyclopedia of Genes and Genomes) pathway and Gene Ontology annotations. Specifically, we preliminarily identified differentially expressed genes using an empirical Bayes test. A recently developed algorithm-RANWAR-was then utilized to determine the association rules from these genes. Based on that, we computed the integrated similarity scores of these rule-based similarity measures between each rule-pair, and the resultant scores were used for clustering to identify the co-expressed rule-modules. We applied our method to a gene expression dataset for lung squamous cell carcinoma and a genome methylation dataset for uterine cervical carcinogenesis. Our proposed module discovery method produced better results than the traditional gene-module discovery measures. In summary, our proposed rule-based method is useful for exploring biomarker modules from transcriptomic data.

  15. Investigating a multigene prognostic assay based on significant pathways for Luminal A breast cancer through gene expression profile analysis.

    Science.gov (United States)

    Gao, Haiyan; Yang, Mei; Zhang, Xiaolan

    2018-04-01

    The present study aimed to investigate potential recurrence-risk biomarkers based on significant pathways for Luminal A breast cancer through gene expression profile analysis. Initially, the gene expression profiles of Luminal A breast cancer patients were downloaded from The Cancer Genome Atlas database. The differentially expressed genes (DEGs) were identified using a Limma package and the hierarchical clustering analysis was conducted for the DEGs. In addition, the functional pathways were screened using Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses and rank ratio calculation. The multigene prognostic assay was exploited based on the statistically significant pathways and its prognostic function was tested using train set and verified using the gene expression data and survival data of Luminal A breast cancer patients downloaded from the Gene Expression Omnibus. A total of 300 DEGs were identified between good and poor outcome groups, including 176 upregulated genes and 124 downregulated genes. The DEGs may be used to effectively distinguish Luminal A samples with different prognoses verified by hierarchical clustering analysis. There were 9 pathways screened as significant pathways and a total of 18 DEGs involved in these 9 pathways were identified as prognostic biomarkers. According to the survival analysis and receiver operating characteristic curve, the obtained 18-gene prognostic assay exhibited good prognostic function with high sensitivity and specificity to both the train and test samples. In conclusion the 18-gene prognostic assay including the key genes, transcription factor 7-like 2, anterior parietal cortex and lymphocyte enhancer factor-1 may provide a new method for predicting outcomes and may be conducive to the promotion of precision medicine for Luminal A breast cancer.

  16. Modulation of gene expression made easy

    DEFF Research Database (Denmark)

    Solem, Christian; Jensen, Peter Ruhdal

    2002-01-01

    A new approach for modulating gene expression, based on randomization of promoter (spacer) sequences, was developed. The method was applied to chromosomal genes in Lactococcus lactis and shown to generate libraries of clones with broad ranges of expression levels of target genes. In one example...... that the method can be applied to modulating the expression of native genes on the chromosome. We constructed a series of strains in which the expression of the las operon, containing the genes pfk, pyk, and ldh, was modulated by integrating a truncated copy of the pfk gene. Importantly, the modulation affected...

  17. Human cancer cells express Slug-based epithelial-mesenchymal transition gene expression signature obtained in vivo

    International Nuclear Information System (INIS)

    Anastassiou, Dimitris; Rumjantseva, Viktoria; Cheng, Weiyi; Huang, Jianzhong; Canoll, Peter D; Yamashiro, Darrell J; Kandel, Jessica J

    2011-01-01

    The biological mechanisms underlying cancer cell motility and invasiveness remain unclear, although it has been hypothesized that they involve some type of epithelial-mesenchymal transition (EMT). We used xenograft models of human cancer cells in immunocompromised mice, profiling the harvested tumors separately with species-specific probes and computationally analyzing the results. Here we show that human cancer cells express in vivo a precise multi-cancer invasion-associated gene expression signature that prominently includes many EMT markers, among them the transcription factor Slug, fibronectin, and α-SMA. We found that human, but not mouse, cells express the signature and Slug is the only upregulated EMT-inducing transcription factor. The signature is also present in samples from many publicly available cancer gene expression datasets, suggesting that it is produced by the cancer cells themselves in multiple cancer types, including nonepithelial cancers such as neuroblastoma. Furthermore, we found that the presence of the signature in human xenografted cells was associated with a downregulation of adipocyte markers in the mouse tissue adjacent to the invasive tumor, suggesting that the signature is triggered by contextual microenvironmental interactions when the cancer cells encounter adipocytes, as previously reported. The known, precise and consistent gene composition of this cancer mesenchymal transition signature, particularly when combined with simultaneous analysis of the adjacent microenvironment, provides unique opportunities for shedding light on the underlying mechanisms of cancer invasiveness as well as identifying potential diagnostic markers and targets for metastasis-inhibiting therapeutics

  18. Classification based upon gene expression data: bias and precision of error rates.

    Science.gov (United States)

    Wood, Ian A; Visscher, Peter M; Mengersen, Kerrie L

    2007-06-01

    Gene expression data offer a large number of potentially useful predictors for the classification of tissue samples into classes, such as diseased and non-diseased. The predictive error rate of classifiers can be estimated using methods such as cross-validation. We have investigated issues of interpretation and potential bias in the reporting of error rate estimates. The issues considered here are optimization and selection biases, sampling effects, measures of misclassification rate, baseline error rates, two-level external cross-validation and a novel proposal for detection of bias using the permutation mean. Reporting an optimal estimated error rate incurs an optimization bias. Downward bias of 3-5% was found in an existing study of classification based on gene expression data and may be endemic in similar studies. Using a simulated non-informative dataset and two example datasets from existing studies, we show how bias can be detected through the use of label permutations and avoided using two-level external cross-validation. Some studies avoid optimization bias by using single-level cross-validation and a test set, but error rates can be more accurately estimated via two-level cross-validation. In addition to estimating the simple overall error rate, we recommend reporting class error rates plus where possible the conditional risk incorporating prior class probabilities and a misclassification cost matrix. We also describe baseline error rates derived from three trivial classifiers which ignore the predictors. R code which implements two-level external cross-validation with the PAMR package, experiment code, dataset details and additional figures are freely available for non-commercial use from http://www.maths.qut.edu.au/profiles/wood/permr.jsp

  19. In Silico Analysis of Microarray-Based Gene Expression Profiles Predicts Tumor Cell Response to Withanolides

    Directory of Open Access Journals (Sweden)

    Thomas Efferth

    2012-05-01

    Full Text Available Withania somnifera (L. Dunal (Indian ginseng, winter cherry, Solanaceae is widely used in traditional medicine. Roots are either chewed or used to prepare beverages (aqueous decocts. The major secondary metabolites of Withania somnifera are the withanolides, which are C-28-steroidal lactone triterpenoids. Withania somnifera extracts exert chemopreventive and anticancer activities in vitro and in vivo. The aims of the present in silico study were, firstly, to investigate whether tumor cells develop cross-resistance between standard anticancer drugs and withanolides and, secondly, to elucidate the molecular determinants of sensitivity and resistance of tumor cells towards withanolides. Using IC50 concentrations of eight different withanolides (withaferin A, withaferin A diacetate, 3-azerininylwithaferin A, withafastuosin D diacetate, 4-B-hydroxy-withanolide E, isowithanololide E, withafastuosin E, and withaperuvin and 19 established anticancer drugs, we analyzed the cross-resistance profile of 60 tumor cell lines. The cell lines revealed cross-resistance between the eight withanolides. Consistent cross-resistance between withanolides and nitrosoureas (carmustin, lomustin, and semimustin was also observed. Then, we performed transcriptomic microarray-based COMPARE and hierarchical cluster analyses of mRNA expression to identify mRNA expression profiles predicting sensitivity or resistance towards withanolides. Genes from diverse functional groups were significantly associated with response of tumor cells to withaferin A diacetate, e.g. genes functioning in DNA damage and repair, stress response, cell growth regulation, extracellular matrix components, cell adhesion and cell migration, constituents of the ribosome, cytoskeletal organization and regulation, signal transduction, transcription factors, and others.

  20. Argudas: lessons for argumentation in biology based on a gene expression use case.

    Science.gov (United States)

    McLeod, Kenneth; Ferguson, Gus; Burger, Albert

    2012-01-25

    In situ hybridisation gene expression information helps biologists identify where a gene is expressed. However, the databases that republish the experimental information online are often both incomplete and inconsistent. Non-monotonic reasoning can help resolve such difficulties - one such form of reasoning is computational argumentation. Essentially this involves asking a computer to debate (i.e. reason about) the validity of a particular statement. Arguments are produced for both sides - the statement is true and, the statement is false - then the most powerful argument is used. In this work the computer is asked to debate whether or not a gene is expressed in a particular mouse anatomical structure. The information generated during the debate can be passed to the biological end-user, enabling their own decision-making process. This paper examines the evolution of a system, Argudas, which tests using computational argumentation in an in situ gene hybridisation gene expression use case. Argudas reasons using information extracted from several different online resources that publish gene expression information for the mouse. The development and evaluation of two prototypes is discussed. Throughout a number of issues shall be raised including the appropriateness of computational argumentation in biology and the challenges faced when integrating apparently similar online biological databases. From the work described in this paper it is clear that for argumentation to be effective in the biological domain the argumentation community need to develop further the tools and resources they provide. Additionally, the biological community must tackle the incongruity between overlapping and adjacent resources, thus facilitating the integration and modelling of biological information. Finally, this work highlights both the importance of, and difficulty in creating, a good model of the domain.

  1. Microarray-based screening of differentially expressed genes in glucocorticoid-induced avascular necrosis

    Science.gov (United States)

    Huang, Gangyong; Wei, Yibing; Zhao, Guanglei; Xia, Jun; Wang, Siqun; Wu, Jianguo; Chen, Feiyan; Chen, Jie; Shi, Jingshen

    2017-01-01

    The underlying mechanisms of glucocorticoid (GC)-induced avascular necrosis of the femoral head (ANFH) have yet to be fully understood, in particular the mechanisms associated with the change of gene expression pattern. The present study aimed to identify key genes with a differential expression pattern in GC-induced ANFH. E-MEXP-2751 microarray data were downloaded from the ArrayExpress database. Differentially expressed genes (DEGs) were identified in 5 femoral head samples of steroid-induced ANFH rats compared with 5 placebo-treated rat samples. Gene Ontology (GO) and pathway enrichment analyses were performed upon these DEGs. A total 93 DEGs (46 upregulated and 47 downregulated genes) were identified in GC-induced ANFH samples. These DEGs were enriched in different GO terms and pathways, including chondrocyte differentiation and detection of chemical stimuli. The enrichment map revealed that skeletal system development was interconnected with several other GO terms by gene overlap. The literature mined network analysis revealed that 5 upregulated genes were associated with femoral necrosis, including parathyroid hormone receptor 1 (PTHR1), vitamin D (1,25-Dihydroxyvitamin D3) receptor (VDR), collagen, type II, α1, proprotein convertase subtilisin/kexin type 6 and zinc finger protein 354C (ZFP354C). In addition, ZFP354C and VDR were identified to transcription factors. Furthermore, PTHR1 was revealed to interact with VDR, and α-2-macroglobulin (A2M) interacted with fibronectin 1 (FN1) in the PPI network. PTHR1 may be involved in GC-induced ANFH via interacting with VDR. A2M may also be involved in the development of GC-induced ANFH through interacting with FN1. An improved understanding of the molecular mechanisms underlying GC-induced ANFH may provide novel targets for diagnostics and therapeutic treatment. PMID:28393228

  2. Microarray‑based screening of differentially expressed genes in glucocorticoid‑induced avascular necrosis.

    Science.gov (United States)

    Huang, Gangyong; Wei, Yibing; Zhao, Guanglei; Xia, Jun; Wang, Siqun; Wu, Jianguo; Chen, Feiyan; Chen, Jie; Shi, Jingshen

    2017-06-01

    The underlying mechanisms of glucocorticoid (GC)‑induced avascular necrosis of the femoral head (ANFH) have yet to be fully understood, in particular the mechanisms associated with the change of gene expression pattern. The present study aimed to identify key genes with a differential expression pattern in GC‑induced ANFH. E‑MEXP‑2751 microarray data were downloaded from the ArrayExpress database. Differentially expressed genes (DEGs) were identified in 5 femoral head samples of steroid‑induced ANFH rats compared with 5 placebo‑treated rat samples. Gene Ontology (GO) and pathway enrichment analyses were performed upon these DEGs. A total 93 DEGs (46 upregulated and 47 downregulated genes) were identified in GC‑induced ANFH samples. These DEGs were enriched in different GO terms and pathways, including chondrocyte differentiation and detection of chemical stimuli. The enrichment map revealed that skeletal system development was interconnected with several other GO terms by gene overlap. The literature mined network analysis revealed that 5 upregulated genes were associated with femoral necrosis, including parathyroid hormone receptor 1 (PTHR1), vitamin D (1,25‑Dihydroxyvitamin D3) receptor (VDR), collagen, type II, α1, proprotein convertase subtilisin/kexin type 6 and zinc finger protein 354C (ZFP354C). In addition, ZFP354C and VDR were identified to transcription factors. Furthermore, PTHR1 was revealed to interact with VDR, and α‑2‑macroglobulin (A2M) interacted with fibronectin 1 (FN1) in the PPI network. PTHR1 may be involved in GC‑induced ANFH via interacting with VDR. A2M may also be involved in the development of GC‑induced ANFH through interacting with FN1. An improved understanding of the molecular mechanisms underlying GC‑induced ANFH may provide novel targets for diagnostics and therapeutic treatment.

  3. A novel mutual information-based Boolean network inference method from time-series gene expression data.

    Directory of Open Access Journals (Sweden)

    Shohag Barman

    Full Text Available Inferring a gene regulatory network from time-series gene expression data in systems biology is a challenging problem. Many methods have been suggested, most of which have a scalability limitation due to the combinatorial cost of searching a regulatory set of genes. In addition, they have focused on the accurate inference of a network structure only. Therefore, there is a pressing need to develop a network inference method to search regulatory genes efficiently and to predict the network dynamics accurately.In this study, we employed a Boolean network model with a restricted update rule scheme to capture coarse-grained dynamics, and propose a novel mutual information-based Boolean network inference (MIBNI method. Given time-series gene expression data as an input, the method first identifies a set of initial regulatory genes using mutual information-based feature selection, and then improves the dynamics prediction accuracy by iteratively swapping a pair of genes between sets of the selected regulatory genes and the other genes. Through extensive simulations with artificial datasets, MIBNI showed consistently better performance than six well-known existing methods, REVEAL, Best-Fit, RelNet, CST, CLR, and BIBN in terms of both structural and dynamics prediction accuracy. We further tested the proposed method with two real gene expression datasets for an Escherichia coli gene regulatory network and a fission yeast cell cycle network, and also observed better results using MIBNI compared to the six other methods.Taken together, MIBNI is a promising tool for predicting both the structure and the dynamics of a gene regulatory network.

  4. Digital Gene Expression Analysis Based on De Novo Transcriptome Assembly Reveals New Genes Associated with Floral Organ Differentiation of the Orchid Plant Cymbidium ensifolium.

    Directory of Open Access Journals (Sweden)

    Fengxi Yang

    Full Text Available Cymbidium ensifolium belongs to the genus Cymbidium of the orchid family. Owing to its spectacular flower morphology, C. ensifolium has considerable ecological and cultural value. However, limited genetic data is available for this non-model plant, and the molecular mechanism underlying floral organ identity is still poorly understood. In this study, we characterize the floral transcriptome of C. ensifolium and present, for the first time, extensive sequence and transcript abundance data of individual floral organs. After sequencing, over 10 Gb clean sequence data were generated and assembled into 111,892 unigenes with an average length of 932.03 base pairs, including 1,227 clusters and 110,665 singletons. Assembled sequences were annotated with gene descriptions, gene ontology, clusters of orthologous group terms, the Kyoto Encyclopedia of Genes and Genomes, and the plant transcription factor database. From these annotations, 131 flowering-associated unigenes, 61 CONSTANS-LIKE (COL unigenes and 90 floral homeotic genes were identified. In addition, four digital gene expression libraries were constructed for the sepal, petal, labellum and gynostemium, and 1,058 genes corresponding to individual floral organ development were identified. Among them, eight MADS-box genes were further investigated by full-length cDNA sequence analysis and expression validation, which revealed two APETALA1/AGL9-like MADS-box genes preferentially expressed in the sepal and petal, two AGAMOUS-like genes particularly restricted to the gynostemium, and four DEF-like genes distinctively expressed in different floral organs. The spatial expression of these genes varied distinctly in different floral mutant corresponding to different floral morphogenesis, which validated the specialized roles of them in floral patterning and further supported the effectiveness of our in silico analysis. This dataset generated in our study provides new insights into the molecular mechanisms

  5. Gene Expression Music Algorithm-Based Characterization of the Ewing Sarcoma Stem Cell Signature

    Directory of Open Access Journals (Sweden)

    Martin Sebastian Staege

    2016-01-01

    Full Text Available Gene Expression Music Algorithm (GEMusicA is a method for the transformation of DNA microarray data into melodies that can be used for the characterization of differentially expressed genes. Using this method we compared gene expression profiles from endothelial cells (EC, hematopoietic stem cells, neuronal stem cells, embryonic stem cells (ESC, and mesenchymal stem cells (MSC and defined a set of genes that can discriminate between the different stem cell types. We analyzed the behavior of public microarray data sets from Ewing sarcoma (“Ewing family tumors,” EFT cell lines and biopsies in GEMusicA after prefiltering DNA microarray data for the probe sets from the stem cell signature. Our results demonstrate that individual Ewing sarcoma cell lines have a high similarity to ESC or EC. Ewing sarcoma cell lines with inhibited Ewing sarcoma breakpoint region 1-Friend leukemia virus integration 1 (EWSR1-FLI1 oncogene retained the similarity to ESC and EC. However, correlation coefficients between GEMusicA-processed expression data between EFT and ESC decreased whereas correlation coefficients between EFT and EC as well as between EFT and MSC increased after knockdown of EWSR1-FLI1. Our data support the concept of EFT being derived from cells with features of embryonic and endothelial cells.

  6. Differential gene expression in an elite hybrid rice cultivar (Oryza sativa, L and its parental lines based on SAGE data

    Directory of Open Access Journals (Sweden)

    Chen Chen

    2007-09-01

    Full Text Available Abstract Background It was proposed that differentially-expressed genes, aside from genetic variations affecting protein processing and functioning, between hybrid and its parents provide essential candidates for studying heterosis or hybrid vigor. Based our serial analysis of gene expression (SAGE data from an elite Chinese super-hybrid rice (LYP9 and its parental cultivars (93-11 and PA64s in three major tissue types (leaves, roots and panicles at different developmental stages, we analyzed the transcriptome and looked for candidate genes related to rice heterosis. Results By using an improved strategy of tag-to-gene mapping and two recently annotated genome assemblies (93-11 and PA64s, we identified 10,268 additional high-quality tags, reaching a grand total of 20,595 together with our previous result. We further detected 8.5% and 5.9% physically-mapped genes that are differentially-expressed among the triad (in at least one of the three stages with P-values less than 0.05 and 0.01, respectively. These genes distributed in 12 major gene expression patterns; among them, 406 up-regulated and 469 down-regulated genes (P Conclusion We improved tag-to-gene mapping strategy by combining information from transcript sequences and rice genome annotation, and obtained a more comprehensive view on genes that related to rice heterosis. The candidates for heterosis-related genes among different genotypes provided new avenue for exploring the molecular mechanism underlying heterosis.

  7. An efficient model for auxiliary diagnosis of hepatocellular carcinoma based on gene expression programming.

    Science.gov (United States)

    Zhang, Li; Chen, Jiasheng; Gao, Chunming; Liu, Chuanmiao; Xu, Kuihua

    2018-03-16

    Hepatocellular carcinoma (HCC) is a leading cause of cancer-related death worldwide. The early diagnosis of HCC is greatly helpful to achieve long-term disease-free survival. However, HCC is usually difficult to be diagnosed at an early stage. The aim of this study was to create the prediction model to diagnose HCC based on gene expression programming (GEP). GEP is an evolutionary algorithm and a domain-independent problem-solving technique. Clinical data show that six serum biomarkers, including gamma-glutamyl transferase, C-reaction protein, carcinoembryonic antigen, alpha-fetoprotein, carbohydrate antigen 153, and carbohydrate antigen 199, are related to HCC characteristics. In this study, the prediction of HCC was made based on these six biomarkers (195 HCC patients and 215 non-HCC controls) by setting up optimal joint models with GEP. The GEP model discriminated 353 out of 410 subjects, representing a determination coefficient of 86.28% (283/328) and 85.37% (70/82) for training and test sets, respectively. Compared to the results from the support vector machine, the artificial neural network, and the multilayer perceptron, GEP showed a better outcome. The results suggested that GEP modeling was a promising and excellent tool in diagnosis of hepatocellular carcinoma, and it could be widely used in HCC auxiliary diagnosis. Graphical abstract The process to establish an efficient model for auxiliary diagnosis of hepatocellular carcinoma.

  8. Prediction of metabolic flux distribution from gene expression data based on the flux minimization principle.

    Directory of Open Access Journals (Sweden)

    Hyun-Seob Song

    Full Text Available Prediction of possible flux distributions in a metabolic network provides detailed phenotypic information that links metabolism to cellular physiology. To estimate metabolic steady-state fluxes, the most common approach is to solve a set of macroscopic mass balance equations subjected to stoichiometric constraints while attempting to optimize an assumed optimal objective function. This assumption is justifiable in specific cases but may be invalid when tested across different conditions, cell populations, or other organisms. With an aim to providing a more consistent and reliable prediction of flux distributions over a wide range of conditions, in this article we propose a framework that uses the flux minimization principle to predict active metabolic pathways from mRNA expression data. The proposed algorithm minimizes a weighted sum of flux magnitudes, while biomass production can be bounded to fit an ample range from very low to very high values according to the analyzed context. We have formulated the flux weights as a function of the corresponding enzyme reaction's gene expression value, enabling the creation of context-specific fluxes based on a generic metabolic network. In case studies of wild-type Saccharomyces cerevisiae, and wild-type and mutant Escherichia coli strains, our method achieved high prediction accuracy, as gauged by correlation coefficients and sums of squared error, with respect to the experimentally measured values. In contrast to other approaches, our method was able to provide quantitative predictions for both model organisms under a variety of conditions. Our approach requires no prior knowledge or assumption of a context-specific metabolic functionality and does not require trial-and-error parameter adjustments. Thus, our framework is of general applicability for modeling the transcription-dependent metabolism of bacteria and yeasts.

  9. Prediction of lymphatic metastasis based on gene expression profile analysis after brachytherapy for early-stage oral tongue carcinoma

    International Nuclear Information System (INIS)

    Watanabe, Hiroshi; Mogushi, Kaoru; Miura, Masahiko; Yoshimura, Ryo-ichi; Kurabayashi, Tohru; Shibuya, Hitoshi; Tanaka, Hiroshi; Noda, Shuhei; Iwakawa, Mayumi; Imai, Takashi

    2008-01-01

    Background and purpose: The management of lymphatic metastasis of early-stage oral tongue carcinoma patients is crucial for its prognosis. The purpose of this study was to evaluate the predictive ability of lymphatic metastasis after brachytherapy (BRT) for early-stage tongue carcinoma based on gene expression profiling. Patients and methods: Pre-therapeutic biopsies from 39 patients with T1 or T2 tongue cancer were analyzed for gene expression signatures using Codelink Uniset Human 20K Bioarray. All patients were treated with low dose-rate BRT for their primary lesions and underwent strict follow-up under a wait-and-see policy for cervical lymphatic metastasis. Candidate genes were selected for predicting lymph-node status in the reference group by the permutation test. Predictive accuracy was further evaluated by the prediction strength (PS) scoring system using an independent validation group. Results: We selected a set of 19 genes whose expression differed significantly between classes with or without lymphatic metastasis in the reference group. The lymph-node status in the validation group was predicted by the PS scoring system with an accuracy of 76%. Conclusions: Gene expression profiling using 19 genes in primary tumor tissues may allow prediction of lymphatic metastasis after BRT for early-stage oral tongue carcinoma

  10. A reference gene set for sex pheromone biosynthesis and degradation genes from the diamondback moth, Plutella xylostella, based on genome and transcriptome digital gene expression analyses

    OpenAIRE

    He, Peng; Zhang, Yun-Fei; Hong, Duan-Yang; Wang, Jun; Wang, Xing-Liang; Zuo, Ling-Hua; Tang, Xian-Fu; Xu, Wei-Ming; He, Ming

    2017-01-01

    Background Female moths synthesize species-specific sex pheromone components and release them to attract male moths, which depend on precise sex pheromone chemosensory system to locate females. Two types of genes involved in the sex pheromone biosynthesis and degradation pathways play essential roles in this important moth behavior. To understand the function of genes in the sex pheromone pathway, this study investigated the genome-wide and digital gene expression of sex pheromone biosynthesi...

  11. Prediction of essential proteins based on subcellular localization and gene expression correlation.

    Science.gov (United States)

    Fan, Yetian; Tang, Xiwei; Hu, Xiaohua; Wu, Wei; Ping, Qing

    2017-12-01

    Essential proteins are indispensable to the survival and development process of living organisms. To understand the functional mechanisms of essential proteins, which can be applied to the analysis of disease and design of drugs, it is important to identify essential proteins from a set of proteins first. As traditional experimental methods designed to test out essential proteins are usually expensive and laborious, computational methods, which utilize biological and topological features of proteins, have attracted more attention in recent years. Protein-protein interaction networks, together with other biological data, have been explored to improve the performance of essential protein prediction. The proposed method SCP is evaluated on Saccharomyces cerevisiae datasets and compared with five other methods. The results show that our method SCP outperforms the other five methods in terms of accuracy of essential protein prediction. In this paper, we propose a novel algorithm named SCP, which combines the ranking by a modified PageRank algorithm based on subcellular compartments information, with the ranking by Pearson correlation coefficient (PCC) calculated from gene expression data. Experiments show that subcellular localization information is promising in boosting essential protein prediction.

  12. Hessian regularization based symmetric nonnegative matrix factorization for clustering gene expression and microbiome data.

    Science.gov (United States)

    Ma, Yuanyuan; Hu, Xiaohua; He, Tingting; Jiang, Xingpeng

    2016-12-01

    Nonnegative matrix factorization (NMF) has received considerable attention due to its interpretation of observed samples as combinations of different components, and has been successfully used as a clustering method. As an extension of NMF, Symmetric NMF (SNMF) inherits the advantages of NMF. Unlike NMF, however, SNMF takes a nonnegative similarity matrix as an input, and two lower rank nonnegative matrices (H, H T ) are computed as an output to approximate the original similarity matrix. Laplacian regularization has improved the clustering performance of NMF and SNMF. However, Laplacian regularization (LR), as a classic manifold regularization method, suffers some problems because of its weak extrapolating ability. In this paper, we propose a novel variant of SNMF, called Hessian regularization based symmetric nonnegative matrix factorization (HSNMF), for this purpose. In contrast to Laplacian regularization, Hessian regularization fits the data perfectly and extrapolates nicely to unseen data. We conduct extensive experiments on several datasets including text data, gene expression data and HMP (Human Microbiome Project) data. The results show that the proposed method outperforms other methods, which suggests the potential application of HSNMF in biological data clustering. Copyright © 2016. Published by Elsevier Inc.

  13. Gene expression-based biological test for major depressive disorder: an advanced study

    Directory of Open Access Journals (Sweden)

    Watanabe S

    2017-02-01

    Full Text Available Shin-ya Watanabe,1 Shusuke Numata,1 Jun-ichi Iga,2 Makoto Kinoshita,1 Hidehiro Umehara,1 Kazuo Ishii,3 Tetsuro Ohmori1 1Department of Psychiatry, Institute of Biomedical Sciences, Tokushima University Graduate School, Tokushima, 2Department of Neuropsychiatry, Molecules and Function, Ehime University Graduate School of Medicine, Ehime, 3Department of Applied Biological Science, Faculty of Agriculture, Tokyo University of Agriculture and Technology, Tokyo, Japan Purpose: Recently, we could distinguished patients with major depressive disorder (MDD from nonpsychiatric controls with high accuracy using a panel of five gene expression markers (ARHGAP24, HDAC5, PDGFC, PRNP, and SLC6A4 in leukocyte. In the present study, we examined whether this biological test is able to discriminate patients with MDD from those without MDD, including those with schizophrenia and bipolar disorder.Patients and methods: We measured messenger ribonucleic acid expression levels of the aforementioned five genes in peripheral leukocytes in 17 patients with schizophrenia and 36 patients with bipolar disorder using quantitative real-time polymerase chain reaction (PCR, and we combined these expression data with our previous expression data of 25 patients with MDD and 25 controls. Subsequently, a linear discriminant function was developed for use in discriminating between patients with MDD and without MDD.Results: This expression panel was able to segregate patients with MDD from those without MDD with a sensitivity and specificity of 64% and 67.9%, respectively.Conclusion: Further research to identify MDD-specific markers is needed to improve the performance of this biological test. Keywords: depressive disorder, biomarker, gene expression, schizophrenia, bipolar disorder

  14. Prediction of Metastasis and Recurrence in Colorectal Cancer Based on Gene Expression Analysis: Ready for the Clinic?

    International Nuclear Information System (INIS)

    Shibayama, Masaki; Maak, Matthias; Nitsche, Ulrich; Gotoh, Kengo; Rosenberg, Robert; Janssen, Klaus-Peter

    2011-01-01

    Cancers of the colon and rectum, which rank among the most frequent human tumors, are currently treated by surgical resection in locally restricted tumor stages. However, disease recurrence and formation of local and distant metastasis frequently occur even in cases with successful curative resection of the primary tumor (R0). Recent technological advances in molecular diagnostic analysis have led to a wealth of knowledge about the changes in gene transcription in all stages of colorectal tumors. Differential gene expression, or transcriptome analysis, has been proposed by many groups to predict disease recurrence, clinical outcome, and also response to therapy, in addition to the well-established clinico-pathological factors. However, the clinical usability of gene expression profiling as a reliable and robust prognostic tool that allows evidence-based clinical decisions is currently under debate. In this review, we will discuss the most recent data on the prognostic significance and potential clinical application of genome wide expression analysis in colorectal cancer

  15. Prediction of Metastasis and Recurrence in Colorectal Cancer Based on Gene Expression Analysis: Ready for the Clinic?

    Energy Technology Data Exchange (ETDEWEB)

    Shibayama, Masaki [Sysmex Corporation, Central Research Laboratories, Kobe 651-2271 (Japan); Maak, Matthias; Nitsche, Ulrich [Chirurgische Klinik, Klinikum Rechts der Isar der TUM, München 81657 (Germany); Gotoh, Kengo [Sysmex Corporation, Central Research Laboratories, Kobe 651-2271 (Japan); Rosenberg, Robert; Janssen, Klaus-Peter, E-mail: klaus-peter.janssen@lrz.tum.de [Chirurgische Klinik, Klinikum Rechts der Isar der TUM, München 81657 (Germany)

    2011-07-07

    Cancers of the colon and rectum, which rank among the most frequent human tumors, are currently treated by surgical resection in locally restricted tumor stages. However, disease recurrence and formation of local and distant metastasis frequently occur even in cases with successful curative resection of the primary tumor (R0). Recent technological advances in molecular diagnostic analysis have led to a wealth of knowledge about the changes in gene transcription in all stages of colorectal tumors. Differential gene expression, or transcriptome analysis, has been proposed by many groups to predict disease recurrence, clinical outcome, and also response to therapy, in addition to the well-established clinico-pathological factors. However, the clinical usability of gene expression profiling as a reliable and robust prognostic tool that allows evidence-based clinical decisions is currently under debate. In this review, we will discuss the most recent data on the prognostic significance and potential clinical application of genome wide expression analysis in colorectal cancer.

  16. Prediction of drug efficacy for cancer treatment based on comparative analysis of chemosensitivity and gene expression data

    DEFF Research Database (Denmark)

    Wan, Peng; Li, Qiyuan; Larsen, Jens Erik Pontoppidan

    2012-01-01

    The NCI60 database is the largest available collection of compounds with measured anti-cancer activity. The strengths and limitations for using the NCI60 database as a source of new anti-cancer agents are explored and discussed in relation to previous studies. We selected a sub-set of 2333...... and in a data set of expression profiles of 1901 genes for the corresponding tumor cell lines. Five clusters were identified based on the gene expression data using self-organizing maps (SOM), comprising leukemia, melanoma, ovarian and prostate, basal breast, and luminal breast cancer cells, respectively....... The strong difference in gene expression between basal and luminal breast cancer cells was reflected clearly in the chemosensitivity data. Although most compounds in the data set were of low potency, high efficacy compounds that showed specificity with respect to tissue of origin could be found. Furthermore...

  17. iSyTE 2.0: a database for expression-based gene discovery in the eye

    Science.gov (United States)

    Kakrana, Atul; Yang, Andrian; Anand, Deepti; Djordjevic, Djordje; Ramachandruni, Deepti; Singh, Abhyudai; Huang, Hongzhan

    2018-01-01

    Abstract Although successful in identifying new cataract-linked genes, the previous version of the database iSyTE (integrated Systems Tool for Eye gene discovery) was based on expression information on just three mouse lens stages and was functionally limited to visualization by only UCSC-Genome Browser tracks. To increase its efficacy, here we provide an enhanced iSyTE version 2.0 (URL: http://research.bioinformatics.udel.edu/iSyTE) based on well-curated, comprehensive genome-level lens expression data as a one-stop portal for the effective visualization and analysis of candidate genes in lens development and disease. iSyTE 2.0 includes all publicly available lens Affymetrix and Illumina microarray datasets representing a broad range of embryonic and postnatal stages from wild-type and specific gene-perturbation mouse mutants with eye defects. Further, we developed a new user-friendly web interface for direct access and cogent visualization of the curated expression data, which supports convenient searches and a range of downstream analyses. The utility of these new iSyTE 2.0 features is illustrated through examples of established genes associated with lens development and pathobiology, which serve as tutorials for its application by the end-user. iSyTE 2.0 will facilitate the prioritization of eye development and disease-linked candidate genes in studies involving transcriptomics or next-generation sequencing data, linkage analysis and GWAS approaches. PMID:29036527

  18. Correlation of gene expression and contaminat concentrations in wild largescale suckers: a field-based study

    Science.gov (United States)

    Christiansen, Helena E.; Mehinto, Alvine C.; Yu, Fahong; Perry, Russell W.; Denslow, Nancy D.; Maule, Alec G.; Mesa, Matthew G.

    2014-01-01

    Toxic compounds such as organochlorine pesticides (OCs), polychlorinated biphenyls (PCBs), and polybrominated diphenyl ether flame retardants (PBDEs) have been detected in fish, birds, and aquatic mammals that live in the Columbia River or use food resources from within the river. We developed a custom microarray for largescale suckers (Catostomus macrocheilus) and used it to investigate the molecular effects of contaminant exposure on wild fish in the Columbia River. Using Significance Analysis of Microarrays (SAM) we identified 72 probes representing 69 unique genes with expression patterns that correlated with hepatic tissue levels of OCs, PCBs, or PBDEs. These genes were involved in many biological processes previously shown to respond to contaminant exposure, including drug and lipid metabolism, apoptosis, cellular transport, oxidative stress, and cellular chaperone function. The relation between gene expression and contaminant concentration suggests that these genes may respond to environmental contaminant exposure and are promising candidates for further field and laboratory studies to develop biomarkers for monitoring exposure of wild fish to contaminant mixtures found in the Columbia River Basin. The array developed in this study could also be a useful tool for studies involving endangered sucker species and other sucker species used in contaminant research.

  19. Analyzing large gene expression and methylation data profiles using StatBicRM: statistical biclustering-based rule mining.

    Directory of Open Access Journals (Sweden)

    Ujjwal Maulik

    Full Text Available Microarray and beadchip are two most efficient techniques for measuring gene expression and methylation data in bioinformatics. Biclustering deals with the simultaneous clustering of genes and samples. In this article, we propose a computational rule mining framework, StatBicRM (i.e., statistical biclustering-based rule mining to identify special type of rules and potential biomarkers using integrated approaches of statistical and binary inclusion-maximal biclustering techniques from the biological datasets. At first, a novel statistical strategy has been utilized to eliminate the insignificant/low-significant/redundant genes in such way that significance level must satisfy the data distribution property (viz., either normal distribution or non-normal distribution. The data is then discretized and post-discretized, consecutively. Thereafter, the biclustering technique is applied to identify maximal frequent closed homogeneous itemsets. Corresponding special type of rules are then extracted from the selected itemsets. Our proposed rule mining method performs better than the other rule mining algorithms as it generates maximal frequent closed homogeneous itemsets instead of frequent itemsets. Thus, it saves elapsed time, and can work on big dataset. Pathway and Gene Ontology analyses are conducted on the genes of the evolved rules using David database. Frequency analysis of the genes appearing in the evolved rules is performed to determine potential biomarkers. Furthermore, we also classify the data to know how much the evolved rules are able to describe accurately the remaining test (unknown data. Subsequently, we also compare the average classification accuracy, and other related factors with other rule-based classifiers. Statistical significance tests are also performed for verifying the statistical relevance of the comparative results. Here, each of the other rule mining methods or rule-based classifiers is also starting with the same post

  20. Analyzing large gene expression and methylation data profiles using StatBicRM: statistical biclustering-based rule mining.

    Science.gov (United States)

    Maulik, Ujjwal; Mallik, Saurav; Mukhopadhyay, Anirban; Bandyopadhyay, Sanghamitra

    2015-01-01

    Microarray and beadchip are two most efficient techniques for measuring gene expression and methylation data in bioinformatics. Biclustering deals with the simultaneous clustering of genes and samples. In this article, we propose a computational rule mining framework, StatBicRM (i.e., statistical biclustering-based rule mining) to identify special type of rules and potential biomarkers using integrated approaches of statistical and binary inclusion-maximal biclustering techniques from the biological datasets. At first, a novel statistical strategy has been utilized to eliminate the insignificant/low-significant/redundant genes in such way that significance level must satisfy the data distribution property (viz., either normal distribution or non-normal distribution). The data is then discretized and post-discretized, consecutively. Thereafter, the biclustering technique is applied to identify maximal frequent closed homogeneous itemsets. Corresponding special type of rules are then extracted from the selected itemsets. Our proposed rule mining method performs better than the other rule mining algorithms as it generates maximal frequent closed homogeneous itemsets instead of frequent itemsets. Thus, it saves elapsed time, and can work on big dataset. Pathway and Gene Ontology analyses are conducted on the genes of the evolved rules using David database. Frequency analysis of the genes appearing in the evolved rules is performed to determine potential biomarkers. Furthermore, we also classify the data to know how much the evolved rules are able to describe accurately the remaining test (unknown) data. Subsequently, we also compare the average classification accuracy, and other related factors with other rule-based classifiers. Statistical significance tests are also performed for verifying the statistical relevance of the comparative results. Here, each of the other rule mining methods or rule-based classifiers is also starting with the same post-discretized data

  1. Gene expression inference with deep learning.

    Science.gov (United States)

    Chen, Yifei; Li, Yi; Narayan, Rajiv; Subramanian, Aravind; Xie, Xiaohui

    2016-06-15

    Large-scale gene expression profiling has been widely used to characterize cellular states in response to various disease conditions, genetic perturbations, etc. Although the cost of whole-genome expression profiles has been dropping steadily, generating a compendium of expression profiling over thousands of samples is still very expensive. Recognizing that gene expressions are often highly correlated, researchers from the NIH LINCS program have developed a cost-effective strategy of profiling only ∼1000 carefully selected landmark genes and relying on computational methods to infer the expression of remaining target genes. However, the computational approach adopted by the LINCS program is currently based on linear regression (LR), limiting its accuracy since it does not capture complex nonlinear relationship between expressions of genes. We present a deep learning method (abbreviated as D-GEX) to infer the expression of target genes from the expression of landmark genes. We used the microarray-based Gene Expression Omnibus dataset, consisting of 111K expression profiles, to train our model and compare its performance to those from other methods. In terms of mean absolute error averaged across all genes, deep learning significantly outperforms LR with 15.33% relative improvement. A gene-wise comparative analysis shows that deep learning achieves lower error than LR in 99.97% of the target genes. We also tested the performance of our learned model on an independent RNA-Seq-based GTEx dataset, which consists of 2921 expression profiles. Deep learning still outperforms LR with 6.57% relative improvement, and achieves lower error in 81.31% of the target genes. D-GEX is available at https://github.com/uci-cbcl/D-GEX CONTACT: xhx@ics.uci.edu Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

  2. Regulation of eucaryotic gene expression

    Energy Technology Data Exchange (ETDEWEB)

    Brent, R.; Ptashne, M.S

    1989-05-23

    This patent describes a method of regulating the expression of a gene in a eucaryotic cell. The method consists of: providing in the eucaryotic cell, a peptide, derived from or substantially similar to a peptide of a procaryotic cell able to bind to DNA upstream from or within the gene, the amount of the peptide being sufficient to bind to the gene and thereby control expression of the gene.

  3. Profiling Gene Expression in Germinating Brassica Roots.

    Science.gov (United States)

    Park, Myoung Ryoul; Wang, Yi-Hong; Hasenstein, Karl H

    2014-01-01

    Based on previously developed solid-phase gene extraction (SPGE) we examined the mRNA profile in primary roots of Brassica rapa seedlings for highly expressed genes like ACT7 (actin7), TUB (tubulin1), UBQ (ubiquitin), and low expressed GLK (glucokinase) during the first day post-germination. The assessment was based on the mRNA load of the SPGE probe of about 2.1 ng. The number of copies of the investigated genes changed spatially along the length of primary roots. The expression level of all genes differed significantly at each sample position. Among the examined genes ACT7 expression was most even along the root. UBQ was highest at the tip and root-shoot junction (RS). TUB and GLK showed a basipetal gradient. The temporal expression of UBQ was highest in the MZ 9 h after primary root emergence and higher than at any other sample position. Expressions of GLK in EZ and RS increased gradually over time. SPGE extraction is the result of oligo-dT and oligo-dA hybridization and the results illustrate that SPGE can be used for gene expression profiling at high spatial and temporal resolution. SPGE needles can be used within two weeks when stored at 4 °C. Our data indicate that gene expression studies that are based on the entire root miss important differences in gene expression that SPGE is able to resolve for example growth adjustments during gravitropism.

  4. Using rule-based machine learning for candidate disease gene prioritization and sample classification of cancer gene expression data.

    Directory of Open Access Journals (Sweden)

    Enrico Glaab

    Full Text Available Microarray data analysis has been shown to provide an effective tool for studying cancer and genetic diseases. Although classical machine learning techniques have successfully been applied to find informative genes and to predict class labels for new samples, common restrictions of microarray analysis such as small sample sizes, a large attribute space and high noise levels still limit its scientific and clinical applications. Increasing the interpretability of prediction models while retaining a high accuracy would help to exploit the information content in microarray data more effectively. For this purpose, we evaluate our rule-based evolutionary machine learning systems, BioHEL and GAssist, on three public microarray cancer datasets, obtaining simple rule-based models for sample classification. A comparison with other benchmark microarray sample classifiers based on three diverse feature selection algorithms suggests that these evolutionary learning techniques can compete with state-of-the-art methods like support vector machines. The obtained models reach accuracies above 90% in two-level external cross-validation, with the added value of facilitating interpretation by using only combinations of simple if-then-else rules. As a further benefit, a literature mining analysis reveals that prioritizations of informative genes extracted from BioHEL's classification rule sets can outperform gene rankings obtained from a conventional ensemble feature selection in terms of the pointwise mutual information between relevant disease terms and the standardized names of top-ranked genes.

  5. Using rule-based machine learning for candidate disease gene prioritization and sample classification of cancer gene expression data.

    Science.gov (United States)

    Glaab, Enrico; Bacardit, Jaume; Garibaldi, Jonathan M; Krasnogor, Natalio

    2012-01-01

    Microarray data analysis has been shown to provide an effective tool for studying cancer and genetic diseases. Although classical machine learning techniques have successfully been applied to find informative genes and to predict class labels for new samples, common restrictions of microarray analysis such as small sample sizes, a large attribute space and high noise levels still limit its scientific and clinical applications. Increasing the interpretability of prediction models while retaining a high accuracy would help to exploit the information content in microarray data more effectively. For this purpose, we evaluate our rule-based evolutionary machine learning systems, BioHEL and GAssist, on three public microarray cancer datasets, obtaining simple rule-based models for sample classification. A comparison with other benchmark microarray sample classifiers based on three diverse feature selection algorithms suggests that these evolutionary learning techniques can compete with state-of-the-art methods like support vector machines. The obtained models reach accuracies above 90% in two-level external cross-validation, with the added value of facilitating interpretation by using only combinations of simple if-then-else rules. As a further benefit, a literature mining analysis reveals that prioritizations of informative genes extracted from BioHEL's classification rule sets can outperform gene rankings obtained from a conventional ensemble feature selection in terms of the pointwise mutual information between relevant disease terms and the standardized names of top-ranked genes.

  6. Expression of Separate Proteins in the Same Plant Leaves and Cells Using Two Independent Virus-Based Gene Vectors

    Directory of Open Access Journals (Sweden)

    Maria R. Mendoza

    2017-11-01

    Full Text Available Plant viral vectors enable the expression of proteins at high levels in a relatively short time. For many purposes (e.g., cell biological interaction studies it may be desirable to express more than one protein in a single cell but that is often not feasible when using a single virus vector. Such a co-expression strategy requires the simultaneous delivery by two compatible and non-competitive viruses that can co-exist to each express a separate protein. Here, we report on the use of two agro-launchable coat-protein gene substitution GFP-expressing virus vector systems based on Tomato bushy stunt virus (TBSV referred to as TG, and Tobacco mosaic virus (TMV annotated as TRBO-G. TG expressed GFP in Nicotiana benthamiana, tomato, lettuce and cowpea, whereas expression from TRBO-G was detected only in the first two species. Upon co-infiltration of the two vectors co-expression was monitored by: molecular detection of the two slightly differently sized GFPs, suppressor-complementation assays, and using TG in combination with TRBO-RFP. All the results revealed that in N. benthamiana and tomato the TBSV and TMV vectors accumulated and expressed proteins in the same plants, the same leaves, and in the same cells. Therefore, co-expression by these two vectors provides a platform for fast and high level expression of proteins to study their cell biology or other properties.

  7. Differential Gene Expression and Aging

    Directory of Open Access Journals (Sweden)

    Laurent Seroude

    2002-01-01

    Full Text Available It has been established that an intricate program of gene expression controls progression through the different stages in development. The equally complex biological phenomenon known as aging is genetically determined and environmentally modulated. This review focuses on the genetic component of aging, with a special emphasis on differential gene expression. At least two genetic pathways regulating organism longevity act by modifying gene expression. Many genes are also subjected to age-dependent transcriptional regulation. Some age-related gene expression changes are prevented by caloric restriction, the most robust intervention that slows down the aging process. Manipulating the expression of some age-regulated genes can extend an organism's life span. Remarkably, the activity of many transcription regulatory elements is linked to physiological age as opposed to chronological age, indicating that orderly and tightly controlled regulatory pathways are active during aging.

  8. Automated Detection of Cancer Associated Genes Using a Combined Fuzzy-Rough-Set-Based F-Information and Water Swirl Algorithm of Human Gene Expression Data.

    Directory of Open Access Journals (Sweden)

    Pugalendhi Ganesh Kumar

    Full Text Available This study describes a novel approach to reducing the challenges of highly nonlinear multiclass gene expression values for cancer diagnosis. To build a fruitful system for cancer diagnosis, in this study, we introduced two levels of gene selection such as filtering and embedding for selection of potential genes and the most relevant genes associated with cancer, respectively. The filter procedure was implemented by developing a fuzzy rough set (FR-based method for redefining the criterion function of f-information (FI to identify the potential genes without discretizing the continuous gene expression values. The embedded procedure is implemented by means of a water swirl algorithm (WSA, which attempts to optimize the rule set and membership function required to classify samples using a fuzzy-rule-based multiclassification system (FRBMS. Two novel update equations are proposed in WSA, which have better exploration and exploitation abilities while designing a self-learning FRBMS. The efficiency of our new approach was evaluated on 13 multicategory and 9 binary datasets of cancer gene expression. Additionally, the performance of the proposed FRFI-WSA method in designing an FRBMS was compared with existing methods for gene selection and optimization such as genetic algorithm (GA, particle swarm optimization (PSO, and artificial bee colony algorithm (ABC on all the datasets. In the global cancer map with repeated measurements (GCM_RM dataset, the FRFI-WSA showed the smallest number of 16 most relevant genes associated with cancer using a minimal number of 26 compact rules with the highest classification accuracy (96.45%. In addition, the statistical validation used in this study revealed that the biological relevance of the most relevant genes associated with cancer and their linguistics detected by the proposed FRFI-WSA approach are better than those in the other methods. The simple interpretable rules with most relevant genes and effectively

  9. Determinants of human adipose tissue gene expression

    DEFF Research Database (Denmark)

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

    2012-01-01

    weight maintenance diets. For 175 genes, opposite regulation was observed during calorie restriction and weight maintenance phases, independently of variations in body weight. Metabolism and immunity genes showed inverse profiles. During the dietary intervention, network-based analyses revealed strong...... interconnection between expression of genes involved in de novo lipogenesis and components of the metabolic syndrome. Sex had a marked influence on AT expression of 88 transcripts, which persisted during the entire dietary intervention and after control for fat mass. In women, the influence of body mass index...... on expression of a subset of genes persisted during the dietary intervention. Twenty-two genes revealed a metabolic syndrome signature common to men and women. Genetic control of AT gene expression by cis signals was observed for 46 genes. Dietary intervention, sex, and cis genetic variants independently...

  10. A New Method for the Evaluation of Vaccine Safety Based on Comprehensive Gene Expression Analysis

    Directory of Open Access Journals (Sweden)

    Haruka Momose

    2010-01-01

    Full Text Available For the past 50 years, quality control and safety tests have been used to evaluate vaccine safety. However, conventional animal safety tests need to be improved in several aspects. For example, the number of test animals used needs to be reduced and the test period shortened. It is, therefore, necessary to develop a new vaccine evaluation system. In this review, we show that gene expression patterns are well correlated to biological responses in vaccinated rats. Our findings and methods using experimental biology and genome science provide an important means of assessment for vaccine toxicity.

  11. cis sequence effects on gene expression

    Directory of Open Access Journals (Sweden)

    Jacobs Kevin

    2007-08-01

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

  12. Model-based deconvolution of cell cycle time-series data reveals gene expression details at high resolution.

    Directory of Open Access Journals (Sweden)

    Dan Siegal-Gaskins

    2009-08-01

    Full Text Available In both prokaryotic and eukaryotic cells, gene expression is regulated across the cell cycle to ensure "just-in-time" assembly of select cellular structures and molecular machines. However, present in all time-series gene expression measurements is variability that arises from both systematic error in the cell synchrony process and variance in the timing of cell division at the level of the single cell. Thus, gene or protein expression data collected from a population of synchronized cells is an inaccurate measure of what occurs in the average single-cell across a cell cycle. Here, we present a general computational method to extract "single-cell"-like information from population-level time-series expression data. This method removes the effects of 1 variance in growth rate and 2 variance in the physiological and developmental state of the cell. Moreover, this method represents an advance in the deconvolution of molecular expression data in its flexibility, minimal assumptions, and the use of a cross-validation analysis to determine the appropriate level of regularization. Applying our deconvolution algorithm to cell cycle gene expression data from the dimorphic bacterium Caulobacter crescentus, we recovered critical features of cell cycle regulation in essential genes, including ctrA and ftsZ, that were obscured in population-based measurements. In doing so, we highlight the problem with using population data alone to decipher cellular regulatory mechanisms and demonstrate how our deconvolution algorithm can be applied to produce a more realistic picture of temporal regulation in a cell.

  13. Digital gene expression analysis based on integrated de novo transcriptome assembly of sweet potato [Ipomoea batatas (L. Lam].

    Directory of Open Access Journals (Sweden)

    Xiang Tao

    Full Text Available BACKGROUND: Sweet potato (Ipomoea batatas L. [Lam.] ranks among the top six most important food crops in the world. It is widely grown throughout the world with high and stable yield, strong adaptability, rich nutrient content, and multiple uses. However, little is known about the molecular biology of this important non-model organism due to lack of genomic resources. Hence, studies based on high-throughput sequencing technologies are needed to get a comprehensive and integrated genomic resource and better understanding of gene expression patterns in different tissues and at various developmental stages. METHODOLOGY/PRINCIPAL FINDINGS: Illumina paired-end (PE RNA-Sequencing was performed, and generated 48.7 million of 75 bp PE reads. These reads were de novo assembled into 128,052 transcripts (≥ 100 bp, which correspond to 41.1 million base pairs, by using a combined assembly strategy. Transcripts were annotated by Blast2GO and 51,763 transcripts got BLASTX hits, in which 39,677 transcripts have GO terms and 14,117 have ECs that are associated with 147 KEGG pathways. Furthermore, transcriptome differences of seven tissues were analyzed by using Illumina digital gene expression (DGE tag profiling and numerous differentially and specifically expressed transcripts were identified. Moreover, the expression characteristics of genes involved in viral genomes, starch metabolism and potential stress tolerance and insect resistance were also identified. CONCLUSIONS/SIGNIFICANCE: The combined de novo transcriptome assembly strategy can be applied to other organisms whose reference genomes are not available. The data provided here represent the most comprehensive and integrated genomic resources for cloning and identifying genes of interest in sweet potato. Characterization of sweet potato transcriptome provides an effective tool for better understanding the molecular mechanisms of cellular processes including development of leaves and storage roots

  14. A Link-Based Cluster Ensemble Approach For Improved Gene Expression Data Analysis

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    P.Balaji

    2015-01-01

    Full Text Available Abstract It is difficult from possibilities to select a most suitable effective way of clustering algorithm and its dataset for a defined set of gene expression data because we have a huge number of ways and huge number of gene expressions. At present many researchers are preferring to use hierarchical clustering in different forms this is no more totally optimal. Cluster ensemble research can solve this type of problem by automatically merging multiple data partitions from a wide range of different clusterings of any dimensions to improve both the quality and robustness of the clustering result. But we have many existing ensemble approaches using an association matrix to condense sample-cluster and co-occurrence statistics and relations within the ensemble are encapsulated only at raw level while the existing among clusters are totally discriminated. Finding these missing associations can greatly expand the capability of those ensemble methodologies for microarray data clustering. We propose general K-means cluster ensemble approach for the clustering of general categorical data into required number of partitions.

  15. Artificial Neural Networks and Gene Expression Programing based age estimation using facial features

    Directory of Open Access Journals (Sweden)

    Baddrud Z. Laskar

    2015-10-01

    Full Text Available This work is about estimating human age automatically through analysis of facial images. It has got a lot of real-world applications. Due to prompt advances in the fields of machine vision, facial image processing, and computer graphics, automatic age estimation via faces in computer is one of the dominant topics these days. This is due to widespread real-world applications, in areas of biometrics, security, surveillance, control, forensic art, entertainment, online customer management and support, along with cosmetology. As it is difficult to estimate the exact age, this system is to estimate a certain range of ages. Four sets of classifications have been used to differentiate a person’s data into one of the different age groups. The uniqueness about this study is the usage of two technologies i.e., Artificial Neural Networks (ANN and Gene Expression Programing (GEP to estimate the age and then compare the results. New methodologies like Gene Expression Programing (GEP have been explored here and significant results were found. The dataset has been developed to provide more efficient results by superior preprocessing methods. This proposed approach has been developed, tested and trained using both the methods. A public data set was used to test the system, FG-NET. The quality of the proposed system for age estimation using facial features is shown by broad experiments on the available database of FG-NET.

  16. Microarray-Based Gene Expression Analysis for Veterinary Pathologists: A Review.

    Science.gov (United States)

    Raddatz, Barbara B; Spitzbarth, Ingo; Matheis, Katja A; Kalkuhl, Arno; Deschl, Ulrich; Baumgärtner, Wolfgang; Ulrich, Reiner

    2017-09-01

    High-throughput, genome-wide transcriptome analysis is now commonly used in all fields of life science research and is on the cusp of medical and veterinary diagnostic application. Transcriptomic methods such as microarrays and next-generation sequencing generate enormous amounts of data. The pathogenetic expertise acquired from understanding of general pathology provides veterinary pathologists with a profound background, which is essential in translating transcriptomic data into meaningful biological knowledge, thereby leading to a better understanding of underlying disease mechanisms. The scientific literature concerning high-throughput data-mining techniques usually addresses mathematicians or computer scientists as the target audience. In contrast, the present review provides the reader with a clear and systematic basis from a veterinary pathologist's perspective. Therefore, the aims are (1) to introduce the reader to the necessary methodological background; (2) to introduce the sequential steps commonly performed in a microarray analysis including quality control, annotation, normalization, selection of differentially expressed genes, clustering, gene ontology and pathway analysis, analysis of manually selected genes, and biomarker discovery; and (3) to provide references to publically available and user-friendly software suites. In summary, the data analysis methods presented within this review will enable veterinary pathologists to analyze high-throughput transcriptome data obtained from their own experiments, supplemental data that accompany scientific publications, or public repositories in order to obtain a more in-depth insight into underlying disease mechanisms.

  17. 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; Wong, Yue Him; Tsang, Ling Ming; Chu, Ka Hou; Qian, Pei Yuan; Chan, Benny K K

    2013-01-01

    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.

  18. 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.

  19. Polycistronic gene expression in Aspergillus niger.

    Science.gov (United States)

    Schuetze, Tabea; Meyer, Vera

    2017-09-25

    Genome mining approaches predict dozens of biosynthetic gene clusters in each of the filamentous fungal genomes sequenced so far. However, the majority of these gene clusters still remain cryptic because they are not expressed in their natural host. Simultaneous expression of all genes belonging to a biosynthetic pathway in a heterologous host is one approach to activate biosynthetic gene clusters and to screen the metabolites produced for bioactivities. Polycistronic expression of all pathway genes under control of a single and tunable promoter would be the method of choice, as this does not only simplify cloning procedures, but also offers control on timing and strength of expression. However, polycistronic gene expression is a feature not commonly found in eukaryotic host systems, such as Aspergillus niger. In this study, we tested the suitability of the viral P2A peptide for co-expression of three genes in A. niger. Two genes descend from Fusarium oxysporum and are essential to produce the secondary metabolite enniatin (esyn1, ekivR). The third gene (luc) encodes the reporter luciferase which was included to study position effects. Expression of the polycistronic gene cassette was put under control of the Tet-On system to ensure tunable gene expression in A. niger. In total, three polycistronic expression cassettes which differed in the position of luc were constructed and targeted to the pyrG locus in A. niger. This allowed direct comparison of the luciferase activity based on the position of the luciferase gene. Doxycycline-mediated induction of the Tet-On expression cassettes resulted in the production of one long polycistronic mRNA as proven by Northern analyses, and ensured comparable production of enniatin in all three strains. Notably, gene position within the polycistronic expression cassette matters, as, luciferase activity was lowest at position one and had a comparable activity at positions two and three. The P2A peptide can be used to express at

  20. Modulation of radiation-induced base excision repair pathway gene expression by melatonin

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    Saeed Rezapoor

    2017-01-01

    Full Text Available Objective: Approximately 70% of all cancer patients receive radiotherapy. Although radiotherapy is effective in killing cancer cells, it has adverse effects on normal cells as well. Melatonin (MLT as a potent antioxidant and anti-inflammatory agent has been proposed to stimulate DNA repair capacity. We investigated the capability of MLT in the modification of radiation-induced DNA damage in rat peripheral blood cells. Materials and Methods: In this experimental study, male rats (n = 162 were divided into 27 groups (n = 6 in each group including: irradiation only, vehicle only, vehicle with irradiation, 100 mg/kg MLT alone, 100 mg/kg MLT plus irradiation in 3 different time points, and control. Subsequently, they were irradiated with a single whole-body X-ray radiation dose of 2 and 8 Gy at a dose rate of 200 MU/min. Rats were given an intraperitoneal injection of MLT or the same volume of vehicle alone 1 h prior to irradiation. Blood samples were also taken 8, 24, and 48 h postirradiation, in order to measure the 8-oxoguanine glycosylase1 (Ogg1, Apex1, and Xrcc1 expression using quantitative real-time-polymerase chain reaction. Results: Exposing to the ionizing radiation resulted in downregulation of Ogg1, Apex1, and Xrcc1 gene expression. The most obvious suppression was observed in 8 h after exposure. Pretreatments with MLT were able to upregulate these genes when compared to the irradiation-only and vehicle plus irradiation groups (P < 0.05 in all time points. Conclusion: Our results suggested that MLT in mentioned dose may result in modulation of Ogg1, Apex1, and Xrcc1 gene expression in peripheral blood cells to reduce X-ray irradiation-induced DNA damage. Therefore, administration of MLT may increase the normal tissue tolerance to radiation through enhancing the cell DNA repair capacity. We believed that MLT could play a radiation toxicity reduction role in patients who have undergone radiation treatment as a part of cancer radiotherapy.

  1. Liposome-based DNA carriers may induce cellular stress response and change gene expression pattern in transfected cells

    Science.gov (United States)

    2011-01-01

    Background During functional studies on the rat stress-inducible Hspa1b (hsp70.1) gene we noticed that some liposome-based DNA carriers, which are used for transfection, induce its promoter activity. This observation concerned commercial liposome formulations (LA), Lipofectin and Lipofectamine 2000. This work was aimed to understand better the mechanism of this phenomenon and its potential biological and practical consequences. Results We found that a reporter gene driven by Hspa1b promoter is activated both in the case of transient transfections and in the stably transfected cells treated with LA. Using several deletion clones containing different fragments of Hspa1b promoter, we found that the regulatory elements responsible for most efficient LA-driven inducibility were located between nucleotides -269 and +85, relative to the transcription start site. Further studies showed that the induction mechanism was independent of the classical HSE-HSF interaction that is responsible for gene activation during heat stress. Using DNA microarrays we also detected significant activation of the endogenous Hspa1b gene in cells treated with Lipofectamine 2000. Several other stress genes were also induced, along with numerous genes involved in cellular metabolism, cell cycle control and pro-apoptotic pathways. Conclusions Our observations suggest that i) some cationic liposomes may not be suitable for functional studies on hsp promoters, ii) lipofection may cause unintended changes in global gene expression in the transfected cells. PMID:21663599

  2. Liposome-based DNA carriers may induce cellular stress response and change gene expression pattern in transfected cells

    Directory of Open Access Journals (Sweden)

    Lisowska Katarzyna Marta

    2011-06-01

    Full Text Available Abstract Background During functional studies on the rat stress-inducible Hspa1b (hsp70.1 gene we noticed that some liposome-based DNA carriers, which are used for transfection, induce its promoter activity. This observation concerned commercial liposome formulations (LA, Lipofectin and Lipofectamine 2000. This work was aimed to understand better the mechanism of this phenomenon and its potential biological and practical consequences. Results We found that a reporter gene driven by Hspa1b promoter is activated both in the case of transient transfections and in the stably transfected cells treated with LA. Using several deletion clones containing different fragments of Hspa1b promoter, we found that the regulatory elements responsible for most efficient LA-driven inducibility were located between nucleotides -269 and +85, relative to the transcription start site. Further studies showed that the induction mechanism was independent of the classical HSE-HSF interaction that is responsible for gene activation during heat stress. Using DNA microarrays we also detected significant activation of the endogenous Hspa1b gene in cells treated with Lipofectamine 2000. Several other stress genes were also induced, along with numerous genes involved in cellular metabolism, cell cycle control and pro-apoptotic pathways. Conclusions Our observations suggest that i some cationic liposomes may not be suitable for functional studies on hsp promoters, ii lipofection may cause unintended changes in global gene expression in the transfected cells.

  3. Expression Profiling of Tyrosine Kinase Genes

    National Research Council Canada - National Science Library

    Weier, Heinz

    2000-01-01

    ... of these genes parallels the progression of tumors to a more malignant phenotype. We developed a DNA micro-array based screening system to monitor the level of expression of tyrosine kinase (tk...

  4. Comparative Analysis of RNAi-Based Methods to Down-Regulate Expression of Two Genes Expressed at Different Levels in Myzus persicae

    Directory of Open Access Journals (Sweden)

    Michaël Mulot

    2016-11-01

    Full Text Available With the increasing availability of aphid genomic data, it is necessary to develop robust functional validation methods to evaluate the role of specific aphid genes. This work represents the first study in which five different techniques, all based on RNA interference and on oral acquisition of double-stranded RNA (dsRNA, were developed to silence two genes, ALY and Eph, potentially involved in polerovirus transmission by aphids. Efficient silencing of only Eph transcripts, which are less abundant than those of ALY, could be achieved by feeding aphids on transgenic Arabidopsis thaliana expressing an RNA hairpin targeting Eph, on Nicotiana benthamiana infected with a Tobacco rattle virus (TRV-Eph recombinant virus, or on in vitro-synthesized Eph-targeting dsRNA. These experiments showed that the silencing efficiency may differ greatly between genes and that aphid gut cells seem to be preferentially affected by the silencing mechanism after oral acquisition of dsRNA. In addition, the use of plants infected with recombinant TRV proved to be a promising technique to silence aphid genes as it does not require plant transformation. This work highlights the need to pursue development of innovative strategies to reproducibly achieve reduction of expression of aphid genes.

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

    Energy Technology Data Exchange (ETDEWEB)

    Tholouli, Eleni [Department of Haematology, Manchester Royal Infirmary, Oxford Road, Manchester, M13 9WL (United Kingdom); MacDermott, Sarah [The Medical School, The University of Manchester, Oxford Road, M13 9PT Manchester (United Kingdom); Hoyland, Judith [School of Biomedicine, Faculty of Medical and Human Sciences, The University of Manchester, Oxford Road, M13 9PT Manchester (United Kingdom); Yin, John Liu [Department of Haematology, Manchester Royal Infirmary, Oxford Road, Manchester, M13 9WL (United Kingdom); Byers, Richard, E-mail: richard.byers@cmft.nhs.uk [School of Cancer and Enabling Sciences, Faculty of Medical and Human Sciences, The University of Manchester, Stopford Building, Oxford Road, M13 9PT Manchester (United Kingdom)

    2012-08-24

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

  6. Tumor Classification Using High-Order Gene Expression Profiles Based on Multilinear ICA

    Directory of Open Access Journals (Sweden)

    Ming-gang Du

    2009-01-01

    Full Text Available Motivation. Independent Components Analysis (ICA maximizes the statistical independence of the representational components of a training gene expression profiles (GEP ensemble, but it cannot distinguish relations between the different factors, or different modes, and it is not available to high-order GEP Data Mining. In order to generalize ICA, we introduce Multilinear-ICA and apply it to tumor classification using high order GEP. Firstly, we introduce the basis conceptions and operations of tensor and recommend Support Vector Machine (SVM classifier and Multilinear-ICA. Secondly, the higher score genes of original high order GEP are selected by using t-statistics and tabulate tensors. Thirdly, the tensors are performed by Multilinear-ICA. Finally, the SVM is used to classify the tumor subtypes. Results. To show the validity of the proposed method, we apply it to tumor classification using high order GEP. Though we only use three datasets, the experimental results show that the method is effective and feasible. Through this survey, we hope to gain some insight into the problem of high order GEP tumor classification, in aid of further developing more effective tumor classification algorithms.

  7. Microarray-based analysis of the differential expression of melanin synthesis genes in dark and light-muzzle Korean cattle.

    Science.gov (United States)

    Kim, Sang Hwan; Hwang, Sue Yun; Yoon, Jong Taek

    2014-01-01

    The coat color of mammals is determined by the melanogenesis pathway, which is responsible for maintaining the balance between black-brown eumelanin and yellow-reddish pheomelanin. It is also believed that the color of the bovine muzzle is regulated in a similar manner; however, the molecular mechanism underlying pigment deposition in the dark-muzzle has yet to be elucidated. The aim of the present study was to identify melanogenesis-associated genes that are differentially expressed in the dark vs. light muzzle of native Korean cows. Using microarray clustering and real-time polymerase chain reaction techniques, we observed that the expression of genes involved in the mitogen-activated protein kinase (MAPK) and Wnt signaling pathways is distinctively regulated in the dark and light muzzle tissues. Differential expression of tyrosinase was also noticed, although the difference was not as distinct as those of MAPK and Wnt. We hypothesize that emphasis on the MAPK pathway in the dark-muzzle induces eumelanin synthesis through the activation of cAMP response element-binding protein and tyrosinase, while activation of Wnt signaling counteracts this process and raises the amount of pheomelanin in the light-muzzle. We also found 2 novel genes (GenBank No. NM-001076026 and XM-588439) with increase expression in the black nose, which may provide additional information about the mechanism of nose pigmentation. Regarding the increasing interest in the genetic diversity of cattle stocks, genes we identified for differential expression in the dark vs. light muzzle may serve as novel markers for genetic diversity among cows based on the muzzle color phenotype.

  8. Microarray-based analysis of the differential expression of melanin synthesis genes in dark and light-muzzle Korean cattle.

    Directory of Open Access Journals (Sweden)

    Sang Hwan Kim

    Full Text Available The coat color of mammals is determined by the melanogenesis pathway, which is responsible for maintaining the balance between black-brown eumelanin and yellow-reddish pheomelanin. It is also believed that the color of the bovine muzzle is regulated in a similar manner; however, the molecular mechanism underlying pigment deposition in the dark-muzzle has yet to be elucidated. The aim of the present study was to identify melanogenesis-associated genes that are differentially expressed in the dark vs. light muzzle of native Korean cows. Using microarray clustering and real-time polymerase chain reaction techniques, we observed that the expression of genes involved in the mitogen-activated protein kinase (MAPK and Wnt signaling pathways is distinctively regulated in the dark and light muzzle tissues. Differential expression of tyrosinase was also noticed, although the difference was not as distinct as those of MAPK and Wnt. We hypothesize that emphasis on the MAPK pathway in the dark-muzzle induces eumelanin synthesis through the activation of cAMP response element-binding protein and tyrosinase, while activation of Wnt signaling counteracts this process and raises the amount of pheomelanin in the light-muzzle. We also found 2 novel genes (GenBank No. NM-001076026 and XM-588439 with increase expression in the black nose, which may provide additional information about the mechanism of nose pigmentation. Regarding the increasing interest in the genetic diversity of cattle stocks, genes we identified for differential expression in the dark vs. light muzzle may serve as novel markers for genetic diversity among cows based on the muzzle color phenotype.

  9. Temperature based daily incoming solar radiation modeling based on gene expression programming, neuro-fuzzy and neural network computing techniques.

    Science.gov (United States)

    Landeras, G.; López, J. J.; Kisi, O.; Shiri, J.

    2012-04-01

    The correct observation/estimation of surface incoming solar radiation (RS) is very important for many agricultural, meteorological and hydrological related applications. While most weather stations are provided with sensors for air temperature detection, the presence of sensors necessary for the detection of solar radiation is not so habitual and the data quality provided by them is sometimes poor. In these cases it is necessary to estimate this variable. Temperature based modeling procedures are reported in this study for estimating daily incoming solar radiation by using Gene Expression Programming (GEP) for the first time, and other artificial intelligence models such as Artificial Neural Networks (ANNs), and Adaptive Neuro-Fuzzy Inference System (ANFIS). Traditional temperature based solar radiation equations were also included in this study and compared with artificial intelligence based approaches. Root mean square error (RMSE), mean absolute error (MAE) RMSE-based skill score (SSRMSE), MAE-based skill score (SSMAE) and r2 criterion of Nash and Sutcliffe criteria were used to assess the models' performances. An ANN (a four-input multilayer perceptron with ten neurons in the hidden layer) presented the best performance among the studied models (2.93 MJ m-2 d-1 of RMSE). A four-input ANFIS model revealed as an interesting alternative to ANNs (3.14 MJ m-2 d-1 of RMSE). Very limited number of studies has been done on estimation of solar radiation based on ANFIS, and the present one demonstrated the ability of ANFIS to model solar radiation based on temperatures and extraterrestrial radiation. By the way this study demonstrated, for the first time, the ability of GEP models to model solar radiation based on daily atmospheric variables. Despite the accuracy of GEP models was slightly lower than the ANFIS and ANN models the genetic programming models (i.e., GEP) are superior to other artificial intelligence models in giving a simple explicit equation for the

  10. Lung cancer gene expression database analysis incorporating prior knowledge with support vector machine-based classification method

    Directory of Open Access Journals (Sweden)

    Huang Desheng

    2009-07-01

    Full Text Available Abstract Background A reliable and precise classification is essential for successful diagnosis and treatment of cancer. Gene expression microarrays have provided the high-throughput platform to discover genomic biomarkers for cancer diagnosis and prognosis. Rational use of the available bioinformation can not only effectively remove or suppress noise in gene chips, but also avoid one-sided results of separate experiment. However, only some studies have been aware of the importance of prior information in cancer classification. Methods Together with the application of support vector machine as the discriminant approach, we proposed one modified method that incorporated prior knowledge into cancer classification based on gene expression data to improve accuracy. A public well-known dataset, Malignant pleural mesothelioma and lung adenocarcinoma gene expression database, was used in this study. Prior knowledge is viewed here as a means of directing the classifier using known lung adenocarcinoma related genes. The procedures were performed by software R 2.80. Results The modified method performed better after incorporating prior knowledge. Accuracy of the modified method improved from 98.86% to 100% in training set and from 98.51% to 99.06% in test set. The standard deviations of the modified method decreased from 0.26% to 0 in training set and from 3.04% to 2.10% in test set. Conclusion The method that incorporates prior knowledge into discriminant analysis could effectively improve the capacity and reduce the impact of noise. This idea may have good future not only in practice but also in methodology.

  11. The functional landscape of mouse gene expression

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    Zhang Wen

    2004-12-01

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

  12. Mining gene expression data of multiple sclerosis.

    Directory of Open Access Journals (Sweden)

    Pi Guo

    Full Text Available Microarray produces a large amount of gene expression data, containing various biological implications. The challenge is to detect a panel of discriminative genes associated with disease. This study proposed a robust classification model for gene selection using gene expression data, and performed an analysis to identify disease-related genes using multiple sclerosis as an example.Gene expression profiles based on the transcriptome of peripheral blood mononuclear cells from a total of 44 samples from 26 multiple sclerosis patients and 18 individuals with other neurological diseases (control were analyzed. Feature selection algorithms including Support Vector Machine based on Recursive Feature Elimination, Receiver Operating Characteristic Curve, and Boruta algorithms were jointly performed to select candidate genes associating with multiple sclerosis. Multiple classification models categorized samples into two different groups based on the identified genes. Models' performance was evaluated using cross-validation methods, and an optimal classifier for gene selection was determined.An overlapping feature set was identified consisting of 8 genes that were differentially expressed between the two phenotype groups. The genes were significantly associated with the pathways of apoptosis and cytokine-cytokine receptor interaction. TNFSF10 was significantly associated with multiple sclerosis. A Support Vector Machine model was established based on the featured genes and gave a practical accuracy of ∼86%. This binary classification model also outperformed the other models in terms of Sensitivity, Specificity and F1 score.The combined analytical framework integrating feature ranking algorithms and Support Vector Machine model could be used for selecting genes for other diseases.

  13. A comparative gene expression database for invertebrates

    Directory of Open Access Journals (Sweden)

    Ormestad Mattias

    2011-08-01

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

  14. Flavin mononucleotide (FMN)-based fluorescent protein (FbFP) as reporter for gene expression in the anaerobe Bacteroides fragilis.

    Science.gov (United States)

    Lobo, Leandro A; Smith, Charles J; Rocha, Edson R

    2011-04-01

    In this study, we show the expression of flavin mononucleotide-based fluorescent protein (FbFP) BS2 as a marker for gene expression in the opportunistic human anaerobic pathogen Bacteroides fragilis. Bacteroides fragilis 638R strain carrying osu∷bs2 constructs showed inducible fluorescence following addition of maltose anaerobically compared with nonfluorescent cells under glucose-repressed conditions. Bacteria carrying ahpC∷bs2 or dps∷bs2 constructs were fluorescent following induction by oxygen compared with nonfluorescent cells from the anaerobic control cultures. In addition, when these transcriptional fusion constructs were mobilized into B. fragilis IB263, a constitutive peroxide response strain, fluorescent BS2, was detected in both anaerobic and aerobic cultures, confirming the unique properties of the FbFP BS2 to yield fluorescent signal in B. fragilis in the presence and in the absence of oxygen. Moreover, intracellular expression of BS2 was also detected when cell culture monolayers of J774.1 macrophages were incubated with B. fragilis ahpC∷bs2 or dps∷bs2 strains within an anaerobic chamber. This suggests that ahpC and dps are induced following internalization by macrophages. Thus, we show that BS2 is a suitable tool for the detection of gene expression in obligate anaerobic bacteria in in vivo studies. © 2011 Federation of European Microbiological Societies. Published by Blackwell Publishing Ltd. All rights reserved.

  15. A Seasonal Time-Series Model Based on Gene Expression Programming for Predicting Financial Distress

    Directory of Open Access Journals (Sweden)

    Ching-Hsue Cheng

    2018-01-01

    Full Text Available The issue of financial distress prediction plays an important and challenging research topic in the financial field. Currently, there have been many methods for predicting firm bankruptcy and financial crisis, including the artificial intelligence and the traditional statistical methods, and the past studies have shown that the prediction result of the artificial intelligence method is better than the traditional statistical method. Financial statements are quarterly reports; hence, the financial crisis of companies is seasonal time-series data, and the attribute data affecting the financial distress of companies is nonlinear and nonstationary time-series data with fluctuations. Therefore, this study employed the nonlinear attribute selection method to build a nonlinear financial distress prediction model: that is, this paper proposed a novel seasonal time-series gene expression programming model for predicting the financial distress of companies. The proposed model has several advantages including the following: (i the proposed model is different from the previous models lacking the concept of time series; (ii the proposed integrated attribute selection method can find the core attributes and reduce high dimensional data; and (iii the proposed model can generate the rules and mathematical formulas of financial distress for providing references to the investors and decision makers. The result shows that the proposed method is better than the listing classifiers under three criteria; hence, the proposed model has competitive advantages in predicting the financial distress of companies.

  16. A Seasonal Time-Series Model Based on Gene Expression Programming for Predicting Financial Distress

    Science.gov (United States)

    2018-01-01

    The issue of financial distress prediction plays an important and challenging research topic in the financial field. Currently, there have been many methods for predicting firm bankruptcy and financial crisis, including the artificial intelligence and the traditional statistical methods, and the past studies have shown that the prediction result of the artificial intelligence method is better than the traditional statistical method. Financial statements are quarterly reports; hence, the financial crisis of companies is seasonal time-series data, and the attribute data affecting the financial distress of companies is nonlinear and nonstationary time-series data with fluctuations. Therefore, this study employed the nonlinear attribute selection method to build a nonlinear financial distress prediction model: that is, this paper proposed a novel seasonal time-series gene expression programming model for predicting the financial distress of companies. The proposed model has several advantages including the following: (i) the proposed model is different from the previous models lacking the concept of time series; (ii) the proposed integrated attribute selection method can find the core attributes and reduce high dimensional data; and (iii) the proposed model can generate the rules and mathematical formulas of financial distress for providing references to the investors and decision makers. The result shows that the proposed method is better than the listing classifiers under three criteria; hence, the proposed model has competitive advantages in predicting the financial distress of companies. PMID:29765399

  17. A Seasonal Time-Series Model Based on Gene Expression Programming for Predicting Financial Distress.

    Science.gov (United States)

    Cheng, Ching-Hsue; Chan, Chia-Pang; Yang, Jun-He

    2018-01-01

    The issue of financial distress prediction plays an important and challenging research topic in the financial field. Currently, there have been many methods for predicting firm bankruptcy and financial crisis, including the artificial intelligence and the traditional statistical methods, and the past studies have shown that the prediction result of the artificial intelligence method is better than the traditional statistical method. Financial statements are quarterly reports; hence, the financial crisis of companies is seasonal time-series data, and the attribute data affecting the financial distress of companies is nonlinear and nonstationary time-series data with fluctuations. Therefore, this study employed the nonlinear attribute selection method to build a nonlinear financial distress prediction model: that is, this paper proposed a novel seasonal time-series gene expression programming model for predicting the financial distress of companies. The proposed model has several advantages including the following: (i) the proposed model is different from the previous models lacking the concept of time series; (ii) the proposed integrated attribute selection method can find the core attributes and reduce high dimensional data; and (iii) the proposed model can generate the rules and mathematical formulas of financial distress for providing references to the investors and decision makers. The result shows that the proposed method is better than the listing classifiers under three criteria; hence, the proposed model has competitive advantages in predicting the financial distress of companies.

  18. Mining and gene ontology based annotation of SSR markers from expressed sequence tags of Humulus lupulus

    Science.gov (United States)

    Singh, Swati; Gupta, Sanchita; Mani, Ashutosh; Chaturvedi, Anoop

    2012-01-01

    Humulus lupulus is commonly known as hops, a member of the family moraceae. Currently many projects are underway leading to the accumulation of voluminous genomic and expressed sequence tag sequences in public databases. The genetically characterized domains in these databases are limited due to non-availability of reliable molecular markers. The large data of EST sequences are available in hops. The simple sequence repeat markers extracted from EST data are used as molecular markers for genetic characterization, in the present study. 25,495 EST sequences were examined and assembled to get full-length sequences. Maximum frequency distribution was shown by mononucleotide SSR motifs i.e. 60.44% in contig and 62.16% in singleton where as minimum frequency are observed for hexanucleotide SSR in contig (0.09%) and pentanucleotide SSR in singletons (0.12%). Maximum trinucleotide motifs code for Glutamic acid (GAA) while AT/TA were the most frequent repeat of dinucleotide SSRs. Flanking primer pairs were designed in-silico for the SSR containing sequences. Functional categorization of SSRs containing sequences was done through gene ontology terms like biological process, cellular component and molecular function. PMID:22368382

  19. Improving sensitivity of linear regression-based cell type-specific differential expression deconvolution with per-gene vs. global significance threshold.

    Science.gov (United States)

    Glass, Edmund R; Dozmorov, Mikhail G

    2016-10-06

    The goal of many human disease-oriented studies is to detect molecular mechanisms different between healthy controls and patients. Yet, commonly used gene expression measurements from blood samples suffer from variability of cell composition. This variability hinders the detection of differentially expressed genes and is often ignored. Combined with cell counts, heterogeneous gene expression may provide deeper insights into the gene expression differences on the cell type-specific level. Published computational methods use linear regression to estimate cell type-specific differential expression, and a global cutoff to judge significance, such as False Discovery Rate (FDR). Yet, they do not consider many artifacts hidden in high-dimensional gene expression data that may negatively affect linear regression. In this paper we quantify the parameter space affecting the performance of linear regression (sensitivity of cell type-specific differential expression detection) on a per-gene basis. We evaluated the effect of sample sizes, cell type-specific proportion variability, and mean squared error on sensitivity of cell type-specific differential expression detection using linear regression. Each parameter affected variability of cell type-specific expression estimates and, subsequently, the sensitivity of differential expression detection. We provide the R package, LRCDE, which performs linear regression-based cell type-specific differential expression (deconvolution) detection on a gene-by-gene basis. Accounting for variability around cell type-specific gene expression estimates, it computes per-gene t-statistics of differential detection, p-values, t-statistic-based sensitivity, group-specific mean squared error, and several gene-specific diagnostic metrics. The sensitivity of linear regression-based cell type-specific differential expression detection differed for each gene as a function of mean squared error, per group sample sizes, and variability of the proportions

  20. 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.

  1. A novel approach to select differential pathways associated with hypertrophic cardiomyopathy based on gene co‑expression analysis.

    Science.gov (United States)

    Chen, Xiao-Min; Feng, Ming-Jun; Shen, Cai-Jie; He, Bin; Du, Xian-Feng; Yu, Yi-Bo; Liu, Jing; Chu, Hui-Min

    2017-07-01

    The present study was designed to develop a novel method for identifying significant pathways associated with human hypertrophic cardiomyopathy (HCM), based on gene co‑expression analysis. The microarray dataset associated with HCM (E‑GEOD‑36961) was obtained from the European Molecular Biology Laboratory‑European Bioinformatics Institute database. Informative pathways were selected based on the Reactome pathway database and screening treatments. An empirical Bayes method was utilized to construct co‑expression networks for informative pathways, and a weight value was assigned to each pathway. Differential pathways were extracted based on weight threshold, which was calculated using a random model. In order to assess whether the co‑expression method was feasible, it was compared with traditional pathway enrichment analysis of differentially expressed genes, which were identified using the significance analysis of microarrays package. A total of 1,074 informative pathways were screened out for subsequent investigations and their weight values were also obtained. According to the threshold of weight value of 0.01057, 447 differential pathways, including folding of actin by chaperonin containing T‑complex protein 1 (CCT)/T‑complex protein 1 ring complex (TRiC), purine ribonucleoside monophosphate biosynthesis and ubiquinol biosynthesis, were obtained. Compared with traditional pathway enrichment analysis, the number of pathways obtained from the co‑expression approach was increased. The results of the present study demonstrated that this method may be useful to predict marker pathways for HCM. The pathways of folding of actin by CCT/TRiC and purine ribonucleoside monophosphate biosynthesis may provide evidence of the underlying molecular mechanisms of HCM, and offer novel therapeutic directions for HCM.

  2. Vector for IS element entrapment and functional characterization based on turning on expression of distal promoterless genes.

    Science.gov (United States)

    Szeverényi, I; Hodel, A; Arber, W; Olasz, F

    1996-09-26

    We constructed and characterized a novel trap vector for rapid isolation of insertion sequences. The strategy used for the isolation of IS elements is based on the ability of many IS elements to turn on the expression of otherwise silent genes distal to some sites of insertion. The simple transposition of an IS element can sometimes cause the constitutive expression of promoterless antibiotic resistance genes resulting in selectable phenotypes. The trap vector pAW1326 is based on a pBR322 replicon, it carries ampicillin and streptomycin resistance genes, and also silenced genes that confer chloramphenicol and kanamycin resistance once activated. The trap vector pAW1326 proved to be efficient and 85 percent of all isolated mutations were insertions. The majority of IS elements resident in the studied Escherichia coli strains tested became trapped, namely IS2, IS3, IS5, IS150, IS186 and Tn1000. We also encountered an insertion sequence, called IS10L/R-2, which is a hybrid of the two IS variants IS10L and IS10R. IS10L/R-2 is absent from most E. coli strains, but it is detectable in some strains such as JM109 which had been submitted to Tn10 mutagenesis. The distribution of the insertion sequences within the trap region was not random. Rather, the integration of chromosomal mobile genetic elements into the offered target sequence occurred in element-specific clusters. This is explained both by the target specificity and by the specific requirements for the activation of gene transcription by the DNA rearrangement. The employed trap vector pAW1326 proved to be useful for the isolation of mobile genetic elements, for a demonstration of their transposition activity as well as for the further characterization of some of the functional parameters of transposition.

  3. Gene expression-based classifiers identify Staphylococcus aureus infection in mice and humans.

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    Sun Hee Ahn

    Full Text Available Staphylococcus aureus causes a spectrum of human infection. Diagnostic delays and uncertainty lead to treatment delays and inappropriate antibiotic use. A growing literature suggests the host's inflammatory response to the pathogen represents a potential tool to improve upon current diagnostics. The hypothesis of this study is that the host responds differently to S. aureus than to E. coli infection in a quantifiable way, providing a new diagnostic avenue. This study uses Bayesian sparse factor modeling and penalized binary regression to define peripheral blood gene-expression classifiers of murine and human S. aureus infection. The murine-derived classifier distinguished S. aureus infection from healthy controls and Escherichia coli-infected mice across a range of conditions (mouse and bacterial strain, time post infection and was validated in outbred mice (AUC>0.97. A S. aureus classifier derived from a cohort of 94 human subjects distinguished S. aureus blood stream infection (BSI from healthy subjects (AUC 0.99 and E. coli BSI (AUC 0.84. Murine and human responses to S. aureus infection share common biological pathways, allowing the murine model to classify S. aureus BSI in humans (AUC 0.84. Both murine and human S. aureus classifiers were validated in an independent human cohort (AUC 0.95 and 0.92, respectively. The approach described here lends insight into the conserved and disparate pathways utilized by mice and humans in response to these infections. Furthermore, this study advances our understanding of S. aureus infection; the host response to it; and identifies new diagnostic and therapeutic avenues.

  4. Predicting Recurrence and Progression of Noninvasive Papillary Bladder Cancer at Initial Presentation Based on Quantitative Gene Expression Profiles

    DEFF Research Database (Denmark)

    Birkhahn, M.; Mitra, A.P.; Williams, Johan

    2010-01-01

    Background: Currently, tumor grade is the best predictor of outcome at first presentation of noninvasive papillary (Ta) bladder cancer. However, reliable predictors of Ta tumor recurrence and progression for individual patients, which could optimize treatment and follow-up schedules based...... on specific tumor biology, are yet to be identified. Objective: To identify genes predictive for recurrence and progression in Ta bladder cancer at first presentation using a quantitative, pathway-specific approach. Design, setting, and participants: Retrospective study of patients with Ta G2/3 bladder tumors...... at initial presentation with three distinct clinical outcomes: absence of recurrence (n = 16), recurrence without progression (n = 16), and progression to carcinoma in situ or invasive disease (n = 16). Measurements: Expressions of 24 genes that feature in relevant pathways that are deregulated in bladder...

  5. Predicting Recurrence and Progression of Noninvasive Papillary Bladder Cancer at Initial Presentation Based on Quantitative Gene Expression Profiles

    DEFF Research Database (Denmark)

    Birkhahn, M.; Mitra, A.P.; Williams, Johan

    2010-01-01

    % specificity. Since this is a small retrospective study using medium-throughput profiling, larger confirmatory studies are needed. Conclusions: Gene expression profiling across relevant cancer pathways appears to be a promising approach for Ta bladder tumor outcome prediction at initial diagnosis......Background: Currently, tumor grade is the best predictor of outcome at first presentation of noninvasive papillary (Ta) bladder cancer. However, reliable predictors of Ta tumor recurrence and progression for individual patients, which could optimize treatment and follow-up schedules based...... on specific tumor biology, are yet to be identified. Objective: To identify genes predictive for recurrence and progression in Ta bladder cancer at first presentation using a quantitative, pathway-specific approach. Design, setting, and participants: Retrospective study of patients with Ta G2/3 bladder tumors...

  6. Inferring gene networks from discrete expression data

    KAUST Repository

    Zhang, L.

    2013-07-18

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

  7. Network-based differential gene expression analysis suggests cell cycle related genes regulated by E2F1 underlie the molecular difference between smoker and non-smoker lung adenocarcinoma

    Science.gov (United States)

    2013-01-01

    Background Differential gene expression (DGE) analysis is commonly used to reveal the deregulated molecular mechanisms of complex diseases. However, traditional DGE analysis (e.g., the t test or the rank sum test) tests each gene independently without considering interactions between them. Top-ranked differentially regulated genes prioritized by the analysis may not directly relate to the coherent molecular changes underlying complex diseases. Joint analyses of co-expression and DGE have been applied to reveal the deregulated molecular modules underlying complex diseases. Most of these methods consist of separate steps: first to identify gene-gene relationships under the studied phenotype then to integrate them with gene expression changes for prioritizing signature genes, or vice versa. It is warrant a method that can simultaneously consider gene-gene co-expression strength and corresponding expression level changes so that both types of information can be leveraged optimally. Results In this paper, we develop a gene module based method for differential gene expression analysis, named network-based differential gene expression (nDGE) analysis, a one-step integrative process for prioritizing deregulated genes and grouping them into gene modules. We demonstrate that nDGE outperforms existing methods in prioritizing deregulated genes and discovering deregulated gene modules using simulated data sets. When tested on a series of smoker and non-smoker lung adenocarcinoma data sets, we show that top differentially regulated genes identified by the rank sum test in different sets are not consistent while top ranked genes defined by nDGE in different data sets significantly overlap. nDGE results suggest that a differentially regulated gene module, which is enriched for cell cycle related genes and E2F1 targeted genes, plays a role in the molecular differences between smoker and non-smoker lung adenocarcinoma. Conclusions In this paper, we develop nDGE to prioritize

  8. Widespread ectopic expression of olfactory receptor genes

    Directory of Open Access Journals (Sweden)

    Yanai Itai

    2006-05-01

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

  9. Transgenic Arabidopsis Gene Expression System

    Science.gov (United States)

    Ferl, Robert; Paul, Anna-Lisa

    2009-01-01

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

  10. Human papillomavirus gene expression

    International Nuclear Information System (INIS)

    Chow, L.T.; Hirochika, H.; Nasseri, M.; Stoler, M.H.; Wolinsky, S.M.; Chin, M.T.; Hirochika, R.; Arvan, D.S.; Broker, T.R.

    1987-01-01

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

  11. Genome-wide targeted prediction of ABA responsive genes in rice based on over-represented cis-motif in co-expressed genes.

    Science.gov (United States)

    Lenka, Sangram K; Lohia, Bikash; Kumar, Abhay; Chinnusamy, Viswanathan; Bansal, Kailash C

    2009-02-01

    Abscisic acid (ABA), the popular plant stress hormone, plays a key role in regulation of sub-set of stress responsive genes. These genes respond to ABA through specific transcription factors which bind to cis-regulatory elements present in their promoters. We discovered the ABA Responsive Element (ABRE) core (ACGT) containing CGMCACGTGB motif as over-represented motif among the promoters of ABA responsive co-expressed genes in rice. Targeted gene prediction strategy using this motif led to the identification of 402 protein coding genes potentially regulated by ABA-dependent molecular genetic network. RT-PCR analysis of arbitrarily chosen 45 genes from the predicted 402 genes confirmed 80% accuracy of our prediction. Plant Gene Ontology (GO) analysis of ABA responsive genes showed enrichment of signal transduction and stress related genes among diverse functional categories.

  12. Prioritization of candidate genes for cattle reproductive traits, based on protein-protein interactions, gene expression, and text-mining

    DEFF Research Database (Denmark)

    Hulsegge, Ina; Woelders, Henri; Smits, Mari

    2013-01-01

    Reproduction is of significant economic importance in dairy cattle. Improved understanding of mechanisms that control estrous behavior and other reproduction traits could help in developing strategies to improve and/or monitor these traits. The objective of this study was to predict and rank gene...

  13. Inhibitory effect of live-attenuated Listeria monocytogenes-based vaccines expressing MIA gene on malignant melanoma.

    Science.gov (United States)

    Qian, Yue; Zhang, Na; Jiang, Ping; Chen, Siyuan; Chu, Shujuan; Hamze, Firas; Wu, Yan; Luo, Qin; Feng, Aiping

    2012-08-01

    Listeria monocytogenes (LM), a Gram-positive facultative intracellular bacterium, can be used as an effective exogenous antigen expression vector in tumor-target therapy. But for successful clinical application, it is necessary to construct attenuated LM stain that is safe yet retains the potency of LM based on the full virulent pathogen. In this study, attenuated LM and recombinants of LM expressing melanoma inhibitory activity (MIA) were constructed successfully. The median lethal dose (LD(50)) and invasion efficiency of attenuated LM strains were detected. The recombinants were utilized for immunotherapy of animal model of B16F10 melanoma. The level of MIA mRNA expression in tumor tissue was detected by using real-time polymerase chain reaction (PCR) with specific sequence, meanwhile the anti-tumor immune response was assayed by flow cytometric analysis and enzyme-linked immunosorbent spot (ELISPOT) assay. The results showed the toxicity and invasiveness of attenuated LM were decreased as compared with LM, and attenuated LM expressing MIA, especially the double-genes attenuated LM recombinant, could significantly induce anti-tumor immune response and inhibit tumor growth. This study implicates attenuated LM may be a safer and more effective vector for immunotherapy of melanoma.

  14. CRISPR/Cas9-based genome editing for simultaneous interference with gene expression and protein stability

    DEFF Research Database (Denmark)

    Martinez, Virginia; Lauritsen, Ida; Hobel, Tonja

    2017-01-01

    Interference with genes is the foundation of reverse genetics and is key to manipulation of living cells for biomedical and biotechnological applications. However, classical genetic knockout and transcriptional knockdown technologies have different drawbacks and offer no control over existing pro...

  15. Bayesian assignment of gene ontology terms to gene expression experiments.

    Science.gov (United States)

    Sykacek, P

    2012-09-15

    Gene expression assays allow for genome scale analyses of molecular biological mechanisms. State-of-the-art data analysis provides lists of involved genes, either by calculating significance levels of mRNA abundance or by Bayesian assessments of gene activity. A common problem of such approaches is the difficulty of interpreting the biological implication of the resulting gene lists. This lead to an increased interest in methods for inferring high-level biological information. A common approach for representing high level information is by inferring gene ontology (GO) terms which may be attributed to the expression data experiment. This article proposes a probabilistic model for GO term inference. Modelling assumes that gene annotations to GO terms are available and gene involvement in an experiment is represented by a posterior probabilities over gene-specific indicator variables. Such probability measures result from many Bayesian approaches for expression data analysis. The proposed model combines these indicator probabilities in a probabilistic fashion and provides a probabilistic GO term assignment as a result. Experiments on synthetic and microarray data suggest that advantages of the proposed probabilistic GO term inference over statistical test-based approaches are in particular evident for sparsely annotated GO terms and in situations of large uncertainty about gene activity. Provided that appropriate annotations exist, the proposed approach is easily applied to inferring other high level assignments like pathways. Source code under GPL license is available from the author. peter.sykacek@boku.ac.at.

  16. Bayesian assignment of gene ontology terms to gene expression experiments

    Science.gov (United States)

    Sykacek, P.

    2012-01-01

    Motivation: Gene expression assays allow for genome scale analyses of molecular biological mechanisms. State-of-the-art data analysis provides lists of involved genes, either by calculating significance levels of mRNA abundance or by Bayesian assessments of gene activity. A common problem of such approaches is the difficulty of interpreting the biological implication of the resulting gene lists. This lead to an increased interest in methods for inferring high-level biological information. A common approach for representing high level information is by inferring gene ontology (GO) terms which may be attributed to the expression data experiment. Results: This article proposes a probabilistic model for GO term inference. Modelling assumes that gene annotations to GO terms are available and gene involvement in an experiment is represented by a posterior probabilities over gene-specific indicator variables. Such probability measures result from many Bayesian approaches for expression data analysis. The proposed model combines these indicator probabilities in a probabilistic fashion and provides a probabilistic GO term assignment as a result. Experiments on synthetic and microarray data suggest that advantages of the proposed probabilistic GO term inference over statistical test-based approaches are in particular evident for sparsely annotated GO terms and in situations of large uncertainty about gene activity. Provided that appropriate annotations exist, the proposed approach is easily applied to inferring other high level assignments like pathways. Availability: Source code under GPL license is available from the author. Contact: peter.sykacek@boku.ac.at PMID:22962488

  17. CDNA Microarray Based Comparative Gene Expression Analysis of Primary Breast Tumors Versus In Vitro Transformed Neoplastic Breast Epithelium

    National Research Council Canada - National Science Library

    Szallasi, Zoltan

    2001-01-01

    .... The first group of clones is being sorted by their ability to form tumors. We are currently performing cDNA microarray analysis quantifying the expression level of about 15,000 genes in these cell lines...

  18. Renal Gene Expression Database (RGED): a relational database of gene expression profiles in kidney disease.

    Science.gov (United States)

    Zhang, Qingzhou; Yang, Bo; Chen, Xujiao; Xu, Jing; Mei, Changlin; Mao, Zhiguo

    2014-01-01

    We present a bioinformatics database named Renal Gene Expression Database (RGED), which contains comprehensive gene expression data sets from renal disease research. The web-based interface of RGED allows users to query the gene expression profiles in various kidney-related samples, including renal cell lines, human kidney tissues and murine model kidneys. Researchers can explore certain gene profiles, the relationships between genes of interests and identify biomarkers or even drug targets in kidney diseases. The aim of this work is to provide a user-friendly utility for the renal disease research community to query expression profiles of genes of their own interest without the requirement of advanced computational skills. Website is implemented in PHP, R, MySQL and Nginx and freely available from http://rged.wall-eva.net. http://rged.wall-eva.net. © The Author(s) 2014. Published by Oxford University Press.

  19. Renal Gene Expression Database (RGED): a relational database of gene expression profiles in kidney disease

    Science.gov (United States)

    Zhang, Qingzhou; Yang, Bo; Chen, Xujiao; Xu, Jing; Mei, Changlin; Mao, Zhiguo

    2014-01-01

    We present a bioinformatics database named Renal Gene Expression Database (RGED), which contains comprehensive gene expression data sets from renal disease research. The web-based interface of RGED allows users to query the gene expression profiles in various kidney-related samples, including renal cell lines, human kidney tissues and murine model kidneys. Researchers can explore certain gene profiles, the relationships between genes of interests and identify biomarkers or even drug targets in kidney diseases. The aim of this work is to provide a user-friendly utility for the renal disease research community to query expression profiles of genes of their own interest without the requirement of advanced computational skills. Availability and implementation: Website is implemented in PHP, R, MySQL and Nginx and freely available from http://rged.wall-eva.net. Database URL: http://rged.wall-eva.net PMID:25252782

  20. A new essential protein discovery method based on the integration of protein-protein interaction and gene expression data

    Directory of Open Access Journals (Sweden)

    Li Min

    2012-03-01

    Full Text Available Abstract Background Identification of essential proteins is always a challenging task since it requires experimental approaches that are time-consuming and laborious. With the advances in high throughput technologies, a large number of protein-protein interactions are available, which have produced unprecedented opportunities for detecting proteins' essentialities from the network level. There have been a series of computational approaches proposed for predicting essential proteins based on network topologies. However, the network topology-based centrality measures are very sensitive to the robustness of network. Therefore, a new robust essential protein discovery method would be of great value. Results In this paper, we propose a new centrality measure, named PeC, based on the integration of protein-protein interaction and gene expression data. The performance of PeC is validated based on the protein-protein interaction network of Saccharomyces cerevisiae. The experimental results show that the predicted precision of PeC clearly exceeds that of the other fifteen previously proposed centrality measures: Degree Centrality (DC, Betweenness Centrality (BC, Closeness Centrality (CC, Subgraph Centrality (SC, Eigenvector Centrality (EC, Information Centrality (IC, Bottle Neck (BN, Density of Maximum Neighborhood Component (DMNC, Local Average Connectivity-based method (LAC, Sum of ECC (SoECC, Range-Limited Centrality (RL, L-index (LI, Leader Rank (LR, Normalized α-Centrality (NC, and Moduland-Centrality (MC. Especially, the improvement of PeC over the classic centrality measures (BC, CC, SC, EC, and BN is more than 50% when predicting no more than 500 proteins. Conclusions We demonstrate that the integration of protein-protein interaction network and gene expression data can help improve the precision of predicting essential proteins. The new centrality measure, PeC, is an effective essential protein discovery method.

  1. Tackling heterogeneity: a leaf disc-based assay for the high-throughput screening of transient gene expression in tobacco.

    Directory of Open Access Journals (Sweden)

    Natalia Piotrzkowski

    Full Text Available Transient Agrobacterium-mediated gene expression assays for Nicotiana tabacum (N. tabacum are frequently used because they facilitate the comparison of multiple expression constructs regarding their capacity for maximum recombinant protein production. However, for three model proteins, we found that recombinant protein accumulation (rpa was significantly influenced by leaf age and leaf position effects. The ratio between the highest and lowest amount of protein accumulation (max/min ratio was found to be as high as 11. Therefore, construct-based impacts on the rpa level that are less than 11-fold will be masked by background noise. To address this problem, we developed a leaf disc-based screening assay and infiltration device that allows the rpa level in a whole tobacco plant to be reliably and reproducibly determined. The prototype of the leaf disc infiltration device allows 14 Agrobacterium-mediated infiltration events to be conducted in parallel. As shown for three model proteins, the average max/min rpa ratio was reduced to 1.4 using this method, which allows for a sensitive comparison of different genetic elements affecting recombinant protein expression.

  2. A SAGE-based screen for genes expressed in sub-populations of neurons in the mouse dorsal root ganglion

    Directory of Open Access Journals (Sweden)

    Garces Alain

    2007-11-01

    Full Text Available Abstract Background The different sensory modalities temperature, pain, touch and muscle proprioception are carried by somatosensory neurons of the dorsal root ganglia. Study of this system is hampered by the lack of molecular markers for many of these neuronal sub-types. In order to detect genes expressed in sub-populations of somatosensory neurons, gene profiling was carried out on wild-type and TrkA mutant neonatal dorsal root ganglia (DRG using SAGE (serial analysis of gene expression methodology. Thermo-nociceptors constitute up to 80 % of the neurons in the DRG. In TrkA mutant DRGs, the nociceptor sub-class of sensory neurons is lost due to absence of nerve growth factor survival signaling through its receptor TrkA. Thus, comparison of wild-type and TrkA mutants allows the identification of transcripts preferentially expressed in the nociceptor or mechano-proprioceptor subclasses, respectively. Results Our comparison revealed 240 genes differentially expressed between the two tissues (P Conclusion We have identified and characterized the detailed expression patterns of three genes in the developing DRG, placing them in the context of the known major neuronal sub-types defined by molecular markers. Further analysis of differentially expressed genes in this tissue promises to extend our knowledge of the molecular diversity of different cell types and forms the basis for understanding their particular functional specificities.

  3. Homeobox gene expression in Brachiopoda

    DEFF Research Database (Denmark)

    Altenburger, Andreas; Martinez, Pedro; Wanninger, Andreas

    2011-01-01

    (ectoderm) specification with co-opted functions in notochord formation in chordates and left/right determination in ambulacrarians and vertebrates. The caudal ortholog, TtrCdx, is first expressed in the ectoderm of the gastrulating embryo in the posterior region of the blastopore. Its expression stays......The molecular control that underlies brachiopod ontogeny is largely unknown. In order to contribute to this issue we analyzed the expression pattern of two homeobox containing genes, Not and Cdx, during development of the rhynchonelliform (i.e., articulate) brachiopod Terebratalia transversa...... completion of larval development, which is marked by a three-lobed body with larval setae. Expression starts at gastrulation in two areas lateral to the blastopore and subsequently extends over the animal pole of the gastrula. With elongation of the gastrula, expression at the animal pole narrows to a small...

  4. A derepression system based on the Bacillus subtilis sporulation pathway offers dynamic control of heterologous gene expression

    NARCIS (Netherlands)

    Nijland, Reindert; Veening, Jan-Willem; Kuipers, Oscar P.

    By rewiring the sporulation gene-regulatory network of Bacillus subtilis, we generated a novel expression system relying on derepression. The gene of interest is placed under the control of the abrB promoter, which is active only when Spo0A is absent, and Spo0A is controlled via an IPTG

  5. GEPSI: A Gene Expression Profile Similarity-Based Identification Method of Bioactive Components in Traditional Chinese Medicine Formula.

    Science.gov (United States)

    Zhang, Baixia; He, Shuaibing; Lv, Chenyang; Zhang, Yanling; Wang, Yun

    2018-01-01

    The identification of bioactive components in traditional Chinese medicine (TCM) is an important part of the TCM material foundation research. Recently, molecular docking technology has been extensively used for the identification of TCM bioactive components. However, target proteins that are used in molecular docking may not be the actual TCM target. For this reason, the bioactive components would likely be omitted or incorrect. To address this problem, this study proposed the GEPSI method that identified the target proteins of TCM based on the similarity of gene expression profiles. The similarity of the gene expression profiles affected by TCM and small molecular drugs was calculated. The pharmacological action of TCM may be similar to that of small molecule drugs that have a high similarity score. Indeed, the target proteins of the small molecule drugs could be considered TCM targets. Thus, we identified the bioactive components of a TCM by molecular docking and verified the reliability of this method by a literature investigation. Using the target proteins that TCM actually affected as targets, the identification of the bioactive components was more accurate. This study provides a fast and effective method for the identification of TCM bioactive components.

  6. Vascular Gene Expression: A Hypothesis

    Directory of Open Access Journals (Sweden)

    Angélica Concepción eMartínez-Navarro

    2013-07-01

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

  7. Pathway-based factor analysis of gene expression data produces highly heritable phenotypes that associate with age.

    Science.gov (United States)

    Anand Brown, Andrew; Ding, Zhihao; Viñuela, Ana; Glass, Dan; Parts, Leopold; Spector, Tim; Winn, John; Durbin, Richard

    2015-03-09

    Statistical factor analysis methods have previously been used to remove noise components from high-dimensional data prior to genetic association mapping and, in a guided fashion, to summarize biologically relevant sources of variation. Here, we show how the derived factors summarizing pathway expression can be used to analyze the relationships between expression, heritability, and aging. We used skin gene expression data from 647 twins from the MuTHER Consortium and applied factor analysis to concisely summarize patterns of gene expression to remove broad confounding influences and to produce concise pathway-level phenotypes. We derived 930 "pathway phenotypes" that summarized patterns of variation across 186 KEGG pathways (five phenotypes per pathway). We identified 69 significant associations of age with phenotype from 57 distinct KEGG pathways at a stringent Bonferroni threshold ([Formula: see text]). These phenotypes are more heritable ([Formula: see text]) than gene expression levels. On average, expression levels of 16% of genes within these pathways are associated with age. Several significant pathways relate to metabolizing sugars and fatty acids; others relate to insulin signaling. We have demonstrated that factor analysis methods combined with biological knowledge can produce more reliable phenotypes with less stochastic noise than the individual gene expression levels, which increases our power to discover biologically relevant associations. These phenotypes could also be applied to discover associations with other environmental factors. Copyright © 2015 Brown et al.

  8. 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

  9. A novel minicircle vector based system for inhibting the replication and gene expression of enterovirus 71 and coxsackievirus A16.

    Science.gov (United States)

    Yang, Zhuo; Li, Guodong; Zhang, Yingqiu; Liu, Xiaoman; Tien, Po

    2012-11-01

    Enterovirus 71 (EV 71) and Coxsackievirus A16 (CA 16) are two major causative agents of hand, foot and mouth disease (HFMD). They have been associated with severe neurological and cardiological complications worldwide, and have caused significant mortalities during large-scale outbreaks in China. Currently, there are no effective treatments against EV 71 and CA 16 infections. We now describe the development of a novel minicircle vector based RNA interference (RNAi) system as a therapeutic approach to inhibiting EV 71 and CA 16 replication. Small interfering RNA (siRNA) molecules targeting the conserved regions of the 3C(pro) and 3D(pol) function gene of the EV 71 and CA 16 China strains were designed based on their nucleotide sequences available in GenBank. This RNAi system was found to effectively block the replication and gene expression of these viruses in rhabdomyosarcoma (RD) cells and virus-infected mice model. The inhibitory effects were confirmed by a corresponding decrease in viral RNA, viral protein, and progeny virus production. In addition, no significant adverse off-target silencing or cytotoxic effects were observed. These results demonstrated the potential and feasibility of this novel minicircle vector based RNAi system for antiviral therapy against EV 71 and CA 16 infection. Copyright © 2012 Elsevier B.V. All rights reserved.

  10. Novel subtractive transcription-based amplification of mRNA (STAR method and its application in search of rare and differentially expressed genes in AD brains

    Directory of Open Access Journals (Sweden)

    Walker P Roy

    2006-11-01

    Full Text Available Abstract Background Alzheimer's disease (AD is a complex disorder that involves multiple biological processes. Many genes implicated in these processes may be present in low abundance in the human brain. DNA microarray analysis identifies changed genes that are expressed at high or moderate levels. Complementary to this approach, we described here a novel technology designed specifically to isolate rare and novel genes previously undetectable by other methods. We have used this method to identify differentially expressed genes in brains affected by AD. Our method, termed Subtractive Transcription-based Amplification of mRNA (STAR, is a combination of subtractive RNA/DNA hybridization and RNA amplification, which allows the removal of non-differentially expressed transcripts and the linear amplification of the differentially expressed genes. Results Using the STAR technology we have identified over 800 differentially expressed sequences in AD brains, both up- and down- regulated, compared to age-matched controls. Over 55% of the sequences represent genes of unknown function and roughly half of them were novel and rare discoveries in the human brain. The expression changes of nearly 80 unique genes were further confirmed by qRT-PCR and the association of additional genes with AD and/or neurodegeneration was established using an in-house literature mining tool (LitMiner. Conclusion The STAR process significantly amplifies unique and rare sequences relative to abundant housekeeping genes and, as a consequence, identifies genes not previously linked to AD. This method also offers new opportunities to study the subtle changes in gene expression that potentially contribute to the development and/or progression of AD.

  11. Gene expression profile of pulpitis.

    Science.gov (United States)

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

    2016-06-01

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

  12. Identification of candidate biomarkers of the exposure to PCBs in contaminated cattle: A gene expression- and proteomic-based approach.

    Science.gov (United States)

    Girolami, F; Badino, P; Spalenza, V; Manzini, L; Renzone, G; Salzano, A M; Dal Piaz, F; Scaloni, A; Rychen, G; Nebbia, C

    2018-05-28

    Dioxins and polychlorinated biphenyls (PCBs) are widespread and persistent contaminants. Through a combined gene expression/proteomic-based approach, candidate biomarkers of the exposure to such environmental pollutants in cattle subjected to a real eco-contamination event were identified. Animals were removed from the polluted area and fed a standard ration for 6 months. The decontamination was monitored by evaluating dioxin and PCB levels in pericaudal fat two weeks after the removal from the contaminated area (day 0) and then bimonthly for six months (days 59, 125 and 188). Gene expression measurements demonstrated that CYP1B1 expression was significantly higher in blood lymphocytes collected in contaminated animals (day 0), and decreased over time during decontamination. mRNA levels of interleukin 2 showed an opposite quantitative trend. MALDI-TOF-MS polypeptide profiling of serum samples ascertained a progressive decrease (from day 0 to 188) of serum levels of fibrinogen β-chain and serpin A3-7-like fragments, apolipoprotein (APO) C-II and serum amyloid A-4 protein, along with an augmented representation of transthyretin isoforms, as well as APOC-III and APOA-II proteins during decontamination. When differentially represented species were combined with serum antioxidant, acute phase and proinflammatory protein levels already ascertained in the same animals (Cigliano et al., 2016), bioinformatics unveiled an interaction network linking together almost all components. This suggests the occurrence of a complex PCB-responsive mechanism associated with animal contamination/decontamination, including a cohort of protein/polypeptide species involved in blood redox homeostasis, inflammation and lipid transport. All together, these results suggest the use in combination of such biomarkers for identifying PCB-contaminated animals, and for monitoring the restoring of their healthy condition following a decontamination process. Copyright © 2018 Elsevier B.V. All

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

    Directory of Open Access Journals (Sweden)

    Jean-François Gout

    2010-05-01

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

  14. Allen Brain Atlas-Driven Visualizations: A Web-Based Gene Expression Energy Visualization Tool

    Science.gov (United States)

    2014-05-21

    proportional to the amount of expression energy. As such, there is no need to augment the color intensity of each bar, as its height identifies...REFERENCES Berridge, K. C., and Robinson, T. E. (1998). What is the role of dopamine in reward: hedonic impact, reward learning, or incentive salience

  15. Blood-Based Gene Expression Signatures of Infants and Toddlers with Autism

    Science.gov (United States)

    Glatt, Stephen J.; Tsuang, Ming T.; Winn, Mary; Chandler, Sharon D.; Collins, Melanie; Lopez, Linda; Weinfeld, Melanie; Carter, Cindy; Schork, Nicholas; Pierce, Karen; Courchesne, Eric

    2012-01-01

    Objective: Autism spectrum disorders (ASDs) are highly heritable neurodevelopmental disorders that onset clinically during the first years of life. ASD risk biomarkers expressed early in life could significantly impact diagnosis and treatment, but no transcriptome-wide biomarker classifiers derived from fresh blood samples from children with…

  16. Transcriptome-based identification of antioxidative gene expression after fish oil supplementation in normo- and dyslipidemic men

    Directory of Open Access Journals (Sweden)

    Schmidt Simone

    2012-05-01

    Full Text Available Abstract Background The beneficial effects of omega-3 polyunsaturated fatty acids (n-3 PUFAs, especially in dyslipidemic subjects with a high risk of cardiovascular disease, are widely described in the literature. A lot of effects of n-3 PUFAs and their oxidized metabolites are triggered by regulating the expression of genes. Currently, it is uncertain if the administration of n-3 PUFAs results in different expression changes of genes related to antioxidative mechanisms in normo- and dyslipidemic subjects, which may partly explain their cardioprotective effects. The aim of this study was to investigate the effects of n-3 PUFA supplementation on expression changes of genes involved in oxidative processes. Methods Ten normo- and ten dyslipidemic men were supplemented for twelve weeks with fish oil capsules, providing 1.14 g docosahexaenoic acid and 1.56 g eicosapentaenoic acid. Gene expression levels were determined by whole genome microarray analysis and quantitative real-time polymerase chain reaction (qRT-PCR. Results Using microarrays, we discovered an increased expression of antioxidative enzymes and a decreased expression of pro-oxidative and tissue enzymes, such as cytochrome P450 enzymes and matrix metalloproteinases, in both normo- and dyslipidemic men. An up-regulation of catalase and heme oxigenase 2 in both normo- and dyslipidemic subjects and an up-regulation of cytochrome P450 enzyme 1A2 only in dyslipidemic subjects could be observed by qRT-PCR analysis. Conclusions Supplementation of normo- and dyslipidemic subjects with n-3 PUFAs changed the expression of genes related to oxidative processes, which may suggest antioxidative and potential cardioprotective effects of n-3 PUFAs. Further studies combining genetic and metabolic endpoints are needed to verify the regulative effects of n-3 PUFAs in antioxidative gene expression to better understand their beneficial effects in health and disease prevention. Trial registration Clinical

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

    Energy Technology Data Exchange (ETDEWEB)

    Li, Lu [School of Chemistry and Chemical Engineering, Shandong University, Jinan 250100 (China); Wang, Xianwei [School of Life Sciences, Shandong University, Jinan 250100 (China); Zhang, Xiaoli [School of Chemistry and Chemical Engineering, Shandong University, Jinan 250100 (China); Wang, Jinxing [School of Life Sciences, Shandong University, Jinan 250100 (China); Jin, Wenrui, E-mail: jwr@sdu.edu.cn [School of Chemistry and Chemical Engineering, Shandong University, Jinan 250100 (China)

    2015-01-07

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

  18. Expression Study of Banana Pathogenic Resistance Genes

    Directory of Open Access Journals (Sweden)

    Fenny M. Dwivany

    2016-10-01

    Full Text Available Banana is one of the world's most important trade commodities. However, infection of banana pathogenic fungi (Fusarium oxysporum race 4 is one of the major causes of decreasing production in Indonesia. Genetic engineering has become an alternative way to control this problem by isolating genes that involved in plant defense mechanism against pathogens. Two of the important genes are API5 and ChiI1, each gene encodes apoptosis inhibitory protein and chitinase enzymes. The purpose of this study was to study the expression of API5 and ChiI1 genes as candidate pathogenic resistance genes. The amplified fragments were then cloned, sequenced, and confirmed with in silico studies. Based on sequence analysis, it is showed that partial API5 gene has putative transactivation domain and ChiI1 has 9 chitinase family GH19 protein motifs. Data obtained from this study will contribute in banana genetic improvement.

  19. A network-based predictive gene-expression signature for adjuvant chemotherapy benefit in stage II colorectal cancer.

    Science.gov (United States)

    Cao, Bangrong; Luo, Liping; Feng, Lin; Ma, Shiqi; Chen, Tingqing; Ren, Yuan; Zha, Xiao; Cheng, Shujun; Zhang, Kaitai; Chen, Changmin

    2017-12-13

    The clinical benefit of adjuvant chemotherapy for stage II colorectal cancer (CRC) is controversial. This study aimed to explore novel gene signature to predict outcome benefit of postoperative 5-Fu-based therapy in stage II CRC. Gene-expression profiles of stage II CRCs from two datasets with 5-Fu-based adjuvant chemotherapy (training dataset, n = 212; validation dataset, n = 85) were analyzed to identify the indicator. A systemic approach by integrating gene-expression and protein-protein interaction (PPI) network was implemented to develop the predictive signature. Kaplan-Meier curves and Cox proportional hazards model were used to determine the survival benefit of adjuvant chemotherapy. Experiments with shRNA knock-down were carried out to confirm the signature identified in this study. In the training dataset, we identified 44 PPI sub-modules, by which we separate patients into two clusters (1 and 2) having different chemotherapeutic benefit. A predictor of 11 PPI sub-modules (11-PPI-Mod) was established to discriminate the two sub-groups, with an overall accuracy of 90.1%. This signature was independently validated in an external validation dataset. Kaplan-Meier curves showed an improved outcome for patients who received adjuvant chemotherapy in Cluster 1 sub-group, but even worse survival for those in Cluster 2 sub-group. Similar results were found in both the training and the validation dataset. Multivariate Cox regression revealed an interaction effect between 11-PPI-Mod signature and adjuvant therapy treatment in the training dataset (RFS, p = 0.007; OS, p = 0.006) and the validation dataset (RFS, p = 0.002). From the signature, we found that PTGES gene was up-regulated in CRC cells which were more resistant to 5-Fu. Knock-down of PTGES indicated a growth inhibition and up-regulation of apoptotic markers induced by 5-Fu in CRC cells. Only a small proportion of stage II CRC patients could benefit from adjuvant therapy. The 11-PPI-Mod as

  20. Mapping in an apple (Malus x domestica) F1 segregating population based on physical clustering of differentially expressed genes.

    Science.gov (United States)

    Jensen, Philip J; Fazio, Gennaro; Altman, Naomi; Praul, Craig; McNellis, Timothy W

    2014-04-04

    Apple tree breeding is slow and difficult due to long generation times, self-incompatibility, and complex genetics. The identification of molecular markers linked to traits of interest is a way to expedite the breeding process. In the present study, we aimed to identify genes whose steady-state transcript abundance was associated with inheritance of specific traits segregating in an apple (Malus × domestica) rootstock F1 breeding population, including resistance to powdery mildew (Podosphaera leucotricha) disease and woolly apple aphid (Eriosoma lanigerum). Transcription profiling was performed for 48 individual F1 apple trees from a cross of two highly heterozygous parents, using RNA isolated from healthy, actively-growing shoot tips and a custom apple DNA oligonucleotide microarray representing 26,000 unique transcripts. Genome-wide expression profiles were not clear indicators of powdery mildew or woolly apple aphid resistance phenotype. However, standard differential gene expression analysis between phenotypic groups of trees revealed relatively small sets of genes with trait-associated expression levels. For example, thirty genes were identified that were differentially expressed between trees resistant and susceptible to powdery mildew. Interestingly, the genes encoding twenty-four of these transcripts were physically clustered on chromosome 12. Similarly, seven genes were identified that were differentially expressed between trees resistant and susceptible to woolly apple aphid, and the genes encoding five of these transcripts were also clustered, this time on chromosome 17. In each case, the gene clusters were in the vicinity of previously identified major quantitative trait loci for the corresponding trait. Similar results were obtained for a series of molecular traits. Several of the differentially expressed genes were used to develop DNA polymorphism markers linked to powdery mildew disease and woolly apple aphid resistance. Gene expression profiling

  1. Autonomous Bacterial Localization and Gene Expression Based on Nearby Cell Receptor Density

    Science.gov (United States)

    2013-01-22

    signal-peptide (lpp-ompA) sequences from the template vector, pTX101 (provided by Dr George Georgiou, University of Texas, Austin) (Francisco et al...generously providing the PCI-15B cell line, Dr George Georgiou for kindly providing the ompA surface display vector, and Dr Eiry Kobatake for providing...E, Wong WW, Suen JK, Bulter T, Lee SG, Liao JC (2005) A synthetic gene-metabolic oscillator. Nature 435: 118–122 Gardner TS, Cantor CR, Collins JJ

  2. Gene expression of the endolymphatic sac

    DEFF Research Database (Denmark)

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

    2011-01-01

    that the endolymphatic sac has multiple and diverse functions in the inner ear. Objectives:The objective of this study was to provide a comprehensive review of the genes expressed in the endolymphatic sac in the rat and perform a functional characterization based on measured mRNA abundance. Methods:Microarray technology...

  3. Time-course investigation of the gene expression profile during Fasciola hepatica infection: A microarray-based study

    Directory of Open Access Journals (Sweden)

    Jose Rojas-Caraballo

    2015-12-01

    Full Text Available Fasciolosis is listed as one of the most important neglected tropical diseases according with the World Health Organization and is also considered as a reemerging disease in the human beings. Despite there are several studies describing the immune response induced by Fasciola hepatica in the mammalian host, investigations aimed at identifying the expression profile of genes involved in inducing hepatic injury are currently scarce. Data presented here belong to a time-course investigation of the gene expression profile in the liver of BALB/c mice infected with F. hepatica metacercariae at 7 and 21 days after experimental infection. The data published here have been deposited in NCBI's Gene Expression Omnibus and are accessible through GEO Series accession number GSE69588, previously published by Rojas-Caraballo et al. (2015 in PLoS One [1].

  4. 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.

  5. Transcriptome-based analysis of kidney gene expression changes associated with diabetes in OVE26 mice, in the presence and absence of losartan treatment.

    Directory of Open Access Journals (Sweden)

    Radko Komers

    Full Text Available Diabetes is among the most common causes of end-stage renal disease, although its pathophysiology is incompletely understood. We performed next-generation sequencing-based transcriptome analysis of renal gene expression changes in the OVE26 murine model of diabetes (age 15 weeks, relative to non-diabetic control, in the presence and absence of short-term (seven-day treatment with the angiotensin receptor blocker, losartan (n = 3-6 biological replicates per condition. We detected 1438 statistically significant changes in gene expression across conditions. Of the 638 genes dysregulated in diabetes relative to the non-diabetic state, >70% were downregulation events. Unbiased functional annotation of genes up- and down-regulated by diabetes strongly associated (p52-fold, encoded by the cationic amino acid transporter Slc7a12, and the gene product most highly downregulated by diabetes (>99%--encoded by the "pseudogene" Gm6300--are adjacent in the murine genome, are members of the SLC7 gene family, and are likely paralogous. Therefore, diabetes activates a near-total genetic switch between these two paralogs. Other individual-level changes in gene expression are potentially relevant to diabetic pathophysiology, and novel pathways are suggested. Genes unaffected by diabetes alone but exhibiting increased renal expression with losartan produced a signature consistent with malignant potential.

  6. Comprehensive transcriptome-based characterization of differentially expressed genes involved in microsporogenesis of radish CMS line and its maintainer.

    Science.gov (United States)

    Xie, Yang; Zhang, Wei; Wang, Yan; Xu, Liang; Zhu, Xianwen; Muleke, Everlyne M; Liu, Liwang

    2016-09-01

    Microsporogenesis is an indispensable period for investigating microspore development and cytoplasmic male sterility (CMS) occurrence. Radish CMS line plays a critical role in elite F1 hybrid seed production and heterosis utilization. However, the molecular mechanisms of microspore development and CMS occurrence have not been thoroughly uncovered in radish. In this study, a comparative analysis of radish floral buds from a CMS line (NAU-WA) and its maintainer (NAU-WB) was conducted using next generation sequencing (NGS) technology. Digital gene expression (DGE) profiling revealed that 3504 genes were significantly differentially expressed between NAU-WA and NAU-WB library, among which 1910 were upregulated and 1594 were downregulated. Gene ontology (GO) analysis showed that these differentially expressed genes (DEGs) were mainly enriched in extracellular region, catalytic activity, and response to stimulus. KEGG enrichment analysis revealed that the DEGs were predominantly associated with flavonoid biosynthesis, glycolysis, and biosynthesis of secondary metabolites. Real-time quantitative PCR analysis showed that the expression profiles of 13 randomly selected DEGs were in high agreement with results from Illumina sequencing. Several candidate genes encoding ATP synthase, auxin response factor (ARF), transcription factors (TFs), chalcone synthase (CHS), and male sterility (MS) were responsible for microsporogenesis. Furthermore, a schematic diagram for functional interaction of DEGs from NAU-WA vs. NAU-WB library in radish plants was proposed. These results could provide new information on the dissection of the molecular mechanisms underlying microspore development and CMS occurrence in radish.

  7. Using gene expression noise to understand gene regulation

    NARCIS (Netherlands)

    Munsky, B.; Neuert, G.; van Oudenaarden, A.

    2012-01-01

    Phenotypic variation is ubiquitous in biology and is often traceable to underlying genetic and environmental variation. However, even genetically identical cells in identical environments display variable phenotypes. Stochastic gene expression, or gene expression "noise," has been suggested as a

  8. Single-base resolution maps of cultivated and wild rice methylomes and regulatory roles of DNA methylation in plant gene expression

    Directory of Open Access Journals (Sweden)

    Li Xin

    2012-07-01

    Full Text Available Abstract Background DNA methylation plays important biological roles in plants and animals. To examine the rice genomic methylation landscape and assess its functional significance, we generated single-base resolution DNA methylome maps for Asian cultivated rice Oryza sativa ssp. japonica, indica and their wild relatives, Oryza rufipogon and Oryza nivara. Results The overall methylation level of rice genomes is four times higher than that of Arabidopsis. Consistent with the results reported for Arabidopsis, methylation in promoters represses gene expression while gene-body methylation generally appears to be positively associated with gene expression. Interestingly, we discovered that methylation in gene transcriptional termination regions (TTRs can significantly repress gene expression, and the effect is even stronger than that of promoter methylation. Through integrated analysis of genomic, DNA methylomic and transcriptomic differences between cultivated and wild rice, we found that primary DNA sequence divergence is the major determinant of methylational differences at the whole genome level, but DNA methylational difference alone can only account for limited gene expression variation between the cultivated and wild rice. Furthermore, we identified a number of genes with significant difference in methylation level between the wild and cultivated rice. Conclusions The single-base resolution methylomes of rice obtained in this study have not only broadened our understanding of the mechanism and function of DNA methylation in plant genomes, but also provided valuable data for future studies of rice epigenetics and the epigenetic differentiation between wild and cultivated rice.

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

    KAUST Repository

    Horiuchi, Youko

    2015-12-23

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

  10. Development of a blood-based gene expression algorithm for assessment of obstructive coronary artery disease in non-diabetic patients

    Directory of Open Access Journals (Sweden)

    Ellis Stephen G

    2011-03-01

    Full Text Available Abstract Background Alterations in gene expression in peripheral blood cells have been shown to be sensitive to the presence and extent of coronary artery disease (CAD. A non-invasive blood test that could reliably assess obstructive CAD likelihood would have diagnostic utility. Results Microarray analysis of RNA samples from a 195 patient Duke CATHGEN registry case:control cohort yielded 2,438 genes with significant CAD association (p RT-PCR analysis of these 113 genes in a PREDICT cohort of 640 non-diabetic subject samples was used for algorithm development. Gene expression correlations identified clusters of CAD classifier genes which were reduced to meta-genes using LASSO. The final classifier for assessment of obstructive CAD was derived by Ridge Regression and contained sex-specific age functions and 6 meta-gene terms, comprising 23 genes. This algorithm showed a cross-validated estimated AUC = 0.77 (95% CI 0.73-0.81 in ROC analysis. Conclusions We have developed a whole blood classifier based on gene expression, age and sex for the assessment of obstructive CAD in non-diabetic patients from a combination of microarray and RT-PCR data derived from studies of patients clinically indicated for invasive angiography. Clinical trial registration information PREDICT, Personalized Risk Evaluation and Diagnosis in the Coronary Tree, http://www.clinicaltrials.gov, NCT00500617

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

    Science.gov (United States)

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

    2013-01-01

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

  12. A constructive approach to gene expression dynamics

    International Nuclear Information System (INIS)

    Ochiai, T.; Nacher, J.C.; Akutsu, T.

    2004-01-01

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

  13. Developmentally regulated expression of reporter gene in adult ...

    Indian Academy of Sciences (India)

    pression of reporter gene in adult brain specific GAL4 enhancer traps of. Drosophila ... genes based on their expression pattern, thus enabling us to overcome the ... order association and storage centres of olfactory learning and memory, and ...

  14. Effects of nutritional level of concentrate-based diets on meat quality and expression levels of genes related to meat quality in Hainan black goats.

    Science.gov (United States)

    Wang, Dingfa; Zhou, Luli; Zhou, Hanlin; Hou, Guanyu; Shi, Liguang; Li, Mao; Huang, Xianzhou; Guan, Song

    2015-02-01

    The present study investigated the effects of the nutritional levels of diets on meat quality and related gene expression in Hainan black goat. Twenty-four goats were divided into six dietary treatments and were fed a concentrate-based diet with two levels of crude protein (CP) (15% or 17%) and three levels of digestive energy (DE) (11.72, 12.55 or 13.39 MJ/kg DM) for 90 days. Goats fed the concentrate-based diet with 17% CP had significantly (P meat quality and expression levels of genes associated with meat quality in Hainan black goats. © 2014 Japanese Society of Animal Science.

  15. Food-grade host/vector expression system for Lactobacillus casei based on complementation of plasmid-associated phospho-beta-galactosidase gene lacG.

    Science.gov (United States)

    Takala, T M; Saris, P E J; Tynkkynen, S S H

    2003-01-01

    A new food-grade host/vector system for Lactobacillus casei based on lactose selection was constructed. The wild-type non-starter host Lb. casei strain E utilizes lactose via a plasmid-encoded phosphotransferase system. For food-grade cloning, a stable lactose-deficient mutant was constructed by deleting a 141-bp fragment from the phospho-beta-galactosidase gene lacG via gene replacement. The deletion resulted in an inactive phospho-beta-galactosidase enzyme with an internal in-frame deletion of 47 amino acids. A complementation plasmid was constructed containing a replicon from Lactococcus lactis, the lacG gene from Lb. casei, and the constitutive promoter of pepR for lacG expression from Lb. rhamnosus. The expression of the lacG gene from the resulting food-grade plasmid pLEB600 restored the ability of the lactose-negative mutant strain to grow on lactose to the wild-type level. The vector pLEB600 was used for expression of the proline iminopeptidase gene pepI from Lb. helveticus in Lb. casei. The results show that the food-grade expression system reported in this paper can be used for expression of foreign genes in Lb. casei.

  16. Codon usage and amino acid usage influence genes expression level.

    Science.gov (United States)

    Paul, Prosenjit; Malakar, Arup Kumar; Chakraborty, Supriyo

    2018-02-01

    Highly expressed genes in any species differ in the usage frequency of synonymous codons. The relative recurrence of an event of the favored codon pair (amino acid pairs) varies between gene and genomes due to varying gene expression and different base composition. Here we propose a new measure for predicting the gene expression level, i.e., codon plus amino bias index (CABI). Our approach is based on the relative bias of the favored codon pair inclination among the genes, illustrated by analyzing the CABI score of the Medicago truncatula genes. CABI showed strong correlation with all other widely used measures (CAI, RCBS, SCUO) for gene expression analysis. Surprisingly, CABI outperforms all other measures by showing better correlation with the wet-lab data. This emphasizes the importance of the neighboring codons of the favored codon in a synonymous group while estimating the expression level of a gene.

  17. A biological network-based regularized artificial neural network model for robust phenotype prediction from gene expression data.

    Science.gov (United States)

    Kang, Tianyu; Ding, Wei; Zhang, Luoyan; Ziemek, Daniel; Zarringhalam, Kourosh

    2017-12-19

    Stratification of patient subpopulations that respond favorably to treatment or experience and adverse reaction is an essential step toward development of new personalized therapies and diagnostics. It is currently feasible to generate omic-scale biological measurements for all patients in a study, providing an opportunity for machine learning models to identify molecular markers for disease diagnosis and progression. However, the high variability of genetic background in human populations hampers the reproducibility of omic-scale markers. In this paper, we develop a biological network-based regularized artificial neural network model for prediction of phenotype from transcriptomic measurements in clinical trials. To improve model sparsity and the overall reproducibility of the model, we incorporate regularization for simultaneous shrinkage of gene sets based on active upstream regulatory mechanisms into the model. We benchmark our method against various regression, support vector machines and artificial neural network models and demonstrate the ability of our method in predicting the clinical outcomes using clinical trial data on acute rejection in kidney transplantation and response to Infliximab in ulcerative colitis. We show that integration of prior biological knowledge into the classification as developed in this paper, significantly improves the robustness and generalizability of predictions to independent datasets. We provide a Java code of our algorithm along with a parsed version of the STRING DB database. In summary, we present a method for prediction of clinical phenotypes using baseline genome-wide expression data that makes use of prior biological knowledge on gene-regulatory interactions in order to increase robustness and reproducibility of omic-scale markers. The integrated group-wise regularization methods increases the interpretability of biological signatures and gives stable performance estimates across independent test sets.

  18. Genomics-based screening of differentially expressed genes in the brains of mice exposed to silver nanoparticles via inhalation

    International Nuclear Information System (INIS)

    Lee, Hye-Young; Choi, You-Jin; Jung, Eun-Jung; Yin, Hu-Quan; Kwon, Jung-Taek; Kim, Ji-Eun; Im, Hwang-Tae; Cho, Myung-Haing; Kim, Ju-Han; Kim, Hyun-Young; Lee, Byung-Hoon

    2010-01-01

    Silver nanoparticles (AgNP) are among the fastest growing product categories in the nanotechnology industry. Despite the importance of AgNP in consumer products and clinical applications, relatively little is known regarding AgNP toxicity and its associated risks. We investigated the effects of AgNP on gene expression in the mouse brain using Affymetrix Mouse Genome Arrays. C57BL/6 mice were exposed to AgNP (geometric mean diameter, 22.18 ± 1.72 nm; 1.91 x 10 7 particles/cm 3 ) for 6 h/day, 5 days/week using the nose-only exposure system for 2 weeks. Total RNA isolated from the cerebrum and cerebellum was subjected to hybridization. From over 39,000 probe sets, 468 genes in the cerebrum and 952 genes in the cerebellum were identified as AgNP-responsive (one-way analysis of variance; p < 0.05). The largest groups of gene products affected by AgNP exposure included 73 genes in the cerebrum and 144 genes in the cerebellum. AgNP exposure modulated the expression of several genes associated with motor neuron disorders, neurodegenerative disease, and immune cell function, indicating potential neurotoxicity and immunotoxicity associated with AgNP exposure. Real-time PCR data for five genes analyzed from whole blood showed good correlation with the observed changes in the brain. Following rigorous validation and substantiation, these genes may assist in the development of surrogate markers for AgNP exposure and/or toxicity.

  19. Genomics-based screening of differentially expressed genes in the brains of mice exposed to silver nanoparticles via inhalation

    Energy Technology Data Exchange (ETDEWEB)

    Lee, Hye-Young; Choi, You-Jin; Jung, Eun-Jung; Yin, Hu-Quan [Seoul National University, College of Pharmacy and Research Institute of Pharmaceutical Sciences (Korea, Republic of); Kwon, Jung-Taek; Kim, Ji-Eun; Im, Hwang-Tae; Cho, Myung-Haing [Seoul National University, College of Veterinary Medicine (Korea, Republic of); Kim, Ju-Han [Seoul National University, College of Medicine (Korea, Republic of); Kim, Hyun-Young [Occupational Safety and Health Research Institute, Chemical Safety and Health Research Center (Korea, Republic of); Lee, Byung-Hoon, E-mail: lee@snu.ac.k [Seoul National University, College of Pharmacy and Research Institute of Pharmaceutical Sciences (Korea, Republic of)

    2010-06-15

    Silver nanoparticles (AgNP) are among the fastest growing product categories in the nanotechnology industry. Despite the importance of AgNP in consumer products and clinical applications, relatively little is known regarding AgNP toxicity and its associated risks. We investigated the effects of AgNP on gene expression in the mouse brain using Affymetrix Mouse Genome Arrays. C57BL/6 mice were exposed to AgNP (geometric mean diameter, 22.18 {+-} 1.72 nm; 1.91 x 10{sup 7} particles/cm{sup 3}) for 6 h/day, 5 days/week using the nose-only exposure system for 2 weeks. Total RNA isolated from the cerebrum and cerebellum was subjected to hybridization. From over 39,000 probe sets, 468 genes in the cerebrum and 952 genes in the cerebellum were identified as AgNP-responsive (one-way analysis of variance; p < 0.05). The largest groups of gene products affected by AgNP exposure included 73 genes in the cerebrum and 144 genes in the cerebellum. AgNP exposure modulated the expression of several genes associated with motor neuron disorders, neurodegenerative disease, and immune cell function, indicating potential neurotoxicity and immunotoxicity associated with AgNP exposure. Real-time PCR data for five genes analyzed from whole blood showed good correlation with the observed changes in the brain. Following rigorous validation and substantiation, these genes may assist in the development of surrogate markers for AgNP exposure and/or toxicity.

  20. Heterogeneity wavelet kinetics from DCE-MRI for classifying gene expression based breast cancer recurrence risk.

    Science.gov (United States)

    Mahrooghy, Majid; Ashraf, Ahmed B; Daye, Dania; Mies, Carolyn; Feldman, Michael; Rosen, Mark; Kontos, Despina

    2013-01-01

    Breast tumors are heterogeneous lesions. Intra-tumor heterogeneity presents a major challenge for cancer diagnosis and treatment. Few studies have worked on capturing tumor heterogeneity from imaging. Most studies to date consider aggregate measures for tumor characterization. In this work we capture tumor heterogeneity by partitioning tumor pixels into subregions and extracting heterogeneity wavelet kinetic (HetWave) features from breast dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) to obtain the spatiotemporal patterns of the wavelet coefficients and contrast agent uptake from each partition. Using a genetic algorithm for feature selection, and a logistic regression classifier with leave one-out cross validation, we tested our proposed HetWave features for the task of classifying breast cancer recurrence risk. The classifier based on our features gave an ROC AUC of 0.78, outperforming previously proposed kinetic, texture, and spatial enhancement variance features which give AUCs of 0.69, 0.64, and 0.65, respectively.

  1. Genome-Wide Identification and Transcriptome-Based Expression Profiling of the Sox Gene Family in the Nile Tilapia (Oreochromis niloticus).

    Science.gov (United States)

    Wei, Ling; Yang, Chao; Tao, Wenjing; Wang, Deshou

    2016-02-23

    The Sox transcription factor family is characterized with the presence of a Sry-related high-mobility group (HMG) box and plays important roles in various biological processes in animals, including sex determination and differentiation, and the development of multiple organs. In this study, 27 Sox genes were identified in the genome of the Nile tilapia (Oreochromis niloticus), and were classified into seven groups. The members of each group of the tilapia Sox genes exhibited a relatively conserved exon-intron structure. Comparative analysis showed that the Sox gene family has undergone an expansion in tilapia and other teleost fishes following their whole genome duplication, and group K only exists in teleosts. Transcriptome-based analysis demonstrated that most of the tilapia Sox genes presented stage-specific and/or sex-dimorphic expressions during gonadal development, and six of the group B Sox genes were specifically expressed in the adult brain. Our results provide a better understanding of gene structure and spatio-temporal expression of the Sox gene family in tilapia, and will be useful for further deciphering the roles of the Sox genes during sex determination and gonadal development in teleosts.

  2. Genome-Wide Identification and Transcriptome-Based Expression Profiling of the Sox Gene Family in the Nile Tilapia (Oreochromis niloticus

    Directory of Open Access Journals (Sweden)

    Ling Wei

    2016-02-01

    Full Text Available The Sox transcription factor family is characterized with the presence of a Sry-related high-mobility group (HMG box and plays important roles in various biological processes in animals, including sex determination and differentiation, and the development of multiple organs. In this study, 27 Sox genes were identified in the genome of the Nile tilapia (Oreochromis niloticus, and were classified into seven groups. The members of each group of the tilapia Sox genes exhibited a relatively conserved exon-intron structure. Comparative analysis showed that the Sox gene family has undergone an expansion in tilapia and other teleost fishes following their whole genome duplication, and group K only exists in teleosts. Transcriptome-based analysis demonstrated that most of the tilapia Sox genes presented stage-specific and/or sex-dimorphic expressions during gonadal development, and six of the group B Sox genes were specifically expressed in the adult brain. Our results provide a better understanding of gene structure and spatio-temporal expression of the Sox gene family in tilapia, and will be useful for further deciphering the roles of the Sox genes during sex determination and gonadal development in teleosts.

  3. Spliced leader-based analyses reveal the effects of polycyclic aromatic hydrocarbons on gene expression in the copepod Pseudodiaptomus poplesia.

    Science.gov (United States)

    Zhuang, Yunyun; Yang, Feifei; Xu, Donghui; Chen, Hongju; Zhang, Huan; Liu, Guangxing

    2017-02-01

    Polycyclic aromatic hydrocarbons (PAHs) are a group of toxic and carcinogenic pollutants that can adversely affect the development, growth and reproduction of marine organisms including copepods. However, knowledge on the molecular mechanisms regulating the response to PAH exposure in marine planktonic copepods is limited. In this study, we investigated the survival and gene expression of the calanoid copepod Pseudodiaptomus poplesia upon exposure to two PAHs, 1, 2-dimethylnaphthalene (1, 2-NAPH) and pyrene. Acute toxicity responses resulted in 96-h LC 50 of 788.98μgL -1 and 54.68μgL -1 for 1, 2-NAPH and pyrene, respectively. Using the recently discovered copepod spliced leader as a primer, we constructed full-length cDNA libraries from copepods exposed to sublethal concentrations and revealed 289 unique genes of diverse functions, including stress response genes and novel genes previously undocumented for this species. Eighty-three gene families were specifically expressed in PAH exposure libraries. We further analyzed the expression of seven target genes by reverse transcription-quantitative PCR in a time-course test with three sublethal concentrations. These target genes have primary roles in detoxification, oxidative defense, and signal transduction, and include different forms of glutathione S-transferase (GST), glutathione peroxidases (GPX), peroxiredoxin (PRDX), methylmalonate-semialdehyde dehydrogenase (MSDH) and ras-related C3 botulinum toxin substrate (RAC1). Expression stability of seven candidate reference genes were evaluated and the two most stable ones (RPL15 and RPS20 for 1, 2-NAPH exposure, RPL15 and EF1D for pyrene exposure) were used to normalize the expression levels of the target genes. Significant upregulation was detected in GST-T, GST-DE, GPX4, PRDX6 and RAC1 upon 1, 2-NAPH exposure, and GST-DE and MSDH upon pyrene exposure. These results indicated that the oxidative stress was induced and that signal transduction might be affected by PAH

  4. Synthetic promoter libraries- tuning of gene expression

    DEFF Research Database (Denmark)

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

    2006-01-01

    knockout and strong overexpression. However, applications such as metabolic optimization and control analysis necessitate a continuous set of expression levels with only slight increments in strength to cover a specific window around the wildtype expression level of the studied gene; this requirement can......The study of gene function often requires changing the expression of a gene and evaluating the consequences. In principle, the expression of any given gene can be modulated in a quasi-continuum of discrete expression levels but the traditional approaches are usually limited to two extremes: gene...

  5. Analysis of baseline gene expression levels from ...

    Science.gov (United States)

    The use of gene expression profiling to predict chemical mode of action would be enhanced by better characterization of variance due to individual, environmental, and technical factors. Meta-analysis of microarray data from untreated or vehicle-treated animals within the control arm of toxicogenomics studies has yielded useful information on baseline fluctuations in gene expression. A dataset of control animal microarray expression data was assembled by a working group of the Health and Environmental Sciences Institute's Technical Committee on the Application of Genomics in Mechanism Based Risk Assessment in order to provide a public resource for assessments of variability in baseline gene expression. Data from over 500 Affymetrix microarrays from control rat liver and kidney were collected from 16 different institutions. Thirty-five biological and technical factors were obtained for each animal, describing a wide range of study characteristics, and a subset were evaluated in detail for their contribution to total variability using multivariate statistical and graphical techniques. The study factors that emerged as key sources of variability included gender, organ section, strain, and fasting state. These and other study factors were identified as key descriptors that should be included in the minimal information about a toxicogenomics study needed for interpretation of results by an independent source. Genes that are the most and least variable, gender-selectiv

  6. 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.

  7. Evaluation of a nanotechnology-based approach to induce gene-expression in human THP-1 macrophages under inflammatory conditions.

    Science.gov (United States)

    Bernal, Laura; Alvarado-Vázquez, Abigail; Ferreira, David Wilson; Paige, Candler A; Ulecia-Morón, Cristina; Hill, Bailey; Caesar, Marina; Romero-Sandoval, E Alfonso

    2017-02-01

    Macrophages orchestrate the initiation and resolution of inflammation by producing pro- and anti-inflammatory products. An imbalance in these mediators may originate from a deficient or excessive immune response. Therefore, macrophages are valid therapeutic targets to restore homeostasis under inflammatory conditions. We hypothesize that a specific mannosylated nanoparticle effectively induces gene expression in human macrophages under inflammatory conditions without undesirable immunogenic responses. THP-1 macrophages were challenged with lipopolysaccharide (LPS, 5μg/mL). Polyethylenimine (PEI) nanoparticles grafted with a mannose receptor ligand (Man-PEI) were used as a gene delivery method. Nanoparticle toxicity, Man-PEI cellular uptake rate and gene induction efficiency (GFP, CD14 or CD68) were studied. Potential immunogenic responses were evaluated by measuring the production of tumor necrosis factor-alpha (TNF-α), Interleukin (IL)-6 and IL-10. Man-PEI did not produce cytotoxicity, and it was effectively up-taken by THP-1 macrophages (69%). This approach produced a significant expression of GFP (mRNA and protein), CD14 and CD68 (mRNA), and transiently and mildly reduced IL-6 and IL-10 levels in LPS-challenged macrophages. Our results indicate that Man-PEI is suitable for inducing an efficient gene overexpression in human macrophages under inflammatory conditions with limited immunogenic responses. Our promising results set the foundation to test this technology to induce functional anti-inflammatory genes. Copyright © 2016 Elsevier GmbH. All rights reserved.

  8. Structure and expression of thyroglobulin gene

    Energy Technology Data Exchange (ETDEWEB)

    Vassart, G; Brocas, H; Christophe, D; de Martynoff, G; Leriche, A; Mercken, L; Pohl, V; van Heuverswyn, B [Institut de Recherche Interdisciplinaire en Biologie Humaine et Nucleaire (IRIBHN), Faculte de Medecine, Universite libre de Bruxelles, Campus Hopital Erasme, Brussels (Belgium)

    1982-01-01

    Thyroglobulin is composed of two 300000 dalton polypeptide chains, translated from an 8000 base mRNA. Preparation of a full length cDNA and its cloning in E. coli have lead to the demonstration that the polypeptides of thyroglobulin protomers were identical. Used as molecular probes, the cloned cDNA allowed the isolation of a fragment of thyroglobulin gene. Electron microscopic studies have demonstrated that this gene contains more than 90 % intronic material separating small size exons (<200 bp). Sequencing of bovine thyroglobulin structural gene is in progress. Preliminary results show evidence for the existence of repetitive segments. Availability of cloned DNA complementary to bovine and human thyroglobulin mRNA allows the study of genetic defects of thyroglobulin gene expression in the human and in various animal models.

  9. Determining Physical Mechanisms of Gene Expression Regulation from Single Cell Gene Expression Data

    OpenAIRE

    Ezer, Daphne; Moignard, Victoria; G?ttgens, Berthold; Adryan, Boris

    2016-01-01

    Many genes are expressed in bursts, which can contribute to cell-to-cell heterogeneity. It is now possible to measure this heterogeneity with high throughput single cell gene expression assays (single cell qPCR and RNA-seq). These experimental approaches generate gene expression distributions which can be used to estimate the kinetic parameters of gene expression bursting, namely the rate that genes turn on, the rate that genes turn off, and the rate of transcription. We construct a complete ...

  10. Mindfulness-Based Stress Reduction training reduces loneliness and pro-inflammatory gene expression in older adults: a small randomized controlled trial.

    Science.gov (United States)

    Creswell, J David; Irwin, Michael R; Burklund, Lisa J; Lieberman, Matthew D; Arevalo, Jesusa M G; Ma, Jeffrey; Breen, Elizabeth Crabb; Cole, Steven W

    2012-10-01

    Lonely older adults have increased expression of pro-inflammatory genes as well as increased risk for morbidity and mortality. Previous behavioral treatments have attempted to reduce loneliness and its concomitant health risks, but have had limited success. The present study tested whether the 8-week Mindfulness-Based Stress Reduction (MBSR) program (compared to a Wait-List control group) reduces loneliness and downregulates loneliness-related pro-inflammatory gene expression in older adults (N = 40). Consistent with study predictions, mixed effect linear models indicated that the MBSR program reduced loneliness, compared to small increases in loneliness in the control group (treatment condition × time interaction: F(1,35) = 7.86, p = .008). Moreover, at baseline, there was an association between reported loneliness and upregulated pro-inflammatory NF-κB-related gene expression in circulating leukocytes, and MBSR downregulated this NF-κB-associated gene expression profile at post-treatment. Finally, there was a trend for MBSR to reduce C Reactive Protein (treatment condition × time interaction: (F(1,33) = 3.39, p = .075). This work provides an initial indication that MBSR may be a novel treatment approach for reducing loneliness and related pro-inflammatory gene expression in older adults. Copyright © 2012 Elsevier Inc. All rights reserved.

  11. Analysis of baseline and cisplatin-inducible gene expression in Fanconi anemia cells using oligonucleotide-based microarrays

    Directory of Open Access Journals (Sweden)

    Liu Johnson M

    2002-11-01

    Full Text Available Abstract Background Patients with Fanconi anemia (FA suffer from multiple defects, most notably of the hematological compartment (bone marrow failure, and susceptibility to cancer. Cells from FA patients show increased spontaneous chromosomal damage, which is aggravated by exposure to low concentrations of DNA cross-linking agents such as mitomycin C or cisplatin. Five of the identified FA proteins form a nuclear core complex. However, the molecular function of these proteins remains obscure. Methods Oligonucleotide microarrays were used to compare the expression of approximately 12,000 genes from FA cells with matched controls. Expression profiles were studied in lymphoblastoid cell lines derived from three different FA patients, one from the FA-A and two from the FA-C complementation groups. The isogenic control cell lines were obtained by either transfecting the cells with vectors expressing the complementing cDNAs or by using a spontaneous revertant cell line derived from the same patient. In addition, we analyzed expression profiles from two cell line couples at several time points after a 1-hour pulse treatment with a discriminating dose of cisplatin. Results Analysis of the expression profiles showed differences in expression of a number of genes, many of which have unknown function or are difficult to relate to the FA defect. However, from a selected number of proteins involved in cell cycle regulation, DNA repair and chromatin structure, Western blot analysis showed that p21waf1/Cip1 was significantly upregulated after low dose cisplatin treatment in FA cells specifically (as well as being expressed at elevated levels in untreated FA cells. Conclusions The observed increase in expression of p21waf1/Cip1 after treatment of FA cells with crosslinkers suggests that the sustained elevated levels of p21waf1/Cip1 in untreated FA cells detected by Western blot analysis likely reflect increased spontaneous damage in these cells.

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

    International Nuclear Information System (INIS)

    Salem, Tamer Z.; Zhang, Fengrui; Thiem, Suzanne M.

    2013-01-01

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

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2013-01-20

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

  14. The evolution of gene expression in primates

    OpenAIRE

    Tashakkori Ghanbarian, Avazeh

    2015-01-01

    The evolution of a gene’s expression profile is commonly assumed to be independent of its genomic neighborhood. This is, however, in contrast to what we know about the lack of autonomy between expression of neighboring genes 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 e...

  15. Mining pathway associations for disease-related pathway activity analysis based on gene expression and methylation data.

    Science.gov (United States)

    Lee, Hyeonjeong; Shin, Miyoung

    2017-01-01

    The problem of discovering genetic markers as disease signatures is of great significance for the successful diagnosis, treatment, and prognosis of complex diseases. Even if many earlier studies worked on identifying disease markers from a variety of biological resources, they mostly focused on the markers of genes or gene-sets (i.e., pathways). However, these markers may not be enough to explain biological interactions between genetic variables that are related to diseases. Thus, in this study, our aim is to investigate distinctive associations among active pathways (i.e., pathway-sets) shown each in case and control samples which can be observed from gene expression and/or methylation data. The pathway-sets are obtained by identifying a set of associated pathways that are often active together over a significant number of class samples. For this purpose, gene expression or methylation profiles are first analyzed to identify significant (active) pathways via gene-set enrichment analysis. Then, regarding these active pathways, an association rule mining approach is applied to examine interesting pathway-sets in each class of samples (case or control). By doing so, the sets of associated pathways often working together in activity profiles are finally chosen as our distinctive signature of each class. The identified pathway-sets are aggregated into a pathway activity network (PAN), which facilitates the visualization of differential pathway associations between case and control samples. From our experiments with two publicly available datasets, we could find interesting PAN structures as the distinctive signatures of breast cancer and uterine leiomyoma cancer, respectively. Our pathway-set markers were shown to be superior or very comparable to other genetic markers (such as genes or gene-sets) in disease classification. Furthermore, the PAN structure, which can be constructed from the identified markers of pathway-sets, could provide deeper insights into

  16. Identification of co-expression gene networks, regulatory genes and pathways for obesity based on adipose tissue RNA Sequencing in a porcine model

    DEFF Research Database (Denmark)

    Kogelman, Lisette; Cirera Salicio, Susanna; Zhernakova, Daria V.

    2014-01-01

    interactions. Identification of co-expressed and regulatory genes in RNA extracted from relevant tissues representing lean and obese individuals provides an entry point for the identification of genes and pathways of importance to the development of obesity. The pig, an omnivorous animal, is an excellent model...... (modules). Additionally, regulator genes were detected using Lemon-Tree algorithms. Results WGCNA revealed five modules which were strongly correlated with at least one obesity-related phenotype (correlations ranging from -0.54 to 0.72, P ... the association between obesity and other diseases, like osteoporosis (osteoclast differentiation, P = 1.4E-7), and immune-related complications (e.g. Natural killer cell mediated cytotoxity, P = 3.8E-5; B cell receptor signaling pathway, P = 7.2E-5). Lemon-Tree identified three potential regulator genes, using...

  17. 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......-based gene-lookup webservices, called HemaExplorer and BloodSpot. These web-services support the aim of making data and analysis of haematopoietic cells from mouse and human accessible for researchers without bioinformatics expertise. Finally, in order to aid the analysis of the very limited number...

  18. Microarray-Based Analysis of the Differential Expression of Melanin Synthesis Genes in Dark and Light-Muzzle Korean Cattle

    OpenAIRE

    Kim, Sang Hwan; Hwang, Sue Yun; Yoon, Jong Taek

    2014-01-01

    The coat color of mammals is determined by the melanogenesis pathway, which is responsible for maintaining the balance between black-brown eumelanin and yellow-reddish pheomelanin. It is also believed that the color of the bovine muzzle is regulated in a similar manner; however, the molecular mechanism underlying pigment deposition in the dark-muzzle has yet to be elucidated. The aim of the present study was to identify melanogenesis-associated genes that are differentially expressed in the d...

  19. Expression regulation of design process gene in product design

    DEFF Research Database (Denmark)

    Li, Bo; Fang, Lusheng; Li, Bo

    2011-01-01

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

  20. Gene expression patterns regulating embryogenesis based on the integrated de novo transcriptome assembly of the Japanese flounder.

    Science.gov (United States)

    Fu, Yuanshuai; Jia, Liang; Shi, Zhiyi; Zhang, Junling; Li, Wenjuan

    2017-06-01

    The Japanese flounder (Paralichthys olivaceus) is one of the most important commercial and biological marine fishes. However, the molecular biology involved during embryogenesis and early development of the Japanese flounder remains largely unknown due to a lack of genomic resources. A comprehensive and integrated transcriptome is necessary to study the molecular mechanisms of early development and to allow for the detailed characterization of gene expression patterns during embryogenesis; this approach is critical to understanding the processes that occur prior to mesectoderm formation during early embryonic development. In this study, more than 117.8 million 100bp PE reads were generated from pooled RNA extracted from unfertilized eggs to 41dph (days post-hatching) embryos and were sequenced using Illumina pair-end sequencing technology. In total, 121,513 transcripts (≥200bp) were obtained using de novo assembly. A sequence similarity search indicated that 52,338 transcripts show significant similarity to 22,462 known proteins from the NCBI non-redundant database and the Swiss-Prot protein database and were annotated using Blast2GO. GO terms were assigned to 44,627 transcripts with 12,006 functional terms, and 10,024 transcripts were assigned to 133 KEGG pathways. Furthermore, gene expression differences between the unfertilized egg and the gastrula embryo were analysed using Illumina RNA-Seq with single-read sequencing technology, and 24,837 differentially and specifically expressed transcripts were identified and included 5,286 annotated transcripts and 19,569 non-annotated transcripts. All of the expressed transcripts in the unfertilized egg and gastrula embryo were further classified as maternal, zygotic, or maternal-zygotic transcripts, which may help us to understand the roles of these transcripts during the embryonic development of the Japanese flounder. Thus, the results will contribute to an improved understanding of the gene expression patterns and

  1. Molecular Characterization of Heterologous HIV-1gp120 Gene Expression Disruption in Mycobacterium bovis BCG Host Strain: A Critical Issue for Engineering Mycobacterial Based-Vaccine Vectors

    Science.gov (United States)

    Joseph, Joan; Fernández-Lloris, Raquel; Pezzat, Elías; Saubi, Narcís; Cardona, Pere-Joan; Mothe, Beatriz; Gatell, Josep Maria

    2010-01-01

    Mycobacterium bovis Bacillus Calmette-Guérin (BCG) as a live vector of recombinant bacterial vaccine is a promising system to be used. In this study, we evaluate the disrupted expression of heterologous HIV-1gp120 gene in BCG Pasteur host strain using replicative vectors pMV261 and pJH222. pJH222 carries a lysine complementing gene in BCG lysine auxotrophs. The HIV-1 gp120 gene expression was regulated by BCG hsp60 promoter (in plasmid pMV261) and Mycobacteria spp. α-antigen promoter (in plasmid pJH222). Among 14 rBCG:HIV-1gp120 (pMV261) colonies screened, 12 showed a partial deletion and two showed a complete deletion. However, deletion was not observed in all 10 rBCG:HIV-1gp120 (pJH222) colonies screened. In this study, we demonstrated that E. coli/Mycobacterial expression vectors bearing a weak promoter and lysine complementing gene in a recombinant lysine auxotroph of BCG could prevent genetic rearrangements and disruption of HIV 1gp120 gene expression, a key issue for engineering Mycobacterial based vaccine vectors. PMID:20617151

  2. Molecular Characterization of Heterologous HIV-1gp120 Gene Expression Disruption in Mycobacterium bovis BCG Host Strain: A Critical Issue for Engineering Mycobacterial Based-Vaccine Vectors

    Directory of Open Access Journals (Sweden)

    Joan Joseph

    2010-01-01

    Full Text Available Mycobacterium bovis Bacillus Calmette-Guérin (BCG as a live vector of recombinant bacterial vaccine is a promising system to be used. In this study, we evaluate the disrupted expression of heterologous HIV-1gp120 gene in BCG Pasteur host strain using replicative vectors pMV261 and pJH222. pJH222 carries a lysine complementing gene in BCG lysine auxotrophs. The HIV-1 gp120 gene expression was regulated by BCG hsp60 promoter (in plasmid pMV261 and Mycobacteria spp. α-antigen promoter (in plasmid pJH222. Among 14 rBCG:HIV-1gp120 (pMV261 colonies screened, 12 showed a partial deletion and two showed a complete deletion. However, deletion was not observed in all 10 rBCG:HIV-1gp120 (pJH222 colonies screened. In this study, we demonstrated that E. coli/Mycobacterial expression vectors bearing a weak promoter and lysine complementing gene in a recombinant lysine auxotroph of BCG could prevent genetic rearrangements and disruption of HIV 1gp120 gene expression, a key issue for engineering Mycobacterial based vaccine vectors.

  3. A combined blood based gene expression and plasma protein abundance signature for diagnosis of epithelial ovarian cancer - a study of the OVCAD consortium

    International Nuclear Information System (INIS)

    Pils, Dietmar; Sehouli, Jalid; Braicu, Ioana; Vergote, Ignace; Van Gorp, Toon; Mahner, Sven; Concin, Nicole; Speiser, Paul; Zeillinger, Robert; Tong, Dan; Hager, Gudrun; Obermayr, Eva; Aust, Stefanie; Heinze, Georg; Kohl, Maria; Schuster, Eva; Wolf, Andrea

    2013-01-01

    The immune system is a key player in fighting cancer. Thus, we sought to identify a molecular ‘immune response signature’ indicating the presence of epithelial ovarian cancer (EOC) and to combine this with a serum protein biomarker panel to increase the specificity and sensitivity for earlier detection of EOC. Comparing the expression of 32,000 genes in a leukocytes fraction from 44 EOC patients and 19 controls, three uncorrelated shrunken centroid models were selected, comprised of 7, 14, and 6 genes. A second selection step using RT-qPCR data and significance analysis of microarrays yielded 13 genes (AP2A1, B4GALT1, C1orf63, CCR2, CFP, DIS3, NEAT1, NOXA1, OSM, PAPOLG, PRIC285, ZNF419, and BC037918) which were finally used in 343 samples (90 healthy, six cystadenoma, eight low malignant potential tumor, 19 FIGO I/II, and 220 FIGO III/IV EOC patients). Using new 65 controls and 224 EOC patients (thereof 14 FIGO I/II) the abundances of six plasma proteins (MIF, prolactin, CA125, leptin, osteopondin, and IGF2) was determined and used in combination with the expression values from the 13 genes for diagnosis of EOC. Combined diagnostic models using either each five gene expression and plasma protein abundance values or 13 gene expression and six plasma protein abundance values can discriminate controls from patients with EOC with Receiver Operator Characteristics Area Under the Curve values of 0.998 and bootstrap .632+ validated classification errors of 3.1% and 2.8%, respectively. The sensitivities were 97.8% and 95.6%, respectively, at a set specificity of 99.6%. The combination of gene expression and plasma protein based blood derived biomarkers in one diagnostic model increases the sensitivity and the specificity significantly. Such a diagnostic test may allow earlier diagnosis of epithelial ovarian cancer

  4. A safer, urea-based in situ hybridization method improves detection of gene expression in diverse animal species.

    Science.gov (United States)

    Sinigaglia, Chiara; Thiel, Daniel; Hejnol, Andreas; Houliston, Evelyn; Leclère, Lucas

    2018-02-01

    In situ hybridization is a widely employed technique allowing spatial visualization of gene expression in fixed specimens. It has greatly advanced our understanding of biological processes, including developmental regulation. In situ protocols are today routinely followed in numerous laboratories, and although details might change, they all include a hybridization step, where specific antisense RNA or DNA probes anneal to the target nucleic acid sequence. This step is generally carried out at high temperatures and in a denaturing solution, called hybridization buffer, commonly containing 50% (v/v) formamide - a hazardous chemical. When applied to the soft-bodied hydrozoan medusa Clytia hemisphaerica, we found that this traditional hybridization approach was not fully satisfactory, causing extensive deterioration of morphology and tissue texture which compromised our observation and interpretation of results. We thus tested alternative solutions for in situ detection of gene expression and, inspired by optimized protocols for Northern and Southern blot analysis, we substituted the 50% formamide with an equal volume of 8M urea solution in the hybridization buffer. Our new protocol not only yielded better morphologies and tissue consistency, but also notably improved the resolution of the signal, allowing more precise localization of gene expression and reducing aspecific staining associated with problematic areas. Given the improved results and reduced manipulation risks, we tested the urea protocol on other metazoans, two brachiopod species (Novocrania anomala and Terebratalia transversa) and the priapulid worm Priapulus caudatus, obtaining a similar reduction of aspecific probe binding. Overall, substitution of formamide by urea during in situ hybridization offers a safer alternative, potentially of widespread use in research, medical and teaching contexts. We encourage other workers to test this approach on their study organisms, and hope that they will also

  5. Expression profiling identifies genes involved in emphysema severity

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    Bowman Rayleen V

    2009-09-01

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

  6. Methods for monitoring multiple gene expression

    Energy Technology Data Exchange (ETDEWEB)

    Berka, Randy [Davis, CA; Bachkirova, Elena [Davis, CA; Rey, Michael [Davis, CA

    2012-05-01

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

  7. Methods for monitoring multiple gene expression

    Energy Technology Data Exchange (ETDEWEB)

    Berka, Randy; Bachkirova, Elena; Rey, Michael

    2013-10-01

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

  8. BCDForest: a boosting cascade deep forest model towards the classification of cancer subtypes based on gene expression data.

    Science.gov (United States)

    Guo, Yang; Liu, Shuhui; Li, Zhanhuai; Shang, Xuequn

    2018-04-11

    The classification of cancer subtypes is of great importance to cancer disease diagnosis and therapy. Many supervised learning approaches have been applied to cancer subtype classification in the past few years, especially of deep learning based approaches. Recently, the deep forest model has been proposed as an alternative of deep neural networks to learn hyper-representations by using cascade ensemble decision trees. It has been proved that the deep forest model has competitive or even better performance than deep neural networks in some extent. However, the standard deep forest model may face overfitting and ensemble diversity challenges when dealing with small sample size and high-dimensional biology data. In this paper, we propose a deep learning model, so-called BCDForest, to address cancer subtype classification on small-scale biology datasets, which can be viewed as a modification of the standard deep forest model. The BCDForest distinguishes from the standard deep forest model with the following two main contributions: First, a named multi-class-grained scanning method is proposed to train multiple binary classifiers to encourage diversity of ensemble. Meanwhile, the fitting quality of each classifier is considered in representation learning. Second, we propose a boosting strategy to emphasize more important features in cascade forests, thus to propagate the benefits of discriminative features among cascade layers to improve the classification performance. Systematic comparison experiments on both microarray and RNA-Seq gene expression datasets demonstrate that our method consistently outperforms the state-of-the-art methods in application of cancer subtype classification. The multi-class-grained scanning and boosting strategy in our model provide an effective solution to ease the overfitting challenge and improve the robustness of deep forest model working on small-scale data. Our model provides a useful approach to the classification of cancer subtypes

  9. Evaluation of the hormonal state of columnar apple trees (Malus x domestica) based on high throughput gene expression studies.

    Science.gov (United States)

    Krost, Clemens; Petersen, Romina; Lokan, Stefanie; Brauksiepe, Bastienne; Braun, Peter; Schmidt, Erwin R

    2013-02-01

    The columnar phenotype of apple trees (Malus x domestica) is characterized by a compact growth habit with fruit spurs instead of lateral branches. These properties provide significant economic advantages by enabling high density plantings. The columnar growth results from the presence of a dominant allele of the gene Columnar (Co) located on chromosome 10 which can appear in a heterozygous (Co/co) or homozygous (Co/Co) state. Although two deep sequencing approaches could shed some light on the transcriptome of columnar shoot apical meristems (SAMs), the molecular mechanisms of columnar growth are not yet elaborated. Since the influence of phytohormones is believed to have a pivotal role in the establishment of the phenotype, we performed RNA-Seq experiments to study genes associated with hormone homeostasis and clearly affected by the presence of Co. Our results provide a molecular explanation for earlier findings on the hormonal state of columnar apple trees. Additionally, they allow hypotheses on how the columnar phenotype might develop. Furthermore, we show a statistically approved enrichment of differentially regulated genes on chromosome 10 in the course of validating RNA-Seq results using additional gene expression studies.

  10. A probe-based qRT-PCR method to profile immunological gene expression in blood of captive beluga whales (Delphinapterus leucas

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    Ming-An Tsai

    2017-09-01

    Full Text Available Cytokines are fundamental for a functioning immune system, and thus potentially serve as important indicators of animal health. Quantitation of mRNA using quantitative reverse transcription polymerase chain reaction (qRT-PCR is an established immunological technique. It is particularly suitable for detecting the expression of proteins against which monoclonal antibodies are not available. In this study, we developed a probe-based quantitative gene expression assay for immunological assessment of captive beluga whales (Delphinapterus leucas that is one of the most common cetacean species on display in aquariums worldwide. Six immunologically relevant genes (IL-2Rα, -4, -10, -12, TNFα, and IFNγ were selected for analysis, and two validated housekeeping genes (PGK1 and RPL4 with stable expression were used as reference genes. Sixteen blood samples were obtained from four animals with different health conditions and stored in RNAlater™ solution. These samples were used for RNA extraction followed by qRT-PCR analysis. Analysis of gene transcripts was performed by relative quantitation using the comparative Cq method with the integration of amplification efficiency and two reference genes. The expression levels of each gene in the samples from clinically healthy animals were normally distributed. Transcript outliers for IL-2Rα, IL-4, IL-12, TNFα, and IFNγ were noticed in four samples collected from two clinically unhealthy animals. This assay has the potential to identify immune system deviation from normal state, which is caused by health problems. Furthermore, knowing the immune status of captive cetaceans could help both trainers and veterinarians in implementing preventive approaches prior to disease onset.

  11. Deriving Trading Rules Using Gene Expression Programming

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    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.

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

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    Georg K Gerber

    2007-08-01

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

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

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    Sadhukhan Provash

    2004-06-01

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

  14. Abiotic conditions leading to FUM gene expression and fumonisin accumulation by Fusarium proliferatum strains grown on a wheat-based substrate.

    Science.gov (United States)

    Cendoya, Eugenia; Pinson-Gadais, Laetitia; Farnochi, María C; Ramirez, María L; Chéreau, Sylvain; Marcheguay, Giselè; Ducos, Christine; Barreau, Christian; Richard-Forget, Florence

    2017-07-17

    Fusarium proliferatum produces fumonisins B not only on maize but also on diverse crops including wheat. Using a wheat-based medium, the effects of abiotic factors, temperature and water activity (a W ), on growth, fumonisin biosynthesis, and expression of FUM genes were compared for three F. proliferatum strains isolated from durum wheat in Argentina. Although all isolates showed similar profiles of growth, the fumonisin production profiles were slightly different. Regarding FUM gene transcriptional control, both FUM8 and FUM19 expression showed similar behavior in all tested conditions. For both genes, expression at 25°C correlated with fumonisin production, regardless of the a w conditions. However, at 15°C, these two genes were as highly expressed as at 25°C although the amounts of toxin were very weak, suggesting that the kinetics of fumonisin production was slowed at 15°C. This study provides useful baseline data on conditions representing a low or a high risk for contamination of wheat kernels with fumonisins. Copyright © 2017 Elsevier B.V. All rights reserved.

  15. Blood Gene Expression Predicts Bronchiolitis Obliterans Syndrome

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    Richard Danger

    2018-01-01

    Full Text Available Bronchiolitis obliterans syndrome (BOS, the main manifestation of chronic lung allograft dysfunction, leads to poor long-term survival after lung transplantation. Identifying predictors of BOS is essential to prevent the progression of dysfunction before irreversible damage occurs. By using a large set of 107 samples from lung recipients, we performed microarray gene expression profiling of whole blood to identify early biomarkers of BOS, including samples from 49 patients with stable function for at least 3 years, 32 samples collected at least 6 months before BOS diagnosis (prediction group, and 26 samples at or after BOS diagnosis (diagnosis group. An independent set from 25 lung recipients was used for validation by quantitative PCR (13 stables, 11 in the prediction group, and 8 in the diagnosis group. We identified 50 transcripts differentially expressed between stable and BOS recipients. Three genes, namely POU class 2 associating factor 1 (POU2AF1, T-cell leukemia/lymphoma protein 1A (TCL1A, and B cell lymphocyte kinase, were validated as predictive biomarkers of BOS more than 6 months before diagnosis, with areas under the curve of 0.83, 0.77, and 0.78 respectively. These genes allow stratification based on BOS risk (log-rank test p < 0.01 and are not associated with time posttransplantation. This is the first published large-scale gene expression analysis of blood after lung transplantation. The three-gene blood signature could provide clinicians with new tools to improve follow-up and adapt treatment of patients likely to develop BOS.

  16. Algal Functional Annotation Tool: a web-based analysis suite to functionally interpret large gene lists using integrated annotation and expression data

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    Merchant Sabeeha S

    2011-07-01

    Full Text Available Abstract Background Progress in genome sequencing is proceeding at an exponential pace, and several new algal genomes are becoming available every year. One of the challenges facing the community is the association of protein sequences encoded in the genomes with biological function. While most genome assembly projects generate annotations for predicted protein sequences, they are usually limited and integrate functional terms from a limited number of databases. Another challenge is the use of annotations to interpret large lists of 'interesting' genes generated by genome-scale datasets. Previously, these gene lists had to be analyzed across several independent biological databases, often on a gene-by-gene basis. In contrast, several annotation databases, such as DAVID, integrate data from multiple functional databases and reveal underlying biological themes of large gene lists. While several such databases have been constructed for animals, none is currently available for the study of algae. Due to renewed interest in algae as potential sources of biofuels and the emergence of multiple algal genome sequences, a significant need has arisen for such a database to process the growing compendiums of algal genomic data. Description The Algal Functional Annotation Tool is a web-based comprehensive analysis suite integrating annotation data from several pathway, ontology, and protein family databases. The current version provides annotation for the model alga Chlamydomonas reinhardtii, and in the future will include additional genomes. The site allows users to interpret large gene lists by identifying associated functional terms, and their enrichment. Additionally, expression data for several experimental conditions were compiled and analyzed to provide an expression-based enrichment search. A tool to search for functionally-related genes based on gene expression across these conditions is also provided. Other features include dynamic visualization of

  17. RNA-Seq-based analysis of the physiologic cold shock-induced changes in Moraxella catarrhalis gene expression.

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    Violeta Spaniol

    Full Text Available BACKGROUND: Moraxella catarrhalis, a major nasopharyngeal pathogen of the human respiratory tract, is exposed to rapid downshifts of environmental temperature when humans breathe cold air. The prevalence of pharyngeal colonization and respiratory tract infections caused by M. catarrhalis is greatest in winter. We investigated how M. catarrhalis uses the physiologic exposure to cold air to regulate pivotal survival systems that may contribute to M. catarrhalis virulence. RESULTS: In this study we used the RNA-seq techniques to quantitatively catalogue the transcriptome of M. catarrhalis exposed to a 26 °C cold shock or to continuous growth at 37 °C. Validation of RNA-seq data using quantitative RT-PCR analysis demonstrated the RNA-seq results to be highly reliable. We observed that a 26 °C cold shock induces the expression of genes that in other bacteria have been related to virulence a strong induction was observed for genes involved in high affinity phosphate transport and iron acquisition, indicating that M. catarrhalis makes a better use of both phosphate and iron resources after exposure to cold shock. We detected the induction of genes involved in nitrogen metabolism, as well as several outer membrane proteins, including ompA, m35-like porin and multidrug efflux pump (acrAB indicating that M. catarrhalis remodels its membrane components in response to downshift of temperature. Furthermore, we demonstrate that a 26 °C cold shock enhances the induction of genes encoding the type IV pili that are essential for natural transformation, and increases the genetic competence of M. catarrhalis, which may facilitate the rapid spread and acquisition of novel virulence-associated genes. CONCLUSION: Cold shock at a physiologically relevant temperature of 26 °C induces in M. catarrhalis a complex of adaptive mechanisms that could convey novel pathogenic functions and may contribute to enhanced colonization and virulence.

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

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    Nobutaka Hanagata, Taro Takemura and Takashi Minowa

    2010-01-01

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

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

    International Nuclear Information System (INIS)

    Hanagata, Nobutaka; Takemura, Taro; Minowa, Takashi

    2010-01-01

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

  20. Chromatin loops, gene positioning, and gene expression

    NARCIS (Netherlands)

    Holwerda, S.; de Laat, W.

    2012-01-01

    Technological developments and intense research over the last years have led to a better understanding of the 3D structure of the genome and its influence on genome function inside the cell nucleus. We will summarize topological studies performed on four model gene loci: the alpha- and beta-globin

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

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    Turner Renee J

    2009-08-01

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

  2. Serial analysis of gene expression (SAGE)

    NARCIS (Netherlands)

    van Ruissen, Fred; Baas, Frank

    2007-01-01

    In 1995, serial analysis of gene expression (SAGE) was developed as a versatile tool for gene expression studies. SAGE technology does not require pre-existing knowledge of the genome that is being examined and therefore SAGE can be applied to many different model systems. In this chapter, the SAGE

  3. Selection and validation of potato candidate genes for maturity corrected resistance to Phytophthora infestans based on differential expression combined with SNP association and linkage mapping

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    Meki Shehabu Muktar

    2015-09-01

    Full Text Available Late blight of potato (Solanum tuberosum L. caused by the oomycete Phytophthora infestans (Mont. de Bary, is one of the most important bottlenecks of potato production worldwide. Cultivars with high levels of durable, race unspecific, quantitative resistance are part of a solution to this problem. However, breeding for quantitative resistance is hampered by the correlation between resistance and late plant maturity, which is an undesirable agricultural attribute. The objectives of our research are (i the identification of genes that condition quantitative resistance to P. infestans not compromised by late plant maturity and (ii the discovery of diagnostic single nucleotide polymorphism (SNP markers to be used as molecular tools to increase efficiency and precision of resistance breeding. Twenty two novel candidate genes were selected based on comparative transcript profiling by SuperSAGE (serial analysis of gene expression in groups of plants with contrasting levels of maturity corrected resistance (MCR. Reproducibility of differential expression was tested by quantitative real time PCR and allele specific pyrosequencing in four new sets of genotype pools with contrasting late blight resistance levels, at three infection time points and in three independent infection experiments. Reproducibility of expression patterns ranged from 28% to 97%. Association mapping in a panel of 184 tetraploid cultivars identified SNPs in five candidate genes that were associated with MCR. These SNPs can be used in marker-assisted resistance breeding. Linkage mapping in two half-sib families (n = 111 identified SNPs in three candidate genes that were linked with MCR. The differentially expressed genes that showed association and/or linkage with MCR putatively function in phytosterol synthesis, fatty acid synthesis, asparagine synthesis, chlorophyll synthesis, cell wall modification and in the response to pathogen elicitors.

  4. The Malus domestica sugar transporter gene family: identifications based on genome and expression profiling related to the accumulation of fruit sugars.

    Science.gov (United States)

    Wei, Xiaoyu; Liu, Fengli; Chen, Cheng; Ma, Fengwang; Li, Mingjun

    2014-01-01

    In plants, sugar transporters are involved not only in long-distance transport, but also in sugar accumulations in sink cells. To identify members of sugar transporter gene families and to analyze their function in fruit sugar accumulation, we conducted a phylogenetic analysis of the Malus domestica genome. Expression profiling was performed with shoot tips, mature leaves, and developed fruit of "Gala" apple. Genes for sugar alcohol [including 17 sorbitol transporters (SOTs)], sucrose, and monosaccharide transporters, plus SWEET genes, were selected as candidates in 31, 9, 50, and 27 loci, respectively, of the genome. The monosaccharide transporter family appears to include five subfamilies (30 MdHTs, 8 MdEDR6s, 5 MdTMTs, 3 MdvGTs, and 4 MdpGLTs). Phylogenetic analysis of the protein sequences indicated that orthologs exist among Malus, Vitis, and Arabidopsis. Investigations of transcripts revealed that 68 candidate transporters are expressed in apple, albeit to different extents. Here, we discuss their possible roles based on the relationship between their levels of expression and sugar concentrations. The high accumulation of fructose in apple fruit is possibly linked to the coordination and cooperation between MdTMT1/2 and MdEDR6. By contrast, these fruits show low MdSWEET4.1 expression and a high flux of fructose produced from sorbitol. Our study provides an exhaustive survey of sugar transporter genes and demonstrates that sugar transporter gene families in M. domestica are comparable to those in other species. Expression profiling of these transporters will likely contribute to improving our understanding of their physiological functions in fruit formation and the development of sweetness properties.

  5. The Malus domestica sugar transporter gene family: identifications based on genome and expression profiling related to the accumulation of fruit sugars

    Directory of Open Access Journals (Sweden)

    Xiaoyu eWei

    2014-11-01

    Full Text Available In plants, sugar transporters are involved not only in long-distance transport, but also in sugar accumulations in sink cells. To identify members of sugar transporter gene families and to analyze their function in fruit sugar accumulation, we conducted a phylogenetic analysis of the Malus domestica genome. Expression profiling was performed with shoot tips, mature leaves, and developed fruit of ‘Gala’ apple. Genes for sugar alcohol (including 17 sorbitol transporters, sucrose, and monosaccharide transporters, plus SWEET genes, were selected as candidates in 31, 9, 50, and 27 loci, respectively, of the genome. The monosaccharide transporter family appears to include five subfamilies (30 MdHTs, 8 MdEDR6s, 5 MdTMTs, 3 MdvGTs, and 4 MdpGLTs. Phylogenetic analysis of the protein sequences indicated that orthologs exist among Malus, Vitis, and Arabidopsis. Investigations of transcripts revealed that 68 candidate transporters are expressed in apple, albeit to different extents. Here, we discuss their possible roles based on the relationship between their levels of expression and sugar concentrations. The high accumulation of fructose in apple fruit is possibly linked to the coordination and cooperation between MdTMT1/2 and MdEDR6. By contrast, these fruits show low MdSWEET4.1 expression and a high flux of fructose produced from sorbitol. Our study provides an exhaustive survey of sugar transporter genes and demonstrates that sugar transporter gene families in M. domestica are comparable to those in other species. Expression profiling of these transporters will likely contribute to improving our understanding of their physiological functions in fruit formation and the development of sweetness properties.

  6. Expression of Sox genes in tooth development.

    Science.gov (United States)

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

    2015-01-01

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

  7. Positron emission tomography imaging of gene expression

    International Nuclear Information System (INIS)

    Tang Ganghua

    2001-01-01

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

  8. In search of functional association from time-series microarray data based on the change trend and level of gene expression

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    Zeng An-Ping

    2006-02-01

    Full Text Available Abstract Background The increasing availability of time-series expression data opens up new possibilities to study functional linkages of genes. Present methods used to infer functional linkages between genes from expression data are mainly based on a point-to-point comparison. Change trends between consecutive time points in time-series data have been so far not well explored. Results In this work we present a new method based on extracting main features of the change trend and level of gene expression between consecutive time points. The method, termed as trend correlation (TC, includes two major steps: 1, calculating a maximal local alignment of change trend score by dynamic programming and a change trend correlation coefficient between the maximal matched change levels of each gene pair; 2, inferring relationships of gene pairs based on two statistical extraction procedures. The new method considers time shifts and inverted relationships in a similar way as the local clustering (LC method but the latter is merely based on a point-to-point comparison. The TC method is demonstrated with data from yeast cell cycle and compared with the LC method and the widely used Pearson correlation coefficient (PCC based clustering method. The biological significance of the gene pairs is examined with several large-scale yeast databases. Although the TC method predicts an overall lower number of gene pairs than the other two methods at a same p-value threshold, the additional number of gene pairs inferred by the TC method is considerable: e.g. 20.5% compared with the LC method and 49.6% with the PCC method for a p-value threshold of 2.7E-3. Moreover, the percentage of the inferred gene pairs consistent with databases by our method is generally higher than the LC method and similar to the PCC method. A significant number of the gene pairs only inferred by the TC method are process-identity or function-similarity pairs or have well-documented biological

  9. DNA sequence of 15 base pairs is sufficient to mediate both glucocorticoid and progesterone induction of gene expression

    International Nuclear Information System (INIS)

    Straehle, U.; Klock, G.; Schuetz, G.

    1987-01-01

    To define the recognition sequence of the glucocorticoid receptor and its relationship with that of the progesterone receptor, oligonucleotides derived from the glucocorticoid response element of the tyrosine aminotransferase gene were tested upstream of a heterologous promoter for their capacity to mediate effects of these two steroids. The authors show that a 15-base-pair sequence with partial symmetry is sufficient to confer glucocorticoid inducibility on the promoter of the herpes simplex virus thymidine kinase gene. The same 15-base-pair sequence mediates induction by progesterone. Point mutations in the recognition sequence affect inducibility by glucocorticoids and progesterone similarly. Together with the strong conservation of the sequence of the DNA-binding domain of the two receptors, these data suggest that both proteins recognize a sequence that is similar, if not the same

  10. 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

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

    Directory of Open Access Journals (Sweden)

    Lucie Kosinová

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

  12. Blood cell gene expression profiling in rheumatoid arthritis. Discriminative genes and effect of rheumatoid factor

    DEFF Research Database (Denmark)

    Bovin, Lone Frier; Rieneck, Klaus; Workman, Christopher

    2004-01-01

    To study the pathogenic importance of the rheumatoid factor (RF) in rheumatoid arthritis (RA) and to identify genes differentially expressed in patients and healthy individuals, total RNA was isolated from peripheral blood mononuclear cells (PBMC) from eight RF-positive and six RF-negative RA...... patients, and seven healthy controls. Gene expression of about 10,000 genes were examined using oligonucleotide-based DNA chip microarrays. The analyses showed no significant differences in PBMC expression patterns from RF-positive and RF-negative patients. However, comparisons of gene expression patterns...

  13. Molecular mechanisms of curcumin action: gene expression.

    Science.gov (United States)

    Shishodia, Shishir

    2013-01-01

    Curcumin derived from the tropical plant Curcuma longa has a long history of use as a dietary agent, food preservative, and in traditional Asian medicine. It has been used for centuries to treat biliary disorders, anorexia, cough, diabetic wounds, hepatic disorders, rheumatism, and sinusitis. The preventive and therapeutic properties of curcumin are associated with its antioxidant, anti-inflammatory, and anticancer properties. Extensive research over several decades has attempted to identify the molecular mechanisms of curcumin action. Curcumin modulates numerous molecular targets by altering their gene expression, signaling pathways, or through direct interaction. Curcumin regulates the expression of inflammatory cytokines (e.g., TNF, IL-1), growth factors (e.g., VEGF, EGF, FGF), growth factor receptors (e.g., EGFR, HER-2, AR), enzymes (e.g., COX-2, LOX, MMP9, MAPK, mTOR, Akt), adhesion molecules (e.g., ELAM-1, ICAM-1, VCAM-1), apoptosis related proteins (e.g., Bcl-2, caspases, DR, Fas), and cell cycle proteins (e.g., cyclin D1). Curcumin modulates the activity of several transcription factors (e.g., NF-κB, AP-1, STAT) and their signaling pathways. Based on its ability to affect multiple targets, curcumin has the potential for the prevention and treatment of various diseases including cancers, arthritis, allergies, atherosclerosis, aging, neurodegenerative disease, hepatic disorders, obesity, diabetes, psoriasis, and autoimmune diseases. This review summarizes the molecular mechanisms of modulation of gene expression by curcumin. Copyright © 2012 International Union of Biochemistry and Molecular Biology, Inc.

  14. Adaptive Evolution of Gene Expression in Drosophila.

    Science.gov (United States)

    Nourmohammad, Armita; Rambeau, Joachim; Held, Torsten; Kovacova, Viera; Berg, Johannes; Lässig, Michael

    2017-08-08

    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. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

  15. RNAi and Homologous Over-Expression Based Functional Approaches Reveal Triterpenoid Synthase Gene-Cycloartenol Synthase Is Involved in Downstream Withanolide Biosynthesis in Withania somnifera.

    Directory of Open Access Journals (Sweden)

    Smrati Mishra

    Full Text Available Withania somnifera Dunal, is one of the most commonly used medicinal plant in Ayurvedic and indigenous medicine traditionally owing to its therapeutic potential, because of major chemical constituents, withanolides. Withanolide biosynthesis requires the activities of several enzymes in vivo. Cycloartenol synthase (CAS is an important enzyme in the withanolide biosynthetic pathway, catalyzing cyclization of 2, 3 oxidosqualene into cycloartenol. In the present study, we have cloned full-length WsCAS from Withania somnifera by homology-based PCR method. For gene function investigation, we constructed three RNAi gene-silencing constructs in backbone of RNAi vector pGSA and a full-length over-expression construct. These constructs were transformed in Agrobacterium strain GV3101 for plant transformation in W. somnifera. Molecular and metabolite analysis was performed in putative Withania transformants. The PCR and Southern blot results showed the genomic integration of these RNAi and overexpression construct(s in Withania genome. The qRT-PCR analysis showed that the expression of WsCAS gene was considerably downregulated in stable transgenic silenced Withania lines compared with the non-transformed control and HPLC analysis showed that withanolide content was greatly reduced in silenced lines. Transgenic plants over expressing CAS gene displayed enhanced level of CAS transcript and withanolide content compared to non-transformed controls. This work is the first full proof report of functional validation of any metabolic pathway gene in W. somnifera at whole plant level as per our knowledge and it will be further useful to understand the regulatory role of different genes involved in the biosynthesis of withanolides.

  16. Using PCR to Target Misconceptions about Gene Expression

    Directory of Open Access Journals (Sweden)

    Leslie K. Wright

    2013-02-01

    Full Text Available We present a PCR-based laboratory exercise that can be used with first- or second-year biology students to help overcome common misconceptions about gene expression. Biology students typically do not have a clear understanding of the difference between genes (DNA and gene expression (mRNA/protein and often believe that genes exist in an organism or cell only when they are expressed. This laboratory exercise allows students to carry out a PCR-based experiment designed to challenge their misunderstanding of the difference between genes and gene expression. Students first transform E. coli with an inducible GFP gene containing plasmid and observe induced and un-induced colonies. The following exercise creates cognitive dissonance when actual PCR results contradict their initial (incorrect predictions of the presence of the GFP gene in transformed cells. Field testing of this laboratory exercise resulted in learning gains on both knowledge and application questions on concepts related to genes and gene expression.

  17. Tyrosine Kinase Gene Expression Profiling in Prostate Cancer

    National Research Council Canada - National Science Library

    Weier, Heinz-Ulrich

    2001-01-01

    ... of these genes parallels the progression of tumors to a more malignant phenotype. We developed a DNA micro-array based screening system to monitor the level of expression of tyrosine kinase (tk...

  18. Tyrosine Kinase Gene Expression Profiling in Prostate Cancer

    National Research Council Canada - National Science Library

    Weier, Heinz-Ulrich

    2002-01-01

    ... of these genes parallels the progression of tumors to a more malignant phenotype. We developed a DNA micro-array based screening system to monitor the level of expression of tyrosine kinase (tk...

  19. Gene expression in cerebral ischemia: a new approach for neuroprotection.

    Science.gov (United States)

    Millán, Mónica; Arenillas, Juan

    2006-01-01

    Cerebral ischemia is one of the strongest stimuli for gene induction in the brain. Hundreds of genes have been found to be induced by brain ischemia. Many genes are involved in neurodestructive functions such as excitotoxicity, inflammatory response and neuronal apoptosis. However, cerebral ischemia is also a powerful reformatting and reprogramming stimulus for the brain through neuroprotective gene expression. Several genes may participate in both cellular responses. Thus, isolation of candidate genes for neuroprotection strategies and interpretation of expression changes have been proven difficult. Nevertheless, many studies are being carried out to improve the knowledge of the gene activation and protein expression following ischemic stroke, as well as in the development of new therapies that modify biochemical, molecular and genetic changes underlying cerebral ischemia. Owing to the complexity of the process involving numerous critical genes expressed differentially in time, space and concentration, ongoing therapeutic efforts should be based on multiple interventions at different levels. By modification of the acute gene expression induced by ischemia or the apoptotic gene program, gene therapy is a promising treatment but is still in a very experimental phase. Some hurdles will have to be overcome before these therapies can be introduced into human clinical stroke trials. Copyright 2006 S. Karger AG, Basel.

  20. Development of a new comprehensive and reliable endometrial receptivity map (ER Map/ER Grade) based on RT-qPCR gene expression analysis.

    Science.gov (United States)

    Enciso, M; Carrascosa, J P; Sarasa, J; Martínez-Ortiz, P A; Munné, S; Horcajadas, J A; Aizpurua, J

    2018-02-01

    comparing LH + 2 and LH + 7 samples (paired t-test, P terms in this group of genes. Principal component analysis and discriminant functional analysis showed that 40 of the differentially expressed genes allowed accurate classification of samples according to endometrial status (proliferative, pre-receptive, receptive and post-receptive) in both fertile and infertile groups. N/A. To evaluate the efficacy of this new tool to improve ART outcomes, further investigations such as non-selection studies and randomized controlled trials will also be required. A new comprehensive system for human endometrial receptivity evaluation based on gene expression analysis has been developed. The identification of the optimal time for embryo transfer is essential to maximize the effectiveness of ART. This study is a new step in the field of personalized medicine in human reproduction which may help in the management of endometrial preparation for embryo transfer, increasing the chances of pregnancy for many couples. The authors have no potential conflict of interest to declare. No external funding was obtained for this study. © The Author(s) 2018. Published by Oxford University Press on behalf of the European Society of Human Reproduction and Embryology. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

  1. Stochastic gene expression in Arabidopsis thaliana.

    Science.gov (United States)

    Araújo, Ilka Schultheiß; Pietsch, Jessica Magdalena; Keizer, Emma Mathilde; Greese, Bettina; Balkunde, Rachappa; Fleck, Christian; Hülskamp, Martin

    2017-12-14

    Although plant development is highly reproducible, some stochasticity exists. This developmental stochasticity may be caused by noisy gene expression. Here we analyze the fluctuation of protein expression in Arabidopsis thaliana. Using the photoconvertible KikGR marker, we show that the protein expressions of individual cells fluctuate over time. A dual reporter system was used to study extrinsic and intrinsic noise of marker gene expression. We report that extrinsic noise is higher than intrinsic noise and that extrinsic noise in stomata is clearly lower in comparison to several other tissues/cell types. Finally, we show that cells are coupled with respect to stochastic protein expression in young leaves, hypocotyls and roots but not in mature leaves. Our data indicate that stochasticity of gene expression can vary between tissues/cell types and that it can be coupled in a non-cell-autonomous manner.

  2. Array-based gene expression, CGH and tissue data defines a 12q24 gain in neuroblastic tumors with prognostic implication

    Directory of Open Access Journals (Sweden)

    Kilpinen Sami

    2010-05-01

    Full Text Available Abstract Background Neuroblastoma has successfully served as a model system for the identification of neuroectoderm-derived oncogenes. However, in spite of various efforts, only a few clinically useful prognostic markers have been found. Here, we present a framework, which integrates DNA, RNA and tissue data to identify and prioritize genetic events that represent clinically relevant new therapeutic targets and prognostic biomarkers for neuroblastoma. Methods A single-gene resolution aCGH profiling was integrated with microarray-based gene expression profiling data to distinguish genetic copy number alterations that were strongly associated with transcriptional changes in two neuroblastoma cell lines. FISH analysis using a hotspot tumor tissue microarray of 37 paraffin-embedded neuroblastoma samples and in silico data mining for gene expression information obtained from previously published studies including up to 445 healthy nervous system samples and 123 neuroblastoma samples were used to evaluate the clinical significance and transcriptional consequences of the detected alterations and to identify subsequently activated gene(s. Results In addition to the anticipated high-level amplification and subsequent overexpression of MYCN, MEIS1, CDK4 and MDM2 oncogenes, the aCGH analysis revealed numerous other genetic alterations, including microamplifications at 2p and 12q24.11. Most interestingly, we identified and investigated the clinical relevance of a previously poorly characterized amplicon at 12q24.31. FISH analysis showed low-level gain of 12q24.31 in 14 of 33 (42% neuroblastomas. Patients with the low-level gain had an intermediate prognosis in comparison to patients with MYCN amplification (poor prognosis and to those with no MYCN amplification or 12q24.31 gain (good prognosis (P = 0.001. Using the in silico data mining approach, we identified elevated expression of five genes located at the 12q24.31 amplicon in neuroblastoma (DIABLO, ZCCHC

  3. Analysis of gene expression profiles of soft tissue sarcoma using a combination of knowledge-based filtering with integration of multiple statistics.

    Directory of Open Access Journals (Sweden)

    Anna Takahashi

    Full Text Available The diagnosis and treatment of soft tissue sarcomas (STS have been difficult. Of the diverse histological subtypes, undifferentiated pleomorphic sarcoma (UPS is particularly difficult to diagnose accurately, and its classification per se is still controversial. Recent advances in genomic technologies provide an excellent way to address such problems. However, it is often difficult, if not impossible, to identify definitive disease-associated genes using genome-wide analysis alone, primarily because of multiple testing problems. In the present study, we analyzed microarray data from 88 STS patients using a combination method that used knowledge-based filtering and a simulation based on the integration of multiple statistics to reduce multiple testing problems. We identified 25 genes, including hypoxia-related genes (e.g., MIF, SCD1, P4HA1, ENO1, and STAT1 and cell cycle- and DNA repair-related genes (e.g., TACC3, PRDX1, PRKDC, and H2AFY. These genes showed significant differential expression among histological subtypes, including UPS, and showed associations with overall survival. STAT1 showed a strong association with overall survival in UPS patients (logrank p = 1.84 × 10(-6 and adjusted p value 2.99 × 10(-3 after the permutation test. According to the literature, the 25 genes selected are useful not only as markers of differential diagnosis but also as prognostic/predictive markers and/or therapeutic targets for STS. Our combination method can identify genes that are potential prognostic/predictive factors and/or therapeutic targets in STS and possibly in other cancers. These disease-associated genes deserve further preclinical and clinical validation.

  4. Gene expression in periodontal tissues following treatment

    Directory of Open Access Journals (Sweden)

    Eisenacher Martin

    2008-07-01

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

  5. Gene expression results in lipopolysaccharide-stimulated monocytes depend significantly on the choice of reference genes

    Directory of Open Access Journals (Sweden)

    Øvstebø Reidun

    2010-05-01

    Full Text Available Abstract Background Gene expression in lipopolysaccharide (LPS-stimulated monocytes is mainly studied by quantitative real-time reverse transcription PCR (RT-qPCR using GAPDH (glyceraldehyde 3-phosphate dehydrogenase or ACTB (beta-actin as reference gene for normalization. Expression of traditional reference genes has been shown to vary substantially under certain conditions leading to invalid results. To investigate whether traditional reference genes are stably expressed in LPS-stimulated monocytes or if RT-qPCR results are dependent on the choice of reference genes, we have assessed and evaluated gene expression stability of twelve candidate reference genes in this model system. Results Twelve candidate reference genes were quantified by RT-qPCR in LPS-stimulated, human monocytes and evaluated using the programs geNorm, Normfinder and BestKeeper. geNorm ranked PPIB (cyclophilin B, B2M (beta-2-microglobulin and PPIA (cyclophilin A as the best combination for gene expression normalization in LPS-stimulated monocytes. Normfinder suggested TBP (TATA-box binding protein and B2M as the best combination. Compared to these combinations, normalization using GAPDH alone resulted in significantly higher changes of TNF-α (tumor necrosis factor-alpha and IL10 (interleukin 10 expression. Moreover, a significant difference in TNF-α expression between monocytes stimulated with equimolar concentrations of LPS from N. meningitides and E. coli, respectively, was identified when using the suggested combinations of reference genes for normalization, but stayed unrecognized when employing a single reference gene, ACTB or GAPDH. Conclusions Gene expression levels in LPS-stimulated monocytes based on RT-qPCR results differ significantly when normalized to a single gene or a combination of stably expressed reference genes. Proper evaluation of reference gene stabiliy is therefore mandatory before reporting RT-qPCR results in LPS-stimulated monocytes.

  6. Expression analysis of some genes regulated by retinoic acid in controls and triadimefon-exposed embryos: is the amphibian Xenopus laevis a suitable model for gene-based comparative teratology?

    Science.gov (United States)

    Di Renzo, Francesca; Rossi, Federica; Bacchetta, Renato; Prati, Mariangela; Giavini, Erminio; Menegola, Elena

    2011-06-01

    The use of nonmammal models in teratological studies is a matter of debate and seems to be justified if the embryotoxic mechanism involves conserved processes. Published data on mammals and Xenopus laevis suggest that azoles are teratogenic by altering the endogenous concentration of retinoic acid (RA). The expression of some genes (Shh, Ptch-1, Gsc, and Msx2) controlled by retinoic acid is downregulated in rat embryos exposed at the phylotypic stage to the triazole triadimefon (FON). In order to propose X. laevis as a model for gene-based comparative teratology, this work evaluates the expression of Shh, Ptch-1, Gsc, and Msx2 in FON-exposed X. laevis embryos. Embryos, exposed to a high concentration level (500 µM) of FON from stage 13 till 17, were examined at stages 17, 27, and 47. Stage 17 and 27 embryos were processed to perform quantitative RT-PCR. The developmental rate was never affected by FON at any considered stage. FON-exposed stage 47 larvae showed the typical craniofacial malformations. A significant downregulation of Gsc was observed in FON-exposed stage 17 embryos. Shh, Ptch-1, Msx2 showed a high fluctuation of expression both in control and in FON-exposed samples both at stages 17 and 27. The downregulation of Gsc mimics the effects of FON on rat embryos, showing for this gene a common effect of FON in the two vertebrate classes. The high fluctuation observed in the gene expression of the other genes, however, suggests that X. laevis at this stage has limited utility for gene-based comparative teratology. © 2011 Wiley-Liss, Inc.

  7. Transcription activator-like effector-mediated regulation of gene expression based on the inducible packaging and delivery via designed extracellular vesicles

    International Nuclear Information System (INIS)

    Lainšček, Duško; Lebar, Tina; Jerala, Roman

    2017-01-01

    Transcription activator-like effector (TALE) proteins present a powerful tool for genome editing and engineering, enabling introduction of site-specific mutations, gene knockouts or regulation of the transcription levels of selected genes. TALE nucleases or TALE-based transcription regulators are introduced into mammalian cells mainly via delivery of the coding genes. Here we report an extracellular vesicle-mediated delivery of TALE transcription regulators and their ability to upregulate the reporter gene in target cells. Designed transcriptional activator TALE-VP16 fused to the appropriate dimerization domain was enriched as a cargo protein within extracellular vesicles produced by mammalian HEK293 cells stimulated by Ca-ionophore and using blue light- or rapamycin-inducible dimerization systems. Blue light illumination or rapamycin increased the amount of the TALE-VP16 activator in extracellular vesicles and their addition to the target cells resulted in an increased expression of the reporter gene upon addition of extracellular vesicles to the target cells. This technology therefore represents an efficient delivery for the TALE-based transcriptional regulators. - Highlights: • Inducible dimerization enriched cargo proteins within extracellular vesicles (EV). • Farnesylation surpassed LAMP-1 fusion proteins for the EV packing. • Extracellular vesicles were able to deliver TALE regulators to mammalian cells. • TALE mediated transcriptional activation was achieved by designed EV.

  8. An Interactive Database of Cocaine-Responsive Gene Expression

    Directory of Open Access Journals (Sweden)

    Willard M. Freeman

    2002-01-01

    Full Text Available The postgenomic era of large-scale gene expression studies is inundating drug abuse researchers and many other scientists with findings related to gene expression. This information is distributed across many different journals, and requires laborious literature searches. Here, we present an interactive database that combines existing information related to cocaine-mediated changes in gene expression in an easy-to-use format. The database is limited to statistically significant changes in mRNA or protein expression after cocaine administration. The Flash-based program is integrated into a Web page, and organizes changes in gene expression based on neuroanatomical region, general function, and gene name. Accompanying each gene is a description of the gene, links to the original publications, and a link to the appropriate OMIM (Online Mendelian Inheritance in Man entry. The nature of this review allows for timely modifications and rapid inclusion of new publications, and should help researchers build second-generation hypotheses on the role of gene expression changes in the physiology and behavior of cocaine abuse. Furthermore, this method of organizing large volumes of scientific information can easily be adapted to assist researchers in fields outside of drug abuse.

  9. A deep auto-encoder model for gene expression prediction.

    Science.gov (United States)

    Xie, Rui; Wen, Jia; Quitadamo, Andrew; Cheng, Jianlin; Shi, Xinghua

    2017-11-17

    Gene expression is a key intermediate level that genotypes lead to a particular trait. Gene expression is affected by various factors including genotypes of genetic variants. With an aim of delineating the genetic impact on gene expression, we build a deep auto-encoder model to assess how good genetic variants will contribute to gene expression changes. This new deep learning model is a regression-based predictive model based on the MultiLayer Perceptron and Stacked Denoising Auto-encoder (MLP-SAE). The model is trained using a stacked denoising auto-encoder for feature selection and a multilayer perceptron framework for backpropagation. We further improve the model by introducing dropout to prevent overfitting and improve performance. To demonstrate the usage of this model, we apply MLP-SAE to a real genomic datasets with genotypes and gene expression profiles measured in yeast. Our results show that the MLP-SAE model with dropout outperforms other models including Lasso, Random Forests and the MLP-SAE model without dropout. Using the MLP-SAE model with dropout, we show that gene expression quantifications predicted by the model solely based on genotypes, align well with true gene expression patterns. We provide a deep auto-encoder model for predicting gene expression from SNP genotypes. This study demonstrates that deep learning is appropriate for tackling another genomic problem, i.e., building predictive models to understand genotypes' contribution to gene expression. With the emerging availability of richer genomic data, we anticipate that deep learning models play a bigger role in modeling and interpreting genomics.

  10. 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.

  11. Regulation of gene expression in protozoa parasites.

    Science.gov (United States)

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

    2010-01-01

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

  12. Inferring gene networks from discrete expression data

    KAUST Repository

    Zhang, L.; Mallick, B. K.

    2013-01-01

    graphical models applied to continuous data, which give a closedformmarginal likelihood. In this paper,we extend network modeling to discrete data, specifically data from serial analysis of gene expression, and RNA-sequencing experiments, both of which

  13. Gene Expression and Microarray Investigation of Dendrobium ...

    African Journals Online (AJOL)

    blood glucose > 16.7 mmol/L were used as the model group and treated with Dendrobium mixture. (DEN ... Keywords: Diabetes, Gene expression, Dendrobium mixture, Microarray testing ..... homeostasis in airway smooth muscle. Am J.

  14. Identification of genes showing differential expression profile ...

    Indian Academy of Sciences (India)

    3Department of Natural Sciences, International Christian University, Mitaka, Tokyo 181-8585, Japan ... the changes of expression predicted from gene function suggested association ... ate School of Science and Technology, Niigata University.

  15. Drosophila melanogaster gene expression changes after spaceflight.

    Data.gov (United States)

    National Aeronautics and Space Administration — Gene expression levels were determined in 3rd instar and adult Drosophila melanogaster reared during spaceflight to elucidate the genetic and molecular mechanisms...

  16. Exertional Heat Illness and Human Gene Expression

    National Research Council Canada - National Science Library

    Sonna, L.A; Sawka, M. N; Lilly, C. M

    2007-01-01

    Microarray analysis of gene expression at the level of RNA has generated new insights into the relationship between cellular responses to acute heat shock in vitro, exercise, and exertional heat illness...

  17. 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.

  18. Identification of genes preferentially expressed during

    African Journals Online (AJOL)

    雨林木风

    2012-08-16

    Aug 16, 2012 ... The suppression subtractive hybridization (SSH) method conducted to generate ... which showed the lack of genomic information currently available for lily. ..... characterization of genes expressed during somatic embryo.

  19. DTFP-Growth: Dynamic Threshold-Based FP-Growth Rule Mining Algorithm Through Integrating Gene Expression, Methylation, and Protein-Protein Interaction Profiles.

    Science.gov (United States)

    Mallik, Saurav; Bhadra, Tapas; Mukherji, Ayan; Mallik, Saurav; Bhadra, Tapas; Mukherji, Ayan; Mallik, Saurav; Bhadra, Tapas; Mukherji, Ayan

    2018-04-01

    Association rule mining is an important technique for identifying interesting relationships between gene pairs in a biological data set. Earlier methods basically work for a single biological data set, and, in maximum cases, a single minimum support cutoff can be applied globally, i.e., across all genesets/itemsets. To overcome this limitation, in this paper, we propose dynamic threshold-based FP-growth rule mining algorithm that integrates gene expression, methylation and protein-protein interaction profiles based on weighted shortest distance to find the novel associations among different pairs of genes in multi-view data sets. For this purpose, we introduce three new thresholds, namely, Distance-based Variable/Dynamic Supports (DVS), Distance-based Variable Confidences (DVC), and Distance-based Variable Lifts (DVL) for each rule by integrating co-expression, co-methylation, and protein-protein interactions existed in the multi-omics data set. We develop the proposed algorithm utilizing these three novel multiple threshold measures. In the proposed algorithm, the values of , , and are computed for each rule separately, and subsequently it is verified whether the support, confidence, and lift of each evolved rule are greater than or equal to the corresponding individual , , and values, respectively, or not. If all these three conditions for a rule are found to be true, the rule is treated as a resultant rule. One of the major advantages of the proposed method compared with other related state-of-the-art methods is that it considers both the quantitative and interactive significance among all pairwise genes belonging to each rule. Moreover, the proposed method generates fewer rules, takes less running time, and provides greater biological significance for the resultant top-ranking rules compared to previous methods.

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

    Science.gov (United States)

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

    2015-01-01

    Trichomonas vaginalis is the etiologic agent of trichomonosis, the most common non-viral sexually transmitted disease worldwide. This infection is associated with several health consequences, including cervical and prostate cancers and HIV acquisition. Gene expression analysis has been facilitated because of available genome sequences and large-scale transcriptomes in T. vaginalis, particularly using quantitative real-time polymerase chain reaction (qRT-PCR), one of the most used methods for molecular studies. Reference genes for normalization are crucial to ensure the accuracy of this method. However, to the best of our knowledge, a systematic validation of reference genes has not been performed for T. vaginalis. In this study, the transcripts of nine candidate reference genes were quantified using qRT-PCR under different cultivation conditions, and the stability of these genes was compared using the geNorm and NormFinder algorithms. The most stable reference genes were α-tubulin, actin and DNATopII, and, conversely, the widely used T. vaginalis reference genes GAPDH and β-tubulin were less stable. The PFOR gene was used to validate the reliability of the use of these candidate reference genes. As expected, the PFOR gene was upregulated when the trophozoites were cultivated with ferrous ammonium sulfate when the DNATopII, α-tubulin and actin genes were used as normalizing gene. By contrast, the PFOR gene was downregulated when the GAPDH gene was used as an internal control, leading to misinterpretation of the data. These results provide an important starting point for reference gene selection and gene expression analysis with qRT-PCR studies of T. vaginalis. PMID:26393928

  1. Evaluation of suitable reference genes for gene expression studies ...

    Indian Academy of Sciences (India)

    2011-12-14

    Dec 14, 2011 ... MADS family of TFs control floral organ identity within each whorl of the flower by activating downstream genes. Measuring gene expression in different tissue types and developmental stages is of fundamental importance in TFs functional research. In last few years, quantitative real-time. PCR (qRT-PCR) ...

  2. PRAME gene expression profile in medulloblastoma

    Directory of Open Access Journals (Sweden)

    Tânia Maria Vulcani-Freitas

    2011-02-01

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

  3. Comparative gene expression between two yeast species

    Directory of Open Access Journals (Sweden)

    Guan Yuanfang

    2013-01-01

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

  4. Systematic identification of human housekeeping genes possibly useful as references in gene expression studies.

    Science.gov (United States)

    Caracausi, Maria; Piovesan, Allison; Antonaros, Francesca; Strippoli, Pierluigi; Vitale, Lorenza; Pelleri, Maria Chiara

    2017-09-01

    The ideal reference, or control, gene for the study of gene expression in a given organism should be expressed at a medium‑high level for easy detection, should be expressed at a constant/stable level throughout different cell types and within the same cell type undergoing different treatments, and should maintain these features through as many different tissues of the organism. From a biological point of view, these theoretical requirements of an ideal reference gene appear to be best suited to housekeeping (HK) genes. Recent advancements in the quality and completeness of human expression microarray data and in their statistical analysis may provide new clues toward the quantitative standardization of human gene expression studies in biology and medicine, both cross‑ and within‑tissue. The systematic approach used by the present study is based on the Transcriptome Mapper tool and exploits the automated reassignment of probes to corresponding genes, intra‑ and inter‑sample normalization, elaboration and representation of gene expression values in linear form within an indexed and searchable database with a graphical interface recording quantitative levels of expression, expression variability and cross‑tissue width of expression for more than 31,000 transcripts. The present study conducted a meta‑analysis of a pool of 646 expression profile data sets from 54 different human tissues and identified actin γ 1 as the HK gene that best fits the combination of all the traditional criteria to be used as a reference gene for general use; two ribosomal protein genes, RPS18 and RPS27, and one aquaporin gene, POM121 transmembrane nucleporin C, were also identified. The present study provided a list of tissue‑ and organ‑specific genes that may be most suited for the following individual tissues/organs: Adipose tissue, bone marrow, brain, heart, kidney, liver, lung, ovary, skeletal muscle and testis; and also provides in these cases a representative

  5. 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...

  6. Based on Molecular Profiling of Gene Expression, Palmoplantar Pustulosis and Palmoplantar Pustular Psoriasis Are Highly Related Diseases that Appear to Be Distinct from Psoriasis Vulgaris.

    Directory of Open Access Journals (Sweden)

    Robert Bissonnette

    Full Text Available There is a controversy surrounding the existence of palmoplantar pustulosis (PPP and palmoplantar pustular psoriasis (PPPP as separate clinical entities or as variants of the same clinical entity. We used gene expression microarray to compare gene expression in PPP and PPPP.Skin biopsies from subjects with PPP (3, PPPP (6, psoriasis vulgaris (10 and acral skin from normal subjects (7 were analyzed using gene expression microarray. Principal component analysis showed that PPP and PPPP were different from psoriasis vulgaris and normal acral skin. However gene expression of PPP and PPPP clustered together and could not be used to differentiate PPP from PPPP. Gene-wise comparison between PPP and PPPP found no gene to be differentially expressed at a false discovery rate lower than 0.05. Surprisingly we found a higher expression of several genes involved in neural pathways (e.g. GPRIN and ADAM23 in PPP/PPPP as compared to psoriasis vulgaris and normal acral skin. Immunohistochemistry confirmed those findings and showed a keratinocyte localization for those proteins.PPP and PPPP could not be differentiated using gene expression microarray suggesting that they are not distinct clinical entities. Increased expression of GPRIN1, and ADAM23 in keratinocytes suggests that these proteins could be new therapeutic targets for PPP/PPPP.

  7. Identification of salt-stress induced differentially expressed genes in ...

    African Journals Online (AJOL)

    Identification of salt-stress induced differentially expressed genes in barley leaves using the annealingcontrol- primer-based GeneFishing technique. S Lee, K Lee, K Kim, GJ Choi, SH Yoon, HC Ji, S Seo, YC Lim, N Ahsan ...

  8. Reference Gene Screening for Analyzing Gene Expression Across Goat Tissue

    Directory of Open Access Journals (Sweden)

    Yu Zhang

    2013-12-01

    Full Text Available Real-time quantitative PCR (qRT-PCR is one of the important methods for investigating the changes in mRNA expression levels in cells and tissues. Selection of the proper reference genes is very important when calibrating the results of real-time quantitative PCR. Studies on the selection of reference genes in goat tissues are limited, despite the economic importance of their meat and dairy products. We used real-time quantitative PCR to detect the expression levels of eight reference gene candidates (18S, TBP, HMBS, YWHAZ, ACTB, HPRT1, GAPDH and EEF1A2 in ten tissues types sourced from Boer goats. The optimal reference gene combination was selected according to the results determined by geNorm, NormFinder and Bestkeeper software packages. The analyses showed that tissue is an important variability factor in genes expression stability. When all tissues were considered, 18S, TBP and HMBS is the optimal reference combination for calibrating quantitative PCR analysis of gene expression from goat tissues. Dividing data set by tissues, ACTB was the most stable in stomach, small intestine and ovary, 18S in heart and spleen, HMBS in uterus and lung, TBP in liver, HPRT1 in kidney and GAPDH in muscle. Overall, this study provided valuable information about the goat reference genes that can be used in order to perform a proper normalisation when relative quantification by qRT-PCR studies is undertaken.

  9. Identifying key genes in rheumatoid arthritis by weighted gene co-expression network analysis.

    Science.gov (United States)

    Ma, Chunhui; Lv, Qi; Teng, Songsong; Yu, Yinxian; Niu, Kerun; Yi, Chengqin

    2017-08-01

    This study aimed to identify rheumatoid arthritis (RA) related genes based on microarray data using the WGCNA (weighted gene co-expression network analysis) method. Two gene expression profile datasets GSE55235 (10 RA samples and 10 healthy controls) and GSE77298 (16 RA samples and seven healthy controls) were downloaded from Gene Expression Omnibus database. Characteristic genes were identified using metaDE package. WGCNA was used to find disease-related networks based on gene expression correlation coefficients, and module significance was defined as the average gene significance of all genes used to assess the correlation between the module and RA status. Genes in the disease-related gene co-expression network were subject to functional annotation and pathway enrichment analysis using Database for Annotation Visualization and Integrated Discovery. Characteristic genes were also mapped to the Connectivity Map to screen small molecules. A total of 599 characteristic genes were identified. For each dataset, characteristic genes in the green, red and turquoise modules were most closely associated with RA, with gene numbers of 54, 43 and 79, respectively. These genes were enriched in totally enriched in 17 Gene Ontology terms, mainly related to immune response (CD97, FYB, CXCL1, IKBKE, CCR1, etc.), inflammatory response (CD97, CXCL1, C3AR1, CCR1, LYZ, etc.) and homeostasis (C3AR1, CCR1, PLN, CCL19, PPT1, etc.). Two small-molecule drugs sanguinarine and papaverine were predicted to have a therapeutic effect against RA. Genes related to immune response, inflammatory response and homeostasis presumably have critical roles in RA pathogenesis. Sanguinarine and papaverine have a potential therapeutic effect against RA. © 2017 Asia Pacific League of Associations for Rheumatology and John Wiley & Sons Australia, Ltd.

  10. Predicting cellular growth from gene expression signatures.

    Directory of Open Access Journals (Sweden)

    Edoardo M Airoldi

    2009-01-01

    Full Text Available Maintaining balanced growth in a changing environment is a fundamental systems-level challenge for cellular physiology, particularly in microorganisms. While the complete set of regulatory and functional pathways supporting growth and cellular proliferation are not yet known, portions of them are well understood. In particular, cellular proliferation is governed by mechanisms that are highly conserved from unicellular to multicellular organisms, and the disruption of these processes in metazoans is a major factor in the development of cancer. In this paper, we develop statistical methodology to identify quantitative aspects of the regulatory mechanisms underlying cellular proliferation in Saccharomyces cerevisiae. We find that the expression levels of a small set of genes can be exploited to predict the instantaneous growth rate of any cellular culture with high accuracy. The predictions obtained in this fashion are robust to changing biological conditions, experimental methods, and technological platforms. The proposed model is also effective in predicting growth rates for the related yeast Saccharomyces bayanus and the highly diverged yeast Schizosaccharomyces pombe, suggesting that the underlying regulatory signature is conserved across a wide range of unicellular evolution. We investigate the biological significance of the gene expression signature that the predictions are based upon from multiple perspectives: by perturbing the regulatory network through the Ras/PKA pathway, observing strong upregulation of growth rate even in the absence of appropriate nutrients, and discovering putative transcription factor binding sites, observing enrichment in growth-correlated genes. More broadly, the proposed methodology enables biological insights about growth at an instantaneous time scale, inaccessible by direct experimental methods. Data and tools enabling others to apply our methods are available at http://function.princeton.edu/growthrate.

  11. Identification, expression profiling and fluorescence-based binding assays of a chemosensory protein gene from the Western flower thrips, Frankliniella occidentalis.

    Directory of Open Access Journals (Sweden)

    Zhi-Ke Zhang

    Full Text Available Using RT-PCR and RACE-PCR strategies, we cloned and identified a new chemosensory protein (FoccCSP from the Western flower thrips, Frankliniella occidentalis, a species for which no chemosensory protein (CSP has yet been identified. The FoccCSP gene contains a 387 bp open-reading frame encoding a putative protein of 128 amino acids with a molecular weight of 14.51 kDa and an isoelectric point of 5.41. The deduced amino acid sequence contains a putative signal peptide of 19 amino acid residues at the N-terminus, as well as the typical four-cysteine signature found in other insect CSPs. As FoccCSP is from a different order of insect than other known CSPs, the GenBank FoccCSP homolog showed only 31-50% sequence identity with them. A neighbor-joining tree was constructed and revealed that FoccCSP is in a group with CSPs from Homopteran insects (e.g., AgosCSP4, AgosCSP10, ApisCSP, and NlugCSP9, suggesting that these genes likely developed from a common ancestral gene. The FoccCSP gene expression profile of different tissues and development stages was measured by quantitative real-time PCR. The results of this analysis revealed this gene is predominantly expressed in the antennae and also highly expressed in the first instar nymph, suggesting a function for FoccCSP in olfactory reception and in particular life activities during the first instar nymph stage. We expressed recombinant FoccCSP protein in a prokaryotic expression system and purified FoccCSP protein by affinity chromatography using a Ni-NTA-Sepharose column. Using N-phenyl-1-naphthylamine (1-NPN as a fluorescent probe in fluorescence-based competitive binding assay, we determined the binding affinities of 19 volatile substances for FoccCSP protein. This analysis revealed that anisic aldehyde, geraniol and methyl salicylate have high binding affinities for FoccCSP, with KD values of 10.50, 15.35 and 35.24 μM, respectively. Thus, our study indicates that FoccCSP may play an important role in

  12. Patterns of Immune Infiltration in Breast Cancer and Their Clinical Implications: A Gene-Expression-Based Retrospective Study

    Science.gov (United States)

    Ali, H. Raza; Chlon, Leon; Pharoah, Paul D. P.; Caldas, Carlos

    2016-01-01

    Background Immune infiltration of breast tumours is associated with clinical outcome. However, past work has not accounted for the diversity of functionally distinct cell types that make up the immune response. The aim of this study was to determine whether differences in the cellular composition of the immune infiltrate in breast tumours influence survival and treatment response, and whether these effects differ by molecular subtype. Methods and Findings We applied an established computational approach (CIBERSORT) to bulk gene expression profiles of almost 11,000 tumours to infer the proportions of 22 subsets of immune cells. We investigated associations between each cell type and survival and response to chemotherapy, modelling cellular proportions as quartiles. We found that tumours with little or no immune infiltration were associated with different survival patterns according to oestrogen receptor (ER) status. In ER-negative disease, tumours lacking immune infiltration were associated with the poorest prognosis, whereas in ER-positive disease, they were associated with intermediate prognosis. Of the cell subsets investigated, T regulatory cells and M0 and M2 macrophages emerged as the most strongly associated with poor outcome, regardless of ER status. Among ER-negative tumours, CD8+ T cells (hazard ratio [HR] = 0.89, 95% CI 0.80–0.98; p = 0.02) and activated memory T cells (HR 0.88, 95% CI 0.80–0.97; p = 0.01) were associated with favourable outcome. T follicular helper cells (odds ratio [OR] = 1.34, 95% CI 1.14–1.57; p < 0.001) and memory B cells (OR = 1.18, 95% CI 1.0–1.39; p = 0.04) were associated with pathological complete response to neoadjuvant chemotherapy in ER-negative disease, suggesting a role for humoral immunity in mediating response to cytotoxic therapy. Unsupervised clustering analysis using immune cell proportions revealed eight subgroups of tumours, largely defined by the balance between M0, M1, and M2 macrophages, with distinct

  13. 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.

  14. 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.

  15. Noise minimization in eukaryotic gene expression

    International Nuclear Information System (INIS)

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

    2004-01-01

    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

  16. Intrinsic subtypes from PAM50 gene expression assay in a population-based breast cancer cohort: differences by age, race, and tumor characteristics.

    Science.gov (United States)

    Sweeney, Carol; Bernard, Philip S; Factor, Rachel E; Kwan, Marilyn L; Habel, Laurel A; Quesenberry, Charles P; Shakespear, Kaylynn; Weltzien, Erin K; Stijleman, Inge J; Davis, Carole A; Ebbert, Mark T W; Castillo, Adrienne; Kushi, Lawrence H; Caan, Bette J

    2014-05-01

    Data are lacking to describe gene expression-based breast cancer intrinsic subtype patterns for population-based patient groups. We studied a diverse cohort of women with breast cancer from the Life After Cancer Epidemiology and Pathways studies. RNA was extracted from 1 mm punches from fixed tumor tissue. Quantitative reverse-transcriptase PCR was conducted for the 50 genes that comprise the PAM50 intrinsic subtype classifier. In a subcohort of 1,319 women, the overall subtype distribution based on PAM50 was 53.1% luminal A, 20.5% luminal B, 13.0% HER2-enriched, 9.8% basal-like, and 3.6% normal-like. Among low-risk endocrine-positive tumors (i.e., estrogen and progesterone receptor positive by immunohistochemistry, HER2 negative, and low histologic grade), only 76.5% were categorized as luminal A by PAM50. Continuous-scale luminal A, luminal B, HER2-enriched, and normal-like scores from PAM50 were mutually positively correlated. Basal-like score was inversely correlated with other subtypes. The proportion with non-luminal A subtype decreased with older age at diagnosis, P Trend < 0.0001. Compared with non-Hispanic Whites, African American women were more likely to have basal-like tumors, age-adjusted OR = 4.4 [95% confidence intervals (CI), 2.3-8.4], whereas Asian and Pacific Islander women had reduced odds of basal-like subtype, OR = 0.5 (95% CI, 0.3-0.9). Our data indicate that over 50% of breast cancers treated in the community have luminal A subtype. Gene expression-based classification shifted some tumors categorized as low risk by surrogate clinicopathologic criteria to higher-risk subtypes. Subtyping in a population-based cohort revealed distinct profiles by age and race. ©2014 AACR.

  17. A comprehensive comparison of RNA-Seq-based transcriptome analysis from reads to differential gene expression and cross-comparison with microarrays: a case study in Saccharomyces cerevisiae

    DEFF Research Database (Denmark)

    Nookaew, Intawat; Papini, Marta; Pornputtapong, Natapol

    2012-01-01

    RNA-seq, has recently become an attractive method of choice in the studies of transcriptomes, promising several advantages compared with microarrays. In this study, we sought to assess the contribution of the different analytical steps involved in the analysis of RNA-seq data generated with the I......RNA-seq, has recently become an attractive method of choice in the studies of transcriptomes, promising several advantages compared with microarrays. In this study, we sought to assess the contribution of the different analytical steps involved in the analysis of RNA-seq data generated...... gene expression identification derived from the different statistical methods, as well as their integrated analysis results based on gene ontology annotation are in good agreement. Overall, our study provides a useful and comprehensive comparison between the two platforms (RNA-seq and microrrays...

  18. Development of Gene Expression Fingerprints for Identification of Environmental Contaminants Using cDNA Arrays

    National Research Council Canada - National Science Library

    Inouye, L

    2004-01-01

    ...) to develop cDNA array-based assays that map gene expression from contaminant exposures. Results substantiate that distinct gene expression profiles exist for major contaminant classes such as PARs, PCBs, and PCDD/Fs...

  19. Comparison of a Rat Primary Cell-Based Blood-Brain Barrier Model With Epithelial and Brain Endothelial Cell Lines: Gene Expression and Drug Transport

    Directory of Open Access Journals (Sweden)

    Szilvia Veszelka

    2018-05-01

    Full Text Available Cell culture-based blood-brain barrier (BBB models are useful tools for screening of CNS drug candidates. Cell sources for BBB models include primary brain endothelial cells or immortalized brain endothelial cell lines. Despite their well-known differences, epithelial cell lines are also used as surrogate models for testing neuropharmaceuticals. The aim of the present study was to compare the expression of selected BBB related genes including tight junction proteins, solute carriers (SLC, ABC transporters, metabolic enzymes and to describe the paracellular properties of nine different culture models. To establish a primary BBB model rat brain capillary endothelial cells were co-cultured with rat pericytes and astrocytes (EPA. As other BBB and surrogate models four brain endothelial cells lines, rat GP8 and RBE4 cells, and human hCMEC/D3 cells with or without lithium treatment (D3 and D3L, and four epithelial cell lines, native human intestinal Caco-2 and high P-glycoprotein expressing vinblastine-selected VB-Caco-2 cells, native MDCK and MDR1 transfected MDCK canine kidney cells were used. To test transporter functionality, the permeability of 12 molecules, glucopyranose, valproate, baclofen, gabapentin, probenecid, salicylate, rosuvastatin, pravastatin, atorvastatin, tacrine, donepezil, was also measured in the EPA and epithelial models. Among the junctional protein genes, the expression level of occludin was high in all models except the GP8 and RBE4 cells, and each model expressed a unique claudin pattern. Major BBB efflux (P-glycoprotein or ABCB1 and influx transporters (GLUT-1, LAT-1 were present in all models at mRNA levels. The transcript of BCRP (ABCG2 was not expressed in MDCK, GP8 and RBE4 cells. The absence of gene expression of important BBB efflux and influx transporters BCRP, MRP6, -9, MCT6, -8, PHT2, OATPs in one or both types of epithelial models suggests that Caco-2 or MDCK models are not suitable to test drug candidates which

  20. Imaging of Herpes Simplex Virus Type 1 Thymidine Kinase Gene Expression with Radiolabeled 5-(2-iodovinyl)-2'-deoxyuridine (IVDU) in Liver by Hydrodynamic-based Procedure

    Energy Technology Data Exchange (ETDEWEB)

    Song, In Ho; Lee, Tae Sup; Kang, Joo Hyun; Lee, Yong Jin; Kim, Kwang Il; An, Gwang Il; Chung, Wee Sup; Cheon, Gi Jeong; Choi, Chang Woon; Lim, Sang Moo [Korea Institute of Radiological and Medical Sciences, Seoul (Korea, Republic of)

    2009-10-15

    Hydrodynamic-based procedure is a simple and effective gene delivery method to lead a high gene expression in liver tissue. Non-invasive imaging reporter gene system has been used widely with herpes simplex virus type 1 thymidine kinase (HSV1-tk) and its various substrates. In the present study, we investigated to image the expression of HSV1-tk gene with 5-(2-iodovinyl)-2'-deoxyuridine (IVDU) in mouse liver by the hydrodynamicbased procedure. HSV1-tk or enhanced green fluorescence protein (EGFP) encoded plasmid DNA was transferred into the mouse liver by hydrodynamic injection. At 24 h post-injection, RT-PCR, biodistribution, fluorescence imaging, nuclear imaging and digital wholebody autoradiography (DWBA) were performed to confirm transferred gene expression. In RT-PCR assay using mRNA from the mouse liver, specific bands of HSV1-tk and EGFP gene were observed in HSV1-tk and EGFP expressing plasmid injected mouse, respectively. Higher uptake of radiolabeled IVDU was exhibited in liver of HSV1-tk gene transferred mouse by biodistribution study. In fluorescence imaging, the liver showed specific fluorescence signal in EGFP gene transferred mouse. Gamma-camera image and DWBA results showed that radiolabeled IVDU was accumulated in the liver of HSV1-tk gene transferred mouse. In this study, hydrodynamic-based procedure was effective in liver-specific gene delivery and it could be quantified with molecular imaging methods. Therefore, co-expression of HSV1-tk reporter gene and target gene by hydrodynamic-based procedure is expected to be a useful method for the evaluation of the target gene expression level with radiolabeled IVDU.

  1. Evaluation of suitable reference genes for gene expression studies in bovine muscular tissue

    Directory of Open Access Journals (Sweden)

    Dunner Susana

    2008-09-01

    Full Text Available Abstract Background Real-time reverse transcriptase quantitative polymerase chain reaction (real-time RTqPCR is a technique used to measure mRNA species copy number as a way to determine key genes involved in different biological processes. However, the expression level of these key genes may vary among tissues or cells not only as a consequence of differential expression but also due to different factors, including choice of reference genes to normalize the expression levels of the target genes; thus the selection of reference genes is critical for expression studies. For this purpose, ten candidate reference genes were investigated in bovine muscular tissue. Results The value of stability of ten candidate reference genes included in three groups was estimated: the so called 'classical housekeeping' genes (18S, GAPDH and ACTB, a second set of genes used in expression studies conducted on other tissues (B2M, RPII, UBC and HMBS and a third set of novel genes (SF3A1, EEF1A2 and CASC3. Three different statistical algorithms were used to rank the genes by their stability measures as produced by geNorm, NormFinder and Bestkeeper. The three methods tend to agree on the most stably expressed genes and the least in muscular tissue. EEF1A2 and HMBS followed by SF3A1, ACTB, and CASC3 can be considered as stable reference genes, and B2M, RPII, UBC and GAPDH would not be appropriate. Although the rRNA-18S stability measure seems to be within the range of acceptance, its use is not recommended because its synthesis regulation is not representative of mRNA levels. Conclusion Based on geNorm algorithm, we propose the use of three genes SF3A1, EEF1A2 and HMBS as references for normalization of real-time RTqPCR in muscle expression studies.

  2. SIGNATURE: A workbench for gene expression signature analysis

    Directory of Open Access Journals (Sweden)

    Chang Jeffrey T

    2011-11-01

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

  3. 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...... have been found in numerous studies. It is unclear whether such alterations are related to specific mood states. As a biphasic disorder, mood state-related alterations in gene expression have the potential to point to markers of disease activity, and trait-related alterations might indicate...... vulnerability pathways. This review therefore evaluated the evidence for whether gene expression in bipolar disorder is state or trait related. Methods:  A systematic review, using the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guideline for reporting systematic reviews, based...

  4. GESearch: An Interactive GUI Tool for Identifying Gene Expression Signature

    Directory of Open Access Journals (Sweden)

    Ning Ye

    2015-01-01

    Full Text Available The huge amount of gene expression data generated by microarray and next-generation sequencing technologies present challenges to exploit their biological meanings. When searching for the coexpression genes, the data mining process is largely affected by selection of algorithms. Thus, it is highly desirable to provide multiple options of algorithms in the user-friendly analytical toolkit to explore the gene expression signatures. For this purpose, we developed GESearch, an interactive graphical user interface (GUI toolkit, which is written in MATLAB and supports a variety of gene expression data files. This analytical toolkit provides four models, including the mean, the regression, the delegate, and the ensemble models, to identify the coexpression genes, and enables the users to filter data and to select gene expression patterns by browsing the display window or by importing knowledge-based genes. Subsequently, the utility of this analytical toolkit is demonstrated by analyzing two sets of real-life microarray datasets from cell-cycle experiments. Overall, we have developed an interactive GUI toolkit that allows for choosing multiple algorithms for analyzing the gene expression signatures.

  5. Supplementary Material for: Global expression differences and tissue specific expression differences in rice evolution result in two contrasting types of differentially expressed genes

    KAUST Repository

    Horiuchi, Youko; Harushima, Yoshiaki; Fujisawa, Hironori; Mochizuki, Takako; Fujita, Masahiro; Ohyanagi, Hajime; Kurata, Nori

    2015-01-01

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

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

    Science.gov (United States)

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

    2012-12-03

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

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

    Directory of Open Access Journals (Sweden)

    Asadulina Albina

    2012-12-01

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

  8. Dlx homeobox gene family expression in osteoclasts.

    Science.gov (United States)

    Lézot, F; Thomas, B L; Blin-Wakkach, C; Castaneda, B; Bolanos, A; Hotton, D; Sharpe, P T; Heymann, D; Carles, G F; Grigoriadis, A E; Berdal, A

    2010-06-01

    Skeletal growth and homeostasis require the finely orchestrated secretion of mineralized tissue matrices by highly specialized cells, balanced with their degradation by osteoclasts. Time- and site-specific expression of Dlx and Msx homeobox genes in the cells secreting these matrices have been identified as important elements in the regulation of skeletal morphology. Such specific expression patterns have also been reported in osteoclasts for Msx genes. The aim of the present study was to establish the expression patterns of Dlx genes in osteoclasts and identify their function in regulating skeletal morphology. The expression patterns of all Dlx genes were examined during the whole osteoclastogenesis using different in vitro models. The results revealed that Dlx1 and Dlx2 are the only Dlx family members with a possible function in osteoclastogenesis as well as in mature osteoclasts. Dlx5 and Dlx6 were detected in the cultures but appear to be markers of monocytes and their derivatives. In vivo, Dlx2 expression in osteoclasts was examined using a Dlx2/LacZ transgenic mouse. Dlx2 is expressed in a subpopulation of osteoclasts in association with tooth, brain, nerve, and bone marrow volumetric growths. Altogether the present data suggest a role for Dlx2 in regulation of skeletal morphogenesis via functions within osteoclasts. (c) 2010 Wiley-Liss, Inc.

  9. Hepatocyte specific expression of human cloned genes

    Energy Technology Data Exchange (ETDEWEB)

    Cortese, R

    1986-01-01

    A large number of proteins are specifically synthesized in the hepatocyte. Only the adult liver expresses the complete repertoire of functions which are required at various stages during development. There is therefore a complex series of regulatory mechanisms responsible for the maintenance of the differentiated state and for the developmental and physiological variations in the pattern of gene expression. Human hepatoma cell lines HepG2 and Hep3B display a pattern of gene expression similar to adult and fetal liver, respectively; in contrast, cultured fibroblasts or HeLa cells do not express most of the liver specific genes. They have used these cell lines for transfection experiments with cloned human liver specific genes. DNA segments coding for alpha1-antitrypsin and retinol binding protein (two proteins synthesized both in fetal and adult liver) are expressed in the hepatoma cell lines HepG2 and Hep3B, but not in HeLa cells or fibroblasts. A DNA segment coding for haptoglobin (a protein synthesized only after birth) is only expressed in the hepatoma cell line HepG2 but not in Hep3B nor in non hepatic cell lines. The information for tissue specific expression is located in the 5' flanking region of all three genes. In vivo competition experiments show that these DNA segments bind to a common, apparently limiting, transacting factor. Conventional techniques (Bal deletions, site directed mutagenesis, etc.) have been used to precisely identify the DNA sequences responsible for these effects. The emerging picture is complex: they have identified multiple, separate transcriptional signals, essential for maximal promoter activation and tissue specific expression. Some of these signals show a negative effect on transcription in fibroblast cell lines.

  10. Gene Expression Signature in Endemic Osteoarthritis by Microarray Analysis

    Directory of Open Access Journals (Sweden)

    Xi Wang

    2015-05-01

    Full Text Available Kashin-Beck Disease (KBD is an endemic osteochondropathy with an unknown pathogenesis. Diagnosis of KBD is effective only in advanced cases, which eliminates the possibility of early treatment and leads to an inevitable exacerbation of symptoms. Therefore, we aim to identify an accurate blood-based gene signature for the detection of KBD. Previously published gene expression profile data on cartilage and peripheral blood mononuclear cells (PBMCs from adults with KBD were compared to select potential target genes. Microarray analysis was conducted to evaluate the expression of the target genes in a cohort of 100 KBD patients and 100 healthy controls. A gene expression signature was identified using a training set, which was subsequently validated using an independent test set with a minimum redundancy maximum relevance (mRMR algorithm and support vector machine (SVM algorithm. Fifty unique genes were differentially expressed between KBD patients and healthy controls. A 20-gene signature was identified that distinguished between KBD patients and controls with 90% accuracy, 85% sensitivity, and 95% specificity. This study identified a 20-gene signature that accurately distinguishes between patients with KBD and controls using peripheral blood samples. These results promote the further development of blood-based genetic biomarkers for detection of KBD.

  11. Gene expression profiles in skeletal muscle after gene electrotransfer

    DEFF Research Database (Denmark)

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

    2007-01-01

    BACKGROUND: Gene transfer by electroporation (DNA electrotransfer) to muscle results in high level long term transgenic expression, showing great promise for treatment of e.g. protein deficiency syndromes. However little is known about the effects of DNA electrotransfer on muscle fibres. We have...... caused down-regulation of structural proteins e.g. sarcospan and catalytic enzymes. Injection of DNA induced down-regulation of intracellular transport proteins e.g. sentrin. The effects on muscle fibres were transient as the expression profiles 3 weeks after treatment were closely related......) followed by a long low voltage pulse (LV, 100 V/cm, 400 ms); a pulse combination optimised for efficient and safe gene transfer. Muscles were transfected with green fluorescent protein (GFP) and excised at 4 hours, 48 hours or 3 weeks after treatment. RESULTS: Differentially expressed genes were...

  12. Classification across gene expression microarray studies

    Directory of Open Access Journals (Sweden)

    Kuner Ruprecht

    2009-12-01

    Full Text Available Abstract Background The increasing number of gene expression microarray studies represents an important resource in biomedical research. As a result, gene expression based diagnosis has entered clinical practice for patient stratification in breast cancer. However, the integration and combined analysis of microarray studies remains still a challenge. We assessed the potential benefit of data integration on the classification accuracy and systematically evaluated the generalization performance of selected methods on four breast cancer studies comprising almost 1000 independent samples. To this end, we introduced an evaluation framework which aims to establish good statistical practice and a graphical way to monitor differences. The classification goal was to correctly predict estrogen receptor status (negative/positive and histological grade (low/high of each tumor sample in an independent study which was not used for the training. For the classification we chose support vector machines (SVM, predictive analysis of microarrays (PAM, random forest (RF and k-top scoring pairs (kTSP. Guided by considerations relevant for classification across studies we developed a generalization of kTSP which we evaluated in addition. Our derived version (DV aims to improve the robustness of the intrinsic invariance of kTSP with respect to technologies and preprocessing. Results For each individual study the generalization error was benchmarked via complete cross-validation and was found to be similar for all classification methods. The misclassification rates were substantially higher in classification across studies, when each single study was used as an independent test set while all remaining studies were combined for the training of the classifier. However, with increasing number of independent microarray studies used in the training, the overall classification performance improved. DV performed better than the average and showed slightly less variance. In

  13. GSNFS: Gene subnetwork biomarker identification of lung cancer expression data.

    Science.gov (United States)

    Doungpan, Narumol; Engchuan, Worrawat; Chan, Jonathan H; Meechai, Asawin

    2016-12-05

    Gene expression has been used to identify disease gene biomarkers, but there are ongoing challenges. Single gene or gene-set biomarkers are inadequate to provide sufficient understanding of complex disease mechanisms and the relationship among those genes. Network-based methods have thus been considered for inferring the interaction within a group of genes to further study the disease mechanism. Recently, the Gene-Network-based Feature Set (GNFS), which is capable of handling case-control and multiclass expression for gene biomarker identification, has been proposed, partly taking into account of network topology. However, its performance relies on a greedy search for building subnetworks and thus requires further improvement. In this work, we establish a new approach named Gene Sub-Network-based Feature Selection (GSNFS) by implementing the GNFS framework with two proposed searching and scoring algorithms, namely gene-set-based (GS) search and parent-node-based (PN) search, to identify subnetworks. An additional dataset is used to validate the results. The two proposed searching algorithms of the GSNFS method for subnetwork expansion are concerned with the degree of connectivity and the scoring scheme for building subnetworks and their topology. For each iteration of expansion, the neighbour genes of a current subnetwork, whose expression data improved the overall subnetwork score, is recruited. While the GS search calculated the subnetwork score using an activity score of a current subnetwork and the gene expression values of its neighbours, the PN search uses the expression value of the corresponding parent of each neighbour gene. Four lung cancer expression datasets were used for subnetwork identification. In addition, using pathway data and protein-protein interaction as network data in order to consider the interaction among significant genes were discussed. Classification was performed to compare the performance of the identified gene subnetworks with three

  14. Gene expression analysis of flax seed development

    Science.gov (United States)

    2011-01-01

    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 clones that comprise

  15. 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

  16. 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.

  17. Scaling of gene expression data allowing the comparison of different gene expression platforms

    NARCIS (Netherlands)

    van Ruissen, Fred; Schaaf, Gerben J.; Kool, Marcel; Baas, Frank; Ruijter, Jan M.

    2008-01-01

    Serial analysis of gene expression (SAGE) and microarrays have found a widespread application, but much ambiguity exists regarding the amalgamation of the data resulting from these technologies. Cross-platform utilization of gene expression data from the SAGE and microarray technology could reduce

  18. Gene expression profiles in stages II and III colon cancers

    DEFF Research Database (Denmark)

    Thorsteinsson, Morten; Kirkeby, Lene T; Hansen, Raino

    2012-01-01

    PURPOSE: A 128-gene signature has been proposed to predict outcome in patients with stages II and III colorectal cancers. In the present study, we aimed to reproduce and validate the 128-gene signature in external and independent material. METHODS: Gene expression data from the original material...... were retrieved from the Gene Expression Omnibus (GEO) (n¿=¿111) in addition to a Danish data set (n¿=¿37). All patients had stages II and III colon cancers. A Prediction Analysis of Microarray classifier, based on the 128-gene signature and the original training set of stage I (n¿=¿65) and stage IV (n...... correctly predicted as stage IV-like, and the remaining patients were predicted as stage I-like and unclassifiable, respectively. Stage II patients could not be stratified. CONCLUSIONS: The 128-gene signature showed reproducibility in stage III colon cancer, but could not predict recurrence in stage II...

  19. Bayesian median regression for temporal gene expression data

    Science.gov (United States)

    Yu, Keming; Vinciotti, Veronica; Liu, Xiaohui; 't Hoen, Peter A. C.

    2007-09-01

    Most of the existing methods for the identification of biologically interesting genes in a temporal expression profiling dataset do not fully exploit the temporal ordering in the dataset and are based on normality assumptions for the gene expression. In this paper, we introduce a Bayesian median regression model to detect genes whose temporal profile is significantly different across a number of biological conditions. The regression model is defined by a polynomial function where both time and condition effects as well as interactions between the two are included. MCMC-based inference returns the posterior distribution of the polynomial coefficients. From this a simple Bayes factor test is proposed to test for significance. The estimation of the median rather than the mean, and within a Bayesian framework, increases the robustness of the method compared to a Hotelling T2-test previously suggested. This is shown on simulated data and on muscular dystrophy gene expression data.

  20. In situ gene expression and ecophysiology of thermophilic Cyanobacteria

    DEFF Research Database (Denmark)

    Jensen, Sheila Ingemann

    -378), the expression patterns of various functional genes (with an emphasis on nif genes involved in N2-fixation), the protein levels of nitrogenase (NifH), the N2-fixation activity, as well as microsensor based measurements on O2 availability, production and consumption were investigated in situ over the entire diel...... cycle. Interestingly, it was found that while the nif genes are expressed, and nitrogenase is synthesized once the mat gets anoxic in the early evening, the largest N2-fixation activity occurs as a burst during dim light in the early morning, albeit protein levels remained high over the entire course...

  1. Novel gene sets improve set-level classification of prokaryotic gene expression data.

    Science.gov (United States)

    Holec, Matěj; Kuželka, Ondřej; Železný, Filip

    2015-10-28

    Set-level classification of gene expression data has received significant attention recently. In this setting, high-dimensional vectors of features corresponding to genes are converted into lower-dimensional vectors of features corresponding to biologically interpretable gene sets. The dimensionality reduction brings the promise of a decreased risk of overfitting, potentially resulting in improved accuracy of the learned classifiers. However, recent empirical research has not confirmed this expectation. Here we hypothesize that the reported unfavorable classification results in the set-level framework were due to the adoption of unsuitable gene sets defined typically on the basis of the Gene ontology and the KEGG database of metabolic networks. We explore an alternative approach to defining gene sets, based on regulatory interactions, which we expect to collect genes with more correlated expression. We hypothesize that such more correlated gene sets will enable to learn more accurate classifiers. We define two families of gene sets using information on regulatory interactions, and evaluate them on phenotype-classification tasks using public prokaryotic gene expression data sets. From each of the two gene-set families, we first select the best-performing subtype. The two selected subtypes are then evaluated on independent (testing) data sets against state-of-the-art gene sets and against the conventional gene-level approach. The novel gene sets are indeed more correlated than the conventional ones, and lead to significantly more accurate classifiers. The novel gene sets are indeed more correlated than the conventional ones, and lead to significantly more accurate classifiers. Novel gene sets defined on the basis of regulatory interactions improve set-level classification of gene expression data. The experimental scripts and other material needed to reproduce the experiments are available at http://ida.felk.cvut.cz/novelgenesets.tar.gz.

  2. Conditional gene expression in the mouse using a Sleeping Beauty gene-trap transposon

    Directory of Open Access Journals (Sweden)

    Hackett Perry B

    2006-06-01

    Full Text Available Abstract Background Insertional mutagenesis techniques with transposable elements have been popular among geneticists studying model organisms from E. coli to Drosophila and, more recently, the mouse. One such element is the Sleeping Beauty (SB transposon that has been shown in several studies to be an effective insertional mutagen in the mouse germline. SB transposon vector studies have employed different functional elements and reporter molecules to disrupt and report the expression of endogenous mouse genes. We sought to generate a transposon system that would be capable of reporting the expression pattern of a mouse gene while allowing for conditional expression of a gene of interest in a tissue- or temporal-specific pattern. Results Here we report the systematic development and testing of a transposon-based gene-trap system incorporating the doxycycline-repressible Tet-Off (tTA system that is capable of activating the expression of genes under control of a Tet response element (TRE promoter. We demonstrate that the gene trap system is fully functional in vitro by introducing the "gene-trap tTA" vector into human cells by transposition and identifying clones that activate expression of a TRE-luciferase transgene in a doxycycline-dependent manner. In transgenic mice, we mobilize gene-trap tTA vectors, discover parameters that can affect germline mobilization rates, and identify candidate gene insertions to demonstrate the in vivo functionality of the vector system. We further demonstrate that the gene-trap can act as a reporter of endogenous gene expression and it can be coupled with bioluminescent imaging to identify genes with tissue-specific expression patterns. Conclusion Akin to the GAL4/UAS system used in the fly, we have made progress developing a tool for mutating and revealing the expression of mouse genes by generating the tTA transactivator in the presence of a secondary TRE-regulated reporter molecule. A vector like the gene

  3. Screening for interaction effects in gene expression data.

    Directory of Open Access Journals (Sweden)

    Peter J Castaldi

    Full Text Available Expression quantitative trait (eQTL studies are a powerful tool for identifying genetic variants that affect levels of messenger RNA. Since gene expression is controlled by a complex network of gene-regulating factors, one way to identify these factors is to search for interaction effects between genetic variants and mRNA levels of transcription factors (TFs and their respective target genes. However, identification of interaction effects in gene expression data pose a variety of methodological challenges, and it has become clear that such analyses should be conducted and interpreted with caution. Investigating the validity and interpretability of several interaction tests when screening for eQTL SNPs whose effect on the target gene expression is modified by the expression level of a transcription factor, we characterized two important methodological issues. First, we stress the scale-dependency of interaction effects and highlight that commonly applied transformation of gene expression data can induce or remove interactions, making interpretation of results more challenging. We then demonstrate that, in the setting of moderate to strong interaction effects on the order of what may be reasonably expected for eQTL studies, standard interaction screening can be biased due to heteroscedasticity induced by true interactions. Using simulation and real data analysis, we outline a set of reasonable minimum conditions and sample size requirements for reliable detection of variant-by-environment and variant-by-TF interactions using the heteroscedasticity consistent covariance-based approach.

  4. Serial Expression Analysis: a web tool for the analysis of serial gene expression data

    Science.gov (United States)

    Nueda, Maria José; Carbonell, José; Medina, Ignacio; Dopazo, Joaquín; Conesa, Ana

    2010-01-01

    Serial transcriptomics experiments investigate the dynamics of gene expression changes associated with a quantitative variable such as time or dosage. The statistical analysis of these data implies the study of global and gene-specific expression trends, the identification of significant serial changes, the comparison of expression profiles and the assessment of transcriptional changes in terms of cellular processes. We have created the SEA (Serial Expression Analysis) suite to provide a complete web-based resource for the analysis of serial transcriptomics data. SEA offers five different algorithms based on univariate, multivariate and functional profiling strategies framed within a user-friendly interface and a project-oriented architecture to facilitate the analysis of serial gene expression data sets from different perspectives. SEA is available at sea.bioinfo.cipf.es. PMID:20525784

  5. The RNA-Seq based high resolution gene expression atlas of chickpea (Cicer arietinum L.) reveals dynamic spatio-temporal changes associated with growth and development.

    Science.gov (United States)

    Kudapa, Himabindu; Garg, Vanika; Chitikineni, Annapurna; Varshney, Rajeev K

    2018-04-10

    Chickpea is one of the world's largest cultivated food legume and is an excellent source of high-quality protein to the human diet. Plant growth and development are controlled by programmed expression of a suite of genes at the given time, stage and tissue. Understanding how the underlying genome sequence translates into specific plant phenotypes at key developmental stages, information on gene expression patterns is crucial. Here we present a comprehensive Cicer arietinum Gene Expression Atlas (CaGEA) across the plant developmental stages and organs covering the entire life cycle of chickpea. One of the widely used drought tolerant cultivar, ICC 4958 has been used to generate RNA-Seq data from 27 samples at five major developmental stages of the plant. A total of 816 million raw reads were generated and of these, 794 million filtered reads after QC were subjected to downstream analysis. A total of 15,947 unique number of differentially expressed genes across different pairwise tissue combinations were identified. Significant differences in gene expression patterns contributing in the process of flowering, nodulation, seed and root development were inferred in this study. Furthermore, differentially expressed candidate genes from "QTL-hotspot" region associated with drought stress response in chickpea were validated. This article is protected by copyright. All rights reserved.

  6. Identification of highly synchronized subnetworks from gene expression data.

    Science.gov (United States)

    Gao, Shouguo; Wang, Xujing

    2013-01-01

    There has been a growing interest in identifying context-specific active protein-protein interaction (PPI) subnetworks through integration of PPI and time course gene expression data. However the interaction dynamics during the biological process under study has not been sufficiently considered previously. Here we propose a topology-phase locking (TopoPL) based scoring metric for identifying active PPI subnetworks from time series expression data. First the temporal coordination in gene expression changes is evaluated through phase locking analysis; The results are subsequently integrated with PPI to define an activity score for each PPI subnetwork, based on individual member expression, as well topological characteristics of the PPI network and of the expression temporal coordination network; Lastly, the subnetworks with the top scores in the whole PPI network are identified through simulated annealing search. Application of TopoPL to simulated data and to the yeast cell cycle data showed that it can more sensitively identify biologically meaningful subnetworks than the method that only utilizes the static PPI topology, or the additive scoring method. Using TopoPL we identified a core subnetwork with 49 genes important to yeast cell cycle. Interestingly, this core contains a protein complex known to be related to arrangement of ribosome subunits that exhibit extremely high gene expression synchronization. Inclusion of interaction dynamics is important to the identification of relevant gene networks.

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

    DEFF Research Database (Denmark)

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

    2015-01-01

    Many cancer-associated somatic copy number alterations (SCNAs) are known. Currently, one of the challenges is to identify the molecular downstream effects of these variants. Although several SCNAs are known to change gene expression levels, it is not clear whether each individual SCNA affects gen...

  8. Metallothionein gene expression in renal cell carcinoma

    Directory of Open Access Journals (Sweden)

    Deeksha Pal

    2014-01-01

    Full Text Available Introduction: Metallothioneins (MTs are a group of low-molecular weight, cysteine-rich proteins. In general, MT is known to modulate three fundamental processes: (1 the release of gaseous mediators such as hydroxyl radical or nitric oxide, (2 apoptosis and (3 the binding and exchange of heavy metals such as zinc, cadmium or copper. Previous studies have shown a positive correlation between the expression of MT with invasion, metastasis and poor prognosis in various cancers. Most of the previous studies primarily used immunohistochemistry to analyze localization of MT in renal cell carcinoma (RCC. No information is available on the gene expression of MT2A isoform in different types and grades of RCC. Materials and Methods: In the present study, total RNA was isolated from 38 histopathologically confirmed cases of RCC of different types and grades. Corresponding adjacent normal renal parenchyma was taken as control. Real-time polymerase chain reaction (RT PCR analysis was done for the MT2A gene expression using b-actin as an internal control. All statistical calculations were performed using SPSS software. Results: The MT2A gene expression was found to be significantly increased (P < 0.01 in clear cell RCC in comparison with the adjacent normal renal parenchyma. The expression of MT2A was two to three-fold higher in sarcomatoid RCC, whereas there was no change in papillary and collecting duct RCC. MT2A gene expression was significantly higher in lower grade (grades I and II, P < 0.05, while no change was observed in high-grade tumor (grade III and IV in comparison to adjacent normal renal tissue. Conclusion: The first report of the expression of MT2A in different types and grades of RCC and also these data further support the role of MT2A in tumorigenesis.

  9. Gene expression in early stage cervical cancer

    NARCIS (Netherlands)

    Biewenga, Petra; Buist, Marrije R.; Moerland, Perry D.; van Thernaat, Emiel Ver Loren; van Kampen, Antoine H. C.; ten Kate, Fiebo J. W.; Baas, Frank

    2008-01-01

    Objective. Pelvic lymph node metastases are the main prognostic factor for survival in early stage cervical cancer, yet accurate detection methods before surgery are lacking. In this study, we examined whether gene expression profiling can predict the presence of lymph node metastasis in early stage

  10. Shrinkage Approach for Gene Expression Data Analysis

    Czech Academy of Sciences Publication Activity Database

    Haman, Jiří; Valenta, Zdeněk; Kalina, Jan

    2013-01-01

    Roč. 1, č. 1 (2013), s. 65-65 ISSN 1805-8698. [EFMI 2013 Special Topic Conference. 17.04.2013-19.04.2013, Prague] Institutional support: RVO:67985807 Keywords : shrinkage estimation * covariance matrix * high dimensional data * gene expression Subject RIV: IN - Informatics, Computer Science

  11. 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.

  12. Regulation of methane genes and genome expression

    Energy Technology Data Exchange (ETDEWEB)

    John N. Reeve

    2009-09-09

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

  13. 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.

  14. Comparative gene expression of intestinal metabolizing enzymes.

    Science.gov (United States)

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

    2009-11-01

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

  15. Mapping in an apple (Malus x domestica) F1 segregating population based on physical clustering of differentially expressed genes

    Science.gov (United States)

    Background: Apple tree breeding is slow and difficult due to long generation times, self incompatibility, and complex genetics. The identification of molecular markers linked to traits of interest is a way to expedite the breeding process. In the present study, we aimed to identify genes whose stead...

  16. Gene expression patterns combined with network analysis identify hub genes associated with bladder cancer.

    Science.gov (United States)

    Bi, Dongbin; Ning, Hao; Liu, Shuai; Que, Xinxiang; Ding, Kejia

    2015-06-01

    To explore molecular mechanisms of bladder cancer (BC), network strategy was used to find biomarkers for early detection and diagnosis. The differentially expressed genes (DEGs) between bladder carcinoma patients and normal subjects were screened using empirical Bayes method of the linear models for microarray data package. Co-expression networks were constructed by differentially co-expressed genes and links. Regulatory impact factors (RIF) metric was used to identify critical transcription factors (TFs). The protein-protein interaction (PPI) networks were constructed by the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) and clusters were obtained through molecular complex detection (MCODE) algorithm. Centralities analyses for complex networks were performed based on degree, stress and betweenness. Enrichment analyses were performed based on Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) databases. Co-expression networks and TFs (based on expression data of global DEGs and DEGs in different stages and grades) were identified. Hub genes of complex networks, such as UBE2C, ACTA2, FABP4, CKS2, FN1 and TOP2A, were also obtained according to analysis of degree. In gene enrichment analyses of global DEGs, cell adhesion, proteinaceous extracellular matrix and extracellular matrix structural constituent were top three GO terms. ECM-receptor interaction, focal adhesion, and cell cycle were significant pathways. Our results provide some potential underlying biomarkers of BC. However, further validation is required and deep studies are needed to elucidate the pathogenesis of BC. Copyright © 2015 Elsevier Ltd. All rights reserved.

  17. Patterns of expression of cell wall related genes in sugarcane

    Directory of Open Access Journals (Sweden)

    Lima D.U.

    2001-01-01

    Full Text Available Our search for genes related to cell wall metabolism in the sugarcane expressed sequence tag (SUCEST database (http://sucest.lbi.dcc.unicamp.br resulted in 3,283 reads (1% of the total reads which were grouped into 459 clusters (potential genes with an average of 7.1 reads per cluster. To more clearly display our correlation coefficients, we constructed surface maps which we used to investigate the relationship between cell wall genes and the sugarcane tissues libraries from which they came. The only significant correlations that we found between cell wall genes and/or their expression within particular libraries were neutral or synergetic. Genes related to cellulose biosynthesis were from the CesA family, and were found to be the most abundant cell wall related genes in the SUCEST database. We found that the highest number of CesA reads came from the root and stem libraries. The genes with the greatest number of reads were those involved in cell wall hydrolases (e.g. beta-1,3-glucanases, xyloglucan endo-beta-transglycosylase, beta-glucosidase and endo-beta-mannanase. Correlation analyses by surface mapping revealed that the expression of genes related to biosynthesis seems to be associated with the hydrolysis of hemicelluloses, pectin hydrolases being mainly associated with xyloglucan hydrolases. The patterns of cell wall related gene expression in sugarcane based on the number of reads per cluster reflected quite well the expected physiological characteristics of the tissues. This is the first work to provide a general view on plant cell wall metabolism through the expression of related genes in almost all the tissues of a plant at the same time. For example, developing flowers behaved similarly to both meristematic tissues and leaf-root transition zone tissues. Besides providing a basis for future research on the mechanisms of plant development which involve the cell wall, our findings will provide valuable tools for plant engineering in the

  18. Differential expression and interaction of host factors augment HIV-1 gene expression in neonatal mononuclear cells

    International Nuclear Information System (INIS)

    Sundaravaradan, Vasudha; Mehta, Roshni; Harris, David T.; Zack, Jerome A.; Ahmad, Nafees

    2010-01-01

    We have previously shown a higher level of HIV-1 replication and gene expression in neonatal (cord) blood mononuclear cells (CBMC) compared with adult blood cells (PBMC), which could be due to differential expression of host factors. We performed the gene expression profile of CBMC and PBMC and found that 8013 genes were expressed at higher levels in CBMC than PBMC and 8028 genes in PBMC than CBMC, including 1181 and 1414 genes upregulated after HIV-1 infection in CBMC and PBMC, respectively. Several transcription factors (NF-κB, E2F, HAT-1, TFIIE, Cdk9, Cyclin T1), signal transducers (STAT3, STAT5A) and cytokines (IL-1β, IL-6, IL-10) were upregulated in CBMC than PBMC, which are known to influence HIV-1 replication. In addition, a repressor of HIV-1 transcription, YY1, was down regulated in CBMC than PBMC and several matrix metalloproteinase (MMP-7, -12, -14) were significantly upregulated in HIV-1 infected CBMC than PBMC. Furthermore, we show that CBMC nuclear extracts interacted with a higher extent to HIV-1 LTR cis-acting sequences, including NF-κB, NFAT, AP1 and NF-IL6 compared with PBMC nuclear extracts and retroviral based short hairpin RNA (shRNA) for STAT3 and IL-6 down regulated their own and HIV-1 gene expression, signifying that these factors influenced differential HIV-1 gene expression in CBMC than PBMC.

  19. Genetic architecture of gene expression in ovine skeletal muscle

    DEFF Research Database (Denmark)

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

    2011-01-01

    architecture to the gene expression data, which also discriminated the sire-based Estimated Breeding Value for the trait. An integrated systems biology approach was then used to identify the major functional pathways contributing to the genetics of enhanced muscling by using both Estimated Breeding Value...... has potential, amongst other mechanisms, to alter gene expression via cis- or trans-acting mechanisms in a manner that impacts the functional activities of specific pathways that contribute to muscling traits. By integrating sire-based genetic merit information for a muscling trait with progeny...

  20. AGEMAP: a gene expression database for aging in mice.

    Directory of Open Access Journals (Sweden)

    Jacob M Zahn

    2007-11-01

    Full Text Available We present the AGEMAP (Atlas of Gene Expression in Mouse Aging Project gene expression database, which is a resource that catalogs changes in gene expression as a function of age in mice. The AGEMAP database includes expression changes for 8,932 genes in 16 tissues as a function of age. We found great heterogeneity in the amount of transcriptional changes with age in different tissues. Some tissues displayed large transcriptional differences in old mice, suggesting that these tissues may contribute strongly to organismal decline. Other tissues showed few or no changes in expression with age, indicating strong levels of homeostasis throughout life. Based on the pattern of age-related transcriptional changes, we found that tissues could be classified into one of three aging processes: (1 a pattern common to neural tissues, (2 a pattern for vascular tissues, and (3 a pattern for steroid-responsive tissues. We observed that different tissues age in a coordinated fashion in individual mice, such that certain mice exhibit rapid aging, whereas others exhibit slow aging for multiple tissues. Finally, we compared the transcriptional profiles for aging in mice to those from humans, flies, and worms. We found that genes involved in the electron transport chain show common age regulation in all four species, indicating that these genes may be exceptionally good markers of aging. However, we saw no overall correlation of age regulation between mice and humans, suggesting that aging processes in mice and humans may be fundamentally different.

  1. Validation of suitable reference genes for quantitative gene expression analysis in Panax ginseng

    Directory of Open Access Journals (Sweden)

    Meizhen eWang

    2016-01-01

    Full Text Available Reverse transcription-qPCR (RT-qPCR has become a popular method for gene expression studies. Its results require data normalization by housekeeping genes. No single gene is proved to be stably expressed under all experimental conditions. Therefore, systematic evaluation of reference genes is necessary. With the aim to identify optimum reference genes for RT-qPCR analysis of gene expression in different tissues of Panax ginseng and the seedlings grown under heat stress, we investigated the expression stability of eight candidate reference genes, including elongation factor 1-beta (EF1-β, elongation factor 1-gamma (EF1-γ, eukaryotic translation initiation factor 3G (IF3G, eukaryotic translation initiation factor 3B (IF3B, actin (ACT, actin11 (ACT11, glyceraldehyde-3-phosphate dehydrogenase (GAPDH and cyclophilin ABH-like protein (CYC, using four widely used computational programs: geNorm, Normfinder, BestKeeper, and the comparative ΔCt method. The results were then integrated using the web-based tool RefFinder. As a result, EF1-γ, IF3G and EF1-β were the three most stable genes in different tissues of P. ginseng, while IF3G, ACT11 and GAPDH were the top three-ranked genes in seedlings treated with heat. Using three better reference genes alone or in combination as internal control, we examined the expression profiles of MAR, a multiple function-associated mRNA-like non-coding RNA (mlncRNA in P. ginseng. Taken together, we recommended EF1-γ/IF3G and IF3G/ACT11 as the suitable pair of reference genes for RT-qPCR analysis of gene expression in different tissues of P. ginseng and the seedlings grown under heat stress, respectively. The results serve as a foundation for future studies on P. ginseng functional genomics.

  2. Gene expression profiles reveal key genes for early diagnosis and treatment of adamantinomatous craniopharyngioma.

    Science.gov (United States)

    Yang, Jun; Hou, Ziming; Wang, Changjiang; Wang, Hao; Zhang, Hongbing

    2018-04-23

    Adamantinomatous craniopharyngioma (ACP) is an aggressive brain tumor that occurs predominantly in the pediatric population. Conventional diagnosis method and standard therapy cannot treat ACPs effectively. In this paper, we aimed to identify key genes for ACP early diagnosis and treatment. Datasets GSE94349 and GSE68015 were obtained from Gene Expression Omnibus database. Consensus clustering was applied to discover the gene clusters in the expression data of GSE94349 and functional enrichment analysis was performed on gene set in each cluster. The protein-protein interaction (PPI) network was built by the Search Tool for the Retrieval of Interacting Genes, and hubs were selected. Support vector machine (SVM) model was built based on the signature genes identified from enrichment analysis and PPI network. Dataset GSE94349 was used for training and testing, and GSE68015 was used for validation. Besides, RT-qPCR analysis was performed to analyze the expression of signature genes in ACP samples compared with normal controls. Seven gene clusters were discovered in the differentially expressed genes identified from GSE94349 dataset. Enrichment analysis of each cluster identified 25 pathways that highly associated with ACP. PPI network was built and 46 hubs were determined. Twenty-five pathway-related genes that overlapped with the hubs in PPI network were used as signatures to establish the SVM diagnosis model for ACP. The prediction accuracy of SVM model for training, testing, and validation data were 94, 85, and 74%, respectively. The expression of CDH1, CCL2, ITGA2, COL8A1, COL6A2, and COL6A3 were significantly upregulated in ACP tumor samples, while CAMK2A, RIMS1, NEFL, SYT1, and STX1A were significantly downregulated, which were consistent with the differentially expressed gene analysis. SVM model is a promising classification tool for screening and early diagnosis of ACP. The ACP-related pathways and signature genes will advance our knowledge of ACP pathogenesis

  3. Cerebrovascular gene expression in spontaneously hypertensive rats

    DEFF Research Database (Denmark)

    Grell, Anne-Sofie; Frederiksen, Simona Denise; Edvinsson, Lars

    2017-01-01

    Hypertension is a hemodynamic disorder and one of the most important and well-established risk factors for vascular diseases such as stroke. Blood vessels exposed to chronic shear stress develop structural changes and remodeling of the vascular wall through many complex mechanisms. However......, the molecular mechanisms involved are not fully understood. Hypertension-susceptible genes may provide a novel insight into potential molecular mechanisms of hypertension and secondary complications associated with hypertension. The aim of this exploratory study was to identify gene expression differences......, the identified genes in the middle cerebral arteries from spontaneously hypertensive rats could be possible mediators of the vascular changes and secondary complications associated with hypertension. This study supports the selection of key genes to investigate in the future research of hypertension-induced end...

  4. USAGE: a web-based approach towards the analysis of SAGE data. Serial Analysis of Gene Expression

    NARCIS (Netherlands)

    van Kampen, A. H.; van Schaik, B. D.; Pauws, E.; Michiels, E. M.; Ruijter, J. M.; Caron, H. N.; Versteeg, R.; Heisterkamp, S. H.; Leunissen, J. A.; Baas, F.; van der Mee, M.

    2000-01-01

    MOTIVATION: SAGE enables the determination of genome-wide mRNA expression profiles. A comprehensive analysis of SAGE data requires software, which integrates (statistical) data analysis methods with a database system. Furthermore, to facilitate data sharing between users, the application should

  5. Analyzing gene expression profiles in dilated cardiomyopathy via bioinformatics methods.

    Science.gov (United States)

    Wang, Liming; Zhu, L; Luan, R; Wang, L; Fu, J; Wang, X; Sui, L

    2016-10-10

    Dilated cardiomyopathy (DCM) is characterized by ventricular dilatation, and it is a common cause of heart failure and cardiac transplantation. This study aimed to explore potential DCM-related genes and their underlying regulatory mechanism using methods of bioinformatics. The gene expression profiles of GSE3586 were downloaded from Gene Expression Omnibus database, including 15 normal samples and 13 DCM samples. The differentially expressed genes (DEGs) were identified between normal and DCM samples using Limma package in R language. Pathway enrichment analysis of DEGs was then performed. Meanwhile, the potential transcription factors (TFs) and microRNAs (miRNAs) of these DEGs were predicted based on their binding sequences. In addition, DEGs were mapped to the cMap database to find the potential small molecule drugs. A total of 4777 genes were identified as DEGs by comparing gene expression profiles between DCM and control samples. DEGs were significantly enriched in 26 pathways, such as lymphocyte TarBase pathway and androgen receptor signaling pathway. Furthermore, potential TFs (SP1, LEF1, and NFAT) were identified, as well as potential miRNAs (miR-9, miR-200 family, and miR-30 family). Additionally, small molecules like isoflupredone and trihexyphenidyl were found to be potential therapeutic drugs for DCM. The identified DEGs (PRSS12 and FOXG1), potential TFs, as well as potential miRNAs, might be involved in DCM.

  6. Analyzing gene expression profiles in dilated cardiomyopathy via bioinformatics methods

    Directory of Open Access Journals (Sweden)

    Liming Wang

    Full Text Available Dilated cardiomyopathy (DCM is characterized by ventricular dilatation, and it is a common cause of heart failure and cardiac transplantation. This study aimed to explore potential DCM-related genes and their underlying regulatory mechanism using methods of bioinformatics. The gene expression profiles of GSE3586 were downloaded from Gene Expression Omnibus database, including 15 normal samples and 13 DCM samples. The differentially expressed genes (DEGs were identified between normal and DCM samples using Limma package in R language. Pathway enrichment analysis of DEGs was then performed. Meanwhile, the potential transcription factors (TFs and microRNAs (miRNAs of these DEGs were predicted based on their binding sequences. In addition, DEGs were mapped to the cMap database to find the potential small molecule drugs. A total of 4777 genes were identified as DEGs by comparing gene expression profiles between DCM and control samples. DEGs were significantly enriched in 26 pathways, such as lymphocyte TarBase pathway and androgen receptor signaling pathway. Furthermore, potential TFs (SP1, LEF1, and NFAT were identified, as well as potential miRNAs (miR-9, miR-200 family, and miR-30 family. Additionally, small molecules like isoflupredone and trihexyphenidyl were found to be potential therapeutic drugs for DCM. The identified DEGs (PRSS12 and FOXG1, potential TFs, as well as potential miRNAs, might be involved in DCM.

  7. Digital gene expression analysis of gene expression differences within Brassica diploids and allopolyploids.

    Science.gov (United States)

    Jiang, Jinjin; Wang, Yue; Zhu, Bao; Fang, Tingting; Fang, Yujie; Wang, Youping

    2015-01-27

    Brassica includes many successfully cultivated crop species of polyploid origin, either by ancestral genome triplication or by hybridization between two diploid progenitors, displaying complex repetitive sequences and transposons. The U's triangle, which consists of three diploids and three amphidiploids, is optimal for the analysis of complicated genomes after polyploidization. Next-generation sequencing enables the transcriptome profiling of polyploids on a global scale. We examined the gene expression patterns of three diploids (Brassica rapa, B. nigra, and B. oleracea) and three amphidiploids (B. napus, B. juncea, and B. carinata) via digital gene expression analysis. In total, the libraries generated between 5.7 and 6.1 million raw reads, and the clean tags of each library were mapped to 18547-21995 genes of B. rapa genome. The unambiguous tag-mapped genes in the libraries were compared. Moreover, the majority of differentially expressed genes (DEGs) were explored among diploids as well as between diploids and amphidiploids. Gene ontological analysis was performed to functionally categorize these DEGs into different classes. The Kyoto Encyclopedia of Genes and Genomes analysis was performed to assign these DEGs into approximately 120 pathways, among which the metabolic pathway, biosynthesis of secondary metabolites, and peroxisomal pathway were enriched. The non-additive genes in Brassica amphidiploids were analyzed, and the results indicated that orthologous genes in polyploids are frequently expressed in a non-additive pattern. Methyltransferase genes showed differential expression pattern in Brassica species. Our results provided an understanding of the transcriptome complexity of natural Brassica species. The gene expression changes in diploids and allopolyploids may help elucidate the morphological and physiological differences among Brassica species.

  8. Gene expression analysis of precision-cut human liver slices indicates stable expression of ADME-Tox related genes

    NARCIS (Netherlands)

    Elferink, M. G. L.; Olinga, P.; van Leeuwen, E. M.; Bauerschmidt, S.; Polman, J.; Schoonen, W. G.; Heisterkamp, S. H.; Groothuis, G. M. M.

    2011-01-01

    In the process of drug development it is of high importance to test the safety of new drugs with predictive value for human toxicity. A promising approach of toxicity testing is based on shifts in gene expression profiling of the liver. Toxicity screening based on animal liver cells cannot be

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

    Science.gov (United States)

    2012-01-01

    Background A common approach for time series gene expression data analysis includes the clustering of genes with similar expression patterns throughout time. Clustered gene expression profiles point to the joint contribution of groups of genes to a particular cellular process. However, since genes belong to intricate networks, other features, besides comparable expression patterns, should provide additional information for the identification of functionally similar genes. Results In this study we perform gene clustering through the identification of Granger causality between and within sets of time series gene expression data. Granger causality is based on the idea that the cause of an event cannot come after its consequence. Conclusions This kind of analysis can be used as a complementary approach for functional clustering, wherein genes would be clustered not solely based on their expression similarity but on their topological proximity built according to the intensity of Granger causality among them. PMID:23107425

  10. Biomarker MicroRNAs for Diagnosis of Oral Squamous Cell Carcinoma Identified Based on Gene Expression Data and MicroRNA-mRNA Network Analysis

    Science.gov (United States)

    Zhang, Hui; Li, Tangxin; Zheng, Linqing

    2017-01-01

    Oral squamous cell carcinoma is one of the most malignant tumors with high mortality rate worldwide. Biomarker discovery is critical for early diagnosis and precision treatment of this disease. MicroRNAs are small noncoding RNA molecules which often regulate essential biological processes and are good candidates for biomarkers. By integrative analysis of both the cancer-associated gene expression data and microRNA-mRNA network, miR-148b-3p, miR-629-3p, miR-27a-3p, and miR-142-3p were screened as novel diagnostic biomarkers for oral squamous cell carcinoma based on their unique regulatory abilities in the network structure of the conditional microRNA-mRNA network and their important functions. These findings were confirmed by literature verification and functional enrichment analysis. Future experimental validation is expected for the further investigation of their molecular mechanisms. PMID:29098014

  11. Global gene expression in Escherichia coli biofilms

    DEFF Research Database (Denmark)

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

    2003-01-01

    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 antimicr......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...... the transition to biofilm growth, and these included genes expressed under oxygen-limiting conditions, genes encoding (putative) transport proteins, putative oxidoreductases and genes associated with enhanced heavy metal resistance. Of particular interest was the observation that many of the genes altered...... 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....

  12. A compendium of canine normal tissue gene expression.

    Directory of Open Access Journals (Sweden)

    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 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.

  13. A mammalianized synthetic nitroreductase gene for high-level expression

    International Nuclear Information System (INIS)

    Grohmann, Maik; Paulmann, Nils; Fleischhauer, Sebastian; Vowinckel, Jakob; Priller, Josef; Walther, Diego J

    2009-01-01

    The nitroreductase/5-(azaridin-1-yl)-2,4-dinitrobenzamide (NTR/CB1954) enzyme/prodrug system is considered as a promising candidate for anti-cancer strategies by gene-directed enzyme prodrug therapy (GDEPT) and has recently entered clinical trials. It requires the genetic modification of tumor cells to express the E. coli enzyme nitroreductase that bioactivates the prodrug CB1954 to a powerful cytotoxin. This metabolite causes apoptotic cell death by DNA interstrand crosslinking. Enhancing the enzymatic NTR activity for CB1954 should improve the therapeutical potential of this enzyme-prodrug combination in cancer gene therapy. We performed de novo synthesis of the bacterial nitroreductase gene adapting codon usage to mammalian preferences. The synthetic gene was investigated for its expression efficacy and ability to sensitize mammalian cells to CB1954 using western blotting analysis and cytotoxicity assays. In our study, we detected cytoplasmic protein aggregates by expressing GFP-tagged NTR in COS-7 cells, suggesting an impaired translation by divergent codon usage between prokaryotes and eukaryotes. Therefore, we generated a synthetic variant of the nitroreductase gene, called ntro, adapted for high-level expression in mammalian cells. A total of 144 silent base substitutions were made within the bacterial ntr gene to change its codon usage to mammalian preferences. The codon-optimized ntro either tagged to gfp or c-myc showed higher expression levels in mammalian cell lines. Furthermore, the ntro rendered several cell lines ten times more sensitive to the prodrug CB1954 and also resulted in an improved bystander effect. Our results show that codon optimization overcomes expression limitations of the bacterial ntr gene in mammalian cells, thereby improving the NTR/CB1954 system at translational level for cancer gene therapy in humans

  14. The claudin gene family: expression in normal and neoplastic tissues

    International Nuclear Information System (INIS)

    Hewitt, Kyle J; Agarwal, Rachana; Morin, Patrice J

    2006-01-01

    The claudin (CLDN) genes encode a family of proteins important in tight junction formation and function. Recently, it has become apparent that CLDN gene expression is frequently altered in several human cancers. However, the exact patterns of CLDN expression in various cancers is unknown, as only a limited number of CLDN genes have been investigated in a few tumors. We identified all the human CLDN genes from Genbank and we used the large public SAGE database to ascertain the gene expression of all 21 CLDN in 266 normal and neoplastic tissues. Using real-time RT-PCR, we also surveyed a subset of 13 CLDN genes in 24 normal and 24 neoplastic tissues. We show that claudins represent a family of highly related proteins, with claudin-16, and -23 being the most different from the others. From in silico analysis and RT-PCR data, we find that most claudin genes appear decreased in cancer, while CLDN3, CLDN4, and CLDN7 are elevated in several malignancies such as those originating from the pancreas, bladder, thyroid, fallopian tubes, ovary, stomach, colon, breast, uterus, and the prostate. Interestingly, CLDN5 is highly expressed in vascular endothelial cells, providing a possible target for antiangiogenic therapy. CLDN18 might represent a biomarker for gastric cancer. Our study confirms previously known CLDN gene expression patterns and identifies new ones, which may have applications in the detection, prognosis and therapy of several human cancers. In particular we identify several malignancies that express CLDN3 and CLDN4. These cancers may represent ideal candidates for a novel therapy being developed based on CPE, a toxin that specifically binds claudin-3 and claudin-4

  15. Xylella fastidiosa gene expression analysis by DNA microarrays

    OpenAIRE

    Travensolo,Regiane F.; Carareto-Alves,Lucia M.; Costa,Maria V.C.G.; Lopes,Tiago J.S.; Carrilho,Emanuel; Lemos,Eliana G.M.

    2009-01-01

    Xylella fastidiosa genome sequencing has generated valuable data by identifying genes acting either on metabolic pathways or in associated pathogenicity and virulence. Based on available information on these genes, new strategies for studying their expression patterns, such as microarray technology, were employed. A total of 2,600 primer pairs were synthesized and then used to generate fragments using the PCR technique. The arrays were hybridized against cDNAs labeled during reverse transcrip...

  16. Automatic Control of Gene Expression in Mammalian Cells.

    Science.gov (United States)

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

    2016-04-15

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

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

    Science.gov (United States)

    2012-01-01

    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. PMID:23164410

  18. Sequential Logic Model Deciphers Dynamic Transcriptional Control of Gene Expressions

    Science.gov (United States)

    Yeo, Zhen Xuan; Wong, Sum Thai; Arjunan, Satya Nanda Vel; Piras, Vincent; Tomita, Masaru; Selvarajoo, Kumar; Giuliani, Alessandro; Tsuchiya, Masa

    2007-01-01

    Background Cellular signaling involves a sequence of events from ligand binding to membrane receptors through transcription factors activation and the induction of mRNA expression. The transcriptional-regulatory system plays a pivotal role in the control of gene expression. A novel computational approach to the study of gene regulation circuits is presented here. Methodology Based on the concept of finite state machine, which provides a discrete view of gene regulation, a novel sequential logic model (SLM) is developed to decipher control mechanisms of dynamic transcriptional regulation of gene expressions. The SLM technique is also used to systematically analyze the dynamic function of transcriptional inputs, the dependency and cooperativity, such as synergy effect, among the binding sites with respect to when, how much and how fast the gene of interest is expressed. Principal Findings SLM is verified by a set of well studied expression data on endo16 of Strongylocentrotus purpuratus (sea urchin) during the embryonic midgut development. A dynamic regulatory mechanism for endo16 expression controlled by three binding sites, UI, R and Otx is identified and demonstrated to be consistent with experimental findings. Furthermore, we show that during transition from specification to differentiation in wild type endo16 expression profile, SLM reveals three binary activities are not sufficient to explain the transcriptional regulation of endo16 expression and additional activities of binding sites are required. Further analyses suggest detailed mechanism of R switch activity where indirect dependency occurs in between UI activity and R switch during specification to differentiation stage. Conclusions/Significance The sequential logic formalism allows for a simplification of regulation network dynamics going from a continuous to a discrete representation of gene activation in time. In effect our SLM is non-parametric and model-independent, yet providing rich biological

  19. Sequential logic model deciphers dynamic transcriptional control of gene expressions.

    Directory of Open Access Journals (Sweden)

    Zhen Xuan Yeo

    Full Text Available BACKGROUND: Cellular signaling involves a sequence of events from ligand binding to membrane receptors through transcription factors activation and the induction of mRNA expression. The transcriptional-regulatory system plays a pivotal role in the control of gene expression. A novel computational approach to the study of gene regulation circuits is presented here. METHODOLOGY: Based on the concept of finite state machine, which provides a discrete view of gene regulation, a novel sequential logic model (SLM is developed to decipher control mechanisms of dynamic transcriptional regulation of gene expressions. The SLM technique is also used to systematically analyze the dynamic function of transcriptional inputs, the dependency and cooperativity, such as synergy effect, among the binding sites with respect to when, how much and how fast the gene of interest is expressed. PRINCIPAL FINDINGS: SLM is verified by a set of well studied expression data on endo16 of Strongylocentrotus purpuratus (sea urchin during the embryonic midgut development. A dynamic regulatory mechanism for endo16 expression controlled by three binding sites, UI, R and Otx is identified and demonstrated to be consistent with experimental findings. Furthermore, we show that during transition from specification to differentiation in wild type endo16 expression profile, SLM reveals three binary activities are not sufficient to explain the transcriptional regulation of endo16 expression and additional activities of binding sites are required. Further analyses suggest detailed mechanism of R switch activity where indirect dependency occurs in between UI activity and R switch during specification to differentiation stage. CONCLUSIONS/SIGNIFICANCE: The sequential logic formalism allows for a simplification of regulation network dynamics going from a continuous to a discrete representation of gene activation in time. In effect our SLM is non-parametric and model-independent, yet

  20. 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

  1. 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

  2. Decomposition of gene expression state space trajectories.

    Directory of Open Access Journals (Sweden)

    Jessica C Mar

    2009-12-01

    Full Text Available Representing and analyzing complex networks remains a roadblock to creating dynamic network models of biological processes and pathways. The study of cell fate transitions can reveal much about the transcriptional regulatory programs that underlie these phenotypic changes and give rise to the coordinated patterns in expression changes that we observe. The application of gene expression state space trajectories to capture cell fate transitions at the genome-wide level is one approach currently used in the literature. In this paper, we analyze the gene expression dataset of Huang et al. (2005 which follows the differentiation of promyelocytes into neutrophil-like cells in the presence of inducers dimethyl sulfoxide and all-trans retinoic acid. Huang et al. (2005 build on the work of Kauffman (2004 who raised the attractor hypothesis, stating that cells exist in an expression landscape and their expression trajectories converge towards attractive sites in this landscape. We propose an alternative interpretation that explains this convergent behavior by recognizing that there are two types of processes participating in these cell fate transitions-core processes that include the specific differentiation pathways of promyelocytes to neutrophils, and transient processes that capture those pathways and responses specific to the inducer. Using functional enrichment analyses, specific biological examples and an analysis of the trajectories and their core and transient components we provide a validation of our hypothesis using the Huang et al. (2005 dataset.

  3. 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.

  4. Repetitive Imaging of Reporter Gene Expression in the Lung

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    Jean-Christophe Richard

    2003-10-01

    Full Text Available Positron emission tomographic imaging is emerging as a powerful technology to monitor reporter transgene expression in the lungs and other organs. However, little information is available about its usefulness for studying gene expression over time. Therefore, we infected 20 rats with a replication-deficient adenovirus containing a fusion gene encoding for a mutant Herpes simplex virus type-1 thymidine kinase and an enhanced green fluorescent protein. Five additional rats were infected with a control virus. Pulmonary gene transfer was performed via intratracheal administration of vector using a surfactant-based method. Imaging was performed 4–6 hr, and 4, 7, and 10 days after gene transfer, using 9-(4-[18F]-fluoro-3-hydroxymethylbutylguanine, an imaging substrate for the mutant kinase. Lung tracer uptake assessed with imaging was moderately but significantly increased 4–6 hr after gene transfer, was maximal after 4 days, and was no longer detectable by 10 days. The temporal pattern of transgene expression measured ex vivo with in vitro assays of thymidine kinase activity and green fluorescent protein was similar to imaging. In conclusion, positron emission tomography is a reliable new tool to evaluate the onset and duration of reporter gene expression noninvasively in the lungs of intact animals.

  5. Xylella fastidiosa gene expression analysis by DNA microarrays

    Directory of Open Access Journals (Sweden)

    Regiane F. Travensolo

    2009-01-01

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

  6. Alteration in follistatin gene expression detected in prenatally androgenized rats.

    Science.gov (United States)

    Salehi Jahromi, Marziyeh; Ramezani Tehrani, Fahimeh; Hill, Jennifer W; Noroozzadeh, Mahsa; Zarkesh, Maryam; Ghasemi, Asghar; Zadeh-Vakili, Azita

    2017-06-01

    Impaired ovarian follicle development, the hallmark of polycystic ovarian syndrome (PCOS), is believed to be due to the changes in expression of related genes such as follistatin (FST). Expression of FST gene and methylation level of its promoter in theca cells from adult female rats, prenatally exposed to androgen excess, during different phases of the estrus cycle was determined and compared with controls. Eight pregnant Wistar rats (experimental group) were treated by subcutaneous injection of 5 mg free testosterone on day 20 of pregnancy, while controls (n = 8) received 500 ml solvent. Based on observed vaginal smear, adult female offspring of mothers were divided into three groups. Levels of serum steroidogenic sexual hormones and gonadotropins, expression and promoter methylation of the FST gene were measured using ELISA, cyber-green real-time PCR and bisulfite sequence PCR (BSP), respectively. Compared to controls, the relative expression of FST gene in the treated group decreased overall by 0.85 fold; despite significant changes in different phases, but no significant differences in methylation of FST promoter. Our results reveal that manifestation of PCOS-like phenotype following prenatal exposure to excess androgen is associated with irregularity in expression of the FST gene during the estrus cycle.

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

    KAUST Repository

    Horiuchi, Youko; Harushima, Yoshiaki; Fujisawa, Hironori; Mochizuki, Takako; Fujita, Masahiro; Ohyanagi, Hajime; Kurata, Nori

    2015-01-01

    Since the development of transcriptome analysis systems, many expression evolution studies characterized evolutionary forces acting on gene expression, without explicit discrimination between global expression differences and tissue

  8. Time-Delay Effects on Constitutive Gene Expression*

    International Nuclear Information System (INIS)

    Feng Yan-Ling; Wang Dan; Tang Xu-Lei; Dong Jian-Min

    2017-01-01

    The dynamics of constitutive gene expression with delayed mRNA degradation is investigated, where the intrinsic noise caused by the small number of reactant molecules is introduced. It is found that the oscillatory behavior claimed in previous investigations does not appear in the approximation of small time delay, and the steady state distribution still follows the Poisson law. Furthermore, we introduce the extrinsic noise induced by surrounding environment to explore the effects of this noise and time delay on the Fano factor. Based on a delay Langevin equation and the corresponding Fokker–Planck equation, the distribution of mRNA copy-number is achieved analytically. The time delay and extrinsic noise play similar roles in the gene expression system, that is, they are able to result in the deviation of the Fano factor from 1 evidently. The measured Fano factor for constitutive gene expression is slightly larger than 1, which is perhaps attributed to the time-delay effect. (paper)

  9. Modeling gene expression measurement error: a quasi-likelihood approach

    Directory of Open Access Journals (Sweden)

    Strimmer Korbinian

    2003-03-01

    Full Text Available Abstract Background Using suitable error models for gene expression measurements is essential in the statistical analysis of microarray data. However, the true probabilistic model underlying gene expression intensity readings is generally not known. Instead, in currently used approaches some simple parametric model is assumed (usually a transformed normal distribution or the empirical distribution is estimated. However, both these strategies may not be optimal for gene expression data, as the non-parametric approach ignores known structural information whereas the fully parametric models run the risk of misspecification. A further related problem is the choice of a suitable scale for the model (e.g. observed vs. log-scale. Results Here a simple semi-parametric model for gene expression measurement error is presented. In this approach inference is based an approximate likelihood function (the extended quasi-likelihood. Only partial knowledge about the unknown true distribution is required to construct this function. In case of gene expression this information is available in the form of the postulated (e.g. quadratic variance structure of the data. As the quasi-likelihood behaves (almost like a proper likelihood, it allows for the estimation of calibration and variance parameters, and it is also straightforward to obtain corresponding approximate confidence intervals. Unlike most other frameworks, it also allows analysis on any preferred scale, i.e. both on the original linear scale as well as on a transformed scale. It can also be employed in regression approaches to model systematic (e.g. array or dye effects. Conclusions The quasi-likelihood framework provides a simple and versatile approach to analyze gene expression data that does not make any strong distributional assumptions about the underlying error model. For several simulated as well as real data sets it provides a better fit to the data than competing models. In an example it also

  10. Network-Based Integration of GWAS and Gene Expression Identifies a HOX-Centric Network Associated with Serous Ovarian Cancer Risk

    DEFF Research Database (Denmark)

    Kar, Siddhartha P; Tyrer, Jonathan P; Li, Qiyuan

    2015-01-01

    BACKGROUND: Genome-wide association studies (GWAS) have so far reported 12 loci associated with serous epithelial ovarian cancer (EOC) risk. We hypothesized that some of these loci function through nearby transcription factor (TF) genes and that putative target genes of these TFs as identified...... in the unified microarray dataset of 489 serous EOC tumors from The Cancer Genome Atlas. Genes represented in this dataset were subsequently ranked using a gene-level test based on results for germline SNPs from a serous EOC GWAS meta-analysis (2,196 cases/4,396 controls). RESULTS: Gene set enrichment analysis...

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

    Directory of Open Access Journals (Sweden)

    Ali Oghabian

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

  12. Confidence in Phase Definition for Periodicity in Genes Expression Time Series.

    Science.gov (United States)

    El Anbari, Mohammed; Fadda, Abeer; Ptitsyn, Andrey

    2015-01-01

    Circadian oscillation in baseline gene expression plays an important role in the regulation of multiple cellular processes. Most of the knowledge of circadian gene expression is based on studies measuring gene expression over time. Our ability to dissect molecular events in time is determined by the sampling frequency of such experiments. However, the real peaks of gene activity can be at any time on or between the time points at which samples are collected. Thus, some genes with a peak activity near the observation point have their phase of oscillation detected with better precision then those which peak between observation time points. Separating genes for which we can confidently identify peak activity from ambiguous genes can improve the analysis of time series gene expression. In this study we propose a new statistical method to quantify the phase confidence of circadian genes. The numerical performance of the proposed method has been tested using three real gene expression data sets.

  13. Three gene expression vector sets for concurrently expressing multiple genes in Saccharomyces cerevisiae.

    Science.gov (United States)

    Ishii, Jun; Kondo, Takashi; Makino, Harumi; Ogura, Akira; Matsuda, Fumio; Kondo, Akihiko

    2014-05-01

    Yeast has the potential to be used in bulk-scale fermentative production of fuels and chemicals due to its tolerance for low pH and robustness for autolysis. However, expression of multiple external genes in one host yeast strain is considerably labor-intensive due to the lack of polycistronic transcription. To promote the metabolic engineering of yeast, we generated systematic and convenient genetic engineering tools to express multiple genes in Saccharomyces cerevisiae. We constructed a series of multi-copy and integration vector sets for concurrently expressing two or three genes in S. cerevisiae by embedding three classical promoters. The comparative expression capabilities of the constructed vectors were monitored with green fluorescent protein, and the concurrent expression of genes was monitored with three different fluorescent proteins. Our multiple gene expression tool will be helpful to the advanced construction of genetically engineered yeast strains in a variety of research fields other than metabolic engineering. © 2014 Federation of European Microbiological Societies. Published by John Wiley & Sons Ltd. All rights reserved.

  14. Development and validation of a gene expression-based signature to predict distant metastasis in locoregionally advanced nasopharyngeal carcinoma: a retrospective, multicentre, cohort study.

    Science.gov (United States)

    Tang, Xin-Ran; Li, Ying-Qin; Liang, Shao-Bo; Jiang, Wei; Liu, Fang; Ge, Wen-Xiu; Tang, Ling-Long; Mao, Yan-Ping; He, Qing-Mei; Yang, Xiao-Jing; Zhang, Yuan; Wen, Xin; Zhang, Jian; Wang, Ya-Qin; Zhang, Pan-Pan; Sun, Ying; Yun, Jing-Ping; Zeng, Jing; Li, Li; Liu, Li-Zhi; Liu, Na; Ma, Jun

    2018-03-01

    Gene expression patterns can be used as prognostic biomarkers in various types of cancers. We aimed to identify a gene expression pattern for individual distant metastatic risk assessment in patients with locoregionally advanced nasopharyngeal carcinoma. In this multicentre, retrospective, cohort analysis, we included 937 patients with locoregionally advanced nasopharyngeal carcinoma from three Chinese hospitals: the Sun Yat-sen University Cancer Center (Guangzhou, China), the Affiliated Hospital of Guilin Medical University (Guilin, China), and the First People's Hospital of Foshan (Foshan, China). Using microarray analysis, we profiled mRNA gene expression between 24 paired locoregionally advanced nasopharyngeal carcinoma tumours from patients at Sun Yat-sen University Cancer Center with or without distant metastasis after radical treatment. Differentially expressed genes were examined using digital expression profiling in a training cohort (Guangzhou training cohort; n=410) to build a gene classifier using a penalised regression model. We validated the prognostic accuracy of this gene classifier in an internal validation cohort (Guangzhou internal validation cohort, n=204) and two external independent cohorts (Guilin cohort, n=165; Foshan cohort, n=158). The primary endpoint was distant metastasis-free survival. Secondary endpoints were disease-free survival and overall survival. We identified 137 differentially expressed genes between metastatic and non-metastatic locoregionally advanced nasopharyngeal carcinoma tissues. A distant metastasis gene signature for locoregionally advanced nasopharyngeal carcinoma (DMGN) that consisted of 13 genes was generated to classify patients into high-risk and low-risk groups in the training cohort. Patients with high-risk scores in the training cohort had shorter distant metastasis-free survival (hazard ratio [HR] 4·93, 95% CI 2·99-8·16; padvanced nasopharyngeal carcinoma and might be able to predict which patients benefit

  15. Gene Expression Profiling of Xeroderma Pigmentosum

    Directory of Open Access Journals (Sweden)

    Bowden Nikola A

    2006-05-01

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

  16. Changes in gene expression following androgen receptor blockade ...

    Indian Academy of Sciences (India)

    Madhu urs

    of gene expression in the ventral prostate, it is not clear whether all the gene expression ... These include clusterin, methionine adenosyl transferase IIα, and prostate-specific ..... MAGEE1 melanoma antigen and no similarity was found with the ...

  17. Rubisco activity and gene expression of tropical tree species under ...

    African Journals Online (AJOL)

    Young

    2013-05-15

    May 15, 2013 ... Proteomics analysis associated with gene expression of plants reveal .... Consequently, Rubisco enzyme plays a role in assi- milating into ... technique for examining gene expression encoded at the. mRNA level .... Ammonia.

  18. Gene structure, phylogeny and expression profile of the sucrose ...

    Indian Academy of Sciences (India)

    Gene structure, phylogeny and expression profile of the sucrose synthase gene family in .... 24, 701–713. Bate N. and Twell D. 1998 Functional architecture of a late pollen .... Manzara T. and Gruissem W. 1988 Organization and expression.

  19. 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...

  20. Functional features of gene expression profiles differentiating gastrointestinal stromal tumours according to KIT mutations and expression

    International Nuclear Information System (INIS)

    Ostrowski, Jerzy; Dobosz, Anna Jerzak Vel; Jarosz, Dorota; Ruka, Wlodzimierz; Wyrwicz, Lucjan S; Polkowski, Marcin; Paziewska, Agnieszka; Skrzypczak, Magdalena; Goryca, Krzysztof; Rubel, Tymon; Kokoszyñska, Katarzyna; Rutkowski, Piotr; Nowecki, Zbigniew I

    2009-01-01

    Gastrointestinal stromal tumours (GISTs) represent a heterogeneous group of tumours of mesenchymal origin characterized by gain-of-function mutations in KIT or PDGFRA of the type III receptor tyrosine kinase family. Although mutations in either receptor are thought to drive an early oncogenic event through similar pathways, two previous studies reported the mutation-specific gene expression profiles. However, their further conclusions were rather discordant. To clarify the molecular characteristics of differentially expressed genes according to GIST receptor mutations, we combined microarray-based analysis with detailed functional annotations. Total RNA was isolated from 29 frozen gastric GISTs and processed for hybridization on GENECHIP ® HG-U133 Plus 2.0 microarrays (Affymetrix). KIT and PDGFRA were analyzed by sequencing, while related mRNA levels were analyzed by quantitative RT-PCR. Fifteen and eleven tumours possessed mutations in KIT and PDGFRA, respectively; no mutation was found in three tumours. Gene expression analysis identified no discriminative profiles associated with clinical or pathological parameters, even though expression of hundreds of genes differentiated tumour receptor mutation and expression status. Functional features of genes differentially expressed between the two groups of GISTs suggested alterations in angiogenesis and G-protein-related and calcium signalling. Our study has identified novel molecular elements likely to be involved in receptor-dependent GIST development and allowed confirmation of previously published results. These elements may be potential therapeutic targets and novel markers of KIT mutation status

  1. Integrating mean and variance heterogeneities to identify differentially expressed genes.

    Science.gov (United States)

    Ouyang, Weiwei; An, Qiang; Zhao, Jinying; Qin, Huaizhen

    2016-12-06

    In functional genomics studies, tests on mean heterogeneity have been widely employed to identify differentially expressed genes with distinct mean expression levels under different experimental conditions. Variance heterogeneity (aka, the difference between condition-specific variances) of gene expression levels is simply neglected or calibrated for as an impediment. The mean heterogeneity in the expression level of a gene reflects one aspect of its distribution alteration; and variance heterogeneity induced by condition change may reflect another aspect. Change in condition may alter both mean and some higher-order characteristics of the distributions of expression levels of susceptible genes. In this report, we put forth a conception of mean-variance differentially expressed (MVDE) genes, whose expression means and variances are sensitive to the change in experimental condition. We mathematically proved the null independence of existent mean heterogeneity tests and variance heterogeneity tests. Based on the independence, we proposed an integrative mean-variance test (IMVT) to combine gene-wise mean heterogeneity and variance heterogeneity induced by condition change. The IMVT outperformed its competitors under comprehensive simulations of normality and Laplace settings. For moderate samples, the IMVT well controlled type I error rates, and so did existent mean heterogeneity test (i.e., the Welch t test (WT), the moderated Welch t test (MWT)) and the procedure of separate tests on mean and variance heterogeneities (SMVT), but the likelihood ratio test (LRT) severely inflated type I error rates. In presence of variance heterogeneity, the IMVT appeared noticeably more powerful than all the valid mean heterogeneity tests. Application to the gene profiles of peripheral circulating B raised solid evidence of informative variance heterogeneity. After adjusting for background data structure, the IMVT replicated previous discoveries and identified novel experiment

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2013-10-01

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

  3. An in vitro evaluation of anti-aging effect of guluronic acid (G2013) based on enzymatic oxidative stress gene expression using healthy individuals PBMCs.

    Science.gov (United States)

    Taeb, Mahsa; Mortazavi-Jahromi, Seyed Shahabeddin; Jafarzadeh, Abdollah; Mirzaei, Mohammad Reza; Mirshafiey, Abbas

    2017-06-01

    Aging is usually associated with increased levels of oxidants, and may result in damages caused by oxidative stress. There is a direct relationship between aging and increased incidence of inflammatory diseases. The present research intended to study the anti-aging and anti-inflammatory effects of the drug G2013 (guluronic acid) at low and high doses on the genes expression of a number of enzymes involved in oxidative stress (including SOD2, GPX1, CAT, GST, iNOS, and MPO) in peripheral blood mononuclear cells (PBMCs) of healthy individuals under in vitro conditions. Venous blood samples were taken from 20 healthy individuals, the PBMCs were isolated and their RNAs extracted and their cDNAs were synthesized, and the genes expression levels were measured using the qRT-PCR technique. Our results indicated that this drug could, at both low and high doses, significantly reduce the expression of the genes for SOD2, GPX1, CAT, and GST compared to the LPS group (phealthy gene expression, and possibly it might reduce the pathological process of aging and age-related inflammatory diseases. Copyright © 2017 Elsevier Masson SAS. All rights reserved.

  4. At the base of colinear Hox gene expression : cis-features and trans-factors orchestrating the initial phase of Hox cluster activation

    NARCIS (Netherlands)

    Neijts, Roel; Deschamps, Jacqueline

    2017-01-01

    Hox genes are crucial players in the generation and pattering of the vertebrate trunk and posterior body during embryogenesis. Their initial expression takes place shortly after the establishment of the primitive streak, in the posterior-most part of the mouse embryo and is a determinant step for

  5. Relaxation rates of gene expression kinetics reveal the feedback signs of autoregulatory gene networks

    Science.gov (United States)

    Jia, Chen; Qian, Hong; Chen, Min; Zhang, Michael Q.

    2018-03-01

    The transient response to a stimulus and subsequent recovery to a steady state are the fundamental characteristics of a living organism. Here we study the relaxation kinetics of autoregulatory gene networks based on the chemical master equation model of single-cell stochastic gene expression with nonlinear feedback regulation. We report a novel relation between the rate of relaxation, characterized by the spectral gap of the Markov model, and the feedback sign of the underlying gene circuit. When a network has no feedback, the relaxation rate is exactly the decaying rate of the protein. We further show that positive feedback always slows down the relaxation kinetics while negative feedback always speeds it up. Numerical simulations demonstrate that this relation provides a possible method to infer the feedback topology of autoregulatory gene networks by using time-series data of gene expression.

  6. Expression of plasmid-based shRNA against the E1 and nsP1 genes effectively silenced Chikungunya virus replication.

    Directory of Open Access Journals (Sweden)

    Shirley Lam

    Full Text Available BACKGROUND: Chikungunya virus (CHIKV is a re-emerging alphavirus that causes chikungunya fever and persistent arthralgia in humans. Currently, there is no effective vaccine or antiviral against CHIKV infection. Therefore, this study evaluates whether RNA interference which targets at viral genomic level may be a novel antiviral strategy to inhibit the medically important CHIKV infection. METHODS: Plasmid-based small hairpin RNA (shRNA was investigated for its efficacy in inhibiting CHIKV replication. Three shRNAs designed against CHIKV Capsid, E1 and nsP1 genes were transfected to establish stable shRNA-expressing cell clones. Following infection of stable shRNA cells clones with CHIKV at M.O.I. 1, viral plaque assay, Western blotting and transmission electron microscopy were performed. The in vivo efficacy of shRNA against CHIKV replication was also evaluated in a suckling murine model of CHIKV infection. RESULTS: Cell clones expressing shRNAs against CHIKV E1 and nsP1 genes displayed significant inhibition of infectious CHIKV production, while shRNA Capsid demonstrated a modest inhibitory effect as compared to scrambled shRNA cell clones and non-transfected cell controls. Western blot analysis of CHIKV E2 protein expression and transmission electron microscopy of shRNA E1 and nsP1 cell clones collectively demonstrated similar inhibitory trends against CHIKV replication. shRNA E1 showed non cell-type specific anti-CHIKV effects and broad-spectrum silencing against different geographical strains of CHIKV. Furthermore, shRNA E1 clones did not exert any inhibition against Dengue virus and Sindbis virus replication, thus indicating the high specificity of shRNA against CHIKV replication. Moreover, no shRNA-resistant CHIKV mutant was generated after 50 passages of CHIKV in the stable cell clones. More importantly, strong and sustained anti-CHIKV protection was conferred in suckling mice pre-treated with shRNA E1. CONCLUSION: Taken together, these

  7. 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.

  8. 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.

  9. Nuclear AXIN2 represses MYC gene expression

    International Nuclear Information System (INIS)

    Rennoll, Sherri A.; Konsavage, Wesley M.; Yochum, Gregory S.

    2014-01-01

    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. Emerging use of gene expression microarrays in plant physiology.

    Science.gov (United States)

    Wullschleger, Stan D; Difazio, Stephen P

    2003-01-01

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

  11. Emerging Use of Gene Expression Microarrays in Plant Physiology

    Directory of Open Access Journals (Sweden)

    Stephen P. Difazio

    2006-04-01

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

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

    Directory of Open Access Journals (Sweden)

    Mario Huerta

    2014-01-01

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

  13. Learning gene regulatory networks from gene expression data using weighted consensus

    KAUST Repository

    Fujii, Chisato; Kuwahara, Hiroyuki; Yu, Ge; Guo, Lili; Gao, Xin

    2016-01-01

    An accurate determination of the network structure of gene regulatory systems from high-throughput gene expression data is an essential yet challenging step in studying how the expression of endogenous genes is controlled through a complex interaction of gene products and DNA. While numerous methods have been proposed to infer the structure of gene regulatory networks, none of them seem to work consistently over different data sets with high accuracy. A recent study to compare gene network inference methods showed that an average-ranking-based consensus method consistently performs well under various settings. Here, we propose a linear programming-based consensus method for the inference of gene regulatory networks. Unlike the average-ranking-based one, which treats the contribution of each individual method equally, our new consensus method assigns a weight to each method based on its credibility. As a case study, we applied the proposed consensus method on synthetic and real microarray data sets, and compared its performance to that of the average-ranking-based consensus and individual inference methods. Our results show that our weighted consensus method achieves superior performance over the unweighted one, suggesting that assigning weights to different individual methods rather than giving them equal weights improves the accuracy. © 2016 Elsevier B.V.

  14. Learning gene regulatory networks from gene expression data using weighted consensus

    KAUST Repository

    Fujii, Chisato

    2016-08-25

    An accurate determination of the network structure of gene regulatory systems from high-throughput gene expression data is an essential yet challenging step in studying how the expression of endogenous genes is controlled through a complex interaction of gene products and DNA. While numerous methods have been proposed to infer the structure of gene regulatory networks, none of them seem to work consistently over different data sets with high accuracy. A recent study to compare gene network inference methods showed that an average-ranking-based consensus method consistently performs well under various settings. Here, we propose a linear programming-based consensus method for the inference of gene regulatory networks. Unlike the average-ranking-based one, which treats the contribution of each individual method equally, our new consensus method assigns a weight to each method based on its credibility. As a case study, we applied the proposed consensus method on synthetic and real microarray data sets, and compared its performance to that of the average-ranking-based consensus and individual inference methods. Our results show that our weighted consensus method achieves superior performance over the unweighted one, suggesting that assigning weights to different individual methods rather than giving them equal weights improves the accuracy. © 2016 Elsevier B.V.

  15. 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

  16. Retrotransposons as regulators of gene expression.

    Science.gov (United States)

    Elbarbary, Reyad A; Lucas, Bronwyn A; Maquat, Lynne E

    2016-02-12

    Transposable elements (TEs) are both a boon and a bane to eukaryotic organisms, depending on where they integrate into the genome and how their sequences function once integrated. We focus on two types of TEs: long interspersed elements (LINEs) and short interspersed elements (SINEs). LINEs and SINEs are retrotransposons; that is, they transpose via an RNA intermediate. We discuss how LINEs and SINEs have expanded in eukaryotic genomes and contribute to genome evolution. An emerging body of evidence indicates that LINEs and SINEs function to regulate gene expression by affecting chromatin structure, gene transcription, pre-mRNA processing, or aspects of mRNA metabolism. We also describe how adenosine-to-inosine editing influences SINE function and how ongoing retrotransposition is countered by the body's defense mechanisms. Copyright © 2016, American Association for the Advancement of Science.

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

    International Nuclear Information System (INIS)

    Wiebe, L. I.

    1997-01-01

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

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

    Energy Technology Data Exchange (ETDEWEB)

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

    1997-10-01

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

  19. Gene expression profiling of cutaneous wound healing

    Directory of Open Access Journals (Sweden)

    Wang Ena

    2007-02-01

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

  20. Differential expression of cell adhesion genes

    DEFF Research Database (Denmark)

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

    2005-01-01

    that compare cells grown in suspension to similar cells grown attached to one another as aggregates have suggested that it is adhesion to the extracellular matrix of the basal membrane that confers resistance to apoptosis and, hence, resistance to cytotoxins. The genes whose expression correlates with poor...... in cell adhesion and the cytoskeleton. If the proteins involved in tethering cells to the extracellular matrix are important in conferring drug resistance, it may be possible to improve chemotherapy by designing drugs that target these proteins....

  1. 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.

  2. 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.