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  1. Gene Therapy Approaches to Hemoglobinopathies.

    Science.gov (United States)

    Ferrari, Giuliana; Cavazzana, Marina; Mavilio, Fulvio

    2017-10-01

    Gene therapy for hemoglobinopathies is currently based on transplantation of autologous hematopoietic stem cells genetically modified with a lentiviral vector expressing a globin gene under the control of globin transcriptional regulatory elements. Preclinical and early clinical studies showed the safety and potential efficacy of this therapeutic approach as well as the hurdles still limiting its general application. In addition, for both beta-thalassemia and sickle cell disease, an altered bone marrow microenvironment reduces the efficiency of stem cell harvesting as well as engraftment. These hurdles need be addressed for gene therapy for hemoglobinopathies to become a clinical reality. Copyright © 2017 Elsevier Inc. All rights reserved.

  2. Gene

    Data.gov (United States)

    U.S. Department of Health & Human Services — Gene integrates information from a wide range of species. A record may include nomenclature, Reference Sequences (RefSeqs), maps, pathways, variations, phenotypes,...

  3. A genetic ensemble approach for gene-gene interaction identification

    Directory of Open Access Journals (Sweden)

    Ho Joshua WK

    2010-10-01

    Full Text Available Abstract Background It has now become clear that gene-gene interactions and gene-environment interactions are ubiquitous and fundamental mechanisms for the development of complex diseases. Though a considerable effort has been put into developing statistical models and algorithmic strategies for identifying such interactions, the accurate identification of those genetic interactions has been proven to be very challenging. Methods In this paper, we propose a new approach for identifying such gene-gene and gene-environment interactions underlying complex diseases. This is a hybrid algorithm and it combines genetic algorithm (GA and an ensemble of classifiers (called genetic ensemble. Using this approach, the original problem of SNP interaction identification is converted into a data mining problem of combinatorial feature selection. By collecting various single nucleotide polymorphisms (SNP subsets as well as environmental factors generated in multiple GA runs, patterns of gene-gene and gene-environment interactions can be extracted using a simple combinatorial ranking method. Also considered in this study is the idea of combining identification results obtained from multiple algorithms. A novel formula based on pairwise double fault is designed to quantify the degree of complementarity. Conclusions Our simulation study demonstrates that the proposed genetic ensemble algorithm has comparable identification power to Multifactor Dimensionality Reduction (MDR and is slightly better than Polymorphism Interaction Analysis (PIA, which are the two most popular methods for gene-gene interaction identification. More importantly, the identification results generated by using our genetic ensemble algorithm are highly complementary to those obtained by PIA and MDR. Experimental results from our simulation studies and real world data application also confirm the effectiveness of the proposed genetic ensemble algorithm, as well as the potential benefits of

  4. 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

  5. Current approaches to gene regulatory network modelling

    Directory of Open Access Journals (Sweden)

    Brazma Alvis

    2007-09-01

    Full Text Available Abstract Many different approaches have been developed to model and simulate gene regulatory networks. We proposed the following categories for gene regulatory network models: network parts lists, network topology models, network control logic models, and dynamic models. Here we will describe some examples for each of these categories. We will study the topology of gene regulatory networks in yeast in more detail, comparing a direct network derived from transcription factor binding data and an indirect network derived from genome-wide expression data in mutants. Regarding the network dynamics we briefly describe discrete and continuous approaches to network modelling, then describe a hybrid model called Finite State Linear Model and demonstrate that some simple network dynamics can be simulated in this model.

  6. A hybrid approach of gene sets and single genes for the prediction of survival risks with gene expression data.

    Science.gov (United States)

    Seok, Junhee; Davis, Ronald W; Xiao, Wenzhong

    2015-01-01

    Accumulated biological knowledge is often encoded as gene sets, collections of genes associated with similar biological functions or pathways. The use of gene sets in the analyses of high-throughput gene expression data has been intensively studied and applied in clinical research. However, the main interest remains in finding modules of biological knowledge, or corresponding gene sets, significantly associated with disease conditions. Risk prediction from censored survival times using gene sets hasn't been well studied. In this work, we propose a hybrid method that uses both single gene and gene set information together to predict patient survival risks from gene expression profiles. In the proposed method, gene sets provide context-level information that is poorly reflected by single genes. Complementarily, single genes help to supplement incomplete information of gene sets due to our imperfect biomedical knowledge. Through the tests over multiple data sets of cancer and trauma injury, the proposed method showed robust and improved performance compared with the conventional approaches with only single genes or gene sets solely. Additionally, we examined the prediction result in the trauma injury data, and showed that the modules of biological knowledge used in the prediction by the proposed method were highly interpretable in biology. A wide range of survival prediction problems in clinical genomics is expected to benefit from the use of biological knowledge.

  7. Gene-based Association Approach Identify Genes Across Stress Traits in Fruit Flies

    DEFF Research Database (Denmark)

    Rohde, Palle Duun; Edwards, Stefan McKinnon; Sarup, Pernille Merete

    Identification of genes explaining variation in quantitative traits or genetic risk factors of human diseases requires both good phenotypic- and genotypic data, but also efficient statistical methods. Genome-wide association studies may reveal association between phenotypic variation and variation...... approach grouping variants accordingly to gene position, thus lowering the number of statistical tests performed and increasing the probability of identifying genes with small to moderate effects. Using this approach we identify numerous genes associated with different types of stresses in Drosophila...... melanogaster, but also identify common genes that affects the stress traits....

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

    Directory of Open Access Journals (Sweden)

    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.

  9. A kernel regression approach to gene-gene interaction detection for case-control studies.

    Science.gov (United States)

    Larson, Nicholas B; Schaid, Daniel J

    2013-11-01

    Gene-gene interactions are increasingly being addressed as a potentially important contributor to the variability of complex traits. Consequently, attentions have moved beyond single locus analysis of association to more complex genetic models. Although several single-marker approaches toward interaction analysis have been developed, such methods suffer from very high testing dimensionality and do not take advantage of existing information, notably the definition of genes as functional units. Here, we propose a comprehensive family of gene-level score tests for identifying genetic elements of disease risk, in particular pairwise gene-gene interactions. Using kernel machine methods, we devise score-based variance component tests under a generalized linear mixed model framework. We conducted simulations based upon coalescent genetic models to evaluate the performance of our approach under a variety of disease models. These simulations indicate that our methods are generally higher powered than alternative gene-level approaches and at worst competitive with exhaustive SNP-level (where SNP is single-nucleotide polymorphism) analyses. Furthermore, we observe that simulated epistatic effects resulted in significant marginal testing results for the involved genes regardless of whether or not true main effects were present. We detail the benefits of our methods and discuss potential genome-wide analysis strategies for gene-gene interaction analysis in a case-control study design. © 2013 WILEY PERIODICALS, INC.

  10. Human gene therapy: novel approaches to improve the current gene delivery systems.

    Science.gov (United States)

    Cucchiarini, Magali

    2016-06-01

    Even though gene therapy made its way through the clinics to treat a number of human pathologies since the early years of experimental research and despite the recent approval of the first gene-based product (Glybera) in Europe, the safe and effective use of gene transfer vectors remains a challenge in human gene therapy due to the existence of barriers in the host organism. While work is under active investigation to improve the gene transfer systems themselves, the use of controlled release approaches may offer alternative, convenient tools of vector delivery to achieve a performant gene transfer in vivo while overcoming the various physiological barriers that preclude its wide use in patients. This article provides an overview of the most significant contributions showing how the principles of controlled release strategies may be adapted for human gene therapy.

  11. A stochastic approach to multi-gene expression dynamics

    International Nuclear Information System (INIS)

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

    2005-01-01

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

  12. Genes and Gene Therapy

    Science.gov (United States)

    ... correctly, a child can have a genetic disorder. Gene therapy is an experimental technique that uses genes to ... or prevent disease. The most common form of gene therapy involves inserting a normal gene to replace an ...

  13. A Partial Least Square Approach for Modeling Gene-gene and Gene-environment Interactions When Multiple Markers Are Genotyped

    Science.gov (United States)

    Wang, Tao; Ho, Gloria; Ye, Kenny; Strickler, Howard; Elston, Robert C.

    2008-01-01

    Genetic association studies achieve an unprecedented level of resolution in mapping disease genes by genotyping dense SNPs in a gene region. Meanwhile, these studies require new powerful statistical tools that can optimally handle a large amount of information provided by genotype data. A question that arises is how to model interactions between two genes. Simply modeling all possible interactions between the SNPs in two gene regions is not desirable because a greatly increased number of degrees of freedom can be involved in the test statistic. We introduce an approach to reduce the genotype dimension in modeling interactions. The genotype compression of this approach is built upon the information on both the trait and the cross-locus gametic disequilibrium between SNPs in two interacting genes, in such a way as to parsimoniously model the interactions without loss of useful information in the process of dimension reduction. As a result, it improves power to detect association in the presence of gene-gene interactions. This approach can be similarly applied for modeling gene-environment interactions. We compare this method with other approaches: the corresponding test without modeling any interaction, that based on a saturated interaction model, that based on principal component analysis, and that based on Tukey’s 1-df model. Our simulations suggest that this new approach has superior power to that of the other methods. In an application to endometrial cancer case-control data from the Women’s Health Initiative (WHI), this approach detected AKT1 and AKT2 as being significantly associated with endometrial cancer susceptibility by taking into account their interactions with BMI. PMID:18615621

  14. 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

  15. Translational approach for gene therapy in epilepsy

    DEFF Research Database (Denmark)

    Ledri, Litsa Nikitidou; Melin, Esbjörn; Christiansen, Søren H.

    2016-01-01

    clinical trial for gene therapy of temporal lobe epilepsy was explored: We investigated (i) whether the post intrahippocampal kainate-induced status epilepticus (SE) model of chronic epilepsy in rats could be clinically relevant; and (ii) whether a translationally designed neuropeptide Y (NPY)/Y2 receptor...

  16. The prediction of candidate genes for cervix related cancer through gene ontology and graph theoretical approach.

    Science.gov (United States)

    Hindumathi, V; Kranthi, T; Rao, S B; Manimaran, P

    2014-06-01

    With rapidly changing technology, prediction of candidate genes has become an indispensable task in recent years mainly in the field of biological research. The empirical methods for candidate gene prioritization that succors to explore the potential pathway between genetic determinants and complex diseases are highly cumbersome and labor intensive. In such a scenario predicting potential targets for a disease state through in silico approaches are of researcher's interest. The prodigious availability of protein interaction data coupled with gene annotation renders an ease in the accurate determination of disease specific candidate genes. In our work we have prioritized the cervix related cancer candidate genes by employing Csaba Ortutay and his co-workers approach of identifying the candidate genes through graph theoretical centrality measures and gene ontology. With the advantage of the human protein interaction data, cervical cancer gene sets and the ontological terms, we were able to predict 15 novel candidates for cervical carcinogenesis. The disease relevance of the anticipated candidate genes was corroborated through a literature survey. Also the presence of the drugs for these candidates was detected through Therapeutic Target Database (TTD) and DrugMap Central (DMC) which affirms that they may be endowed as potential drug targets for cervical cancer.

  17. An integrative approach to inferring biologically meaningful gene modules

    Directory of Open Access Journals (Sweden)

    Wang Kai

    2011-07-01

    Full Text Available Abstract Background The ability to construct biologically meaningful gene networks and modules is critical for contemporary systems biology. Though recent studies have demonstrated the power of using gene modules to shed light on the functioning of complex biological systems, most modules in these networks have shown little association with meaningful biological function. We have devised a method which directly incorporates gene ontology (GO annotation in construction of gene modules in order to gain better functional association. Results We have devised a method, Semantic Similarity-Integrated approach for Modularization (SSIM that integrates various gene-gene pairwise similarity values, including information obtained from gene expression, protein-protein interactions and GO annotations, in the construction of modules using affinity propagation clustering. We demonstrated the performance of the proposed method using data from two complex biological responses: 1. the osmotic shock response in Saccharomyces cerevisiae, and 2. the prion-induced pathogenic mouse model. In comparison with two previously reported algorithms, modules identified by SSIM showed significantly stronger association with biological functions. Conclusions The incorporation of semantic similarity based on GO annotation with gene expression and protein-protein interaction data can greatly enhance the functional relevance of inferred gene modules. In addition, the SSIM approach can also reveal the hierarchical structure of gene modules to gain a broader functional view of the biological system. Hence, the proposed method can facilitate comprehensive and in-depth analysis of high throughput experimental data at the gene network level.

  18. A network approach to predict pathogenic genes for Fusarium graminearum.

    Science.gov (United States)

    Liu, Xiaoping; Tang, Wei-Hua; Zhao, Xing-Ming; Chen, Luonan

    2010-10-04

    Fusarium graminearum is the pathogenic agent of Fusarium head blight (FHB), which is a destructive disease on wheat and barley, thereby causing huge economic loss and health problems to human by contaminating foods. Identifying pathogenic genes can shed light on pathogenesis underlying the interaction between F. graminearum and its plant host. However, it is difficult to detect pathogenic genes for this destructive pathogen by time-consuming and expensive molecular biological experiments in lab. On the other hand, computational methods provide an alternative way to solve this problem. Since pathogenesis is a complicated procedure that involves complex regulations and interactions, the molecular interaction network of F. graminearum can give clues to potential pathogenic genes. Furthermore, the gene expression data of F. graminearum before and after its invasion into plant host can also provide useful information. In this paper, a novel systems biology approach is presented to predict pathogenic genes of F. graminearum based on molecular interaction network and gene expression data. With a small number of known pathogenic genes as seed genes, a subnetwork that consists of potential pathogenic genes is identified from the protein-protein interaction network (PPIN) of F. graminearum, where the genes in the subnetwork are further required to be differentially expressed before and after the invasion of the pathogenic fungus. Therefore, the candidate genes in the subnetwork are expected to be involved in the same biological processes as seed genes, which imply that they are potential pathogenic genes. The prediction results show that most of the pathogenic genes of F. graminearum are enriched in two important signal transduction pathways, including G protein coupled receptor pathway and MAPK signaling pathway, which are known related to pathogenesis in other fungi. In addition, several pathogenic genes predicted by our method are verified in other pathogenic fungi, which

  19. Enhanced gene ranking approaches using modified trace ratio algorithm for gene expression data

    Directory of Open Access Journals (Sweden)

    Shruti Mishra

    Full Text Available Microarray technology enables the understanding and investigation of gene expression levels by analyzing high dimensional datasets that contain few samples. Over time, microarray expression data have been collected for studying the underlying biological mechanisms of disease. One such application for understanding the mechanism is by constructing a gene regulatory network (GRN. One of the foremost key criteria for GRN discovery is gene selection. Choosing a generous set of genes for the structure of the network is highly desirable. For this role, two suitable methods were proposed for selection of appropriate genes. The first approach comprises a gene selection method called Information gain, where the dataset is reformed and fused with another distinct algorithm called Trace Ratio (TR. Our second method is the implementation of our projected modified TR algorithm, where the scoring base for finding weight matrices has been re-designed. Both the methods' efficiency was shown with different classifiers that include variants of the Artificial Neural Network classifier, such as Resilient Propagation, Quick Propagation, Back Propagation, Manhattan Propagation and Radial Basis Function Neural Network and also the Support Vector Machine (SVM classifier. In the study, it was confirmed that both of the proposed methods worked well and offered high accuracy with a lesser number of iterations as compared to the original Trace Ratio algorithm. Keywords: Gene regulatory network, Gene selection, Information gain, Trace ratio, Canonical correlation analysis, Classification

  20. Statistical approach for selection of biologically informative genes.

    Science.gov (United States)

    Das, Samarendra; Rai, Anil; Mishra, D C; Rai, Shesh N

    2018-05-20

    Selection of informative genes from high dimensional gene expression data has emerged as an important research area in genomics. Many gene selection techniques have been proposed so far are either based on relevancy or redundancy measure. Further, the performance of these techniques has been adjudged through post selection classification accuracy computed through a classifier using the selected genes. This performance metric may be statistically sound but may not be biologically relevant. A statistical approach, i.e. Boot-MRMR, was proposed based on a composite measure of maximum relevance and minimum redundancy, which is both statistically sound and biologically relevant for informative gene selection. For comparative evaluation of the proposed approach, we developed two biological sufficient criteria, i.e. Gene Set Enrichment with QTL (GSEQ) and biological similarity score based on Gene Ontology (GO). Further, a systematic and rigorous evaluation of the proposed technique with 12 existing gene selection techniques was carried out using five gene expression datasets. This evaluation was based on a broad spectrum of statistically sound (e.g. subject classification) and biological relevant (based on QTL and GO) criteria under a multiple criteria decision-making framework. The performance analysis showed that the proposed technique selects informative genes which are more biologically relevant. The proposed technique is also found to be quite competitive with the existing techniques with respect to subject classification and computational time. Our results also showed that under the multiple criteria decision-making setup, the proposed technique is best for informative gene selection over the available alternatives. Based on the proposed approach, an R Package, i.e. BootMRMR has been developed and available at https://cran.r-project.org/web/packages/BootMRMR. This study will provide a practical guide to select statistical techniques for selecting informative genes

  1. Multiobjective Optimization Methodology A Jumping Gene Approach

    CERN Document Server

    Tang, KS

    2012-01-01

    Complex design problems are often governed by a number of performance merits. These markers gauge how good the design is going to be, but can conflict with the performance requirements that must be met. The challenge is reconciling these two requirements. This book introduces a newly developed jumping gene algorithm, designed to address the multi-functional objectives problem and supplies a viably adequate solution in speed. The text presents various multi-objective optimization techniques and provides the technical know-how for obtaining trade-off solutions between solution spread and converg

  2. A Generalized Approach for Measuring Relationships Among Genes.

    Science.gov (United States)

    Wang, Lijun; Ahsan, Md Asif; Chen, Ming

    2017-07-21

    Several methods for identifying relationships among pairs of genes have been developed. In this article, we present a generalized approach for measuring relationships between any pairs of genes, which is based on statistical prediction. We derive two particular versions of the generalized approach, least squares estimation (LSE) and nearest neighbors prediction (NNP). According to mathematical proof, LSE is equivalent to the methods based on correlation; and NNP is approximate to one popular method called the maximal information coefficient (MIC) according to the performances in simulations and real dataset. Moreover, the approach based on statistical prediction can be extended from two-genes relationships to multi-genes relationships. This application would help to identify relationships among multi-genes.

  3. System Biology Approach: Gene Network Analysis for Muscular Dystrophy.

    Science.gov (United States)

    Censi, Federica; Calcagnini, Giovanni; Mattei, Eugenio; Giuliani, Alessandro

    2018-01-01

    Phenotypic changes at different organization levels from cell to entire organism are associated to changes in the pattern of gene expression. These changes involve the entire genome expression pattern and heavily rely upon correlation patterns among genes. The classical approach used to analyze gene expression data builds upon the application of supervised statistical techniques to detect genes differentially expressed among two or more phenotypes (e.g., normal vs. disease). The use of an a posteriori, unsupervised approach based on principal component analysis (PCA) and the subsequent construction of gene correlation networks can shed a light on unexpected behaviour of gene regulation system while maintaining a more naturalistic view on the studied system.In this chapter we applied an unsupervised method to discriminate DMD patient and controls. The genes having the highest absolute scores in the discrimination between the groups were then analyzed in terms of gene expression networks, on the basis of their mutual correlation in the two groups. The correlation network structures suggest two different modes of gene regulation in the two groups, reminiscent of important aspects of DMD pathogenesis.

  4. A network approach to predict pathogenic genes for Fusarium graminearum.

    Directory of Open Access Journals (Sweden)

    Xiaoping Liu

    Full Text Available Fusarium graminearum is the pathogenic agent of Fusarium head blight (FHB, which is a destructive disease on wheat and barley, thereby causing huge economic loss and health problems to human by contaminating foods. Identifying pathogenic genes can shed light on pathogenesis underlying the interaction between F. graminearum and its plant host. However, it is difficult to detect pathogenic genes for this destructive pathogen by time-consuming and expensive molecular biological experiments in lab. On the other hand, computational methods provide an alternative way to solve this problem. Since pathogenesis is a complicated procedure that involves complex regulations and interactions, the molecular interaction network of F. graminearum can give clues to potential pathogenic genes. Furthermore, the gene expression data of F. graminearum before and after its invasion into plant host can also provide useful information. In this paper, a novel systems biology approach is presented to predict pathogenic genes of F. graminearum based on molecular interaction network and gene expression data. With a small number of known pathogenic genes as seed genes, a subnetwork that consists of potential pathogenic genes is identified from the protein-protein interaction network (PPIN of F. graminearum, where the genes in the subnetwork are further required to be differentially expressed before and after the invasion of the pathogenic fungus. Therefore, the candidate genes in the subnetwork are expected to be involved in the same biological processes as seed genes, which imply that they are potential pathogenic genes. The prediction results show that most of the pathogenic genes of F. graminearum are enriched in two important signal transduction pathways, including G protein coupled receptor pathway and MAPK signaling pathway, which are known related to pathogenesis in other fungi. In addition, several pathogenic genes predicted by our method are verified in other

  5. GSEH: A Novel Approach to Select Prostate Cancer-Associated Genes Using Gene Expression Heterogeneity.

    Science.gov (United States)

    Kim, Hyunjin; Choi, Sang-Min; Park, Sanghyun

    2018-01-01

    When a gene shows varying levels of expression among normal people but similar levels in disease patients or shows similar levels of expression among normal people but different levels in disease patients, we can assume that the gene is associated with the disease. By utilizing this gene expression heterogeneity, we can obtain additional information that abets discovery of disease-associated genes. In this study, we used collaborative filtering to calculate the degree of gene expression heterogeneity between classes and then scored the genes on the basis of the degree of gene expression heterogeneity to find "differentially predicted" genes. Through the proposed method, we discovered more prostate cancer-associated genes than 10 comparable methods. The genes prioritized by the proposed method are potentially significant to biological processes of a disease and can provide insight into them.

  6. Gene therapy: a lipofection approach for gene transfer into primary endothelial cells.

    Science.gov (United States)

    Young, A T L; Lakey, J R T; Murray, A G; Moore, R B

    2002-01-01

    Despite the great potential of gene therapy to become a new treatment modality in future medicine, there are still many limitations to overcome before this gene approach can pass to the stage of human trial. The foremost obstacle is the development of a safe, efficient, and efficacious vector system for in vivo gene application. This study evaluated the efficacy of lipofection as a gene delivery vehicle into primary endothelial cells. Transfection efficiency of several lipid-based reagents (Effectene, Fugene 6, DOTAP) was examined at experimental temperatures of 37 degrees C, 24 degrees C, and 6 degrees C. Human umbilical vein endothelial cells (HUVECs) were transfected with the enhanced green fluorescent protein (EGFP) using precise amounts of DNA (Effectene, 0.2 microg; Fugene 6, 0.5 microg; DOTAP, 2.5 microg) and lipids (Effectene, 10 microl; Fugene 6, 6 microl; DOTAP, 15 microl) optimized in our laboratory. Duration of incubation in the DNA/lipid transfection mixture varied for each lipid transfectant as follows: 5 h for both Fugene 6 and DOTAP and 3 h for Effectene. Efficiency of transfection was quantified by microscopic evaluation of EFGP expression in a minimum of 100 cells per group. Transfection efficiencies achieved with these lipofection agents were 34 +/- 1.3% (mean +/- SEM), 33 +/- 1.4%, and 18 +/- 1.5% for Effectene, Fugene 6, and DOTAP, respectively, at 37 degrees C. Transfection results were lower at 24 degrees C with mean efficiencies of 26 +/- 2.4% for Effectene, 14 +/- 2.9% for Fugene 6, and 15 +/- 3.2% for DOTAP. Furthermore, mean efficiencies at 6 degrees C were 6 +/- 0.5%, 8 +/- 1.5%, and 6 +/- 0.0% for Effectene, Fugene 6, and DOTAP, respectively. Efficiency of transfection appeared to be temperature dependent (ANOVA; p lipofection a potential gene delivery strategy for in vivo gene therapy.

  7. 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

  8. 'Omics' approaches in tomato aimed at identifying candidate genes ...

    African Journals Online (AJOL)

    adriana

    2013-12-04

    Dec 4, 2013 ... approaches could be combined in order to identify candidate genes for the genetic control of ascorbic ..... applied to other traits under the complex control of many ... Engineering increased vitamin C levels in ... Chem. Biol. 13:532–538. Giovannucci E, Rimm EB, Liu Y, Stampfer MJ, Willett WC (2002). A.

  9. From gene networks to drugs: systems pharmacology approaches for AUD.

    Science.gov (United States)

    Ferguson, Laura B; Harris, R Adron; Mayfield, Roy Dayne

    2018-06-01

    The alcohol research field has amassed an impressive number of gene expression datasets spanning key brain areas for addiction, species (humans as well as multiple animal models), and stages in the addiction cycle (binge/intoxication, withdrawal/negative effect, and preoccupation/anticipation). These data have improved our understanding of the molecular adaptations that eventually lead to dysregulation of brain function and the chronic, relapsing disorder of addiction. Identification of new medications to treat alcohol use disorder (AUD) will likely benefit from the integration of genetic, genomic, and behavioral information included in these important datasets. Systems pharmacology considers drug effects as the outcome of the complex network of interactions a drug has rather than a single drug-molecule interaction. Computational strategies based on this principle that integrate gene expression signatures of pharmaceuticals and disease states have shown promise for identifying treatments that ameliorate disease symptoms (called in silico gene mapping or connectivity mapping). In this review, we suggest that gene expression profiling for in silico mapping is critical to improve drug repurposing and discovery for AUD and other psychiatric illnesses. We highlight studies that successfully apply gene mapping computational approaches to identify or repurpose pharmaceutical treatments for psychiatric illnesses. Furthermore, we address important challenges that must be overcome to maximize the potential of these strategies to translate to the clinic and improve healthcare outcomes.

  10. Gene doping detection: evaluation of approach for direct detection of gene transfer using erythropoietin as a model system.

    Science.gov (United States)

    Baoutina, A; Coldham, T; Bains, G S; Emslie, K R

    2010-08-01

    As clinical gene therapy has progressed toward realizing its potential, concern over misuse of the technology to enhance performance in athletes is growing. Although 'gene doping' is banned by the World Anti-Doping Agency, its detection remains a major challenge. In this study, we developed a methodology for direct detection of the transferred genetic material and evaluated its feasibility for gene doping detection in blood samples from athletes. Using erythropoietin (EPO) as a model gene and a simple in vitro system, we developed real-time PCR assays that target sequences within the transgene complementary DNA corresponding to exon/exon junctions. As these junctions are absent in the endogenous gene due to their interruption by introns, the approach allows detection of trace amounts of a transgene in a large background of the endogenous gene. Two developed assays and one commercial gene expression assay for EPO were validated. On the basis of ability of these assays to selectively amplify transgenic DNA and analysis of literature on testing of gene transfer in preclinical and clinical gene therapy, it is concluded that the developed approach would potentially be suitable to detect gene doping through gene transfer by analysis of small volumes of blood using regular out-of-competition testing.

  11. Gene variants associated with antisocial behaviour: a latent variable approach.

    Science.gov (United States)

    Bentley, Mary Jane; Lin, Haiqun; Fernandez, Thomas V; Lee, Maria; Yrigollen, Carolyn M; Pakstis, Andrew J; Katsovich, Liliya; Olds, David L; Grigorenko, Elena L; Leckman, James F

    2013-10-01

    The aim of this study was to determine if a latent variable approach might be useful in identifying shared variance across genetic risk alleles that is associated with antisocial behaviour at age 15 years. Using a conventional latent variable approach, we derived an antisocial phenotype in 328 adolescents utilizing data from a 15-year follow-up of a randomized trial of a prenatal and infancy nurse-home visitation programme in Elmira, New York. We then investigated, via a novel latent variable approach, 450 informative genetic polymorphisms in 71 genes previously associated with antisocial behaviour, drug use, affiliative behaviours and stress response in 241 consenting individuals for whom DNA was available. Haplotype and Pathway analyses were also performed. Eight single-nucleotide polymorphisms (SNPs) from eight genes contributed to the latent genetic variable that in turn accounted for 16.0% of the variance within the latent antisocial phenotype. The number of risk alleles was linearly related to the latent antisocial variable scores. Haplotypes that included the putative risk alleles for all eight genes were also associated with higher latent antisocial variable scores. In addition, 33 SNPs from 63 of the remaining genes were also significant when added to the final model. Many of these genes interact on a molecular level, forming molecular networks. The results support a role for genes related to dopamine, norepinephrine, serotonin, glutamate, opioid and cholinergic signalling as well as stress response pathways in mediating susceptibility to antisocial behaviour. This preliminary study supports use of relevant behavioural indicators and latent variable approaches to study the potential 'co-action' of gene variants associated with antisocial behaviour. It also underscores the cumulative relevance of common genetic variants for understanding the aetiology of complex behaviour. If replicated in future studies, this approach may allow the identification of a

  12. A Network Approach to Analyzing Highly Recombinant Malaria Parasite Genes

    Science.gov (United States)

    Larremore, Daniel B.; Clauset, Aaron; Buckee, Caroline O.

    2013-01-01

    The var genes of the human malaria parasite Plasmodium falciparum present a challenge to population geneticists due to their extreme diversity, which is generated by high rates of recombination. These genes encode a primary antigen protein called PfEMP1, which is expressed on the surface of infected red blood cells and elicits protective immune responses. Var gene sequences are characterized by pronounced mosaicism, precluding the use of traditional phylogenetic tools that require bifurcating tree-like evolutionary relationships. We present a new method that identifies highly variable regions (HVRs), and then maps each HVR to a complex network in which each sequence is a node and two nodes are linked if they share an exact match of significant length. Here, networks of var genes that recombine freely are expected to have a uniformly random structure, but constraints on recombination will produce network communities that we identify using a stochastic block model. We validate this method on synthetic data, showing that it correctly recovers populations of constrained recombination, before applying it to the Duffy Binding Like-α (DBLα) domain of var genes. We find nine HVRs whose network communities map in distinctive ways to known DBLα classifications and clinical phenotypes. We show that the recombinational constraints of some HVRs are correlated, while others are independent. These findings suggest that this micromodular structuring facilitates independent evolutionary trajectories of neighboring mosaic regions, allowing the parasite to retain protein function while generating enormous sequence diversity. Our approach therefore offers a rigorous method for analyzing evolutionary constraints in var genes, and is also flexible enough to be easily applied more generally to any highly recombinant sequences. PMID:24130474

  13. A network approach to analyzing highly recombinant malaria parasite genes.

    Science.gov (United States)

    Larremore, Daniel B; Clauset, Aaron; Buckee, Caroline O

    2013-01-01

    The var genes of the human malaria parasite Plasmodium falciparum present a challenge to population geneticists due to their extreme diversity, which is generated by high rates of recombination. These genes encode a primary antigen protein called PfEMP1, which is expressed on the surface of infected red blood cells and elicits protective immune responses. Var gene sequences are characterized by pronounced mosaicism, precluding the use of traditional phylogenetic tools that require bifurcating tree-like evolutionary relationships. We present a new method that identifies highly variable regions (HVRs), and then maps each HVR to a complex network in which each sequence is a node and two nodes are linked if they share an exact match of significant length. Here, networks of var genes that recombine freely are expected to have a uniformly random structure, but constraints on recombination will produce network communities that we identify using a stochastic block model. We validate this method on synthetic data, showing that it correctly recovers populations of constrained recombination, before applying it to the Duffy Binding Like-α (DBLα) domain of var genes. We find nine HVRs whose network communities map in distinctive ways to known DBLα classifications and clinical phenotypes. We show that the recombinational constraints of some HVRs are correlated, while others are independent. These findings suggest that this micromodular structuring facilitates independent evolutionary trajectories of neighboring mosaic regions, allowing the parasite to retain protein function while generating enormous sequence diversity. Our approach therefore offers a rigorous method for analyzing evolutionary constraints in var genes, and is also flexible enough to be easily applied more generally to any highly recombinant sequences.

  14. A network approach to analyzing highly recombinant malaria parasite genes.

    Directory of Open Access Journals (Sweden)

    Daniel B Larremore

    Full Text Available The var genes of the human malaria parasite Plasmodium falciparum present a challenge to population geneticists due to their extreme diversity, which is generated by high rates of recombination. These genes encode a primary antigen protein called PfEMP1, which is expressed on the surface of infected red blood cells and elicits protective immune responses. Var gene sequences are characterized by pronounced mosaicism, precluding the use of traditional phylogenetic tools that require bifurcating tree-like evolutionary relationships. We present a new method that identifies highly variable regions (HVRs, and then maps each HVR to a complex network in which each sequence is a node and two nodes are linked if they share an exact match of significant length. Here, networks of var genes that recombine freely are expected to have a uniformly random structure, but constraints on recombination will produce network communities that we identify using a stochastic block model. We validate this method on synthetic data, showing that it correctly recovers populations of constrained recombination, before applying it to the Duffy Binding Like-α (DBLα domain of var genes. We find nine HVRs whose network communities map in distinctive ways to known DBLα classifications and clinical phenotypes. We show that the recombinational constraints of some HVRs are correlated, while others are independent. These findings suggest that this micromodular structuring facilitates independent evolutionary trajectories of neighboring mosaic regions, allowing the parasite to retain protein function while generating enormous sequence diversity. Our approach therefore offers a rigorous method for analyzing evolutionary constraints in var genes, and is also flexible enough to be easily applied more generally to any highly recombinant sequences.

  15. Gene Therapy

    Science.gov (United States)

    Gene therapy Overview Gene therapy involves altering the genes inside your body's cells in an effort to treat or stop disease. Genes contain your ... that don't work properly can cause disease. Gene therapy replaces a faulty gene or adds a new ...

  16. Convergent functional genomics in addiction research - a translational approach to study candidate genes and gene networks.

    Science.gov (United States)

    Spanagel, Rainer

    2013-01-01

    Convergent functional genomics (CFG) is a translational methodology that integrates in a Bayesian fashion multiple lines of evidence from studies in human and animal models to get a better understanding of the genetics of a disease or pathological behavior. Here the integration of data sets that derive from forward genetics in animals and genetic association studies including genome wide association studies (GWAS) in humans is described for addictive behavior. The aim of forward genetics in animals and association studies in humans is to identify mutations (e.g. SNPs) that produce a certain phenotype; i.e. "from phenotype to genotype". Most powerful in terms of forward genetics is combined quantitative trait loci (QTL) analysis and gene expression profiling in recombinant inbreed rodent lines or genetically selected animals for a specific phenotype, e.g. high vs. low drug consumption. By Bayesian scoring genomic information from forward genetics in animals is then combined with human GWAS data on a similar addiction-relevant phenotype. This integrative approach generates a robust candidate gene list that has to be functionally validated by means of reverse genetics in animals; i.e. "from genotype to phenotype". It is proposed that studying addiction relevant phenotypes and endophenotypes by this CFG approach will allow a better determination of the genetics of addictive behavior.

  17. Positron emission tomography and gene therapy: basic concepts and experimental approaches for in vivo gene expression imaging.

    Science.gov (United States)

    Peñuelas, Iván; Boán, JoséF; Martí-Climent, Josep M; Sangro, Bruno; Mazzolini, Guillermo; Prieto, Jesús; Richter, José A

    2004-01-01

    More than two decades of intense research have allowed gene therapy to move from the laboratory to the clinical setting, where its use for the treatment of human pathologies has been considerably increased in the last years. However, many crucial questions remain to be solved in this challenging field. In vivo imaging with positron emission tomography (PET) by combination of the appropriate PET reporter gene and PET reporter probe could provide invaluable qualitative and quantitative information to answer multiple unsolved questions about gene therapy. PET imaging could be used to define parameters not available by other techniques that are of substantial interest not only for the proper understanding of the gene therapy process, but also for its future development and clinical application in humans. This review focuses on the molecular biology basis of gene therapy and molecular imaging, describing the fundamentals of in vivo gene expression imaging by PET, and the application of PET to gene therapy, as a technology that can be used in many different ways. It could be applied to avoid invasive procedures for gene therapy monitoring; accurately diagnose the pathology for better planning of the most adequate therapeutic approach; as treatment evaluation to image the functional effects of gene therapy at the biochemical level; as a quantitative noninvasive way to monitor the location, magnitude and persistence of gene expression over time; and would also help to a better understanding of vector biology and pharmacology devoted to the development of safer and more efficient vectors.

  18. 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.

  19. Clustering gene expression regulators: new approach to disease subtyping.

    Directory of Open Access Journals (Sweden)

    Mikhail Pyatnitskiy

    Full Text Available One of the main challenges in modern medicine is to stratify different patient groups in terms of underlying disease molecular mechanisms as to develop more personalized approach to therapy. Here we propose novel method for disease subtyping based on analysis of activated expression regulators on a sample-by-sample basis. Our approach relies on Sub-Network Enrichment Analysis algorithm (SNEA which identifies gene subnetworks with significant concordant changes in expression between two conditions. Subnetwork consists of central regulator and downstream genes connected by relations extracted from global literature-extracted regulation database. Regulators found in each patient separately are clustered together and assigned activity scores which are used for final patients grouping. We show that our approach performs well compared to other related methods and at the same time provides researchers with complementary level of understanding of pathway-level biology behind a disease by identification of significant expression regulators. We have observed the reasonable grouping of neuromuscular disorders (triggered by structural damage vs triggered by unknown mechanisms, that was not revealed using standard expression profile clustering. For another experiment we were able to suggest the clusters of regulators, responsible for colorectal carcinoma vs adenoma discrimination and identify frequently genetically changed regulators that could be of specific importance for the individual characteristics of cancer development. Proposed approach can be regarded as biologically meaningful feature selection, reducing tens of thousands of genes down to dozens of clusters of regulators. Obtained clusters of regulators make possible to generate valuable biological hypotheses about molecular mechanisms related to a clinical outcome for individual patient.

  20. 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.

  1. A Double Selection Approach to Achieve Specific Expression of Toxin Genes for Ovarian Cancer Gene Therapy

    National Research Council Canada - National Science Library

    Curiel, David T; Siegal, Gene; Wang, Minghui

    2007-01-01

    ...) to achieve efficient and selective gene transfer to target tumor cells. Proposed herein is a strategy to modify one candidate vector, recombinant adenovirus, such that it embodies the requisite properties of efficacy and specificity...

  2. Environment-Gene interaction in common complex diseases: New approaches

    Directory of Open Access Journals (Sweden)

    William A. Toscano, Jr.

    2014-10-01

    Full Text Available Approximately 100,000 different environmental chemicals that are in use as high production volume chemicals confront us in our daily lives. Many of the chemicals we encounter are persistent and have long half-lives in the environment and our bodies. These compounds are referred to as Persistent Organic Pollutants, or POPS. The total environment however is broader than just toxic pollutants. It includes social capital, social economic status, and other factors that are not commonly considered in traditional approaches to studying environment-human interactions. The mechanism of action of environmental agents in altering the human phenotype from health to disease is more complex than once thought. The focus in public health has shifted away from the study of single-gene rare diseases and has given way to the study of multifactorial complex diseases that are common in the population. To understand common complex diseases, we need teams of scientists from different fields working together with common aims. We review some approaches for studying the action of the environment by discussing use-inspired research, and transdisciplinary research approaches. The Genomic era has yielded new tools for study of gene-environment interactions, including genomics, epigenomics, and systems biology. We use environmentally-driven diabetes mellitus type two as an example of environmental epigenomics and disease. The aim of this review is to start the conversation of how the application of advances in biomedical science can be used to advance public health.

  3. A partial least-square approach for modeling gene-gene and gene-environment interactions when multiple markers are genotyped.

    Science.gov (United States)

    Wang, Tao; Ho, Gloria; Ye, Kenny; Strickler, Howard; Elston, Robert C

    2009-01-01

    Genetic association studies achieve an unprecedented level of resolution in mapping disease genes by genotyping dense single nucleotype polymorphisms (SNPs) in a gene region. Meanwhile, these studies require new powerful statistical tools that can optimally handle a large amount of information provided by genotype data. A question that arises is how to model interactions between two genes. Simply modeling all possible interactions between the SNPs in two gene regions is not desirable because a greatly increased number of degrees of freedom can be involved in the test statistic. We introduce an approach to reduce the genotype dimension in modeling interactions. The genotype compression of this approach is built upon the information on both the trait and the cross-locus gametic disequilibrium between SNPs in two interacting genes, in such a way as to parsimoniously model the interactions without loss of useful information in the process of dimension reduction. As a result, it improves power to detect association in the presence of gene-gene interactions. This approach can be similarly applied for modeling gene-environment interactions. We compare this method with other approaches, the corresponding test without modeling any interaction, that based on a saturated interaction model, that based on principal component analysis, and that based on Tukey's one-degree-of-freedom model. Our simulations suggest that this new approach has superior power to that of the other methods. In an application to endometrial cancer case-control data from the Women's Health Initiative, this approach detected AKT1 and AKT2 as being significantly associated with endometrial cancer susceptibility by taking into account their interactions with body mass index.

  4. Using the candidate gene approach for detecting genes underlying seed oil concentration and yield in soybean.

    Science.gov (United States)

    Eskandari, Mehrzad; Cober, Elroy R; Rajcan, Istvan

    2013-07-01

    Increasing the oil concentration in soybean seeds has been given more attention in recent years because of demand for both edible oil and biodiesel production. Oil concentration in soybean is a complex quantitative trait regulated by many genes as well as environmental conditions. To identify genes governing seed oil concentration in soybean, 16 putative candidate genes of three important gene families (GPAT: acyl-CoA:sn-glycerol-3-phosphate acyltransferase, DGAT: acyl-CoA:diacylglycerol acyltransferase, and PDAT: phospholipid:diacylglycerol acyltransferase) involved in triacylglycerol (TAG) biosynthesis pathways were selected and their sequences retrieved from the soybean database ( http://www.phytozome.net/soybean ). Three sequence mutations were discovered in either coding or noncoding regions of three DGAT soybean isoforms when comparing the parents of a 203 recombinant inbreed line (RIL) population; OAC Wallace and OAC Glencoe. The RIL population was used to study the effects of these mutations on seed oil concentration and other important agronomic and seed composition traits, including seed yield and protein concentration across three field locations in Ontario, Canada, in 2009 and 2010. An insertion/deletion (indel) mutation in the GmDGAT2B gene in OAC Wallace was significantly associated with reduced seed oil concentration across three environments and reduced seed yield at Woodstock in 2010. A mutation in the 3' untranslated (3'UTR) region of GmDGAT2C was associated with seed yield at Woodstock in 2009. A mutation in the intronic region of GmDGAR1B was associated with seed yield and protein concentration at Ottawa in 2010. The genes identified in this study had minor effects on either seed yield or oil concentration, which was in agreement with the quantitative nature of the traits. However, the novel gene-specific markers designed in the present study can be used in soybean breeding for marker-assisted selection aimed at increasing seed yield and oil

  5. 'Omics' approaches in tomato aimed at identifying candidate genes ...

    African Journals Online (AJOL)

    adriana

    2013-12-04

    Dec 4, 2013 ... importance for human health and nutrition. This species has ... function to genes, proteins and metabolites is still a daunting task. Major challenges ... relation of the expression pattern of genes with the accu- mulation pattern of ..... M, Gordon JS, Rose, JKC, Martin G, Tanksley SD, Bouzayen M,. Jahn MM ...

  6. Imaging reporter gene for monitoring gene therapy

    International Nuclear Information System (INIS)

    Beco, V. de; Baillet, G.; Tamgac, F.; Tofighi, M.; Weinmann, P.; Vergote, J.; Moretti, J.L.; Tamgac, G.

    2002-01-01

    Scintigraphic images can be obtained to document gene function at cellular level. This approach is presented here and the use of a reporter gene to monitor gene therapy is described. Two main ways are presented: either the use of a reporter gene coding for an enzyme the action of which will be monitored by radiolabeled pro-drug, or a cellular receptor gene, the action of which is documented by a radio labeled cognate receptor ligand. (author)

  7. 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.)

  8. Pediatric Multiple Sclerosis: Genes, Environment, and a Comprehensive Therapeutic Approach.

    Science.gov (United States)

    Cappa, Ryan; Theroux, Liana; Brenton, J Nicholas

    2017-10-01

    Pediatric multiple sclerosis is an increasingly recognized and studied disorder that accounts for 3% to 10% of all patients with multiple sclerosis. The risk for pediatric multiple sclerosis is thought to reflect a complex interplay between environmental and genetic risk factors. Environmental exposures, including sunlight (ultraviolet radiation, vitamin D levels), infections (Epstein-Barr virus), passive smoking, and obesity, have been identified as potential risk factors in youth. Genetic predisposition contributes to the risk of multiple sclerosis, and the major histocompatibility complex on chromosome 6 makes the single largest contribution to susceptibility to multiple sclerosis. With the use of large-scale genome-wide association studies, other non-major histocompatibility complex alleles have been identified as independent risk factors for the disease. The bridge between environment and genes likely lies in the study of epigenetic processes, which are environmentally-influenced mechanisms through which gene expression may be modified. This article will review these topics to provide a framework for discussion of a comprehensive approach to counseling and ultimately treating the pediatric patient with multiple sclerosis. Copyright © 2017 Elsevier Inc. All rights reserved.

  9. Reference gene validation for gene expression normalization in canine osteosarcoma : a geNorm algorithm approach

    NARCIS (Netherlands)

    Selvarajah, G.T.; Bonestroo, F.A.S.; Timmermans Sprang, E.P.M.; Kirpensteijn, J.|info:eu-repo/dai/nl/189846992; Mol, J.A.|info:eu-repo/dai/nl/070918775

    2017-01-01

    Background Quantitative PCR (qPCR) is a common method for quantifying mRNA expression. Given the heterogeneity present in tumor tissues, it is crucial to normalize target mRNA expression data using appropriate reference genes that are stably expressed under a variety of pathological and experimental

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

    Science.gov (United States)

    Li, Yanpeng; Yu, Hong

    2014-01-01

    Gene ontology (GO) and GO annotation are important resources for biological information management and knowledge discovery, but the speed of manual annotation became a major bottleneck of database curation. BioCreative IV GO annotation task aims to evaluate the performance of system that automatically assigns GO terms to genes based on the narrative sentences in biomedical literature. This article presents our work in this task as well as the experimental results after the competition. For the evidence sentence extraction subtask, we built a binary classifier to identify evidence sentences using reference distance estimator (RDE), a recently proposed semi-supervised learning method that learns new features from around 10 million unlabeled sentences, achieving an F1 of 19.3% in exact match and 32.5% in relaxed match. In the post-submission experiment, we obtained 22.1% and 35.7% F1 performance by incorporating bigram features in RDE learning. In both development and test sets, RDE-based method achieved over 20% relative improvement on F1 and AUC performance against classical supervised learning methods, e.g. support vector machine and logistic regression. For the GO term prediction subtask, we developed an information retrieval-based method to retrieve the GO term most relevant to each evidence sentence using a ranking function that combined cosine similarity and the frequency of GO terms in documents, and a filtering method based on high-level GO classes. The best performance of our submitted runs was 7.8% F1 and 22.2% hierarchy F1. We found that the incorporation of frequency information and hierarchy filtering substantially improved the performance. In the post-submission evaluation, we obtained a 10.6% F1 using a simpler setting. Overall, the experimental analysis showed our approaches were robust in both the two tasks. © The Author(s) 2014. Published by Oxford University Press.

  11. Gene editing as a promising approach for respiratory diseases.

    Science.gov (United States)

    Bai, Yichun; Liu, Yang; Su, Zhenlei; Ma, Yana; Ren, Chonghua; Zhao, Runzhen; Ji, Hong-Long

    2018-03-01

    Respiratory diseases, which are leading causes of mortality and morbidity in the world, are dysfunctions of the nasopharynx, the trachea, the bronchus, the lung and the pleural cavity. Symptoms of chronic respiratory diseases, such as cough, sneezing and difficulty breathing, may seriously affect the productivity, sleep quality and physical and mental well-being of patients, and patients with acute respiratory diseases may have difficulty breathing, anoxia and even life-threatening respiratory failure. Respiratory diseases are generally heterogeneous, with multifaceted causes including smoking, ageing, air pollution, infection and gene mutations. Clinically, a single pulmonary disease can exhibit more than one phenotype or coexist with multiple organ disorders. To correct abnormal function or repair injured respiratory tissues, one of the most promising techniques is to correct mutated genes by gene editing, as some gene mutations have been clearly demonstrated to be associated with genetic or heterogeneous respiratory diseases. Zinc finger nucleases (ZFN), transcription activator-like effector nucleases (TALEN) and clustered regulatory interspaced short palindromic repeats/CRISPR-associated protein 9 (CRISPR/Cas9) systems are three innovative gene editing technologies developed recently. In this short review, we have summarised the structure and operating principles of the ZFNs, TALENs and CRISPR/Cas9 systems and their preclinical and clinical applications in respiratory diseases. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

  12. Gene selection for the reconstruction of stem cell differentiation trees: a linear programming approach.

    Science.gov (United States)

    Ghadie, Mohamed A; Japkowicz, Nathalie; Perkins, Theodore J

    2015-08-15

    Stem cell differentiation is largely guided by master transcriptional regulators, but it also depends on the expression of other types of genes, such as cell cycle genes, signaling genes, metabolic genes, trafficking genes, etc. Traditional approaches to understanding gene expression patterns across multiple conditions, such as principal components analysis or K-means clustering, can group cell types based on gene expression, but they do so without knowledge of the differentiation hierarchy. Hierarchical clustering can organize cell types into a tree, but in general this tree is different from the differentiation hierarchy itself. Given the differentiation hierarchy and gene expression data at each node, we construct a weighted Euclidean distance metric such that the minimum spanning tree with respect to that metric is precisely the given differentiation hierarchy. We provide a set of linear constraints that are provably sufficient for the desired construction and a linear programming approach to identify sparse sets of weights, effectively identifying genes that are most relevant for discriminating different parts of the tree. We apply our method to microarray gene expression data describing 38 cell types in the hematopoiesis hierarchy, constructing a weighted Euclidean metric that uses just 175 genes. However, we find that there are many alternative sets of weights that satisfy the linear constraints. Thus, in the style of random-forest training, we also construct metrics based on random subsets of the genes and compare them to the metric of 175 genes. We then report on the selected genes and their biological functions. Our approach offers a new way to identify genes that may have important roles in stem cell differentiation. tperkins@ohri.ca Supplementary data are available at Bioinformatics online. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

  13. Approaches to diagnose DNA mismatch repair gene defects in cancer

    DEFF Research Database (Denmark)

    Peña-Diaz, Javier; Rasmussen, Lene Juel

    2016-01-01

    development was first observed in colorectal cancer patients that carried inactivating germline mutations in MMR genes and the disease was named as hereditary non-polyposis colorectal cancer (HNPCC). Currently, a growing list of cancers is found to be MMR defective and HNPCC has been renamed Lynch syndrome...

  14. 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

  15. In silico approach to identification of a novel gene responsive to ...

    African Journals Online (AJOL)

    Submergence is one of the major constraints to rice production. Bioinformatics approach has been widely used to identify candidate genes on many biological aspects. In the present study, a novel gene involved in submergence stress in rice, Os07g47670 was identified by in silico approach. The amino acid sequence of ...

  16. Prostate cancer metastasis-driving genes: hurdles and potential approaches in their identification

    Directory of Open Access Journals (Sweden)

    Yan Ting Chiang

    2014-08-01

    Full Text Available Metastatic prostate cancer is currently incurable. Metastasis is thought to result from changes in the expression of specific metastasis-driving genes in nonmetastatic prostate cancer tissue, leading to a cascade of activated downstream genes that set the metastatic process in motion. Such genes could potentially serve as effective therapeutic targets for improved management of the disease. They could be identified by comparative analysis of gene expression profiles of patient-derived metastatic and nonmetastatic prostate cancer tissues to pinpoint genes showing altered expression, followed by determining whether silencing of such genes can lead to inhibition of metastatic properties. Various hurdles encountered in this approach are discussed, including (i the need for clinically relevant, nonmetastatic and metastatic prostate cancer tissues such as xenografts of patients' prostate cancers developed via subrenal capsule grafting technology and (ii limitations in the currently available methodology for identification of master regulatory genes.

  17. A transgenic approach to study argininosuccinate synthetase gene expression

    Science.gov (United States)

    2014-01-01

    Background Argininosuccinate synthetase (ASS) participates in urea, nitric oxide and arginine production. Besides transcriptional regulation, a post-transcriptional regulation affecting nuclear precursor RNA stability has been reported. To study whether such post-transcriptional regulation underlines particular temporal and spatial ASS expression, and to investigate how human ASS gene behaves in a mouse background, a transgenic mouse system using a modified bacterial artificial chromosome carrying the human ASS gene tagged with EGFP was employed. Results Two lines of ASS-EGFP transgenic mice were generated: one with EGFP under transcriptional control similar to that of the endogenous ASS gene, another with EGFP under both transcriptional and post-transcriptional regulation as that of the endogenous ASS mRNA. EGFP expression in the liver, the organ for urea production, and in the intestine and kidney that are responsible for arginine biosynthesis, was examined. Organs taken from embryos E14.5 stage to young adult were examined under a fluorescence microscope either directly or after cryosectioning. The levels of EGFP and endogenous mouse Ass mRNAs were also quantified by S1 nuclease mapping. EGFP fluorescence and EGFP mRNA levels in both the liver and kidney were found to increase progressively from embryonic stage toward birth. In contrast, EGFP expression in the intestine was higher in neonates and started to decline at about 3 weeks after birth. Comparison between the EGFP profiles of the two transgenic lines indicated the developmental and tissue-specific regulation was mainly controlled at the transcriptional level. The ASS transgene was of human origin. EGFP expression in the liver followed essentially the mouse Ass pattern as evidenced by zonation distribution of fluorescence and the level of EGFP mRNA at birth. However, in the small intestine, Ass mRNA level declined sharply at 3 week of age, and yet substantial EGFP mRNA was still detectable at this stage

  18. An integrated approach for finding overlooked genes in Shigella.

    Directory of Open Access Journals (Sweden)

    Junping Peng

    Full Text Available BACKGROUND: The completion of numerous genome sequences introduced an era of whole-genome study. However, many genes are missed during genome annotation, including small RNAs (sRNAs and small open reading frames (sORFs. In order to improve genome annotation, we aimed to identify novel sRNAs and sORFs in Shigella, the principal etiologic agents of bacillary dysentery. METHODOLOGY/PRINCIPAL FINDINGS: We identified 64 sRNAs in Shigella, which were experimentally validated in other bacteria based on sequence conservation. We employed computer-based and tiling array-based methods to search for sRNAs, followed by RT-PCR and northern blots, to identify nine sRNAs in Shigella flexneri strain 301 (Sf301 and 256 regions containing possible sRNA genes. We found 29 candidate sORFs using bioinformatic prediction, array hybridization and RT-PCR verification. We experimentally validated 557 (57.9% DOOR operon predictions in the chromosomes of Sf301 and 46 (76.7% in virulence plasmid.We found 40 additional co-expressed gene pairs that were not predicted by DOOR. CONCLUSIONS/SIGNIFICANCE: We provide an updated and comprehensive annotation of the Shigella genome. Our study increased the expected numbers of sORFs and sRNAs, which will impact on future functional genomics and proteomics studies. Our method can be used for large scale reannotation of sRNAs and sORFs in any microbe with a known genome sequence.

  19. Candidate gene linkage approach to identify DNA variants that predispose to preterm birth

    DEFF Research Database (Denmark)

    Bream, Elise N A; Leppellere, Cara R; Cooper, Margaret E

    2013-01-01

    Background:The aim of this study was to identify genetic variants contributing to preterm birth (PTB) using a linkage candidate gene approach.Methods:We studied 99 single-nucleotide polymorphisms (SNPs) for 33 genes in 257 families with PTBs segregating. Nonparametric and parametric analyses were...... through the infant and/or the mother in the etiology of PTB....

  20. Rapid approach for cloning bacterial single-genes directly from soils ...

    African Journals Online (AJOL)

    Obtaining functional genes of bacteria from environmental samples usually depends on library-based approach which is not favored as its large amount of work with small possibility of positive clones. A kind of bacterial single-gene encoding glutamine synthetase (GS) was selected as example to detect the efficiency of ...

  1. An extended Kalman filtering approach to modeling nonlinear dynamic gene regulatory networks via short gene expression time series.

    Science.gov (United States)

    Wang, Zidong; Liu, Xiaohui; Liu, Yurong; Liang, Jinling; Vinciotti, Veronica

    2009-01-01

    In this paper, the extended Kalman filter (EKF) algorithm is applied to model the gene regulatory network from gene time series data. The gene regulatory network is considered as a nonlinear dynamic stochastic model that consists of the gene measurement equation and the gene regulation equation. After specifying the model structure, we apply the EKF algorithm for identifying both the model parameters and the actual value of gene expression levels. It is shown that the EKF algorithm is an online estimation algorithm that can identify a large number of parameters (including parameters of nonlinear functions) through iterative procedure by using a small number of observations. Four real-world gene expression data sets are employed to demonstrate the effectiveness of the EKF algorithm, and the obtained models are evaluated from the viewpoint of bioinformatics.

  2. Trichoderma genes

    Science.gov (United States)

    Foreman, Pamela [Los Altos, CA; Goedegebuur, Frits [Vlaardingen, NL; Van Solingen, Pieter [Naaldwijk, NL; Ward, Michael [San Francisco, CA

    2012-06-19

    Described herein are novel gene sequences isolated from Trichoderma reesei. Two genes encoding proteins comprising a cellulose binding domain, one encoding an arabionfuranosidase and one encoding an acetylxylanesterase are described. The sequences, CIP1 and CIP2, contain a cellulose binding domain. These proteins are especially useful in the textile and detergent industry and in pulp and paper industry.

  3. PREFACE: Physics approaches to protein interactions and gene regulation Physics approaches to protein interactions and gene regulation

    Science.gov (United States)

    Nussinov, Ruth; Panchenko, Anna R.; Przytycka, Teresa

    2011-06-01

    networks have been identified, including scale free distribution of the vertex degree, network motifs, and modularity, to name a few. These studies of network organization require the network to be as complete as possible, which given the limitations of experimental techniques is not currently the case. Therefore, experimental procedures for detecting biomolecular interactions should be complemented by computational approaches. The paper by Lees et al provides a review of computational methods, integrating multiple independent sources of data to infer physical and functional protein-protein interaction networks. One of the important aspects of protein interactions that should be accounted for in the prediction of protein interaction networks is that many proteins are composed of distinct domains. Protein domains may mediate protein interactions while proteins and their interaction networks may gain complexity through gene duplication and expansion of existing domain architectures via domain rearrangements. The latter mechanisms have been explored in detail in the paper by Cohen-Gihon et al. Protein-protein interactions are not the only component of the cell's interactome. Regulation of cell activity can be achieved at the level of transcription and involve a transcription factor—DNA binding which typically requires recognition of a specific DNA sequence motif. Chip-Chip and the more recent Chip-Seq technologies allow in vivo identification of DNA binding sites and, together with novel in vitro approaches, provide data necessary for deciphering the corresponding binding motifs. Such information, complemented by structures of protein-DNA complexes and knowledge of the differences in binding sites among homologs, opens the door to constructing predictive binding models. The paper by Persikov and Singh provides an example of such a model in the Cys2His2 zinc finger family. Recent studies have indicated that the presence of such binding motifs is, however, neither necessary

  4. A novel approach to simultaneously scan genes at fragile sites

    International Nuclear Information System (INIS)

    Willem, Pascale; Brown, Jacqueline; Schouten, Jan

    2006-01-01

    Fragile sites are regions of the genome sensitive to replication stress and to exposure to environmental carcinogens. The two most commonly expressed fragile sites FRA3B and FRA16D host the histidine triad (FHIT) and WW domain containing oxidoreductase (WWOX) genes respectively. There is growing evidence that both genes contribute to cancer development and they are frequently altered by allelic and homozygous deletions in a variety of tumors. Their status is linked to prognosis in several malignancies and they are thought to be involved in early tumorigenesis. The loci for FHIT and WWOX both span over a megabase but the genes encode for small transcripts. Thus the screening of intragenic deletion can be difficult and has relied on loss of heterozygosity LOH assays, or genomic arrays. Multiplex ligation dependent probe amplification MLPA, allows for the detection of deletions/duplications and relative quantification of up to 40 specific probes in a single assay. A FHIT/WWOX MLPA assay was designed, applied and validated in five esophageal squamous cell carcinoma ESCC, cell lines established in South Africa where this cancer is of high prevalence. Sixteen probes covered all FHIT exons and 7 probes covered WWOX. Both homozygous and hemizygous deletions were detected in FHIT, in four of the cell lines with a preferential deletion of exons 5 and 4. Chromosome 3 short arm was present in normal copy number indicating that deletions were site specific. In contrast WWOX was not altered in any cell lines. RT-PCR expression pattern paralleled the pattern of deletions. Ten primary ESCC tumor specimens were subsequently screened with this assay. FHIT exon deletions were found in four of them. This method offers an alternative to loss of heterozygosity studies. Simultaneous scanning of FHIT and WWOX exons in the context of early tumorigenesis and tumor progression, may help clarify the mechanistic events related to cancer development which are not revealed by imuno

  5. Discovering genes underlying QTL

    Energy Technology Data Exchange (ETDEWEB)

    Vanavichit, Apichart [Kasetsart University, Kamphaengsaen, Nakorn Pathom (Thailand)

    2002-02-01

    A map-based approach has allowed scientists to discover few genes at a time. In addition, the reproductive barrier between cultivated rice and wild relatives has prevented us from utilizing the germ plasm by a map-based approach. Most genetic traits important to agriculture or human diseases are manifested as observable, quantitative phenotypes called Quantitative Trait Loci (QTL). In many instances, the complexity of the phenotype/genotype interaction and the general lack of clearly identifiable gene products render the direct molecular cloning approach ineffective, thus additional strategies like genome mapping are required to identify the QTL in question. Genome mapping requires no prior knowledge of the gene function, but utilizes statistical methods to identify the most likely gene location. To completely characterize genes of interest, the initially mapped region of a gene location will have to be narrowed down to a size that is suitable for cloning and sequencing. Strategies for gene identification within the critical region have to be applied after the sequencing of a potentially large clone or set of clones that contains this gene(s). Tremendous success of positional cloning has been shown for cloning many genes responsible for human diseases, including cystic fibrosis and muscular dystrophy as well as plant disease resistance genes. Genome and QTL mapping, positional cloning: the pre-genomics era, comparative approaches to gene identification, and positional cloning: the genomics era are discussed in the report. (M. Suetake)

  6. Tumor targeted gene therapy

    International Nuclear Information System (INIS)

    Kang, Joo Hyun

    2006-01-01

    Knowledge of molecular mechanisms governing malignant transformation brings new opportunities for therapeutic intervention against cancer using novel approaches. One of them is gene therapy based on the transfer of genetic material to an organism with the aim of correcting a disease. The application of gene therapy to the cancer treatment had led to the development of new experimental approaches such as suicidal gene therapy, inhibition of oncogenes and restoration of tumor-suppressor genes. Suicidal gene therapy is based on the expression in tumor cells of a gene encoding an enzyme that converts a prodrug into a toxic product. Representative suicidal genes are Herpes simplex virus type 1 thymidine kinase (HSV1-tk) and cytosine deaminase (CD). Especially, physicians and scientists of nuclear medicine field take an interest in suicidal gene therapy because they can monitor the location and magnitude, and duration of expression of HSV1-tk and CD by PET scanner

  7. Linking Genes and Brain Development of Honeybee Workers: A Whole-Transcriptome Approach.

    Directory of Open Access Journals (Sweden)

    Christina Vleurinck

    Full Text Available Honeybees live in complex societies whose capabilities far exceed those of the sum of their single members. This social synergism is achieved mainly by the worker bees, which form a female caste. The worker bees display diverse collaborative behaviors and engage in different behavioral tasks, which are controlled by the central nervous system (CNS. The development of the worker brain is determined by the female sex and the worker caste determination signal. Here, we report on genes that are controlled by sex or by caste during differentiation of the worker's pupal brain. We sequenced and compared transcriptomes from the pupal brains of honeybee workers, queens and drones. We detected 333 genes that are differently expressed and 519 genes that are differentially spliced between the sexes, and 1760 genes that are differentially expressed and 692 genes that are differentially spliced between castes. We further found that 403 genes are differentially regulated by both the sex and caste signals, providing evidence of the integration of both signals through differential gene regulation. In this gene set, we found that the molecular processes of restructuring the cell shape and cell-to-cell signaling are overrepresented. Our approach identified candidate genes that may be involved in brain differentiation that ensures the various social worker behaviors.

  8. Looking into flowering time in almond (Prunus dulcis (Mill) D. A. Webb): the candidate gene approach.

    Science.gov (United States)

    Silva, C; Garcia-Mas, J; Sánchez, A M; Arús, P; Oliveira, M M

    2005-03-01

    Blooming time is one of the most important agronomic traits in almond. Biochemical and molecular events underlying flowering regulation must be understood before methods to stimulate late flowering can be developed. Attempts to elucidate the genetic control of this process have led to the identification of a major gene (Lb) and quantitative trait loci (QTLs) linked to observed phenotypic differences, but although this gene and these QTLs have been placed on the Prunus reference genetic map, their sequences and specific functions remain unknown. The aim of our investigation was to associate these loci with known genes using a candidate gene approach. Two almond cDNAs and eight Prunus expressed sequence tags were selected as candidate genes (CGs) since their sequences were highly identical to those of flowering regulatory genes characterized in other species. The CGs were amplified from both parental lines of the mapping population using specific primers. Sequence comparison revealed DNA polymorphisms between the parental lines, mainly of the single nucleotide type. Polymorphisms were used to develop co-dominant cleaved amplified polymorphic sequence markers or length polymorphisms based on insertion/deletion events for mapping the candidate genes on the Prunus reference map. Ten candidate genes were assigned to six linkage groups in the Prunus genome. The positions of two of these were compatible with the regions where two QTLs for blooming time were detected. One additional candidate was localized close to the position of the Evergrowing gene, which determines a non-deciduous behaviour in peach.

  9. Ageing genes

    DEFF Research Database (Denmark)

    Rattan, Suresh

    2018-01-01

    The idea of gerontogenes is in line with the evolutionary explanation of ageing as being an emergent phenomenon as a result of the imperfect maintenance and repair systems. Although evolutionary processes did not select for any specific ageing genes that restrict and determine the lifespan...... of an individual, the term ‘gerontogenes’ primarily refers to any genes that may seem to influence ageing and longevity, without being specifically selected for that role. Such genes can also be called ‘virtual gerontogenes’ by virtue of their indirect influence on the rate and process of ageing. More than 1000...... virtual gerontogenes have been associated with ageing and longevity in model organisms and humans. The ‘real’ genes, which do influence the essential lifespan of a species, and have been selected for in accordance with the evolutionary life history of the species, are known as the longevity assurance...

  10. A synbio approach for selection of highly expressed gene variants in Gram-positive bacteria

    DEFF Research Database (Denmark)

    Ferro, Roberto; Rennig, Maja; Hernández Rollán, Cristina

    2018-01-01

    with a long history in food fermentation. We have developed a synbio approach for increasing gene expression in two Gram-positive bacteria. First of all, the gene of interest was coupled to an antibiotic resistance gene to create a growth-based selection system. We then randomised the translation initiation...... region (TIR) preceding the gene of interest and selected clones that produced high protein titres, as judged by their ability to survive on high concentrations of antibiotic. Using this approach, we were able to significantly increase production of two industrially relevant proteins; sialidase in B....... subtilis and tyrosine ammonia lyase in L. lactis. Gram-positive bacteria are widely used to produce industrial enzymes. High titres are necessary to make the production economically feasible. The synbio approach presented here is a simple and inexpensive way to increase protein titres, which can be carried...

  11. Coalitional game theory as a promising approach to identify candidate autism genes.

    Science.gov (United States)

    Gupta, Anika; Sun, Min Woo; Paskov, Kelley Marie; Stockham, Nate Tyler; Jung, Jae-Yoon; Wall, Dennis Paul

    2018-01-01

    Despite mounting evidence for the strong role of genetics in the phenotypic manifestation of Autism Spectrum Disorder (ASD), the specific genes responsible for the variable forms of ASD remain undefined. ASD may be best explained by a combinatorial genetic model with varying epistatic interactions across many small effect mutations. Coalitional or cooperative game theory is a technique that studies the combined effects of groups of players, known as coalitions, seeking to identify players who tend to improve the performance--the relationship to a specific disease phenotype--of any coalition they join. This method has been previously shown to boost biologically informative signal in gene expression data but to-date has not been applied to the search for cooperative mutations among putative ASD genes. We describe our approach to highlight genes relevant to ASD using coalitional game theory on alteration data of 1,965 fully sequenced genomes from 756 multiplex families. Alterations were encoded into binary matrices for ASD (case) and unaffected (control) samples, indicating likely gene-disrupting, inherited mutations in altered genes. To determine individual gene contributions given an ASD phenotype, a "player" metric, referred to as the Shapley value, was calculated for each gene in the case and control cohorts. Sixty seven genes were found to have significantly elevated player scores and likely represent significant contributors to the genetic coordination underlying ASD. Using network and cross-study analysis, we found that these genes are involved in biological pathways known to be affected in the autism cases and that a subset directly interact with several genes known to have strong associations to autism. These findings suggest that coalitional game theory can be applied to large-scale genomic data to identify hidden yet influential players in complex polygenic disorders such as autism.

  12. A Multiomics Approach to Identify Genes Associated with Childhood Asthma Risk and Morbidity.

    Science.gov (United States)

    Forno, Erick; Wang, Ting; Yan, Qi; Brehm, John; Acosta-Perez, Edna; Colon-Semidey, Angel; Alvarez, Maria; Boutaoui, Nadia; Cloutier, Michelle M; Alcorn, John F; Canino, Glorisa; Chen, Wei; Celedón, Juan C

    2017-10-01

    Childhood asthma is a complex disease. In this study, we aim to identify genes associated with childhood asthma through a multiomics "vertical" approach that integrates multiple analytical steps using linear and logistic regression models. In a case-control study of childhood asthma in Puerto Ricans (n = 1,127), we used adjusted linear or logistic regression models to evaluate associations between several analytical steps of omics data, including genome-wide (GW) genotype data, GW methylation, GW expression profiling, cytokine levels, asthma-intermediate phenotypes, and asthma status. At each point, only the top genes/single-nucleotide polymorphisms/probes/cytokines were carried forward for subsequent analysis. In step 1, asthma modified the gene expression-protein level association for 1,645 genes; pathway analysis showed an enrichment of these genes in the cytokine signaling system (n = 269 genes). In steps 2-3, expression levels of 40 genes were associated with intermediate phenotypes (asthma onset age, forced expiratory volume in 1 second, exacerbations, eosinophil counts, and skin test reactivity); of those, methylation of seven genes was also associated with asthma. Of these seven candidate genes, IL5RA was also significant in analytical steps 4-8. We then measured plasma IL-5 receptor α levels, which were associated with asthma age of onset and moderate-severe exacerbations. In addition, in silico database analysis showed that several of our identified IL5RA single-nucleotide polymorphisms are associated with transcription factors related to asthma and atopy. This approach integrates several analytical steps and is able to identify biologically relevant asthma-related genes, such as IL5RA. It differs from other methods that rely on complex statistical models with various assumptions.

  13. More powerful significant testing for time course gene expression data using functional principal component analysis approaches.

    Science.gov (United States)

    Wu, Shuang; Wu, Hulin

    2013-01-16

    One of the fundamental problems in time course gene expression data analysis is to identify genes associated with a biological process or a particular stimulus of interest, like a treatment or virus infection. Most of the existing methods for this problem are designed for data with longitudinal replicates. But in reality, many time course gene experiments have no replicates or only have a small number of independent replicates. We focus on the case without replicates and propose a new method for identifying differentially expressed genes by incorporating the functional principal component analysis (FPCA) into a hypothesis testing framework. The data-driven eigenfunctions allow a flexible and parsimonious representation of time course gene expression trajectories, leaving more degrees of freedom for the inference compared to that using a prespecified basis. Moreover, the information of all genes is borrowed for individual gene inferences. The proposed approach turns out to be more powerful in identifying time course differentially expressed genes compared to the existing methods. The improved performance is demonstrated through simulation studies and a real data application to the Saccharomyces cerevisiae cell cycle data.

  14. Gene doping.

    Science.gov (United States)

    Haisma, H J; de Hon, O

    2006-04-01

    Together with the rapidly increasing knowledge on genetic therapies as a promising new branch of regular medicine, the issue has arisen whether these techniques might be abused in the field of sports. Previous experiences have shown that drugs that are still in the experimental phases of research may find their way into the athletic world. Both the World Anti-Doping Agency (WADA) and the International Olympic Committee (IOC) have expressed concerns about this possibility. As a result, the method of gene doping has been included in the list of prohibited classes of substances and prohibited methods. This review addresses the possible ways in which knowledge gained in the field of genetic therapies may be misused in elite sports. Many genes are readily available which may potentially have an effect on athletic performance. The sporting world will eventually be faced with the phenomena of gene doping to improve athletic performance. A combination of developing detection methods based on gene arrays or proteomics and a clear education program on the associated risks seems to be the most promising preventive method to counteract the possible application of gene doping.

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

    Directory of Open Access Journals (Sweden)

    Gong Binsheng

    2011-05-01

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

  16. GO-Bayes: Gene Ontology-based overrepresentation analysis using a Bayesian approach.

    Science.gov (United States)

    Zhang, Song; Cao, Jing; Kong, Y Megan; Scheuermann, Richard H

    2010-04-01

    A typical approach for the interpretation of high-throughput experiments, such as gene expression microarrays, is to produce groups of genes based on certain criteria (e.g. genes that are differentially expressed). To gain more mechanistic insights into the underlying biology, overrepresentation analysis (ORA) is often conducted to investigate whether gene sets associated with particular biological functions, for example, as represented by Gene Ontology (GO) annotations, are statistically overrepresented in the identified gene groups. However, the standard ORA, which is based on the hypergeometric test, analyzes each GO term in isolation and does not take into account the dependence structure of the GO-term hierarchy. We have developed a Bayesian approach (GO-Bayes) to measure overrepresentation of GO terms that incorporates the GO dependence structure by taking into account evidence not only from individual GO terms, but also from their related terms (i.e. parents, children, siblings, etc.). The Bayesian framework borrows information across related GO terms to strengthen the detection of overrepresentation signals. As a result, this method tends to identify sets of closely related GO terms rather than individual isolated GO terms. The advantage of the GO-Bayes approach is demonstrated with a simulation study and an application example.

  17. Gene editing in hematopoietic stem cells: a potential therapeutic approach for Fanconi anemia

    International Nuclear Information System (INIS)

    Diez Cabezas, B.

    2015-01-01

    Gene therapy nowadays constitutes a safe and efficient treatment for a number of monogenic diseases affecting the hematopoietic system. Risks of insertional mutagenesis derived from the use of integrative vectors cannot, however, be completely excluded. Therefore, gene targeting has been proposed as a safer alternative, since the insertion of the herapeutic gene is driven to a specific locus in the genome. Gene targeting approaches are based on the use of specific nucleases which generate double strand breaks (DSBs) in a specific site of the genome,markedly enhancing the efficacy of homologous recombination (HR) with donor constructs harboring the gene of interest flanked by the corresponding homology arms. In this study we have optimized the conditions to target human lymphoblastic cell lines (LCLs) and also hematopoietic stem cells (HSCs) from healthy donors, with the final aim of correcting by gene editing the hematopoietic progenitor cells from Fanconi anemia subtype A (FA-A) patients. In particular, we have established a robust method to target both LCLs and HSCs in a safe harbor site in the genome, the AAVS1 locus. Our approach is based on the transduction of these cells with integrase-defective lentiviral vectors carrying a donor with the gene of interest, followed by the nucleofection of these cells with zinc finger nucleases used as mRNA. Using a control donor vector carrying the GFP reporter gene we have obtained, on average, 9.43% gene targeting efficiency in cord blood CD34+ cells from healthy donors. Moreover, we confirmed that gene targeting was also efficient in HSCs with long term and multipotent repopulation capacity, as demonstrated by transplants into immunodeficient mice. To improve the gene targeting efficiency, we investigated the feasibility of using gold nanoparticles, which were shown to improve the transduction efficiency of integrase-defective and competent lentiviral vectors in HSCs. This increment, however, did not lead to a higher gene

  18. Gene editing in hematopoietic stem cells: a potential therapeutic approach for Fanconi anemia

    Energy Technology Data Exchange (ETDEWEB)

    Diez Cabezas, B.

    2015-07-01

    Gene therapy nowadays constitutes a safe and efficient treatment for a number of monogenic diseases affecting the hematopoietic system. Risks of insertional mutagenesis derived from the use of integrative vectors cannot, however, be completely excluded. Therefore, gene targeting has been proposed as a safer alternative, since the insertion of the herapeutic gene is driven to a specific locus in the genome. Gene targeting approaches are based on the use of specific nucleases which generate double strand breaks (DSBs) in a specific site of the genome,markedly enhancing the efficacy of homologous recombination (HR) with donor constructs harboring the gene of interest flanked by the corresponding homology arms. In this study we have optimized the conditions to target human lymphoblastic cell lines (LCLs) and also hematopoietic stem cells (HSCs) from healthy donors, with the final aim of correcting by gene editing the hematopoietic progenitor cells from Fanconi anemia subtype A (FA-A) patients. In particular, we have established a robust method to target both LCLs and HSCs in a safe harbor site in the genome, the AAVS1 locus. Our approach is based on the transduction of these cells with integrase-defective lentiviral vectors carrying a donor with the gene of interest, followed by the nucleofection of these cells with zinc finger nucleases used as mRNA. Using a control donor vector carrying the GFP reporter gene we have obtained, on average, 9.43% gene targeting efficiency in cord blood CD34+ cells from healthy donors. Moreover, we confirmed that gene targeting was also efficient in HSCs with long term and multipotent repopulation capacity, as demonstrated by transplants into immunodeficient mice. To improve the gene targeting efficiency, we investigated the feasibility of using gold nanoparticles, which were shown to improve the transduction efficiency of integrase-defective and competent lentiviral vectors in HSCs. This increment, however, did not lead to a higher gene

  19. Gene Locater

    DEFF Research Database (Denmark)

    Anwar, Muhammad Zohaib; Sehar, Anoosha; Rehman, Inayat-Ur

    2012-01-01

    software's for calculating recombination frequency is mostly limited to the range and flexibility of this type of analysis. GENE LOCATER is a fully customizable program for calculating recombination frequency, written in JAVA. Through an easy-to-use interface, GENE LOCATOR allows users a high degree...... of flexibility in calculating genetic linkage and displaying linkage group. Among other features, this software enables user to identify linkage groups with output visualized graphically. The program calculates interference and coefficient of coincidence with elevated accuracy in sample datasets. AVAILABILITY...

  20. Uropathogenic Escherichia coli virulence genes: invaluable approaches for designing DNA microarray probes.

    Science.gov (United States)

    Jahandeh, Nadia; Ranjbar, Reza; Behzadi, Payam; Behzadi, Elham

    2015-01-01

    The pathotypes of uropathogenic Escherichia coli (UPEC) cause different types of urinary tract infections (UTIs). The presence of a wide range of virulence genes in UPEC enables us to design appropriate DNA microarray probes. These probes, which are used in DNA microarray technology, provide us with an accurate and rapid diagnosis and definitive treatment in association with UTIs caused by UPEC pathotypes. The main goal of this article is to introduce the UPEC virulence genes as invaluable approaches for designing DNA microarray probes. Main search engines such as Google Scholar and databases like NCBI were searched to find and study several original pieces of literature, review articles, and DNA gene sequences. In parallel with in silico studies, the experiences of the authors were helpful for selecting appropriate sources and writing this review article. There is a significant variety of virulence genes among UPEC strains. The DNA sequences of virulence genes are fabulous patterns for designing microarray probes. The location of virulence genes and their sequence lengths influence the quality of probes. The use of selected virulence genes for designing microarray probes gives us a wide range of choices from which the best probe candidates can be chosen. DNA microarray technology provides us with an accurate, rapid, cost-effective, sensitive, and specific molecular diagnostic method which is facilitated by designing microarray probes. Via these tools, we are able to have an accurate diagnosis and a definitive treatment regarding UTIs caused by UPEC pathotypes.

  1. Bioinformatics approach of salt tolerance gene in mangrove plant Rhizophora stylosa

    Science.gov (United States)

    Basyuni, M.; Sumardi

    2017-01-01

    This study descibes bioinformatics approach on the analyze of the salt tolerance genes in mangrove plant, Rhizophora stylosa on DDBJ/EMBL/GenBank as well as similarity, phylogenetic, potential peptide, and subcellular localization. The DNA sequence between salt tolerance gene from R. stylosa exhibited 42-11% between themselves The target peptide value of mitochondria varied from 0.163 to 0.430, indicated it was possible to exist. These results suggested the importance of understanding the diversity and functional of properties of the different amino acids in mangrove OSC genes. To clarify the relationship among the salt-tolerant genes in R. stylosa, a phylogenetic tree was constructed. The phylogenetic tree shows that there are three clusters, first branch of Cu/Zn SOD and reverse transcriptase genes, the second branch consists of the majority genes and the last group was MAP3K alpha protein kinase only. The present study, therefore, suggested that salt tolerance genes form distinct clusters in the tree.

  2. A Third Approach to Gene Prediction Suggests Thousands of Additional Human Transcribed Regions

    Science.gov (United States)

    Glusman, Gustavo; Qin, Shizhen; El-Gewely, M. Raafat; Siegel, Andrew F; Roach, Jared C; Hood, Leroy; Smit, Arian F. A

    2006-01-01

    The identification and characterization of the complete ensemble of genes is a main goal of deciphering the digital information stored in the human genome. Many algorithms for computational gene prediction have been described, ultimately derived from two basic concepts: (1) modeling gene structure and (2) recognizing sequence similarity. Successful hybrid methods combining these two concepts have also been developed. We present a third orthogonal approach to gene prediction, based on detecting the genomic signatures of transcription, accumulated over evolutionary time. We discuss four algorithms based on this third concept: Greens and CHOWDER, which quantify mutational strand biases caused by transcription-coupled DNA repair, and ROAST and PASTA, which are based on strand-specific selection against polyadenylation signals. We combined these algorithms into an integrated method called FEAST, which we used to predict the location and orientation of thousands of putative transcription units not overlapping known genes. Many of the newly predicted transcriptional units do not appear to code for proteins. The new algorithms are particularly apt at detecting genes with long introns and lacking sequence conservation. They therefore complement existing gene prediction methods and will help identify functional transcripts within many apparent “genomic deserts.” PMID:16543943

  3. A guide to approaching regulatory considerations for lentiviral-mediated gene therapies.

    Science.gov (United States)

    White, Michael; Whittaker, Roger; Stoll, Elizabeth Ann

    2017-06-12

    Lentiviral vectors are increasingly the gene transfer tool of choice for gene or cell therapies, with multiple clinical investigations showing promise for this viral vector in terms of both safety and efficacy. The third-generation vector system is well-characterized, effectively delivers genetic material and maintains long-term stable expression in target cells, delivers larger amounts of genetic material than other methods, is non-pathogenic and does not cause an inflammatory response in the recipient. This report aims to help academic scientists and regulatory managers negotiate the governance framework to achieve successful translation of a lentiviral vector-based gene therapy. The focus is on European regulations, and how they are administered in the United Kingdom, although many of the principles will be similar for other regions including the United States. The report justifies the rationale for using third-generation lentiviral vectors to achieve gene delivery for in vivo and ex vivo applications; briefly summarises the extant regulatory guidance for gene therapies, categorised as advanced therapeutic medicinal products (ATMPs); provides guidance on specific regulatory issues regarding gene therapies; presents an overview of the key stakeholders to be approached when pursuing clinical trials authorization for an ATMP; and includes a brief catalogue of the documentation required to submit an application for regulatory approval of a new gene therapy.

  4. Vaccine-induced modulation of gene expression in turbot peritoneal cells. A microarray approach.

    Science.gov (United States)

    Fontenla, Francisco; Blanco-Abad, Verónica; Pardo, Belén G; Folgueira, Iria; Noia, Manuel; Gómez-Tato, Antonio; Martínez, Paulino; Leiro, José M; Lamas, Jesús

    2016-07-01

    We used a microarray approach to examine changes in gene expression in turbot peritoneal cells after injection of the fish with vaccines containing the ciliate parasite Philasterides dicentrarchi as antigen and one of the following adjuvants: chitosan-PVMMA microspheres, Freund́s complete adjuvant, aluminium hydroxide gel or Matrix-Q (Isconova, Sweden). We identified 374 genes that were differentially expressed in all groups of fish. Forty-two genes related to tight junctions and focal adhesions and/or actin cytoskeleton were differentially expressed in free peritoneal cells. The profound changes in gene expression related to cell adherence and cytoskeleton may be associated with cell migration and also with the formation of cell-vaccine masses and their attachment to the peritoneal wall. Thirty-five genes related to apoptosis were differentially expressed. Although most of the proteins coded by these genes have a proapoptotic effect, others are antiapoptotic, indicating that both types of signals occur in peritoneal leukocytes of vaccinated fish. Interestingly, many of the genes related to lymphocytes and lymphocyte activity were downregulated in the groups injected with vaccine. We also observed decreased expression of genes related to antigen presentation, suggesting that macrophages (which were abundant in the peritoneal cavity after vaccination) did not express these during the early inflammatory response in the peritoneal cavity. Finally, several genes that participate in the inflammatory response were differentially expressed, and most participated in resolution of inflammation, indicating that an M2 macrophage response is generated in the peritoneal cavity of fish one day post vaccination. Copyright © 2016 Elsevier Ltd. All rights reserved.

  5. Gene therapy: An overview

    Directory of Open Access Journals (Sweden)

    Sudip Indu

    2013-01-01

    Full Text Available Gene therapy "the use of genes as medicine" involves the transfer of a therapeutic or working copy of a gene into specific cells of an individual in order to repair a faulty gene copy. The technique may be used to replace a faulty gene, or to introduce a new gene whose function is to cure or to favorably modify the clinical course of a condition. The objective of gene therapy is to introduce new genetic material into target cells while causing no damage to the surrounding healthy cells and tissues, hence the treatment related morbidity is decreased. The delivery system includes a vector that delivers a therapeutic gene into the patient′s target cell. Functional proteins are created from the therapeutic gene causing the cell to return to a normal stage. The vectors used in gene therapy can be viral and non-viral. Gene therapy, an emerging field of biomedicine, is still at infancy and much research remains to be done before this approach to the treatment of condition will realize its full potential.

  6. Gene therapy in periodontics.

    Science.gov (United States)

    Chatterjee, Anirban; Singh, Nidhi; Saluja, Mini

    2013-03-01

    GENES are made of DNA - the code of life. They are made up of two types of base pair from different number of hydrogen bonds AT, GC which can be turned into instruction. Everyone inherits genes from their parents and passes them on in turn to their children. Every person's genes are different, and the changes in sequence determine the inherited differences between each of us. Some changes, usually in a single gene, may cause serious diseases. Gene therapy is 'the use of genes as medicine'. It involves the transfer of a therapeutic or working gene copy into specific cells of an individual in order to repair a faulty gene copy. Thus it may be used to replace a faulty gene, or to introduce a new gene whose function is to cure or to favorably modify the clinical course of a condition. It has a promising era in the field of periodontics. Gene therapy has been used as a mode of tissue engineering in periodontics. The tissue engineering approach reconstructs the natural target tissue by combining four elements namely: Scaffold, signaling molecules, cells and blood supply and thus can help in the reconstruction of damaged periodontium including cementum, gingival, periodontal ligament and bone.

  7. Identification of conserved drought-adaptive genes using a cross-species meta-analysis approach.

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    Shaar-Moshe, Lidor; Hübner, Sariel; Peleg, Zvi

    2015-05-03

    Drought is the major environmental stress threatening crop-plant productivity worldwide. Identification of new genes and metabolic pathways involved in plant adaptation to progressive drought stress at the reproductive stage is of great interest for agricultural research. We developed a novel Cross-Species meta-Analysis of progressive Drought stress at the reproductive stage (CSA:Drought) to identify key drought adaptive genes and mechanisms and to test their evolutionary conservation. Empirically defined filtering criteria were used to facilitate a robust integration of 17 deposited microarray experiments (148 arrays) of Arabidopsis, rice, wheat and barley. By prioritizing consistency over intensity, our approach was able to identify 225 differentially expressed genes shared across studies and taxa. Gene ontology enrichment and pathway analyses classified the shared genes into functional categories involved predominantly in metabolic processes (e.g. amino acid and carbohydrate metabolism), regulatory function (e.g. protein degradation and transcription) and response to stimulus. We further investigated drought related cis-acting elements in the shared gene promoters, and the evolutionary conservation of shared genes. The universal nature of the identified drought-adaptive genes was further validated in a fifth species, Brachypodium distachyon that was not included in the meta-analysis. qPCR analysis of 27, randomly selected, shared orthologs showed similar expression pattern as was found by the CSA:Drought.In accordance, morpho-physiological characterization of progressive drought stress, in B. distachyon, highlighted the key role of osmotic adjustment as evolutionary conserved drought-adaptive mechanism. Our CSA:Drought strategy highlights major drought-adaptive genes and metabolic pathways that were only partially, if at all, reported in the original studies included in the meta-analysis. These genes include a group of unclassified genes that could be involved

  8. Gene Variants Associated with Antisocial Behaviour: A Latent Variable Approach

    Science.gov (United States)

    Bentley, Mary Jane; Lin, Haiqun; Fernandez, Thomas V.; Lee, Maria; Yrigollen, Carolyn M.; Pakstis, Andrew J.; Katsovich, Liliya; Olds, David L.; Grigorenko, Elena L.; Leckman, James F.

    2013-01-01

    Objective: The aim of this study was to determine if a latent variable approach might be useful in identifying shared variance across genetic risk alleles that is associated with antisocial behaviour at age 15 years. Methods: Using a conventional latent variable approach, we derived an antisocial phenotype in 328 adolescents utilizing data from a…

  9. A synbio approach for selection of highly expressed gene variants in Gram-positive bacteria.

    Science.gov (United States)

    Ferro, Roberto; Rennig, Maja; Hernández-Rollán, Cristina; Daley, Daniel O; Nørholm, Morten H H

    2018-03-08

    The market for recombinant proteins is on the rise, and Gram-positive strains are widely exploited for this purpose. Bacillus subtilis is a profitable host for protein production thanks to its ability to secrete large amounts of proteins, and Lactococcus lactis is an attractive production organism with a long history in food fermentation. We have developed a synbio approach for increasing gene expression in two Gram-positive bacteria. First of all, the gene of interest was coupled to an antibiotic resistance gene to create a growth-based selection system. We then randomised the translation initiation region (TIR) preceding the gene of interest and selected clones that produced high protein titres, as judged by their ability to survive on high concentrations of antibiotic. Using this approach, we were able to significantly increase production of two industrially relevant proteins; sialidase in B. subtilis and tyrosine ammonia lyase in L. lactis. Gram-positive bacteria are widely used to produce industrial enzymes. High titres are necessary to make the production economically feasible. The synbio approach presented here is a simple and inexpensive way to increase protein titres, which can be carried out in any laboratory within a few days. It could also be implemented as a tool for applications beyond TIR libraries, such as screening of synthetic, homologous or domain-shuffled genes.

  10. Pollen Sterility—A Promising Approach to Gene Confinement and Breeding for Genetically Modified Bioenergy Crops

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    Albert P. Kausch

    2012-10-01

    Full Text Available Advanced genetic and biotechnology tools will be required to realize the full potential of food and bioenergy crops. Given current regulatory concerns, many transgenic traits might never be deregulated for commercial release without a robust gene confinement strategy in place. The potential for transgene flow from genetically modified (GM crops is widely known. Pollen-mediated transfer is a major component of gene flow in flowering plants and therefore a potential avenue for the escape of transgenes from GM crops. One approach for preventing and/or mitigating transgene flow is the production of trait linked pollen sterility. To evaluate the feasibility of generating pollen sterility lines for gene confinement and breeding purposes we tested the utility of a promoter (Zm13Pro from a maize pollen-specific gene (Zm13 for driving expression of the reporter gene GUS and the cytotoxic gene barnase in transgenic rice (Oryza sativa ssp. Japonica cv. Nipponbare as a monocot proxy for bioenergy grasses. This study demonstrates that the Zm13 promoter can drive pollen-specific expression in stably transformed rice and may be useful for gametophytic transgene confinement and breeding strategies by pollen sterility in food and bioenergy crops.

  11. Cell based-gene delivery approaches for the treatment of spinal cord injury and neurodegenerative disorders.

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    Taha, Masoumeh Fakhr

    2010-03-01

    Cell based-gene delivery has provided an important therapeutic strategy for different disorders in the recent years. This strategy is based on the transplantation of genetically modified cells to express specific genes and to target the delivery of therapeutic factors, especially for the treatment of cancers and neurological, immunological, cardiovascular and heamatopoietic disorders. Although, preliminary reports are encouraging, and experimental studies indicate functionally and structurally improvements in the animal models of different disorders, universal application of this strategy for human diseases requires more evidence. There are a number of parameters that need to be evaluated, including the optimal cell source, the most effective gene/genes to be delivered, the optimal vector and method of gene delivery into the cells and the most efficient route for the delivery of genetically modified cells into the patient. Also, some obstacles have to be overcome, including the safety and usefulness of the approaches and the stability of the improvements. Here, recent studies concerning with the cell-based gene delivery for spinal cord injury and some neurodegenerative disorders such as amyotrophic lateral sclerosis, Parkinson's disease and Alzheimer's disease are briefly reviewed, and their exciting consequences are discussed.

  12. Gene Ontology

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    Gaston K. Mazandu

    2012-01-01

    Full Text Available The wide coverage and biological relevance of the Gene Ontology (GO, confirmed through its successful use in protein function prediction, have led to the growth in its popularity. In order to exploit the extent of biological knowledge that GO offers in describing genes or groups of genes, there is a need for an efficient, scalable similarity measure for GO terms and GO-annotated proteins. While several GO similarity measures exist, none adequately addresses all issues surrounding the design and usage of the ontology. We introduce a new metric for measuring the distance between two GO terms using the intrinsic topology of the GO-DAG, thus enabling the measurement of functional similarities between proteins based on their GO annotations. We assess the performance of this metric using a ROC analysis on human protein-protein interaction datasets and correlation coefficient analysis on the selected set of protein pairs from the CESSM online tool. This metric achieves good performance compared to the existing annotation-based GO measures. We used this new metric to assess functional similarity between orthologues, and show that it is effective at determining whether orthologues are annotated with similar functions and identifying cases where annotation is inconsistent between orthologues.

  13. Transgene traceability in transgenic mice: a bioanalytical approach for potential gene-doping analysis.

    Science.gov (United States)

    Bogani, Patrizia; Spiriti, Maria Michela; Lazzarano, Stefano; Arcangeli, Annarosa; Buiatti, Marcello; Minunni, Maria

    2011-11-01

    The World Anti-Doping Agency fears the use of gene doping to enhance athletic performances. Thus, a bioanalytical approach based on end point PCR for detecting markers' of transgenesis traceability was developed. A few sequences from two different vectors using an animal model were selected and traced in different tissues and at different times. In particular, enhanced green fluorescent protein gene and a construct-specific new marker were targeted in the analysis. To make the developed detection approach open to future routine doping analysis, matrices such as urine and tears as well blood were also tested. This study will have impact in evaluating the vector transgenes traceability for the detection of a gene doping event by non-invasive sampling.

  14. Candidate gene approach for parasite resistance in sheep--variation in immune pathway genes and association with fecal egg count.

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    Kathiravan Periasamy

    Full Text Available Sheep chromosome 3 (Oar3 has the largest number of QTLs reported to be significantly associated with resistance to gastro-intestinal nematodes. This study aimed to identify single nucleotide polymorphisms (SNPs within candidate genes located in sheep chromosome 3 as well as genes involved in major immune pathways. A total of 41 SNPs were identified across 38 candidate genes in a panel of unrelated sheep and genotyped in 713 animals belonging to 22 breeds across Asia, Europe and South America. The variations and evolution of immune pathway genes were assessed in sheep populations across these macro-environmental regions that significantly differ in the diversity and load of pathogens. The mean minor allele frequency (MAF did not vary between Asian and European sheep reflecting the absence of ascertainment bias. Phylogenetic analysis revealed two major clusters with most of South Asian, South East Asian and South West Asian breeds clustering together while European and South American sheep breeds clustered together distinctly. Analysis of molecular variance revealed strong phylogeographic structure at loci located in immune pathway genes, unlike microsatellite and genome wide SNP markers. To understand the influence of natural selection processes, SNP loci located in chromosome 3 were utilized to reconstruct haplotypes, the diversity of which showed significant deviations from selective neutrality. Reduced Median network of reconstructed haplotypes showed balancing selection in force at these loci. Preliminary association of SNP genotypes with phenotypes recorded 42 days post challenge revealed significant differences (P<0.05 in fecal egg count, body weight change and packed cell volume at two, four and six SNP loci respectively. In conclusion, the present study reports strong phylogeographic structure and balancing selection operating at SNP loci located within immune pathway genes. Further, SNP loci identified in the study were found to have

  15. Gene doping: gene delivery for olympic victory

    OpenAIRE

    Gould, David

    2012-01-01

    With one recently recommended gene therapy in Europe and a number of other gene therapy treatments now proving effective in clinical trials it is feasible that the same technologies will soon be adopted in the world of sport by unscrupulous athletes and their trainers in so called ‘gene doping’. In this article an overview of the successful gene therapy clinical trials is provided and the potential targets for gene doping are highlighted. Depending on whether a doping gene product is secreted...

  16. Serious limitations of the QTL/Microarray approach for QTL gene discovery

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    Warden Craig H

    2010-07-01

    Full Text Available Abstract Background It has been proposed that the use of gene expression microarrays in nonrecombinant parental or congenic strains can accelerate the process of isolating individual genes underlying quantitative trait loci (QTL. However, the effectiveness of this approach has not been assessed. Results Thirty-seven studies that have implemented the QTL/microarray approach in rodents were reviewed. About 30% of studies showed enrichment for QTL candidates, mostly in comparisons between congenic and background strains. Three studies led to the identification of an underlying QTL gene. To complement the literature results, a microarray experiment was performed using three mouse congenic strains isolating the effects of at least 25 biometric QTL. Results show that genes in the congenic donor regions were preferentially selected. However, within donor regions, the distribution of differentially expressed genes was homogeneous once gene density was accounted for. Genes within identical-by-descent (IBD regions were less likely to be differentially expressed in chromosome 2, but not in chromosomes 11 and 17. Furthermore, expression of QTL regulated in cis (cis eQTL showed higher expression in the background genotype, which was partially explained by the presence of single nucleotide polymorphisms (SNP. Conclusions The literature shows limited successes from the QTL/microarray approach to identify QTL genes. Our own results from microarray profiling of three congenic strains revealed a strong tendency to select cis-eQTL over trans-eQTL. IBD regions had little effect on rate of differential expression, and we provide several reasons why IBD should not be used to discard eQTL candidates. In addition, mismatch probes produced false cis-eQTL that could not be completely removed with the current strains genotypes and low probe density microarrays. The reviewed studies did not account for lack of coverage from the platforms used and therefore removed genes

  17. Integrating network, sequence and functional features using machine learning approaches towards identification of novel Alzheimer genes.

    Science.gov (United States)

    Jamal, Salma; Goyal, Sukriti; Shanker, Asheesh; Grover, Abhinav

    2016-10-18

    Alzheimer's disease (AD) is a complex progressive neurodegenerative disorder commonly characterized by short term memory loss. Presently no effective therapeutic treatments exist that can completely cure this disease. The cause of Alzheimer's is still unclear, however one of the other major factors involved in AD pathogenesis are the genetic factors and around 70 % risk of the disease is assumed to be due to the large number of genes involved. Although genetic association studies have revealed a number of potential AD susceptibility genes, there still exists a need for identification of unidentified AD-associated genes and therapeutic targets to have better understanding of the disease-causing mechanisms of Alzheimer's towards development of effective AD therapeutics. In the present study, we have used machine learning approach to identify candidate AD associated genes by integrating topological properties of the genes from the protein-protein interaction networks, sequence features and functional annotations. We also used molecular docking approach and screened already known anti-Alzheimer drugs against the novel predicted probable targets of AD and observed that an investigational drug, AL-108, had high affinity for majority of the possible therapeutic targets. Furthermore, we performed molecular dynamics simulations and MM/GBSA calculations on the docked complexes to validate our preliminary findings. To the best of our knowledge, this is the first comprehensive study of its kind for identification of putative Alzheimer-associated genes using machine learning approaches and we propose that such computational studies can improve our understanding on the core etiology of AD which could lead to the development of effective anti-Alzheimer drugs.

  18. Gene prediction in metagenomic fragments: A large scale machine learning approach

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    Morgenstern Burkhard

    2008-04-01

    Full Text Available Abstract Background Metagenomics is an approach to the characterization of microbial genomes via the direct isolation of genomic sequences from the environment without prior cultivation. The amount of metagenomic sequence data is growing fast while computational methods for metagenome analysis are still in their infancy. In contrast to genomic sequences of single species, which can usually be assembled and analyzed by many available methods, a large proportion of metagenome data remains as unassembled anonymous sequencing reads. One of the aims of all metagenomic sequencing projects is the identification of novel genes. Short length, for example, Sanger sequencing yields on average 700 bp fragments, and unknown phylogenetic origin of most fragments require approaches to gene prediction that are different from the currently available methods for genomes of single species. In particular, the large size of metagenomic samples requires fast and accurate methods with small numbers of false positive predictions. Results We introduce a novel gene prediction algorithm for metagenomic fragments based on a two-stage machine learning approach. In the first stage, we use linear discriminants for monocodon usage, dicodon usage and translation initiation sites to extract features from DNA sequences. In the second stage, an artificial neural network combines these features with open reading frame length and fragment GC-content to compute the probability that this open reading frame encodes a protein. This probability is used for the classification and scoring of gene candidates. With large scale training, our method provides fast single fragment predictions with good sensitivity and specificity on artificially fragmented genomic DNA. Additionally, this method is able to predict translation initiation sites accurately and distinguishes complete from incomplete genes with high reliability. Conclusion Large scale machine learning methods are well-suited for gene

  19. Functional Associations by Response Overlap (FARO, a functional genomics approach matching gene expression phenotypes.

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    Henrik Bjørn Nielsen

    2007-08-01

    Full Text Available The systematic comparison of transcriptional responses of organisms is a powerful tool in functional genomics. For example, mutants may be characterized by comparing their transcript profiles to those obtained in other experiments querying the effects on gene expression of many experimental factors including treatments, mutations and pathogen infections. Similarly, drugs may be discovered by the relationship between the transcript profiles effectuated or impacted by a candidate drug and by the target disease. The integration of such data enables systems biology to predict the interplay between experimental factors affecting a biological system. Unfortunately, direct comparisons of gene expression profiles obtained in independent, publicly available microarray experiments are typically compromised by substantial, experiment-specific biases. Here we suggest a novel yet conceptually simple approach for deriving 'Functional Association(s by Response Overlap' (FARO between microarray gene expression studies. The transcriptional response is defined by the set of differentially expressed genes independent from the magnitude or direction of the change. This approach overcomes the limited comparability between studies that is typical for methods that rely on correlation in gene expression. We apply FARO to a compendium of 242 diverse Arabidopsis microarray experimental factors, including phyto-hormones, stresses and pathogens, growth conditions/stages, tissue types and mutants. We also use FARO to confirm and further delineate the functions of Arabidopsis MAP kinase 4 in disease and stress responses. Furthermore, we find that a large, well-defined set of genes responds in opposing directions to different stress conditions and predict the effects of different stress combinations. This demonstrates the usefulness of our approach for exploiting public microarray data to derive biologically meaningful associations between experimental factors. Finally, our

  20. An approach for reduction of false predictions in reverse engineering of gene regulatory networks.

    Science.gov (United States)

    Khan, Abhinandan; Saha, Goutam; Pal, Rajat Kumar

    2018-05-14

    A gene regulatory network discloses the regulatory interactions amongst genes, at a particular condition of the human body. The accurate reconstruction of such networks from time-series genetic expression data using computational tools offers a stiff challenge for contemporary computer scientists. This is crucial to facilitate the understanding of the proper functioning of a living organism. Unfortunately, the computational methods produce many false predictions along with the correct predictions, which is unwanted. Investigations in the domain focus on the identification of as many correct regulations as possible in the reverse engineering of gene regulatory networks to make it more reliable and biologically relevant. One way to achieve this is to reduce the number of incorrect predictions in the reconstructed networks. In the present investigation, we have proposed a novel scheme to decrease the number of false predictions by suitably combining several metaheuristic techniques. We have implemented the same using a dataset ensemble approach (i.e. combining multiple datasets) also. We have employed the proposed methodology on real-world experimental datasets of the SOS DNA Repair network of Escherichia coli and the IMRA network of Saccharomyces cerevisiae. Subsequently, we have experimented upon somewhat larger, in silico networks, namely, DREAM3 and DREAM4 Challenge networks, and 15-gene and 20-gene networks extracted from the GeneNetWeaver database. To study the effect of multiple datasets on the quality of the inferred networks, we have used four datasets in each experiment. The obtained results are encouraging enough as the proposed methodology can reduce the number of false predictions significantly, without using any supplementary prior biological information for larger gene regulatory networks. It is also observed that if a small amount of prior biological information is incorporated here, the results improve further w.r.t. the prediction of true positives

  1. Efficacious and safe tissue-selective controlled gene therapy approaches for the cornea.

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    Rajiv R Mohan

    2011-04-01

    Full Text Available Untargeted and uncontrolled gene delivery is a major cause of gene therapy failure. This study aimed to define efficient and safe tissue-selective targeted gene therapy approaches for delivering genes into keratocytes of the cornea in vivo using a normal or diseased rabbit model. New Zealand White rabbits, adeno-associated virus serotype 5 (AAV5, and a minimally invasive hair-dryer based vector-delivery technique were used. Fifty microliters of AAV5 titer (6.5×10(12 vg/ml expressing green fluorescent protein gene (GFP was topically applied onto normal or diseased (fibrotic or neovascularized rabbit corneas for 2-minutes with a custom vector-delivery technique. Corneal fibrosis and neovascularization in rabbit eyes were induced with photorefractive keratectomy using excimer laser and VEGF (630 ng using micropocket assay, respectively. Slit-lamp biomicroscopy and immunocytochemistry were used to confirm fibrosis and neovascularization in rabbit corneas. The levels, location and duration of delivered-GFP gene expression in the rabbit stroma were measured with immunocytochemistry and/or western blotting. Slot-blot measured delivered-GFP gene copy number. Confocal microscopy performed in whole-mounts of cornea and thick corneal sections determined geometric and spatial localization of delivered-GFP in three-dimensional arrangement. AAV5 toxicity and safety were evaluated with clinical eye exam, stereomicroscopy, slit-lamp biomicroscopy, and H&E staining. A single 2-minute AAV5 topical application via custom delivery-technique efficiently and selectively transduced keratocytes in the anterior stroma of normal and diseased rabbit corneas as evident from immunocytochemistry and confocal microscopy. Transgene expression was first detected at day 3, peaked at day 7, and was maintained up to 16 weeks (longest tested time point. Clinical and slit-lamp eye examination in live rabbits and H&E staining did not reveal any significant changes between AAV5

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

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    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

  3. Genes and Hearing Loss

    Science.gov (United States)

    ... ENTCareers Marketplace Find an ENT Doctor Near You Genes and Hearing Loss Genes and Hearing Loss Patient ... mutation may only have dystopia canthorum. How Do Genes Work? Genes are a road map for the ...

  4. A New Two-Step Approach for Hands-On Teaching of Gene Technology: Effects on Students' Activities during Experimentation in an Outreach Gene Technology Lab

    Science.gov (United States)

    Scharfenberg, Franz-Josef; Bogner, Franz X.

    2011-01-01

    Emphasis on improving higher level biology education continues. A new two-step approach to the experimental phases within an outreach gene technology lab, derived from cognitive load theory, is presented. We compared our approach using a quasi-experimental design with the conventional one-step mode. The difference consisted of additional focused…

  5. History of gene therapy.

    Science.gov (United States)

    Wirth, Thomas; Parker, Nigel; Ylä-Herttuala, Seppo

    2013-08-10

    Two decades after the initial gene therapy trials and more than 1700 approved clinical trials worldwide we not only have gained much new information and knowledge regarding gene therapy in general, but also learned to understand the concern that has persisted in society. Despite the setbacks gene therapy has faced, success stories have increasingly emerged. Examples for these are the positive recommendation for a gene therapy product (Glybera) by the EMA for approval in the European Union and the positive trials for the treatment of ADA deficiency, SCID-X1 and adrenoleukodystrophy. Nevertheless, our knowledge continues to grow and during the course of time more safety data has become available that helps us to develop better gene therapy approaches. Also, with the increased understanding of molecular medicine, we have been able to develop more specific and efficient gene transfer vectors which are now producing clinical results. In this review, we will take a historical view and highlight some of the milestones that had an important impact on the development of gene therapy. We will also discuss briefly the safety and ethical aspects of gene therapy and address some concerns that have been connected with gene therapy as an important therapeutic modality. Copyright © 2013 Elsevier B.V. All rights reserved.

  6. Refining discordant gene trees.

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    Górecki, Pawel; Eulenstein, Oliver

    2014-01-01

    Evolutionary studies are complicated by discordance between gene trees and the species tree in which they evolved. Dealing with discordant trees often relies on comparison costs between gene and species trees, including the well-established Robinson-Foulds, gene duplication, and deep coalescence costs. While these costs have provided credible results for binary rooted gene trees, corresponding cost definitions for non-binary unrooted gene trees, which are frequently occurring in practice, are challenged by biological realism. We propose a natural extension of the well-established costs for comparing unrooted and non-binary gene trees with rooted binary species trees using a binary refinement model. For the duplication cost we describe an efficient algorithm that is based on a linear time reduction and also computes an optimal rooted binary refinement of the given gene tree. Finally, we show that similar reductions lead to solutions for computing the deep coalescence and the Robinson-Foulds costs. Our binary refinement of Robinson-Foulds, gene duplication, and deep coalescence costs for unrooted and non-binary gene trees together with the linear time reductions provided here for computing these costs significantly extends the range of trees that can be incorporated into approaches dealing with discordance.

  7. A re-assessment of gene-tag classification approaches for describing var gene expression patterns during human Plasmodium falciparum malaria parasite infections.

    Science.gov (United States)

    Githinji, George; Bull, Peter C

    2017-01-01

    PfEMP1 are variant parasite antigens that are inserted on the surface of Plasmodium falciparum infected erythrocytes (IE). Through interactions with various host molecules, PfEMP1 mediate IE sequestration in tissues and play a key role in the pathology of severe malaria. PfEMP1 is encoded by a diverse multi-gene family called var . Previous studies have shown that that expression of specific subsets of var genes are associated with low levels of host immunity and severe malaria. However, in most clinical studies to date, full-length var gene sequences were unavailable and various approaches have been used to make comparisons between var gene expression profiles in different parasite isolates using limited information. Several studies have relied on the classification of a 300 - 500 base-pair "DBLα tag" region in the DBLα domain located at the 5' end of most var genes. We assessed the relationship between various DBLα tag classification methods, and sequence features that are only fully assessable through full-length var gene sequences. We compared these different sequence features in full-length var gene from six fully sequenced laboratory isolates. These comparisons show that despite a long history of recombination,   DBLα sequence tag classification can provide functional information on important features of full-length var genes. Notably, a specific subset of DBLα tags previously defined as "group A-like" is associated with CIDRα1 domains proposed to bind to endothelial protein C receptor. This analysis helps to bring together different sources of data that have been used to assess var gene expression in clinical parasite isolates.

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

    Science.gov (United States)

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

    2015-02-01

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

  9. Bioinformatics approach of three partial polyprenol reductase genes in Kandelia obovata

    Science.gov (United States)

    Basyuni, M.; Wati, R.; Sagami, H.; Oku, H.; Baba, S.

    2018-03-01

    This present study describesthe bioinformatics approach to analyze three partial polyprenol reductase genes from mangrove plant, Kandeliaobovataas well aspredictedphysical and chemical properties, potential peptide, subcellular localization, and phylogenetic. The diversity was noted in the physical and chemical properties of three partial polyprenol reductase genes. The values of chloroplast were relatively high, showed that chloroplast transit peptide occurred in mangrove polyprenol reductase. The target peptide value of mitochondria varied from 0.088 to 0.198 indicated it was possible to be present. These results suggested the importance of understanding the diversity of physicochemical properties of the different amino acids in polyprenol reductase. The subcellular localization of two partial genes located in the plasma membrane. To confirm the homology among the polyprenol reductase in the database, a dendrogram was drawn. The phylogenetic tree depicts that there are three clusters, the partial genes of K. obovata joined the largest one: C23157 was close to Ricinus communis polyprenol reductase. Whereas, C23901 and C24171 were grouped with Ipomoea nil polyprenol reductase, suggested that these polyprenol reductase genes form distinct separation into tropical habitat plants.

  10. A new approach to enhance the performance of decision tree for classifying gene expression data.

    Science.gov (United States)

    Hassan, Md; Kotagiri, Ramamohanarao

    2013-12-20

    Gene expression data classification is a challenging task due to the large dimensionality and very small number of samples. Decision tree is one of the popular machine learning approaches to address such classification problems. However, the existing decision tree algorithms use a single gene feature at each node to split the data into its child nodes and hence might suffer from poor performance specially when classifying gene expression dataset. By using a new decision tree algorithm where, each node of the tree consists of more than one gene, we enhance the classification performance of traditional decision tree classifiers. Our method selects suitable genes that are combined using a linear function to form a derived composite feature. To determine the structure of the tree we use the area under the Receiver Operating Characteristics curve (AUC). Experimental analysis demonstrates higher classification accuracy using the new decision tree compared to the other existing decision trees in literature. We experimentally compare the effect of our scheme against other well known decision tree techniques. Experiments show that our algorithm can substantially boost the classification performance of the decision tree.

  11. Clustering approaches to identifying gene expression patterns from DNA microarray data.

    Science.gov (United States)

    Do, Jin Hwan; Choi, Dong-Kug

    2008-04-30

    The analysis of microarray data is essential for large amounts of gene expression data. In this review we focus on clustering techniques. The biological rationale for this approach is the fact that many co-expressed genes are co-regulated, and identifying co-expressed genes could aid in functional annotation of novel genes, de novo identification of transcription factor binding sites and elucidation of complex biological pathways. Co-expressed genes are usually identified in microarray experiments by clustering techniques. There are many such methods, and the results obtained even for the same datasets may vary considerably depending on the algorithms and metrics for dissimilarity measures used, as well as on user-selectable parameters such as desired number of clusters and initial values. Therefore, biologists who want to interpret microarray data should be aware of the weakness and strengths of the clustering methods used. In this review, we survey the basic principles of clustering of DNA microarray data from crisp clustering algorithms such as hierarchical clustering, K-means and self-organizing maps, to complex clustering algorithms like fuzzy clustering.

  12. An Approach for Predicting Essential Genes Using Multiple Homology Mapping and Machine Learning Algorithms.

    Science.gov (United States)

    Hua, Hong-Li; Zhang, Fa-Zhan; Labena, Abraham Alemayehu; Dong, Chuan; Jin, Yan-Ting; Guo, Feng-Biao

    Investigation of essential genes is significant to comprehend the minimal gene sets of cell and discover potential drug targets. In this study, a novel approach based on multiple homology mapping and machine learning method was introduced to predict essential genes. We focused on 25 bacteria which have characterized essential genes. The predictions yielded the highest area under receiver operating characteristic (ROC) curve (AUC) of 0.9716 through tenfold cross-validation test. Proper features were utilized to construct models to make predictions in distantly related bacteria. The accuracy of predictions was evaluated via the consistency of predictions and known essential genes of target species. The highest AUC of 0.9552 and average AUC of 0.8314 were achieved when making predictions across organisms. An independent dataset from Synechococcus elongatus , which was released recently, was obtained for further assessment of the performance of our model. The AUC score of predictions is 0.7855, which is higher than other methods. This research presents that features obtained by homology mapping uniquely can achieve quite great or even better results than those integrated features. Meanwhile, the work indicates that machine learning-based method can assign more efficient weight coefficients than using empirical formula based on biological knowledge.

  13. Experimental and Modeling Approaches for Understanding the Effect of Gene Expression Noise in Biological Development

    Directory of Open Access Journals (Sweden)

    David M. Holloway

    2018-04-01

    Full Text Available Biological development involves numerous chemical and physical processes which must act in concert to reliably produce a cell, a tissue, or a body. To be successful, the developing organism must be robust to variability at many levels, such as the environment (e.g., temperature, moisture, upstream information (such as long-range positional information gradients, or intrinsic noise due to the stochastic nature of low concentration chemical kinetics. The latter is especially relevant to the regulation of gene expression in cell differentiation. The temporal stochasticity of gene expression has been studied in single celled organisms for nearly two decades, but only recently have techniques become available to gather temporally-resolved data across spatially-distributed gene expression patterns in developing multicellular organisms. These demonstrate temporal noisy “bursting” in the number of gene transcripts per cell, raising the question of how the transcript number defining a particular cell type is produced, such that one cell type can reliably be distinguished from a neighboring cell of different type along a tissue boundary. Stochastic spatio-temporal modeling of tissue-wide expression patterns can identify signatures for specific types of gene regulation, which can be used to extract regulatory mechanism information from experimental time series. This Perspective focuses on using this type of approach to study gene expression noise during the anterior-posterior segmentation of the fruit fly embryo. Advances in experimental and theoretical techniques will lead to an increasing quantification of expression noise that can be used to understand how regulatory mechanisms contribute to embryonic robustness across a range of developmental processes.

  14. Systems Pharmacology-Based Approach of Connecting Disease Genes in Genome-Wide Association Studies with Traditional Chinese Medicine.

    Science.gov (United States)

    Kim, Jihye; Yoo, Minjae; Shin, Jimin; Kim, Hyunmin; Kang, Jaewoo; Tan, Aik Choon

    2018-01-01

    Traditional Chinese medicine (TCM) originated in ancient China has been practiced over thousands of years for treating various symptoms and diseases. However, the molecular mechanisms of TCM in treating these diseases remain unknown. In this study, we employ a systems pharmacology-based approach for connecting GWAS diseases with TCM for potential drug repurposing and repositioning. We studied 102 TCM components and their target genes by analyzing microarray gene expression experiments. We constructed disease-gene networks from 2558 GWAS studies. We applied a systems pharmacology approach to prioritize disease-target genes. Using this bioinformatics approach, we analyzed 14,713 GWAS disease-TCM-target gene pairs and identified 115 disease-gene pairs with q value < 0.2. We validated several of these GWAS disease-TCM-target gene pairs with literature evidence, demonstrating that this computational approach could reveal novel indications for TCM. We also develop TCM-Disease web application to facilitate the traditional Chinese medicine drug repurposing efforts. Systems pharmacology is a promising approach for connecting GWAS diseases with TCM for potential drug repurposing and repositioning. The computational approaches described in this study could be easily expandable to other disease-gene network analysis.

  15. From Genes to Ecosystems in Microbiology: Modeling Approaches and the Importance of Individuality

    Directory of Open Access Journals (Sweden)

    Jan-Ulrich Kreft

    2017-11-01

    Full Text Available Models are important tools in microbial ecology. They can be used to advance understanding by helping to interpret observations and test hypotheses, and to predict the effects of ecosystem management actions or a different climate. Over the past decades, biological knowledge and ecosystem observations have advanced to the molecular and in particular gene level. However, microbial ecology models have changed less and a current challenge is to make them utilize the knowledge and observations at the genetic level. We review published models that explicitly consider genes and make predictions at the population or ecosystem level. The models can be grouped into three general approaches, i.e., metabolic flux, gene-centric and agent-based. We describe and contrast these approaches by applying them to a hypothetical ecosystem and discuss their strengths and weaknesses. An important distinguishing feature is how variation between individual cells (individuality is handled. In microbial ecosystems, individual heterogeneity is generated by a number of mechanisms including stochastic interactions of molecules (e.g., gene expression, stochastic and deterministic cell division asymmetry, small-scale environmental heterogeneity, and differential transport in a heterogeneous environment. This heterogeneity can then be amplified and transferred to other cell properties by several mechanisms, including nutrient uptake, metabolism and growth, cell cycle asynchronicity and the effects of age and damage. For example, stochastic gene expression may lead to heterogeneity in nutrient uptake enzyme levels, which in turn results in heterogeneity in intracellular nutrient levels. Individuality can have important ecological consequences, including division of labor, bet hedging, aging and sub-optimality. Understanding the importance of individuality and the mechanism(s underlying it for the specific microbial system and question investigated is essential for selecting the

  16. A Combinatory Approach for Selecting Prognostic Genes in Microarray Studies of Tumour Survivals

    Directory of Open Access Journals (Sweden)

    Qihua Tan

    2009-01-01

    Full Text Available Different from significant gene expression analysis which looks for genes that are differentially regulated, feature selection in the microarray-based prognostic gene expression analysis aims at finding a subset of marker genes that are not only differentially expressed but also informative for prediction. Unfortunately feature selection in literature of microarray study is predominated by the simple heuristic univariate gene filter paradigm that selects differentially expressed genes according to their statistical significances. We introduce a combinatory feature selection strategy that integrates differential gene expression analysis with the Gram-Schmidt process to identify prognostic genes that are both statistically significant and highly informative for predicting tumour survival outcomes. Empirical application to leukemia and ovarian cancer survival data through-within- and cross-study validations shows that the feature space can be largely reduced while achieving improved testing performances.

  17. A systems genetics approach identifies genes and pathways for type 2 diabetes in human islets

    DEFF Research Database (Denmark)

    Taneera, Jalal; Lang, Stefan; Sharma, Amitabh

    2012-01-01

    Close to 50 genetic loci have been associated with type 2 diabetes (T2D), but they explain only 15% of the heritability. In an attempt to identify additional T2D genes, we analyzed global gene expression in human islets from 63 donors. Using 48 genes located near T2D risk variants, we identified ...

  18. A surgical approach appropriate for targeted cochlear gene therapy in the mouse.

    Science.gov (United States)

    Jero, J; Tseng, C J; Mhatre, A N; Lalwani, A K

    2001-01-01

    Therapeutic manipulations of the mammalian cochlea, including cochlear gene transfer, have been predominantly studied using the guinea pig as the experimental model. With the significant developments in mouse genomics and the availability of mutant strains of mice with well-characterized hearing loss, the mouse justifiably will be the preferred animal model for therapeutic manipulations. However, the potential advantages of the mouse model have not been fully realized due to the surgical difficulty of accessing its small cochlea. This study describes a ventral approach, instead of the routinely used postauricular approach in other rodents, for accessing the mouse middle and inner ear, and its application in cochlear gene transfer. This ventral approach enabled rapid and direct delivery of liposome-transgene complex to the mouse inner ear while avoiding blood loss, facial nerve morbidity, and mortality. Transgene expression at 3 days was detected in Reissner's membrane, spiral limbus, spiral ligament, and spiral ganglion cells, in a pattern similar to that previously described in the guinea pig. The successful access and delivery of material to the mouse cochlea and the replication of gene expression seen in the guinea pig demonstrated in this study should promote the use of the mouse in future studies investigating targeted cochlear therapy.

  19. Radionuclide reporter gene imaging for cardiac gene therapy

    International Nuclear Information System (INIS)

    Inubushi, Masayuki; Tamaki, Nagara

    2007-01-01

    In the field of cardiac gene therapy, angiogenic gene therapy has been most extensively investigated. The first clinical trial of cardiac angiogenic gene therapy was reported in 1998, and at the peak, more than 20 clinical trial protocols were under evaluation. However, most trials have ceased owing to the lack of decisive proof of therapeutic effects and the potential risks of viral vectors. In order to further advance cardiac angiogenic gene therapy, remaining open issues need to be resolved: there needs to be improvement of gene transfer methods, regulation of gene expression, development of much safer vectors and optimisation of therapeutic genes. For these purposes, imaging of gene expression in living organisms is of great importance. In radionuclide reporter gene imaging, ''reporter genes'' transferred into cell nuclei encode for a protein that retains a complementary ''reporter probe'' of a positron or single-photon emitter; thus expression of the reporter genes can be imaged with positron emission tomography or single-photon emission computed tomography. Accordingly, in the setting of gene therapy, the location, magnitude and duration of the therapeutic gene co-expression with the reporter genes can be monitored non-invasively. In the near future, gene therapy may evolve into combination therapy with stem/progenitor cell transplantation, so-called cell-based gene therapy or gene-modified cell therapy. Radionuclide reporter gene imaging is now expected to contribute in providing evidence on the usefulness of this novel therapeutic approach, as well as in investigating the molecular mechanisms underlying neovascularisation and safety issues relevant to further progress in conventional gene therapy. (orig.)

  20. Suicide genes or p53 gene and p53 target genes as targets for cancer gene therapy by ionizing radiation

    International Nuclear Information System (INIS)

    Liu Bing; Chinese Academy of Sciences, Beijing; Zhang Hong

    2005-01-01

    Radiotherapy has some disadvantages due to the severe side-effect on the normal tissues at a curative dose of ionizing radiation (IR). Similarly, as a new developing approach, gene therapy also has some disadvantages, such as lack of specificity for tumors, limited expression of therapeutic gene, potential biological risk. To certain extent, above problems would be solved by the suicide genes or p53 gene and its target genes therapies targeted by ionizing radiation. This strategy not only makes up the disadvantage from radiotherapy or gene therapy alone, but also promotes success rate on the base of lower dose. By present, there have been several vectors measuring up to be reaching clinical trials. This review focused on the development of the cancer gene therapy through suicide genes or p53 and its target genes mediated by IR. (authors)

  1. So many genes, so little time: A practical approach to divergence-time estimation in the genomic era.

    Science.gov (United States)

    Smith, Stephen A; Brown, Joseph W; Walker, Joseph F

    2018-01-01

    Phylogenomic datasets have been successfully used to address questions involving evolutionary relationships, patterns of genome structure, signatures of selection, and gene and genome duplications. However, despite the recent explosion in genomic and transcriptomic data, the utility of these data sources for efficient divergence-time inference remains unexamined. Phylogenomic datasets pose two distinct problems for divergence-time estimation: (i) the volume of data makes inference of the entire dataset intractable, and (ii) the extent of underlying topological and rate heterogeneity across genes makes model mis-specification a real concern. "Gene shopping", wherein a phylogenomic dataset is winnowed to a set of genes with desirable properties, represents an alternative approach that holds promise in alleviating these issues. We implemented an approach for phylogenomic datasets (available in SortaDate) that filters genes by three criteria: (i) clock-likeness, (ii) reasonable tree length (i.e., discernible information content), and (iii) least topological conflict with a focal species tree (presumed to have already been inferred). Such a winnowing procedure ensures that errors associated with model (both clock and topology) mis-specification are minimized, therefore reducing error in divergence-time estimation. We demonstrated the efficacy of this approach through simulation and applied it to published animal (Aves, Diplopoda, and Hymenoptera) and plant (carnivorous Caryophyllales, broad Caryophyllales, and Vitales) phylogenomic datasets. By quantifying rate heterogeneity across both genes and lineages we found that every empirical dataset examined included genes with clock-like, or nearly clock-like, behavior. Moreover, many datasets had genes that were clock-like, exhibited reasonable evolutionary rates, and were mostly compatible with the species tree. We identified overlap in age estimates when analyzing these filtered genes under strict clock and uncorrelated

  2. Snapshot of the Eukaryotic Gene Expression in Muskoxen Rumen—A Metatranscriptomic Approach

    Science.gov (United States)

    O'Toole, Nicholas; Barboza, Perry S.; Ungerfeld, Emilio; Leigh, Mary Beth; Selinger, L. Brent; Butler, Greg; Tsang, Adrian; McAllister, Tim A.; Forster, Robert J.

    2011-01-01

    Background Herbivores rely on digestive tract lignocellulolytic microorganisms, including bacteria, fungi and protozoa, to derive energy and carbon from plant cell wall polysaccharides. Culture independent metagenomic studies have been used to reveal the genetic content of the bacterial species within gut microbiomes. However, the nature of the genes encoded by eukaryotic protozoa and fungi within these environments has not been explored using metagenomic or metatranscriptomic approaches. Methodology/Principal Findings In this study, a metatranscriptomic approach was used to investigate the functional diversity of the eukaryotic microorganisms within the rumen of muskoxen (Ovibos moschatus), with a focus on plant cell wall degrading enzymes. Polyadenylated RNA (mRNA) was sequenced on the Illumina Genome Analyzer II system and 2.8 gigabases of sequences were obtained and 59129 contigs assembled. Plant cell wall degrading enzyme modules including glycoside hydrolases, carbohydrate esterases and polysaccharide lyases were identified from over 2500 contigs. These included a number of glycoside hydrolase family 6 (GH6), GH48 and swollenin modules, which have rarely been described in previous gut metagenomic studies. Conclusions/Significance The muskoxen rumen metatranscriptome demonstrates a much higher percentage of cellulase enzyme discovery and an 8.7x higher rate of total carbohydrate active enzyme discovery per gigabase of sequence than previous rumen metagenomes. This study provides a snapshot of eukaryotic gene expression in the muskoxen rumen, and identifies a number of candidate genes coding for potentially valuable lignocellulolytic enzymes. PMID:21655220

  3. Improvements in algal lipid production: a systems biology and gene editing approach.

    Science.gov (United States)

    Banerjee, Avik; Banerjee, Chiranjib; Negi, Sangeeta; Chang, Jo-Shu; Shukla, Pratyoosh

    2018-05-01

    In the wake of rising energy demands, microalgae have emerged as potential sources of sustainable and renewable carbon-neutral fuels, such as bio-hydrogen and bio-oil. For rational metabolic engineering, the elucidation of metabolic pathways in fine detail and their manipulation according to requirements is the key to exploiting the use of microalgae. Emergence of site-specific nucleases have revolutionized applied research leading to biotechnological gains. Genome engineering as well as modulation of the endogenous genome with high precision using CRISPR systems is being gradually employed in microalgal research. Further, to optimize and produce better algal platforms, use of systems biology network analysis and integration of omics data is required. This review discusses two important approaches: systems biology and gene editing strategies used on microalgal systems with a focus on biofuel production and sustainable solutions. It also emphasizes that the integration of such systems would contribute and compliment applied research on microalgae. Recent advances in microalgae are discussed, including systems biology, gene editing approaches in lipid bio-synthesis, and antenna engineering. Lastly, it has been attempted here to showcase how CRISPR/Cas systems are a better editing tool than existing techniques that can be utilized for gene modulation and engineering during biofuel production.

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

    Directory of Open Access Journals (Sweden)

    Meng Qi

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

  5. Ratiometric Gas Reporting: A Nondisruptive Approach To Monitor Gene Expression in Soils.

    Science.gov (United States)

    Cheng, Hsiao-Ying; Masiello, Caroline A; Del Valle, Ilenne; Gao, Xiaodong; Bennett, George N; Silberg, Jonathan J

    2018-03-16

    Fluorescent proteins are ubiquitous tools that are used to monitor the dynamic functions of natural and synthetic genetic circuits. However, these visual reporters can only be used in transparent settings, a limitation that complicates nondisruptive measurements of gene expression within many matrices, such as soils and sediments. We describe a new ratiometric gas reporting method for nondisruptively monitoring gene expression within hard-to-image environmental matrices. With this approach, C 2 H 4 is continuously synthesized by ethylene forming enzyme to provide information on viable cell number, and CH 3 Br is conditionally synthesized by placing a methyl halide transferase gene under the control of a conditional promoter. We show that ratiometric gas reporting enables the creation of Escherichia coli biosensors that report on acylhomoserine lactone (AHL) autoinducers used for quorum sensing by Gram-negative bacteria. Using these biosensors, we find that an agricultural soil decreases the bioavailable concentration of a long-chain AHL up to 100-fold. We also demonstrate that these biosensors can be used in soil to nondisruptively monitor AHLs synthesized by Rhizobium leguminosarum and degraded by Bacillus thuringiensis. Finally, we show that this new reporting approach can be used in Shewanella oneidensis, a bacterium that lives in sediments.

  6. A novel approach to simulate gene-environment interactions in complex diseases

    Directory of Open Access Journals (Sweden)

    Nicodemi Mario

    2010-01-01

    Full Text Available Abstract Background Complex diseases are multifactorial traits caused by both genetic and environmental factors. They represent the major part of human diseases and include those with largest prevalence and mortality (cancer, heart disease, obesity, etc.. Despite a large amount of information that has been collected about both genetic and environmental risk factors, there are few examples of studies on their interactions in epidemiological literature. One reason can be the incomplete knowledge of the power of statistical methods designed to search for risk factors and their interactions in these data sets. An improvement in this direction would lead to a better understanding and description of gene-environment interactions. To this aim, a possible strategy is to challenge the different statistical methods against data sets where the underlying phenomenon is completely known and fully controllable, for example simulated ones. Results We present a mathematical approach that models gene-environment interactions. By this method it is possible to generate simulated populations having gene-environment interactions of any form, involving any number of genetic and environmental factors and also allowing non-linear interactions as epistasis. In particular, we implemented a simple version of this model in a Gene-Environment iNteraction Simulator (GENS, a tool designed to simulate case-control data sets where a one gene-one environment interaction influences the disease risk. The main aim has been to allow the input of population characteristics by using standard epidemiological measures and to implement constraints to make the simulator behaviour biologically meaningful. Conclusions By the multi-logistic model implemented in GENS it is possible to simulate case-control samples of complex disease where gene-environment interactions influence the disease risk. The user has full control of the main characteristics of the simulated population and a Monte

  7. In-Silico Integration Approach to Identify a Key miRNA Regulating a Gene Network in Aggressive Prostate Cancer

    Science.gov (United States)

    Colaprico, Antonio; Bontempi, Gianluca; Castiglioni, Isabella

    2018-01-01

    Like other cancer diseases, prostate cancer (PC) is caused by the accumulation of genetic alterations in the cells that drives malignant growth. These alterations are revealed by gene profiling and copy number alteration (CNA) analysis. Moreover, recent evidence suggests that also microRNAs have an important role in PC development. Despite efforts to profile PC, the alterations (gene, CNA, and miRNA) and biological processes that correlate with disease development and progression remain partially elusive. Many gene signatures proposed as diagnostic or prognostic tools in cancer poorly overlap. The identification of co-expressed genes, that are functionally related, can identify a core network of genes associated with PC with a better reproducibility. By combining different approaches, including the integration of mRNA expression profiles, CNAs, and miRNA expression levels, we identified a gene signature of four genes overlapping with other published gene signatures and able to distinguish, in silico, high Gleason-scored PC from normal human tissue, which was further enriched to 19 genes by gene co-expression analysis. From the analysis of miRNAs possibly regulating this network, we found that hsa-miR-153 was highly connected to the genes in the network. Our results identify a four-gene signature with diagnostic and prognostic value in PC and suggest an interesting gene network that could play a key regulatory role in PC development and progression. Furthermore, hsa-miR-153, controlling this network, could be a potential biomarker for theranostics in high Gleason-scored PC. PMID:29562723

  8. Stochastic Boolean networks: An efficient approach to modeling gene regulatory networks

    Directory of Open Access Journals (Sweden)

    Liang Jinghang

    2012-08-01

    network inferred from a T cell immune response dataset. An SBN can also implement the function of an asynchronous PBN and is potentially useful in a hybrid approach in combination with a continuous or single-molecule level stochastic model. Conclusions Stochastic Boolean networks (SBNs are proposed as an efficient approach to modelling gene regulatory networks (GRNs. The SBN approach is able to recover biologically-proven regulatory behaviours, such as the oscillatory dynamics of the p53-Mdm2 network and the dynamic attractors in a T cell immune response network. The proposed approach can further predict the network dynamics when the genes are under perturbation, thus providing biologically meaningful insights for a better understanding of the dynamics of GRNs. The algorithms and methods described in this paper have been implemented in Matlab packages, which are attached as Additional files.

  9. Genetic Approaches to Study Meiosis and Meiosis-Specific Gene Expression in Saccharomyces cerevisiae.

    Science.gov (United States)

    Kassir, Yona; Stuart, David T

    2017-01-01

    The budding yeast Saccharomyces cerevisiae has a long history as a model organism for studies of meiosis and the cell cycle. The popularity of this yeast as a model is in large part due to the variety of genetic and cytological approaches that can be effectively performed with the cells. Cultures of the cells can be induced to synchronously progress through meiosis and sporulation allowing large-scale gene expression and biochemical studies to be performed. Additionally, the spore tetrads resulting from meiosis make it possible to characterize the haploid products of meiosis allowing investigation of meiotic recombination and chromosome segregation. Here we describe genetic methods for analysis progression of S. cerevisiae through meiosis and sporulation with an emphasis on strategies for the genetic analysis of regulators of meiosis-specific genes.

  10. Identification and Analysis of Jasmonate Pathway Genes in Coffea canephora (Robusta Coffee) by In Silico Approach.

    Science.gov (United States)

    Bharathi, Kosaraju; Sreenath, H L

    2017-07-01

    bioinformatic approaches confirming the conserved nature of the pathway in coffee. The findings are useful to understand the defense mechanisms of C. canephora and coffee breeding in the long run. JA is a plant hormone that plays an important role in plant defense against insect pests. Genes coding for the 4 key enzymes involved in the production of JA viz., LOX, AOS, AOC and OPR were identified and analyzed in C. canephora (robusta coffee) by in silico approach. The study has confirmed the conserved nature of JA pathway in coffee; the findings are useful to further explore the defense mechanisms of coffee plants. Abbreviations used: C. canephora : Coffea canephora ; C. arabica : Coffea arabica ; JA: Jasmonic acid; CGH: Coffee Genome Hub; NCBI: National Centre for Biotechnology Information; BLAST: Basic Local Alignment Search Tool; A. thaliana : Arabidopsis thaliana ; LOX: Lipoxygenase, AOS: Allene oxide synthase; AOC: Allene oxide cyclase; OPR: 12 oxo phytodienoic reductase.

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

    Directory of Open Access Journals (Sweden)

    Song Cai

    2011-07-01

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

  12. 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

  13. 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

  14. A data science approach to candidate gene selection of pain regarded as a process of learning and neural plasticity.

    Science.gov (United States)

    Ultsch, Alfred; Kringel, Dario; Kalso, Eija; Mogil, Jeffrey S; Lötsch, Jörn

    2016-12-01

    The increasing availability of "big data" enables novel research approaches to chronic pain while also requiring novel techniques for data mining and knowledge discovery. We used machine learning to combine the knowledge about n = 535 genes identified empirically as relevant to pain with the knowledge about the functions of thousands of genes. Starting from an accepted description of chronic pain as displaying systemic features described by the terms "learning" and "neuronal plasticity," a functional genomics analysis proposed that among the functions of the 535 "pain genes," the biological processes "learning or memory" (P = 8.6 × 10) and "nervous system development" (P = 2.4 × 10) are statistically significantly overrepresented as compared with the annotations to these processes expected by chance. After establishing that the hypothesized biological processes were among important functional genomics features of pain, a subset of n = 34 pain genes were found to be annotated with both Gene Ontology terms. Published empirical evidence supporting their involvement in chronic pain was identified for almost all these genes, including 1 gene identified in March 2016 as being involved in pain. By contrast, such evidence was virtually absent in a randomly selected set of 34 other human genes. Hence, the present computational functional genomics-based method can be used for candidate gene selection, providing an alternative to established methods.

  15. Molecular genetic approach to human meningioma: loss of genes on chromosome 22

    International Nuclear Information System (INIS)

    Seizinger, B.R.; De La Monte, S.; Atkins, L.; Gusella, J.F.; Martuza, R.L.

    1987-01-01

    A molecular genetic approach employing polymorphic DNA markers has been used to investigate the role of chromosomal aberrations in meningioma, one of the most common tumors of the human nervous system. Comparison of the alleles detected by DNA markers in tumor DNA versus DNA from normal tissue revealed chromosomal alterations present in primary surgical specimens. In agreement with cytogenetic studies of cultured meningiomas, the most frequent alteration detected was loss of heterozygosity on chromosome 22. Forty of 51 patients were constitutionally heterozygous for at least one chromosome 22 DNA marker. Seventeen of the 40 constitutionally heterozygotic patients (43%) displayed hemizygosity for the corresponding marker in their meningioma tumor tissues. Loss of heterozygosity was also detected at a significantly lower frequency for markers on several other autosomes. In view of the striking association between acoustic neuroma and meningioma in bilateral acoustic neurofibromatosis and the discovery that acoustic neuromas display specific loss of genes on chromosome 22, the authors propose that a common mechanism involving chromosome 22 is operative in the development of both tumor types. Fine-structure mapping to reveal partial deletions in meningiomas may provide the means to clone and characterize a gene (or genes) of importance for tumorigenesis in this and possibly other clinically associated tumors of the human nervous system

  16. An oscillopathic approach to developmental dyslexia: From genes to speech processing.

    Science.gov (United States)

    Jiménez-Bravo, Miguel; Marrero, Victoria; Benítez-Burraco, Antonio

    2017-06-30

    Developmental dyslexia is a heterogeneous condition entailing problems with reading and spelling. Several genes have been linked or associated to the disease, many of which contribute to the development and function of brain areas important for auditory and phonological processing. Nonetheless, a clear link between genes, the brain, and the symptoms of dyslexia is still pending. The goal of this paper is contributing to bridge this gap. With this aim, we have focused on how the dyslexic brain fails to process speech sounds and reading cues. We have adopted an oscillatory perspective, according to which dyslexia may result from a deficient integration of different brain rhythms during reading/spellings tasks. Moreover, we show that some candidate genes for this condition are related to brain rhythms. This fresh approach is expected to provide a better understanding of the aetiology and the clinical presentation of developmental dyslexia, but also to achieve an earlier and more accurate diagnosis of the disease. Copyright © 2017 Elsevier B.V. All rights reserved.

  17. Gene doping: gene delivery for olympic victory.

    Science.gov (United States)

    Gould, David

    2013-08-01

    With one recently recommended gene therapy in Europe and a number of other gene therapy treatments now proving effective in clinical trials it is feasible that the same technologies will soon be adopted in the world of sport by unscrupulous athletes and their trainers in so called 'gene doping'. In this article an overview of the successful gene therapy clinical trials is provided and the potential targets for gene doping are highlighted. Depending on whether a doping gene product is secreted from the engineered cells or is retained locally to, or inside engineered cells will, to some extent, determine the likelihood of detection. It is clear that effective gene delivery technologies now exist and it is important that detection and prevention plans are in place. © 2012 The Author. British Journal of Clinical Pharmacology © 2012 The British Pharmacological Society.

  18. A suicide gene therapy approach to treat epidermolysis bullosa-associated skin cancer

    International Nuclear Information System (INIS)

    Gruber, C.

    2009-01-01

    Recessive dystrophic epidermolysis bullosa (RDEB) is an inherited disease causing extensive blister formation within the basal membrane zone (BMZ) of the skin and mucous membranes. It is caused by premature STOP mutations in the COL7A1 gene, which is indispensable for proper skin assembling. RDEB is associated with the development of a highly malignant skin cancer (squamous cell carcinoma, SCC) in early adulthood that displays a life threatening complication within this patient group. To date, neither chemo- nor radiotherapies showed successful results and due to the high metastatic potential of RDEB SCC wide surgical excision is still favoured. In this study we could reveal a new promising cancer treatment using spliceosome mediated RNA trans-splicing (SMaRT) using a suicide gene therapy approach. First we identified the tumour marker gene MMP-9 expressed by RDEB SCC cells in cell culture which was used to generate various pre-mRNA trans-splicing molecules (PTM). PTMs are able to facilitate trans-splicing between a tumour target gene and a cell death inducing peptide/toxin, encoded by the PTM. As a consequence the toxin is expressed in cancer cells leading to the induction of cell death. This technique offers high specificity in cancer cell targeting compared to other conventional cDNA expression studies. Various trans-splicing molecules were pre-evaluated in a fluorescence screening model for their best trans-splicing efficiency with the target molecule. Herein we identified two potent PTMs (PTM BD0 and PTM BD6), that were further adapted for endogenous suicide studies by inserting the toxin streptolysin O. In two independent in vitro cell culture assays we were able to confirm that the trans-splicing molecules are able to induce expression of the toxin resulting in cell membrane permeabilization and increased cell death induction. The results indicate that SMaRT technology offers a new platform for a suicide gene therapy approach to treat malignant squamous cell

  19. Gene targeting approaches to complex genetic diseases: atherosclerosis and essential hypertension.

    OpenAIRE

    Smithies, O; Maeda, N

    1995-01-01

    Gene targeting allows precise, predetermined changes to be made in a chosen gene in the mouse genome. To date, targeting has been used most often for generation of animals completely lacking the product of a gene of interest. The resulting "knockout" mice have confirmed some hypotheses, have upset others, but have rarely been uninformative. Models of several human genetic diseases have been produced by targeting--including Gaucher disease, cystic fibrosis, and the fragile X syndrome. These di...

  20. A feature selection approach for identification of signature genes from SAGE data

    Directory of Open Access Journals (Sweden)

    Silva Paulo JS

    2007-05-01

    Full Text Available Abstract Background One goal of gene expression profiling is to identify signature genes that robustly distinguish different types or grades of tumors. Several tumor classifiers based on expression profiling have been proposed using microarray technique. Due to important differences in the probabilistic models of microarray and SAGE technologies, it is important to develop suitable techniques to select specific genes from SAGE measurements. Results A new framework to select specific genes that distinguish different biological states based on the analysis of SAGE data is proposed. The new framework applies the bolstered error for the identification of strong genes that separate the biological states in a feature space defined by the gene expression of a training set. Credibility intervals defined from a probabilistic model of SAGE measurements are used to identify the genes that distinguish the different states with more reliability among all gene groups selected by the strong genes method. A score taking into account the credibility and the bolstered error values in order to rank the groups of considered genes is proposed. Results obtained using SAGE data from gliomas are presented, thus corroborating the introduced methodology. Conclusion The model representing counting data, such as SAGE, provides additional statistical information that allows a more robust analysis. The additional statistical information provided by the probabilistic model is incorporated in the methodology described in the paper. The introduced method is suitable to identify signature genes that lead to a good separation of the biological states using SAGE and may be adapted for other counting methods such as Massive Parallel Signature Sequencing (MPSS or the recent Sequencing-By-Synthesis (SBS technique. Some of such genes identified by the proposed method may be useful to generate classifiers.

  1. A systems level approach reveals new gene regulatory modules in the developing ear

    OpenAIRE

    Chen, Jingchen; Tambalo, Monica; Barembaum, Meyer; Ranganathan, Ramya; Simões-Costa, Marcos; Bronner, Marianne E.; Streit, Andrea

    2017-01-01

    The inner ear is a complex vertebrate sense organ, yet it arises from a simple epithelium, the otic placode. Specification towards otic fate requires diverse signals and transcriptional inputs that act sequentially and/or in parallel. Using the chick embryo, we uncover novel genes in the gene regulatory network underlying otic commitment and reveal dynamic changes in gene expression. Functional analysis of selected transcription factors reveals the genetic hierarchy underlying the transition ...

  2. Identifying overrepresented concepts in gene lists from literature: a statistical approach based on Poisson mixture model

    Directory of Open Access Journals (Sweden)

    Zhai Chengxiang

    2010-05-01

    Full Text Available Abstract Background Large-scale genomic studies often identify large gene lists, for example, the genes sharing the same expression patterns. The interpretation of these gene lists is generally achieved by extracting concepts overrepresented in the gene lists. This analysis often depends on manual annotation of genes based on controlled vocabularies, in particular, Gene Ontology (GO. However, the annotation of genes is a labor-intensive process; and the vocabularies are generally incomplete, leaving some important biological domains inadequately covered. Results We propose a statistical method that uses the primary literature, i.e. free-text, as the source to perform overrepresentation analysis. The method is based on a statistical framework of mixture model and addresses the methodological flaws in several existing programs. We implemented this method within a literature mining system, BeeSpace, taking advantage of its analysis environment and added features that facilitate the interactive analysis of gene sets. Through experimentation with several datasets, we showed that our program can effectively summarize the important conceptual themes of large gene sets, even when traditional GO-based analysis does not yield informative results. Conclusions We conclude that the current work will provide biologists with a tool that effectively complements the existing ones for overrepresentation analysis from genomic experiments. Our program, Genelist Analyzer, is freely available at: http://workerbee.igb.uiuc.edu:8080/BeeSpace/Search.jsp

  3. A hybrid gene selection approach for microarray data classification using cellular learning automata and ant colony optimization.

    Science.gov (United States)

    Vafaee Sharbaf, Fatemeh; Mosafer, Sara; Moattar, Mohammad Hossein

    2016-06-01

    This paper proposes an approach for gene selection in microarray data. The proposed approach consists of a primary filter approach using Fisher criterion which reduces the initial genes and hence the search space and time complexity. Then, a wrapper approach which is based on cellular learning automata (CLA) optimized with ant colony method (ACO) is used to find the set of features which improve the classification accuracy. CLA is applied due to its capability to learn and model complicated relationships. The selected features from the last phase are evaluated using ROC curve and the most effective while smallest feature subset is determined. The classifiers which are evaluated in the proposed framework are K-nearest neighbor; support vector machine and naïve Bayes. The proposed approach is evaluated on 4 microarray datasets. The evaluations confirm that the proposed approach can find the smallest subset of genes while approaching the maximum accuracy. Copyright © 2016 Elsevier Inc. All rights reserved.

  4. A Systems’ Biology Approach to Study MicroRNA-Mediated Gene Regulatory Networks

    Directory of Open Access Journals (Sweden)

    Xin Lai

    2013-01-01

    Full Text Available MicroRNAs (miRNAs are potent effectors in gene regulatory networks where aberrant miRNA expression can contribute to human diseases such as cancer. For a better understanding of the regulatory role of miRNAs in coordinating gene expression, we here present a systems biology approach combining data-driven modeling and model-driven experiments. Such an approach is characterized by an iterative process, including biological data acquisition and integration, network construction, mathematical modeling and experimental validation. To demonstrate the application of this approach, we adopt it to investigate mechanisms of collective repression on p21 by multiple miRNAs. We first construct a p21 regulatory network based on data from the literature and further expand it using algorithms that predict molecular interactions. Based on the network structure, a detailed mechanistic model is established and its parameter values are determined using data. Finally, the calibrated model is used to study the effect of different miRNA expression profiles and cooperative target regulation on p21 expression levels in different biological contexts.

  5. Rational design of modular circuits for gene transcription: A test of the bottom-up approach

    Directory of Open Access Journals (Sweden)

    Giordano Emanuele

    2010-11-01

    Full Text Available Abstract Background Most of synthetic circuits developed so far have been designed by an ad hoc approach, using a small number of components (i.e. LacI, TetR and a trial and error strategy. We are at the point where an increasing number of modular, inter-changeable and well-characterized components is needed to expand the construction of synthetic devices and to allow a rational approach to the design. Results We used interchangeable modular biological parts to create a set of novel synthetic devices for controlling gene transcription, and we developed a mathematical model of the modular circuits. Model parameters were identified by experimental measurements from a subset of modular combinations. The model revealed an unexpected feature of the lactose repressor system, i.e. a residual binding affinity for the operator site by induced lactose repressor molecules. Once this residual affinity was taken into account, the model properly reproduced the experimental data from the training set. The parameters identified in the training set allowed the prediction of the behavior of networks not included in the identification procedure. Conclusions This study provides new quantitative evidences that the use of independent and well-characterized biological parts and mathematical modeling, what is called a bottom-up approach to the construction of gene networks, can allow the design of new and different devices re-using the same modular parts.

  6. Assessment of different virus-mediated approaches for retinal gene therapy of Usher 1B.

    Science.gov (United States)

    Lopes, Vanda S; Diemer, Tanja; Williams, David S

    2014-01-01

    Usher syndrome type 1B, which is characterized by congenital deafness and progressive retinal degeneration, is caused by the loss of the function of MYO7A. Prevention of the retinal degeneration should be possible by delivering functional MYO7A to retinal cells. Although this approach has been used successfully in clinical trials for Leber congenital amaurosis (LCA2), it remains a challenge for Usher 1B because of the large size of the MYO7A cDNA. Different viral vectors have been tested for use in MYO7A gene therapy. Here, we review approaches with lentiviruses, which can accommodate larger genes, as well as attempts to use adeno-associated virus (AAV), which has a smaller packaging capacity. In conclusion, both types of viral vector appear to be effective. Despite concerns about the ability of lentiviruses to access the photoreceptor cells, a phenotype of the photoreceptors of Myo7a-mutant mice can be corrected. And although MYO7A cDNA is significantly larger than the nominal carrying capacity of AAV, AAV-MYO7A in single vectors also corrected Myo7a-mutant phenotypes in photoreceptor and RPE cells. Interestingly, however, a dual AAV vector approach was found to be much less effective.

  7. Cross-species transcriptomic approach reveals genes in hamster implantation sites.

    Science.gov (United States)

    Lei, Wei; Herington, Jennifer; Galindo, Cristi L; Ding, Tianbing; Brown, Naoko; Reese, Jeff; Paria, Bibhash C

    2014-12-01

    The mouse model has greatly contributed to understanding molecular mechanisms involved in the regulation of progesterone (P4) plus estrogen (E)-dependent blastocyst implantation process. However, little is known about contributory molecular mechanisms of the P4-only-dependent blastocyst implantation process that occurs in species such as hamsters, guineapigs, rabbits, pigs, rhesus monkeys, and perhaps humans. We used the hamster as a model of P4-only-dependent blastocyst implantation and carried out cross-species microarray (CSM) analyses to reveal differentially expressed genes at the blastocyst implantation site (BIS), in order to advance the understanding of molecular mechanisms of implantation. Upregulation of 112 genes and downregulation of 77 genes at the BIS were identified using a mouse microarray platform, while use of the human microarray revealed 62 up- and 38 down-regulated genes at the BIS. Excitingly, a sizable number of genes (30 up- and 11 down-regulated genes) were identified as a shared pool by both CSMs. Real-time RT-PCR and in situ hybridization validated the expression patterns of several up- and down-regulated genes identified by both CSMs at the hamster and mouse BIS to demonstrate the merit of CSM findings across species, in addition to revealing genes specific to hamsters. Functional annotation analysis found that genes involved in the spliceosome, proteasome, and ubiquination pathways are enriched at the hamster BIS, while genes associated with tight junction, SAPK/JNK signaling, and PPARα/RXRα signalings are repressed at the BIS. Overall, this study provides a pool of genes and evidence of their participation in up- and down-regulated cellular functions/pathways at the hamster BIS. © 2014 Society for Reproduction and Fertility.

  8. Evolution of homeobox genes.

    Science.gov (United States)

    Holland, Peter W H

    2013-01-01

    Many homeobox genes encode transcription factors with regulatory roles in animal and plant development. Homeobox genes are found in almost all eukaryotes, and have diversified into 11 gene classes and over 100 gene families in animal evolution, and 10 to 14 gene classes in plants. The largest group in animals is the ANTP class which includes the well-known Hox genes, plus other genes implicated in development including ParaHox (Cdx, Xlox, Gsx), Evx, Dlx, En, NK4, NK3, Msx, and Nanog. Genomic data suggest that the ANTP class diversified by extensive tandem duplication to generate a large array of genes, including an NK gene cluster and a hypothetical ProtoHox gene cluster that duplicated to generate Hox and ParaHox genes. Expression and functional data suggest that NK, Hox, and ParaHox gene clusters acquired distinct roles in patterning the mesoderm, nervous system, and gut. The PRD class is also diverse and includes Pax2/5/8, Pax3/7, Pax4/6, Gsc, Hesx, Otx, Otp, and Pitx genes. PRD genes are not generally arranged in ancient genomic clusters, although the Dux, Obox, and Rhox gene clusters arose in mammalian evolution as did several non-clustered PRD genes. Tandem duplication and genome duplication expanded the number of homeobox genes, possibly contributing to the evolution of developmental complexity, but homeobox gene loss must not be ignored. Evolutionary changes to homeobox gene expression have also been documented, including Hox gene expression patterns shifting in concert with segmental diversification in vertebrates and crustaceans, and deletion of a Pitx1 gene enhancer in pelvic-reduced sticklebacks. WIREs Dev Biol 2013, 2:31-45. doi: 10.1002/wdev.78 For further resources related to this article, please visit the WIREs website. The author declares that he has no conflicts of interest. Copyright © 2012 Wiley Periodicals, Inc.

  9. Gene cluster statistics with gene families.

    Science.gov (United States)

    Raghupathy, Narayanan; Durand, Dannie

    2009-05-01

    Identifying genomic regions that descended from a common ancestor is important for understanding the function and evolution of genomes. In distantly related genomes, clusters of homologous gene pairs are evidence of candidate homologous regions. Demonstrating the statistical significance of such "gene clusters" is an essential component of comparative genomic analyses. However, currently there are no practical statistical tests for gene clusters that model the influence of the number of homologs in each gene family on cluster significance. In this work, we demonstrate empirically that failure to incorporate gene family size in gene cluster statistics results in overestimation of significance, leading to incorrect conclusions. We further present novel analytical methods for estimating gene cluster significance that take gene family size into account. Our methods do not require complete genome data and are suitable for testing individual clusters found in local regions, such as contigs in an unfinished assembly. We consider pairs of regions drawn from the same genome (paralogous clusters), as well as regions drawn from two different genomes (orthologous clusters). Determining cluster significance under general models of gene family size is computationally intractable. By assuming that all gene families are of equal size, we obtain analytical expressions that allow fast approximation of cluster probabilities. We evaluate the accuracy of this approximation by comparing the resulting gene cluster probabilities with cluster probabilities obtained by simulating a realistic, power-law distributed model of gene family size, with parameters inferred from genomic data. Surprisingly, despite the simplicity of the underlying assumption, our method accurately approximates the true cluster probabilities. It slightly overestimates these probabilities, yielding a conservative test. We present additional simulation results indicating the best choice of parameter values for data

  10. Classification of gene expression data: A hubness-aware semi-supervised approach.

    Science.gov (United States)

    Buza, Krisztian

    2016-04-01

    Classification of gene expression data is the common denominator of various biomedical recognition tasks. However, obtaining class labels for large training samples may be difficult or even impossible in many cases. Therefore, semi-supervised classification techniques are required as semi-supervised classifiers take advantage of unlabeled data. Gene expression data is high-dimensional which gives rise to the phenomena known under the umbrella of the curse of dimensionality, one of its recently explored aspects being the presence of hubs or hubness for short. Therefore, hubness-aware classifiers have been developed recently, such as Naive Hubness-Bayesian k-Nearest Neighbor (NHBNN). In this paper, we propose a semi-supervised extension of NHBNN which follows the self-training schema. As one of the core components of self-training is the certainty score, we propose a new hubness-aware certainty score. We performed experiments on publicly available gene expression data. These experiments show that the proposed classifier outperforms its competitors. We investigated the impact of each of the components (classification algorithm, semi-supervised technique, hubness-aware certainty score) separately and showed that each of these components are relevant to the performance of the proposed approach. Our results imply that our approach may increase classification accuracy and reduce computational costs (i.e., runtime). Based on the promising results presented in the paper, we envision that hubness-aware techniques will be used in various other biomedical machine learning tasks. In order to accelerate this process, we made an implementation of hubness-aware machine learning techniques publicly available in the PyHubs software package (http://www.biointelligence.hu/pyhubs) implemented in Python, one of the most popular programming languages of data science. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

  11. Carboxylesterase 1 genes

    DEFF Research Database (Denmark)

    Rasmussen, Henrik Berg; Madsen, Majbritt Busk

    2018-01-01

    The carboxylesterase 1 gene (CES1) encodes a hydrolase that metabolizes commonly used drugs. The CES1-related pseudogene, carboxylesterase 1 pseudogene 1 (CES1P1), has been implicated in gene exchange with CES1 and in the formation of hybrid genes including the carboxylesterase 1A2 gene (CES1A2...

  12. A comparative study of mutation screening of sarcomeric genes (MYBPC3, MYH7, TNNT2 using single gene approach versus targeted gene panel next generation sequencing in a cohort of HCM patients in Egypt

    Directory of Open Access Journals (Sweden)

    Heba Sh. Kassem

    2017-10-01

    Full Text Available Background: NGS enables simultaneous sequencing of large numbers of associated genes in genetic heterogeneous disorders, in a more rapid and cost-effective manner than traditional technologies. However there have been limited direct comparisons between NGS and more established technologies to assess the sensitivity and false negative rates of this new approach. The scope of the present manuscript is to compare variants detected in MYBPC3, MYH7 and TNNT2 genes using the stepwise dHPLC/Sanger versus targeted NGS. Methods: In this study, we have analysed a group of 150 samples of patients from the Bibliotheca Alexandrina-Aswan Heart Centre National HCM program. The genetic testing was simultaneously undertaken by high throughput denaturing high-performance liquid chromatography (dHPLC followed by Sanger based sequencing and targeted next generation deep sequencing using panel of inherited cardiac genes (ICC. The panel included over 100 genes including the 3 sarcomeric genes. Analysis of the sequencing data of the 3 genes was undertaken in a double blinded strategy. Results: NGS analysis detected all pathogenic and likely pathogenic variants identified by dHPLC (50 in total, some samples had double hits. There was a 0% false negative rate for NGS based analysis. Nineteen variants were missed by dHPLC and detected by NGS, thus increasing the diagnostic yield in this co- analysed cohort from 22.0% (33/150 to 31.3% (47/150.Of interest to note that the mutation spectrum in this Egyptian HCM population revealed a high rate of homozygosity in MYBPC3 and MYH7 genes in comparison to other population studies (6/150, 4%. None of the homozygous samples were detected by dHPLC analysis. Conclusion: NGS provides a useful and rapid tool to allow panoramic screening of several genes simultaneously with a high sensitivity rate amongst genes of known etiologic role allowing high throughput analysis of HCM patients and relevant control series in a less characterised

  13. 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.

  14. 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

  15. Deduction of Novel Genes Potentially Involved in Osteoblasts of Rheumatoid Arthritis Using Next-Generation Sequencing and Bioinformatic Approaches

    Directory of Open Access Journals (Sweden)

    Yi-Jen Chen

    2017-11-01

    Full Text Available The role of osteoblasts in peri-articular bone loss and bone erosion in rheumatoid arthritis (RA has gained much attention, and microRNAs are hypothesized to play critical roles in the regulation of osteoblast function in RA. The aim of this study is to explore novel microRNAs differentially expressed in RA osteoblasts and to identify genes potentially involved in the dysregulated bone homeostasis in RA. RNAs were extracted from cultured normal and RA osteoblasts for sequencing. Using the next generation sequencing and bioinformatics approaches, we identified 35 differentially expressed microRNAs and 13 differentially expressed genes with potential microRNA–mRNA interactions in RA osteoblasts. The 13 candidate genes were involved mainly in cell–matrix adhesion, as classified by the Gene Ontology. Two genes of interest identified from RA osteoblasts, A-kinase anchoring protein 12 (AKAP12 and leucin rich repeat containing 15 (LRRC15, were found to express more consistently in the related RA synovial tissue arrays in the Gene Expression Omnibus database, with the predicted interactions with miR-183-5p and miR-146a-5p, respectively. The Ingenuity Pathway Analysis identified AKAP12 as one of the genes involved in protein kinase A signaling and the function of chemotaxis, interconnecting with molecules related to neovascularization. The findings indicate new candidate genes as the potential indicators in evaluating therapies targeting chemotaxis and neovascularization to control joint destruction in RA.

  16. A comprehensive candidate gene approach identifies genetic variation associated with osteosarcoma

    International Nuclear Information System (INIS)

    Mirabello, Lisa; Grotmol, Tom; Douglass, Chester; Hayes, Richard B; Hoover, Robert N; Savage, Sharon A; Yu, Kai; Berndt, Sonja I; Burdett, Laurie; Wang, Zhaoming; Chowdhury, Salma; Teshome, Kedest; Uzoka, Arinze; Hutchinson, Amy

    2011-01-01

    Osteosarcoma (OS) is a bone malignancy which occurs primarily in adolescents. Since it occurs during a period of rapid growth, genes important in bone formation and growth are plausible modifiers of risk. Genes involved in DNA repair and ribosomal function may contribute to OS pathogenesis, because they maintain the integrity of critical cellular processes. We evaluated these hypotheses in an OS association study of genes from growth/hormone, bone formation, DNA repair, and ribosomal pathways. We evaluated 4836 tag-SNPs across 255 candidate genes in 96 OS cases and 1426 controls. Logistic regression models were used to estimate the odds ratios (OR) and 95% confidence intervals (CI). Twelve SNPs in growth or DNA repair genes were significantly associated with OS after Bonferroni correction. Four SNPs in the DNA repair gene FANCM (ORs 1.9-2.0, P = 0.003-0.004) and 2 SNPs downstream of the growth hormone gene GH1 (OR 1.6, P = 0.002; OR 0.5, P = 0.0009) were significantly associated with OS. One SNP in the region of each of the following genes was significant: MDM2, MPG, FGF2, FGFR3, GNRH2, and IGF1. Our results suggest that several SNPs in biologically plausible pathways are associated with OS. Larger studies are required to confirm our findings

  17. From essential to persistent genes: a functional approach to constructing synthetic life

    DEFF Research Database (Denmark)

    Acevedo-Rocha, Carlos G.; Fang, Gang; Schmidt, Markus

    2013-01-01

    A central undertaking in synthetic biology (SB) is the quest for the ‘minimal genome’. However, ‘minimal sets’ of essential genes are strongly context-dependent and, in all prokaryotic genomes sequenced to date, not a single protein-coding gene is entirely conserved. Furthermore, a lack...

  18. Combining genetical genomics and bulked segregant analysis differential expression: an approach to gene localization

    NARCIS (Netherlands)

    Chen, Xinwei; Hedley, P.E.; Morris, J.; Liu, Hui; Niks, R.E.; Waugh, R.

    2011-01-01

    Positional gene isolation in unsequenced species generally requires either a reference genome sequence or an inference of gene content based on conservation of synteny with a genomic model. In the large unsequenced genomes of the Triticeae cereals the latter, i.e. conservation of synteny with the

  19. Gene-Environment Interactions in Genome-Wide Association Studies: Current Approaches and New Directions

    Science.gov (United States)

    Winham, Stacey J.; Biernacka, Joanna M.

    2013-01-01

    Background: Complex psychiatric traits have long been thought to be the result of a combination of genetic and environmental factors, and gene-environment interactions are thought to play a crucial role in behavioral phenotypes and the susceptibility and progression of psychiatric disorders. Candidate gene studies to investigate hypothesized…

  20. SVMRFE based approach for prediction of most discriminatory gene target for type II diabetes

    Directory of Open Access Journals (Sweden)

    Atul Kumar

    2017-06-01

    Full Text Available Type II diabetes is a chronic condition that affects the way our body metabolizes sugar. The body's important source of fuel is now becoming a chronic disease all over the world. It is now very necessary to identify the new potential targets for the drugs which not only control the disease but also can treat it. Support vector machines are the classifier which has a potential to make a classification of the discriminatory genes and non-discriminatory genes. SVMRFE a modification of SVM ranks the genes based on their discriminatory power and eliminate the genes which are not involved in causing the disease. A gene regulatory network has been formed with the top ranked coding genes to identify their role in causing diabetes. To further validate the results pathway study was performed to identify the involvement of the coding genes in type II diabetes. The genes obtained from this study showed a significant involvement in causing the disease, which may be used as a potential drug target.

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

    Directory of Open Access Journals (Sweden)

    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.

  2. Discovery of Cationic Polymers for Non-viral Gene Delivery using Combinatorial Approaches

    Science.gov (United States)

    Barua, Sutapa; Ramos, James; Potta, Thrimoorthy; Taylor, David; Huang, Huang-Chiao; Montanez, Gabriela; Rege, Kaushal

    2015-01-01

    Gene therapy is an attractive treatment option for diseases of genetic origin, including several cancers and cardiovascular diseases. While viruses are effective vectors for delivering exogenous genes to cells, concerns related to insertional mutagenesis, immunogenicity, lack of tropism, decay and high production costs necessitate the discovery of non-viral methods. Significant efforts have been focused on cationic polymers as non-viral alternatives for gene delivery. Recent studies have employed combinatorial syntheses and parallel screening methods for enhancing the efficacy of gene delivery, biocompatibility of the delivery vehicle, and overcoming cellular level barriers as they relate to polymer-mediated transgene uptake, transport, transcription, and expression. This review summarizes and discusses recent advances in combinatorial syntheses and parallel screening of cationic polymer libraries for the discovery of efficient and safe gene delivery systems. PMID:21843141

  3. Whole genome sequencing options for bacterial strain typing and epidemiologic analysis based on single nucleotide polymorphism versus gene-by-gene-based approaches.

    Science.gov (United States)

    Schürch, A C; Arredondo-Alonso, S; Willems, R J L; Goering, R V

    2018-04-01

    Whole genome sequence (WGS)-based strain typing finds increasing use in the epidemiologic analysis of bacterial pathogens in both public health as well as more localized infection control settings. This minireview describes methodologic approaches that have been explored for WGS-based epidemiologic analysis and considers the challenges and pitfalls of data interpretation. Personal collection of relevant publications. When applying WGS to study the molecular epidemiology of bacterial pathogens, genomic variability between strains is translated into measures of distance by determining single nucleotide polymorphisms in core genome alignments or by indexing allelic variation in hundreds to thousands of core genes, assigning types to unique allelic profiles. Interpreting isolate relatedness from these distances is highly organism specific, and attempts to establish species-specific cutoffs are unlikely to be generally applicable. In cases where single nucleotide polymorphism or core gene typing do not provide the resolution necessary for accurate assessment of the epidemiology of bacterial pathogens, inclusion of accessory gene or plasmid sequences may provide the additional required discrimination. As with all epidemiologic analysis, realizing the full potential of the revolutionary advances in WGS-based approaches requires understanding and dealing with issues related to the fundamental steps of data generation and interpretation. Copyright © 2018 The Authors. Published by Elsevier Ltd.. All rights reserved.

  4. Gene function prediction based on Gene Ontology Hierarchy Preserving Hashing.

    Science.gov (United States)

    Zhao, Yingwen; Fu, Guangyuan; Wang, Jun; Guo, Maozu; Yu, Guoxian

    2018-02-23

    Gene Ontology (GO) uses structured vocabularies (or terms) to describe the molecular functions, biological roles, and cellular locations of gene products in a hierarchical ontology. GO annotations associate genes with GO terms and indicate the given gene products carrying out the biological functions described by the relevant terms. However, predicting correct GO annotations for genes from a massive set of GO terms as defined by GO is a difficult challenge. To combat with this challenge, we introduce a Gene Ontology Hierarchy Preserving Hashing (HPHash) based semantic method for gene function prediction. HPHash firstly measures the taxonomic similarity between GO terms. It then uses a hierarchy preserving hashing technique to keep the hierarchical order between GO terms, and to optimize a series of hashing functions to encode massive GO terms via compact binary codes. After that, HPHash utilizes these hashing functions to project the gene-term association matrix into a low-dimensional one and performs semantic similarity based gene function prediction in the low-dimensional space. Experimental results on three model species (Homo sapiens, Mus musculus and Rattus norvegicus) for interspecies gene function prediction show that HPHash performs better than other related approaches and it is robust to the number of hash functions. In addition, we also take HPHash as a plugin for BLAST based gene function prediction. From the experimental results, HPHash again significantly improves the prediction performance. The codes of HPHash are available at: http://mlda.swu.edu.cn/codes.php?name=HPHash. Copyright © 2018 Elsevier Inc. All rights reserved.

  5. Combining Human Epigenetics and Sleep Studies in Caenorhabditis elegans: A Cross-Species Approach for Finding Conserved Genes Regulating Sleep.

    Science.gov (United States)

    Huang, Huiyan; Zhu, Yong; Eliot, Melissa N; Knopik, Valerie S; McGeary, John E; Carskadon, Mary A; Hart, Anne C

    2017-06-01

    We aimed to test a combined approach to identify conserved genes regulating sleep and to explore the association between DNA methylation and sleep length. We identified candidate genes associated with shorter versus longer sleep duration in college students based on DNA methylation using Illumina Infinium HumanMethylation450 BeadChip arrays. Orthologous genes in Caenorhabditis elegans were identified, and we examined whether their loss of function affected C. elegans sleep. For genes whose perturbation affected C. elegans sleep, we subsequently undertook a small pilot study to re-examine DNA methylation in an independent set of human participants with shorter versus longer sleep durations. Eighty-seven out of 485,577 CpG sites had significant differential methylation in young adults with shorter versus longer sleep duration, corresponding to 52 candidate genes. We identified 34 C. elegans orthologs, including NPY/flp-18 and flp-21, which are known to affect sleep. Loss of five additional genes alters developmentally timed C. elegans sleep (B4GALT6/bre-4, DOCK180/ced-5, GNB2L1/rack-1, PTPRN2/ida-1, ZFYVE28/lst-2). For one of these genes, ZFYVE28 (also known as hLst2), the pilot replication study again found decreased DNA methylation associated with shorter sleep duration at the same two CpG sites in the first intron of ZFYVE28. Using an approach that combines human epigenetics and C. elegans sleep studies, we identified five genes that play previously unidentified roles in C. elegans sleep. We suggest sleep duration in humans may be associated with differential DNA methylation at specific sites and that the conserved genes identified here likely play roles in C. elegans sleep and in other species. © Sleep Research Society 2017. Published by Oxford University Press on behalf of the Sleep Research Society. All rights reserved. For permissions, please e-mail journals.permissions@oup.com.

  6. A systems genetics approach identifies CXCL14, ITGAX, and LPCAT2 as novel aggressive prostate cancer susceptibility genes.

    Directory of Open Access Journals (Sweden)

    Kendra A Williams

    2014-11-01

    Full Text Available Although prostate cancer typically runs an indolent course, a subset of men develop aggressive, fatal forms of this disease. We hypothesize that germline variation modulates susceptibility to aggressive prostate cancer. The goal of this work is to identify susceptibility genes using the C57BL/6-Tg(TRAMP8247Ng/J (TRAMP mouse model of neuroendocrine prostate cancer. Quantitative trait locus (QTL mapping was performed in transgene-positive (TRAMPxNOD/ShiLtJ F2 intercross males (n = 228, which facilitated identification of 11 loci associated with aggressive disease development. Microarray data derived from 126 (TRAMPxNOD/ShiLtJ F2 primary tumors were used to prioritize candidate genes within QTLs, with candidate genes deemed as being high priority when possessing both high levels of expression-trait correlation and a proximal expression QTL. This process enabled the identification of 35 aggressive prostate tumorigenesis candidate genes. The role of these genes in aggressive forms of human prostate cancer was investigated using two concurrent approaches. First, logistic regression analysis in two human prostate gene expression datasets revealed that expression levels of five genes (CXCL14, ITGAX, LPCAT2, RNASEH2A, and ZNF322 were positively correlated with aggressive prostate cancer and two genes (CCL19 and HIST1H1A were protective for aggressive prostate cancer. Higher than average levels of expression of the five genes that were positively correlated with aggressive disease were consistently associated with patient outcome in both human prostate cancer tumor gene expression datasets. Second, three of these five genes (CXCL14, ITGAX, and LPCAT2 harbored polymorphisms associated with aggressive disease development in a human GWAS cohort consisting of 1,172 prostate cancer patients. This study is the first example of using a systems genetics approach to successfully identify novel susceptibility genes for aggressive prostate cancer. Such

  7. Approach of combined cancer gene therapy and radiation: response of promoters to ionizing radiation

    International Nuclear Information System (INIS)

    Anstett, A.

    2005-09-01

    Gene therapy is an emerging cancer treatment modality. We are interested in developing a radiation-inducible gene therapy system to sensitize the tumor vasculature to the effects of ionizing radiation (IR) treatment. An expression system based on irradiation-inducible promoters will drive the expression of anti-tumor genes in the tumor vasculature. Solid tumors are dependent on angio genesis, a process in which new blood vessels are formed from the pre-existing vasculature. Vascular endothelial cells are un transformed and genetically stable, thus avoiding the problem of resistance to the treatments. Vascular endothelial cells may therefore represent a suitable target for this therapeutic gene therapy strategy.The identification of IR-inducible promoters native to endothelial cells was performed by gene expression profiling using cDNA micro array technology. We describe the genes modified by clinically relevant doses of IR. The extension to high doses aimed at studying the effects of total radiation delivery to the tumor. The radio-inductiveness of the genes selected for promoter study was confirmed by RT-PCR. Analysis of the activity of promoters in response to IR was also assessed in a reporter plasmid. We found that authentic promoters cloned onto a plasmid are not suitable for cancer gene therapy due to their low induction after IR. In contrast, synthetic promoters containing repeated sequence-specific binding sites for IR-activated transcription factors such as NF-κB are potential candidates for gene therapy. The activity of five tandemly repeated TGGGGACTTTCCGC elements for NF-κB binding in a luciferase reporter was increased in a dose-dependent manner. Interestingly, the response to fractionated low doses was improved in comparison to the total single dose. Thus, we put present evidence that a synthetic promoter for NF-κB specific binding may have application in the radio-therapeutic treatment of cancer. (author)

  8. Gene doping in sports.

    Science.gov (United States)

    Unal, Mehmet; Ozer Unal, Durisehvar

    2004-01-01

    Gene or cell doping is defined by the World Anti-Doping Agency (WADA) as "the non-therapeutic use of genes, genetic elements and/or cells that have the capacity to enhance athletic performance". New research in genetics and genomics will be used not only to diagnose and treat disease, but also to attempt to enhance human performance. In recent years, gene therapy has shown progress and positive results that have highlighted the potential misuse of this technology and the debate of 'gene doping'. Gene therapies developed for the treatment of diseases such as anaemia (the gene for erythropoietin), muscular dystrophy (the gene for insulin-like growth factor-1) and peripheral vascular diseases (the gene for vascular endothelial growth factor) are potential doping methods. With progress in gene technology, many other genes with this potential will be discovered. For this reason, it is important to develop timely legal regulations and to research the field of gene doping in order to develop methods of detection. To protect the health of athletes and to ensure equal competitive conditions, the International Olympic Committee, WADA and International Sports Federations have accepted performance-enhancing substances and methods as being doping, and have forbidden them. Nevertheless, the desire to win causes athletes to misuse these drugs and methods. This paper reviews the current status of gene doping and candidate performance enhancement genes, and also the use of gene therapy in sports medicine and ethics of genetic enhancement. Copyright 2004 Adis Data Information BV

  9. Pain genes.

    Directory of Open Access Journals (Sweden)

    Tom Foulkes

    2008-07-01

    Full Text Available Pain, which afflicts up to 20% of the population at any time, provides both a massive therapeutic challenge and a route to understanding mechanisms in the nervous system. Specialised sensory neurons (nociceptors signal the existence of tissue damage to the central nervous system (CNS, where pain is represented in a complex matrix involving many CNS structures. Genetic approaches to investigating pain pathways using model organisms have identified the molecular nature of the transducers, regulatory mechanisms involved in changing neuronal activity, as well as the critical role of immune system cells in driving pain pathways. In man, mapping of human pain mutants as well as twin studies and association studies of altered pain behaviour have identified important regulators of the pain system. In turn, new drug targets for chronic pain treatment have been validated in transgenic mouse studies. Thus, genetic studies of pain pathways have complemented the traditional neuroscience approaches of electrophysiology and pharmacology to give us fresh insights into the molecular basis of pain perception.

  10. Comparative genomics and association mapping approaches for blast resistant genes in finger millet using SSRs.

    Directory of Open Access Journals (Sweden)

    B Kalyana Babu

    Full Text Available The major limiting factor for production and productivity of finger millet crop is blast disease caused by Magnaporthe grisea. Since, the genome sequence information available in finger millet crop is scarce, comparative genomics plays a very important role in identification of genes/QTLs linked to the blast resistance genes using SSR markers. In the present study, a total of 58 genic SSRs were developed for use in genetic analysis of a global collection of 190 finger millet genotypes. The 58 SSRs yielded ninety five scorable alleles and the polymorphism information content varied from 0.186 to 0.677 at an average of 0.385. The gene diversity was in the range of 0.208 to 0.726 with an average of 0.487. Association mapping for blast resistance was done using 104 SSR markers which identified four QTLs for finger blast and one QTL for neck blast resistance. The genomic marker RM262 and genic marker FMBLEST32 were linked to finger blast disease at a P value of 0.007 and explained phenotypic variance (R² of 10% and 8% respectively. The genomic marker UGEP81 was associated to finger blast at a P value of 0.009 and explained 7.5% of R². The QTLs for neck blast was associated with the genomic SSR marker UGEP18 at a P value of 0.01, which explained 11% of R². Three QTLs for blast resistance were found common by using both GLM and MLM approaches. The resistant alleles were found to be present mostly in the exotic genotypes. Among the genotypes of NW Himalayan region of India, VHC3997, VHC3996 and VHC3930 were found highly resistant, which may be effectively used as parents for developing blast resistant cultivars in the NW Himalayan region of India. The markers linked to the QTLs for blast resistance in the present study can be further used for cloning of the full length gene, fine mapping and their further use in the marker assisted breeding programmes for introgression of blast resistant alleles into locally adapted cultivars.

  11. Comparative genomics and association mapping approaches for blast resistant genes in finger millet using SSRs.

    Science.gov (United States)

    Babu, B Kalyana; Dinesh, Pandey; Agrawal, Pawan K; Sood, S; Chandrashekara, C; Bhatt, Jagadish C; Kumar, Anil

    2014-01-01

    The major limiting factor for production and productivity of finger millet crop is blast disease caused by Magnaporthe grisea. Since, the genome sequence information available in finger millet crop is scarce, comparative genomics plays a very important role in identification of genes/QTLs linked to the blast resistance genes using SSR markers. In the present study, a total of 58 genic SSRs were developed for use in genetic analysis of a global collection of 190 finger millet genotypes. The 58 SSRs yielded ninety five scorable alleles and the polymorphism information content varied from 0.186 to 0.677 at an average of 0.385. The gene diversity was in the range of 0.208 to 0.726 with an average of 0.487. Association mapping for blast resistance was done using 104 SSR markers which identified four QTLs for finger blast and one QTL for neck blast resistance. The genomic marker RM262 and genic marker FMBLEST32 were linked to finger blast disease at a P value of 0.007 and explained phenotypic variance (R²) of 10% and 8% respectively. The genomic marker UGEP81 was associated to finger blast at a P value of 0.009 and explained 7.5% of R². The QTLs for neck blast was associated with the genomic SSR marker UGEP18 at a P value of 0.01, which explained 11% of R². Three QTLs for blast resistance were found common by using both GLM and MLM approaches. The resistant alleles were found to be present mostly in the exotic genotypes. Among the genotypes of NW Himalayan region of India, VHC3997, VHC3996 and VHC3930 were found highly resistant, which may be effectively used as parents for developing blast resistant cultivars in the NW Himalayan region of India. The markers linked to the QTLs for blast resistance in the present study can be further used for cloning of the full length gene, fine mapping and their further use in the marker assisted breeding programmes for introgression of blast resistant alleles into locally adapted cultivars.

  12. Backward-stochastic-differential-equation approach to modeling of gene expression.

    Science.gov (United States)

    Shamarova, Evelina; Chertovskih, Roman; Ramos, Alexandre F; Aguiar, Paulo

    2017-03-01

    In this article, we introduce a backward method to model stochastic gene expression and protein-level dynamics. The protein amount is regarded as a diffusion process and is described by a backward stochastic differential equation (BSDE). Unlike many other SDE techniques proposed in the literature, the BSDE method is backward in time; that is, instead of initial conditions it requires the specification of end-point ("final") conditions, in addition to the model parametrization. To validate our approach we employ Gillespie's stochastic simulation algorithm (SSA) to generate (forward) benchmark data, according to predefined gene network models. Numerical simulations show that the BSDE method is able to correctly infer the protein-level distributions that preceded a known final condition, obtained originally from the forward SSA. This makes the BSDE method a powerful systems biology tool for time-reversed simulations, allowing, for example, the assessment of the biological conditions (e.g., protein concentrations) that preceded an experimentally measured event of interest (e.g., mitosis, apoptosis, etc.).

  13. A multiplex degenerate PCR analytical approach targeting to eight genes for screening GMOs.

    Science.gov (United States)

    Guo, Jinchao; Chen, Lili; Liu, Xin; Gao, Ying; Zhang, Dabing; Yang, Litao

    2012-06-01

    Currently, the detection methods with lower cost and higher throughput are the major trend in screening genetically modified (GM) food or feed before specific identification. In this study, we developed a quadruplex degenerate PCR screening approach for more than 90 approved GMO events. This assay is consisted of four PCR systems targeting on nine DNA sequences from eight trait genes widely introduced into GMOs, such as CP4-EPSPS derived from Acetobacterium tumefaciens sp. strain CP4, phosphinothricin acetyltransferase gene derived from Streptomyceshygroscopicus (bar) and Streptomyces viridochromogenes (pat), and Cry1Ab, Cry1Ac, Cry1A(b/c), mCry3A, and Cry3Bb1 derived from Bacillus thuringiensis. The quadruplex degenerate PCR assay offers high specificity and sensitivity with the absolute limit of detection (LOD) of approximate 80targetcopies. Furthermore, the applicability of the quadruplex PCR assay was confirmed by screening either several artificially prepared samples or samples of Grain Inspection, Packers and Stockyards Administration (GIPSA) proficiency program. Copyright © 2011 Elsevier Ltd. All rights reserved.

  14. Comparison of two approaches for the classification of 16S rRNA gene sequences.

    Science.gov (United States)

    Chatellier, Sonia; Mugnier, Nathalie; Allard, Françoise; Bonnaud, Bertrand; Collin, Valérie; van Belkum, Alex; Veyrieras, Jean-Baptiste; Emler, Stefan

    2014-10-01

    The use of 16S rRNA gene sequences for microbial identification in clinical microbiology is accepted widely, and requires databases and algorithms. We compared a new research database containing curated 16S rRNA gene sequences in combination with the lca (lowest common ancestor) algorithm (RDB-LCA) to a commercially available 16S rDNA Centroid approach. We used 1025 bacterial isolates characterized by biochemistry, matrix-assisted laser desorption/ionization time-of-flight MS and 16S rDNA sequencing. Nearly 80 % of isolates were identified unambiguously at the species level by both classification platforms used. The remaining isolates were mostly identified correctly at the genus level due to the limited resolution of 16S rDNA sequencing. Discrepancies between both 16S rDNA platforms were due to differences in database content and the algorithm used, and could amount to up to 10.5 %. Up to 1.4 % of the analyses were found to be inconclusive. It is important to realize that despite the overall good performance of the pipelines for analysis, some inconclusive results remain that require additional in-depth analysis performed using supplementary methods. © 2014 The Authors.

  15. Radiopharmaceuticals to monitor gene transfer

    International Nuclear Information System (INIS)

    Wiebe, L. I.; Morin, K. W.; Knaus, E. E.

    1997-01-01

    Advances in genetic engineering and molecular biology have opened the door to disease treatment by transferring genes to cells that are responsible for the pathological condition being addressed. These genes can serve to supplement or introduce the function of indigenous genes that are either inadequately expressed or that are congenitally absent in the patient. They can introduce new functions such as drug sensitization to provide a unique therapeutic target. Gene transfer is readily monitored in vitro using a range of histochemical and biochemical tests that are ''built in'' to the therapeutic gene cassette. In vivo, in situ monitoring of the gene transfer and gene expression processes can be achieved with these tests only if biopsy is possible. Scintigraphic imaging can offer unique information on both the extent and location of gene expression, provided that an appropriate reporter gene is included in the therapeutic cassette. This overview includes a brief orientation to gene transfer therapy and is followed by a review of current approaches to gene therapy imaging. The concluding section deals with imaging based on radiolabelled nucleoside substrates for herpes simplex type-1 thymidine kinase, with emphasis on IVFRU, a stable potent and selective HSV-1 TK substrate developed in their laboratories

  16. Gene Circuit Analysis of the Terminal Gap Gene huckebein

    Science.gov (United States)

    Ashyraliyev, Maksat; Siggens, Ken; Janssens, Hilde; Blom, Joke; Akam, Michael; Jaeger, Johannes

    2009-01-01

    The early embryo of Drosophila melanogaster provides a powerful model system to study the role of genes in pattern formation. The gap gene network constitutes the first zygotic regulatory tier in the hierarchy of the segmentation genes involved in specifying the position of body segments. Here, we use an integrative, systems-level approach to investigate the regulatory effect of the terminal gap gene huckebein (hkb) on gap gene expression. We present quantitative expression data for the Hkb protein, which enable us to include hkb in gap gene circuit models. Gap gene circuits are mathematical models of gene networks used as computational tools to extract regulatory information from spatial expression data. This is achieved by fitting the model to gap gene expression patterns, in order to obtain estimates for regulatory parameters which predict a specific network topology. We show how considering variability in the data combined with analysis of parameter determinability significantly improves the biological relevance and consistency of the approach. Our models are in agreement with earlier results, which they extend in two important respects: First, we show that Hkb is involved in the regulation of the posterior hunchback (hb) domain, but does not have any other essential function. Specifically, Hkb is required for the anterior shift in the posterior border of this domain, which is now reproduced correctly in our models. Second, gap gene circuits presented here are able to reproduce mutants of terminal gap genes, while previously published models were unable to reproduce any null mutants correctly. As a consequence, our models now capture the expression dynamics of all posterior gap genes and some variational properties of the system correctly. This is an important step towards a better, quantitative understanding of the developmental and evolutionary dynamics of the gap gene network. PMID:19876378

  17. DeepARG: a deep learning approach for predicting antibiotic resistance genes from metagenomic data.

    Science.gov (United States)

    Arango-Argoty, Gustavo; Garner, Emily; Pruden, Amy; Heath, Lenwood S; Vikesland, Peter; Zhang, Liqing

    2018-02-01

    Growing concerns about increasing rates of antibiotic resistance call for expanded and comprehensive global monitoring. Advancing methods for monitoring of environmental media (e.g., wastewater, agricultural waste, food, and water) is especially needed for identifying potential resources of novel antibiotic resistance genes (ARGs), hot spots for gene exchange, and as pathways for the spread of ARGs and human exposure. Next-generation sequencing now enables direct access and profiling of the total metagenomic DNA pool, where ARGs are typically identified or predicted based on the "best hits" of sequence searches against existing databases. Unfortunately, this approach produces a high rate of false negatives. To address such limitations, we propose here a deep learning approach, taking into account a dissimilarity matrix created using all known categories of ARGs. Two deep learning models, DeepARG-SS and DeepARG-LS, were constructed for short read sequences and full gene length sequences, respectively. Evaluation of the deep learning models over 30 antibiotic resistance categories demonstrates that the DeepARG models can predict ARGs with both high precision (> 0.97) and recall (> 0.90). The models displayed an advantage over the typical best hit approach, yielding consistently lower false negative rates and thus higher overall recall (> 0.9). As more data become available for under-represented ARG categories, the DeepARG models' performance can be expected to be further enhanced due to the nature of the underlying neural networks. Our newly developed ARG database, DeepARG-DB, encompasses ARGs predicted with a high degree of confidence and extensive manual inspection, greatly expanding current ARG repositories. The deep learning models developed here offer more accurate antimicrobial resistance annotation relative to current bioinformatics practice. DeepARG does not require strict cutoffs, which enables identification of a much broader diversity of ARGs. The

  18. Inflammatory gene regulatory networks in amnion cells following cytokine stimulation: translational systems approach to modeling human parturition.

    Directory of Open Access Journals (Sweden)

    Ruth Li

    Full Text Available A majority of the studies examining the molecular regulation of human labor have been conducted using single gene approaches. While the technology to produce multi-dimensional datasets is readily available, the means for facile analysis of such data are limited. The objective of this study was to develop a systems approach to infer regulatory mechanisms governing global gene expression in cytokine-challenged cells in vitro, and to apply these methods to predict gene regulatory networks (GRNs in intrauterine tissues during term parturition. To this end, microarray analysis was applied to human amnion mesenchymal cells (AMCs stimulated with interleukin-1β, and differentially expressed transcripts were subjected to hierarchical clustering, temporal expression profiling, and motif enrichment analysis, from which a GRN was constructed. These methods were then applied to fetal membrane specimens collected in the absence or presence of spontaneous term labor. Analysis of cytokine-responsive genes in AMCs revealed a sterile immune response signature, with promoters enriched in response elements for several inflammation-associated transcription factors. In comparison to the fetal membrane dataset, there were 34 genes commonly upregulated, many of which were part of an acute inflammation gene expression signature. Binding motifs for nuclear factor-κB were prominent in the gene interaction and regulatory networks for both datasets; however, we found little evidence to support the utilization of pathogen-associated molecular pattern (PAMP signaling. The tissue specimens were also enriched for transcripts governed by hypoxia-inducible factor. The approach presented here provides an uncomplicated means to infer global relationships among gene clusters involved in cellular responses to labor-associated signals.

  19. Human Gene Therapy: Genes without Frontiers?

    Science.gov (United States)

    Simon, Eric J.

    2002-01-01

    Describes the latest advancements and setbacks in human gene therapy to provide reference material for biology teachers to use in their science classes. Focuses on basic concepts such as recombinant DNA technology, and provides examples of human gene therapy such as severe combined immunodeficiency syndrome, familial hypercholesterolemia, and…

  20. Functional Genomic Approaches for the Study of Fetal/Placental Development in Swine with Special Emphasis on Imprinted Genes

    Science.gov (United States)

    The overall focus of this chapter will be the application of functional genomic approaches for the study of the imprinted gene family in swine. While there are varied definitions of “functional genomics” in general they focus on the application of genomic approaches such as DNA microarrays, single n...

  1. Development of a Combination Cell and Gene Therapy Approach for Early-Stage Breast Cancer

    National Research Council Canada - National Science Library

    Lewis, Michael T

    2005-01-01

    The unique biology of the breast presents the opportunity to these cell and gene therapy techniques in a way that circumvents many of these technical limitations for the treatment of early stage breast cancer...

  2. A Complementary Bioinformatics Approach to Identify Potential Plant Cell Wall Glycosyltransferase-Encoding Genes

    DEFF Research Database (Denmark)

    Egelund, Jack; Skjøt, Michael; Geshi, Naomi

    2004-01-01

    Plant cell wall (CW) synthesizing enzymes can be divided into the glycan (i.e. cellulose and callose) synthases, which are multimembrane spanning proteins located at the plasma membrane, and the glycosyltransferases (GTs), which are Golgi localized single membrane spanning proteins, believed....... Although much is known with regard to composition and fine structures of the plant CW, only a handful of CW biosynthetic GT genes-all classified in the CAZy system-have been characterized. In an effort to identify CW GTs that have not yet been classified in the CAZy database, a simple bioinformatics...... approach was adopted. First, the entire Arabidopsis proteome was run through the Transmembrane Hidden Markov Model 2.0 server and proteins containing one or, more rarely, two transmembrane domains within the N-terminal 150 amino acids were collected. Second, these sequences were submitted...

  3. Analyzing the genes related to Alzheimer's disease via a network and pathway-based approach.

    Science.gov (United States)

    Hu, Yan-Shi; Xin, Juncai; Hu, Ying; Zhang, Lei; Wang, Ju

    2017-04-27

    Our understanding of the molecular mechanisms underlying Alzheimer's disease (AD) remains incomplete. Previous studies have revealed that genetic factors provide a significant contribution to the pathogenesis and development of AD. In the past years, numerous genes implicated in this disease have been identified via genetic association studies on candidate genes or at the genome-wide level. However, in many cases, the roles of these genes and their interactions in AD are still unclear. A comprehensive and systematic analysis focusing on the biological function and interactions of these genes in the context of AD will therefore provide valuable insights to understand the molecular features of the disease. In this study, we collected genes potentially associated with AD by screening publications on genetic association studies deposited in PubMed. The major biological themes linked with these genes were then revealed by function and biochemical pathway enrichment analysis, and the relation between the pathways was explored by pathway crosstalk analysis. Furthermore, the network features of these AD-related genes were analyzed in the context of human interactome and an AD-specific network was inferred using the Steiner minimal tree algorithm. We compiled 430 human genes reported to be associated with AD from 823 publications. Biological theme analysis indicated that the biological processes and biochemical pathways related to neurodevelopment, metabolism, cell growth and/or survival, and immunology were enriched in these genes. Pathway crosstalk analysis then revealed that the significantly enriched pathways could be grouped into three interlinked modules-neuronal and metabolic module, cell growth/survival and neuroendocrine pathway module, and immune response-related module-indicating an AD-specific immune-endocrine-neuronal regulatory network. Furthermore, an AD-specific protein network was inferred and novel genes potentially associated with AD were identified. By

  4. Heterologous reconstitution of the intact geodin gene cluster in Aspergillus nidulans through a simple and versatile PCR based approach.

    Directory of Open Access Journals (Sweden)

    Morten Thrane Nielsen

    Full Text Available Fungal natural products are a rich resource for bioactive molecules. To fully exploit this potential it is necessary to link genes to metabolites. Genetic information for numerous putative biosynthetic pathways has become available in recent years through genome sequencing. However, the lack of solid methodology for genetic manipulation of most species severely hampers pathway characterization. Here we present a simple PCR based approach for heterologous reconstitution of intact gene clusters. Specifically, the putative gene cluster responsible for geodin production from Aspergillus terreus was transferred in a two step procedure to an expression platform in A. nidulans. The individual cluster fragments were generated by PCR and assembled via efficient USER fusion prior to transformation and integration via re-iterative gene targeting. A total of 13 open reading frames contained in 25 kb of DNA were successfully transferred between the two species enabling geodin synthesis in A. nidulans. Subsequently, functions of three genes in the cluster were validated by genetic and chemical analyses. Specifically, ATEG_08451 (gedC encodes a polyketide synthase, ATEG_08453 (gedR encodes a transcription factor responsible for activation of the geodin gene cluster and ATEG_08460 (gedL encodes a halogenase that catalyzes conversion of sulochrin to dihydrogeodin. We expect that our approach for transferring intact biosynthetic pathways to a fungus with a well developed genetic toolbox will be instrumental in characterizing the many exciting pathways for secondary metabolite production that are currently being uncovered by the fungal genome sequencing projects.

  5. Using complementary approaches to identify trans-domain nuclear gene transfers in the extremophile Galdieria sulphuraria (Rhodophyta).

    Science.gov (United States)

    Pandey, Ravi S; Saxena, Garima; Bhattacharya, Debashish; Qiu, Huan; Azad, Rajeev K

    2017-02-01

    Identification of horizontal gene transfers (HGTs) has primarily relied on phylogenetic tree based methods, which require a rich sampling of sequenced genomes to ensure a reliable inference. Because the success of phylogenetic approaches depends on the breadth and depth of the database, researchers usually apply stringent filters to detect only the most likely gene transfers in the genomes of interest. One such study focused on a highly conservative estimate of trans-domain gene transfers in the extremophile eukaryote, Galdieria sulphuraria (Galdieri) Merola (Rhodophyta), by applying multiple filters in their phylogenetic pipeline. This led to the identification of 75 inter-domain acquisitions from Bacteria or Archaea. Because of the evolutionary, ecological, and potential biotechnological significance of foreign genes in algae, alternative approaches and pipelines complementing phylogenetics are needed for a more comprehensive assessment of HGT. We present here a novel pipeline that uncovered 17 novel foreign genes of prokaryotic origin in G. sulphuraria, results that are supported by multiple lines of evidence including composition-based, comparative data, and phylogenetics. These genes encode a variety of potentially adaptive functions, from metabolite transport to DNA repair. © 2016 Phycological Society of America.

  6. Ivacaftor: A Novel Gene-Based Therapeutic Approach for Cystic Fibrosis

    OpenAIRE

    Condren, Michelle E.; Bradshaw, Marquita D.

    2013-01-01

    Ivacaftor is a new therapeutic agent that acts at the cystic fibrosis transmembrane conductance regulator (CFTR) channel to alter activity. It is approved for use in patients 6 years and older with cystic fibrosis who have at least 1 G551D mutation in the CFTR gene. It is unlike any other current pharmacologic agent for cystic fibrosis in that it specifically targets the gene defect associated with cystic fibrosis as opposed to treating resulting symptomology. Mucoactive agents, antibiotics, ...

  7. Heterologous Reconstitution of the Intact Geodin Gene Cluster in Aspergillus nidulans through a Simple and Versatile PCR Based Approach

    DEFF Research Database (Denmark)

    Nielsen, Morten Thrane; Nielsen, Jakob Blæsbjerg; Anyaogu, Dianna Chinyere

    2013-01-01

    was transferred in a two step procedure to an expression platform in A. nidulans. The individual cluster fragments were generated by PCR and assembled via efficient USER fusion prior to ransformation and integration via re-iterative gene targeting. A total of 13 open reading frames contained in 25 kb of DNA were...... of solid methodology for genetic manipulation of most species severely hampers pathway haracterization. Here we present a simple PCR based approach for heterologous reconstitution of intact gene clusters. Specifically, the putative gene cluster responsible for geodin production from Aspergillus terreus...... successfully transferred between the two species enabling geodin synthesis in A. nidulans. Subsequently, functions of three genes in the cluster were validated by genetic and chemical analyses. Specifically, ATEG_08451 (gedC) encodes a polyketide synthase, ATEG_08453 (gedR) encodes a transcription factor...

  8. Nature versus nurture: A systematic approach to elucidate gene-environment interactions in the development of myopic refractive errors.

    Science.gov (United States)

    Miraldi Utz, Virginia

    2017-01-01

    Myopia is the most common eye disorder and major cause of visual impairment worldwide. As the incidence of myopia continues to rise, the need to further understand the complex roles of molecular and environmental factors controlling variation in refractive error is of increasing importance. Tkatchenko and colleagues applied a systematic approach using a combination of gene set enrichment analysis, genome-wide association studies, and functional analysis of a murine model to identify a myopia susceptibility gene, APLP2. Differential expression of refractive error was associated with time spent reading for those with low frequency variants in this gene. This provides support for the longstanding hypothesis of gene-environment interactions in refractive error development.

  9. Activation of pluripotency genes in human fibroblast cells by a novel mRNA based approach.

    Directory of Open Access Journals (Sweden)

    Jordan R Plews

    2010-12-01

    Full Text Available Several methods have been used to induce somatic cells to re-enter the pluripotent state. Viral transduction of reprogramming genes yields higher efficiency but involves random insertions of viral sequences into the human genome. Although induced pluripotent stem (iPS cells can be obtained with the removable PiggyBac transposon system or an episomal system, both approaches still use DNA constructs so that resulting cell lines need to be thoroughly analyzed to confirm they are free of harmful genetic modification. Thus a method to change cell fate without using DNA will be very useful in regenerative medicine.In this study, we synthesized mRNAs encoding OCT4, SOX2, cMYC, KLF4 and SV40 large T (LT and electroporated them into human fibroblast cells. Upon transfection, fibroblasts expressed these factors at levels comparable to, or higher than those in human embryonic stem (ES cells. Ectopically expressed OCT4 localized to the cell nucleus within 4 hours after mRNA introduction. Transfecting fibroblasts with a mixture of mRNAs encoding all five factors significantly increased the expression of endogenous OCT4, NANOG, DNMT3β, REX1 and SALL4. When such transfected fibroblasts were also exposed to several small molecules (valproic acid, BIX01294 and 5'-aza-2'-deoxycytidine and cultured in human embryonic stem cell (ES medium they formed small aggregates positive for alkaline phosphatase activity and OCT4 protein within 30 days.Our results demonstrate that mRNA transfection can be a useful approach to precisely control the protein expression level and short-term expression of reprogramming factors is sufficient to activate pluripotency genes in differentiated cells.

  10. Essential Bacillus subtilis genes

    DEFF Research Database (Denmark)

    Kobayashi, K.; Ehrlich, S.D.; Albertini, A.

    2003-01-01

    To estimate the minimal gene set required to sustain bacterial life in nutritious conditions, we carried out a systematic inactivation of Bacillus subtilis genes. Among approximate to4,100 genes of the organism, only 192 were shown to be indispensable by this or previous work. Another 79 genes were...... predicted to be essential. The vast majority of essential genes were categorized in relatively few domains of cell metabolism, with about half involved in information processing, one-fifth involved in the synthesis of cell envelope and the determination of cell shape and division, and one-tenth related...... to cell energetics. Only 4% of essential genes encode unknown functions. Most essential genes are present throughout a wide range of Bacteria, and almost 70% can also be found in Archaea and Eucarya. However, essential genes related to cell envelope, shape, division, and respiration tend to be lost from...

  11. Radiotechnologies and gene therapy

    International Nuclear Information System (INIS)

    Xia Jinsong

    2001-01-01

    Gene therapy is an exciting frontier in medicine today. Radiologist will make an uniquely contribution to these exciting new technologies at every level by choosing sites for targeting therapy, perfecting and establishing routes of delivery, developing imaging strategies to monitor therapy and assess gene expression, developing radiotherapeutic used of gene therapy

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

    KAUST Repository

    Abusamra, Heba; Bajic, Vladimir B.

    2016-01-01

    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

  13. An Evolutionary Genomic Approach to Identify Genes Involved in Human Birth Timing

    Science.gov (United States)

    Orabona, Guilherme; Morgan, Thomas; Haataja, Ritva; Hallman, Mikko; Puttonen, Hilkka; Menon, Ramkumar; Kuczynski, Edward; Norwitz, Errol; Snegovskikh, Victoria; Palotie, Aarno; Fellman, Vineta; DeFranco, Emily A.; Chaudhari, Bimal P.; McGregor, Tracy L.; McElroy, Jude J.; Oetjens, Matthew T.; Teramo, Kari; Borecki, Ingrid; Fay, Justin; Muglia, Louis

    2011-01-01

    Coordination of fetal maturation with birth timing is essential for mammalian reproduction. In humans, preterm birth is a disorder of profound global health significance. The signals initiating parturition in humans have remained elusive, due to divergence in physiological mechanisms between humans and model organisms typically studied. Because of relatively large human head size and narrow birth canal cross-sectional area compared to other primates, we hypothesized that genes involved in parturition would display accelerated evolution along the human and/or higher primate phylogenetic lineages to decrease the length of gestation and promote delivery of a smaller fetus that transits the birth canal more readily. Further, we tested whether current variation in such accelerated genes contributes to preterm birth risk. Evidence from allometric scaling of gestational age suggests human gestation has been shortened relative to other primates. Consistent with our hypothesis, many genes involved in reproduction show human acceleration in their coding or adjacent noncoding regions. We screened >8,400 SNPs in 150 human accelerated genes in 165 Finnish preterm and 163 control mothers for association with preterm birth. In this cohort, the most significant association was in FSHR, and 8 of the 10 most significant SNPs were in this gene. Further evidence for association of a linkage disequilibrium block of SNPs in FSHR, rs11686474, rs11680730, rs12473870, and rs1247381 was found in African Americans. By considering human acceleration, we identified a novel gene that may be associated with preterm birth, FSHR. We anticipate other human accelerated genes will similarly be associated with preterm birth risk and elucidate essential pathways for human parturition. PMID:21533219

  14. Phylogeny of haemosporidian blood parasites revealed by a multi-gene approach.

    Science.gov (United States)

    Borner, Janus; Pick, Christian; Thiede, Jenny; Kolawole, Olatunji Matthew; Kingsley, Manchang Tanyi; Schulze, Jana; Cottontail, Veronika M; Wellinghausen, Nele; Schmidt-Chanasit, Jonas; Bruchhaus, Iris; Burmester, Thorsten

    2016-01-01

    The apicomplexan order Haemosporida is a clade of unicellular blood parasites that infect a variety of reptilian, avian and mammalian hosts. Among them are the agents of human malaria, parasites of the genus Plasmodium, which pose a major threat to human health. Illuminating the evolutionary history of Haemosporida may help us in understanding their enormous biological diversity, as well as tracing the multiple host switches and associated acquisitions of novel life-history traits. However, the deep-level phylogenetic relationships among major haemosporidian clades have remained enigmatic because the datasets employed in phylogenetic analyses were severely limited in either gene coverage or taxon sampling. Using a PCR-based approach that employs a novel set of primers, we sequenced fragments of 21 nuclear genes from seven haemosporidian parasites of the genera Leucocytozoon, Haemoproteus, Parahaemoproteus, Polychromophilus and Plasmodium. After addition of genomic data from 25 apicomplexan species, the unreduced alignment comprised 20,580 bp from 32 species. Phylogenetic analyses were performed based on nucleotide, codon and amino acid data employing Bayesian inference, maximum likelihood and maximum parsimony. All analyses resulted in highly congruent topologies. We found consistent support for a basal position of Leucocytozoon within Haemosporida. In contrast to all previous studies, we recovered a sister group relationship between the genera Polychromophilus and Plasmodium. Within Plasmodium, the sauropsid and mammal-infecting lineages were recovered as sister clades. Support for these relationships was high in nearly all trees, revealing a novel phylogeny of Haemosporida, which is robust to the choice of the outgroup and the method of tree inference. Copyright © 2015 Elsevier Inc. All rights reserved.

  15. Linking genes to microbial growth kinetics: an integrated biochemical systems engineering approach.

    Science.gov (United States)

    Koutinas, Michalis; Kiparissides, Alexandros; Silva-Rocha, Rafael; Lam, Ming-Chi; Martins Dos Santos, Vitor A P; de Lorenzo, Victor; Pistikopoulos, Efstratios N; Mantalaris, Athanasios

    2011-07-01

    The majority of models describing the kinetic properties of a microorganism for a given substrate are unstructured and empirical. They are formulated in this manner so that the complex mechanism of cell growth is simplified. Herein, a novel approach for modelling microbial growth kinetics is proposed, linking biomass growth and substrate consumption rates to the gene regulatory programmes that control these processes. A dynamic model of the TOL (pWW0) plasmid of Pseudomonas putida mt-2 has been developed, describing the molecular interactions that lead to the transcription of the upper and meta operons, known to produce the enzymes for the oxidative catabolism of m-xylene. The genetic circuit model was combined with a growth kinetic model decoupling biomass growth and substrate consumption rates, which are expressed as independent functions of the rate-limiting enzymes produced by the operons. Estimation of model parameters and validation of the model's predictive capability were successfully performed in batch cultures of mt-2 fed with different concentrations of m-xylene, as confirmed by relative mRNA concentration measurements of the promoters encoded in TOL. The growth formation and substrate utilisation patterns could not be accurately described by traditional Monod-type models for a wide range of conditions, demonstrating the critical importance of gene regulation for the development of advanced models closely predicting complex bioprocesses. In contrast, the proposed strategy, which utilises quantitative information pertaining to upstream molecular events that control the production of rate-limiting enzymes, predicts the catabolism of a substrate and biomass formation and could be of central importance for the design of optimal bioprocesses. Copyright © 2011 Elsevier Inc. All rights reserved.

  16. Chassis organism from Corynebacterium glutamicum--a top-down approach to identify and delete irrelevant gene clusters.

    Science.gov (United States)

    Unthan, Simon; Baumgart, Meike; Radek, Andreas; Herbst, Marius; Siebert, Daniel; Brühl, Natalie; Bartsch, Anna; Bott, Michael; Wiechert, Wolfgang; Marin, Kay; Hans, Stephan; Krämer, Reinhard; Seibold, Gerd; Frunzke, Julia; Kalinowski, Jörn; Rückert, Christian; Wendisch, Volker F; Noack, Stephan

    2015-02-01

    For synthetic biology applications, a robust structural basis is required, which can be constructed either from scratch or in a top-down approach starting from any existing organism. In this study, we initiated the top-down construction of a chassis organism from Corynebacterium glutamicum ATCC 13032, aiming for the relevant gene set to maintain its fast growth on defined medium. We evaluated each native gene for its essentiality considering expression levels, phylogenetic conservation, and knockout data. Based on this classification, we determined 41 gene clusters ranging from 3.7 to 49.7 kbp as target sites for deletion. 36 deletions were successful and 10 genome-reduced strains showed impaired growth rates, indicating that genes were hit, which are relevant to maintain biological fitness at wild-type level. In contrast, 26 deleted clusters were found to include exclusively irrelevant genes for growth on defined medium. A combinatory deletion of all irrelevant gene clusters would, in a prophage-free strain, decrease the size of the native genome by about 722 kbp (22%) to 2561 kbp. Finally, five combinatory deletions of irrelevant gene clusters were investigated. The study introduces the novel concept of relevant genes and demonstrates general strategies to construct a chassis suitable for biotechnological application. © 2014 The Authors. Biotechnology Journal published by Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim. This is an open access article under the terms of the Creative Commons Attribution-Non-Commercial-NoDerivs Licence, which permits use and distribution in any medium, provided the original work is properly cited, the use is non- commercial and no modifications or adaptations are made.

  17. Systems approach identifies an organic nitrogen-responsive gene network that is regulated by the master clock control gene CCA1.

    Science.gov (United States)

    Gutiérrez, Rodrigo A; Stokes, Trevor L; Thum, Karen; Xu, Xiaodong; Obertello, Mariana; Katari, Manpreet S; Tanurdzic, Milos; Dean, Alexis; Nero, Damion C; McClung, C Robertson; Coruzzi, Gloria M

    2008-03-25

    Understanding how nutrients affect gene expression will help us to understand the mechanisms controlling plant growth and development as a function of nutrient availability. Nitrate has been shown to serve as a signal for the control of gene expression in Arabidopsis. There is also evidence, on a gene-by-gene basis, that downstream products of nitrogen (N) assimilation such as glutamate (Glu) or glutamine (Gln) might serve as signals of organic N status that in turn regulate gene expression. To identify genome-wide responses to such organic N signals, Arabidopsis seedlings were transiently treated with ammonium nitrate in the presence or absence of MSX, an inhibitor of glutamine synthetase, resulting in a block of Glu/Gln synthesis. Genes that responded to organic N were identified as those whose response to ammonium nitrate treatment was blocked in the presence of MSX. We showed that some genes previously identified to be regulated by nitrate are under the control of an organic N-metabolite. Using an integrated network model of molecular interactions, we uncovered a subnetwork regulated by organic N that included CCA1 and target genes involved in N-assimilation. We validated some of the predicted interactions and showed that regulation of the master clock control gene CCA1 by Glu or a Glu-derived metabolite in turn regulates the expression of key N-assimilatory genes. Phase response curve analysis shows that distinct N-metabolites can advance or delay the CCA1 phase. Regulation of CCA1 by organic N signals may represent a novel input mechanism for N-nutrients to affect plant circadian clock function.

  18. A systems approach identifies networks and genes linking sleep and stress: implications for neuropsychiatric disorders.

    Science.gov (United States)

    Jiang, Peng; Scarpa, Joseph R; Fitzpatrick, Karrie; Losic, Bojan; Gao, Vance D; Hao, Ke; Summa, Keith C; Yang, He S; Zhang, Bin; Allada, Ravi; Vitaterna, Martha H; Turek, Fred W; Kasarskis, Andrew

    2015-05-05

    Sleep dysfunction and stress susceptibility are comorbid complex traits that often precede and predispose patients to a variety of neuropsychiatric diseases. Here, we demonstrate multilevel organizations of genetic landscape, candidate genes, and molecular networks associated with 328 stress and sleep traits in a chronically stressed population of 338 (C57BL/6J × A/J) F2 mice. We constructed striatal gene co-expression networks, revealing functionally and cell-type-specific gene co-regulations important for stress and sleep. Using a composite ranking system, we identified network modules most relevant for 15 independent phenotypic categories, highlighting a mitochondria/synaptic module that links sleep and stress. The key network regulators of this module are overrepresented with genes implicated in neuropsychiatric diseases. Our work suggests that the interplay among sleep, stress, and neuropathology emerges from genetic influences on gene expression and their collective organization through complex molecular networks, providing a framework for interrogating the mechanisms underlying sleep, stress susceptibility, and related neuropsychiatric disorders. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

  19. Comparison of weighting approaches for genetic risk scores in gene-environment interaction studies.

    Science.gov (United States)

    Hüls, Anke; Krämer, Ursula; Carlsten, Christopher; Schikowski, Tamara; Ickstadt, Katja; Schwender, Holger

    2017-12-16

    Weighted genetic risk scores (GRS), defined as weighted sums of risk alleles of single nucleotide polymorphisms (SNPs), are statistically powerful for detection gene-environment (GxE) interactions. To assign weights, the gold standard is to use external weights from an independent study. However, appropriate external weights are not always available. In such situations and in the presence of predominant marginal genetic effects, we have shown in a previous study that GRS with internal weights from marginal genetic effects ("GRS-marginal-internal") are a powerful and reliable alternative to single SNP approaches or the use of unweighted GRS. However, this approach might not be appropriate for detecting predominant interactions, i.e. interactions showing an effect stronger than the marginal genetic effect. In this paper, we present a weighting approach for such predominant interactions ("GRS-interaction-training") in which parts of the data are used to estimate the weights from the interaction terms and the remaining data are used to determine the GRS. We conducted a simulation study for the detection of GxE interactions in which we evaluated power, type I error and sign-misspecification. We compared this new weighting approach to the GRS-marginal-internal approach and to GRS with external weights. Our simulation study showed that in the absence of external weights and with predominant interaction effects, the highest power was reached with the GRS-interaction-training approach. If marginal genetic effects were predominant, the GRS-marginal-internal approach was more appropriate. Furthermore, the power to detect interactions reached by the GRS-interaction-training approach was only slightly lower than the power achieved by GRS with external weights. The power of the GRS-interaction-training approach was confirmed in a real data application to the Traffic, Asthma and Genetics (TAG) Study (N = 4465 observations). When appropriate external weights are unavailable, we

  20. A PiggyBac-mediated approach for muscle gene transfer or cell therapy

    Directory of Open Access Journals (Sweden)

    Déborah Ley

    2014-11-01

    Full Text Available An emerging therapeutic approach for Duchenne muscular dystrophy is the transplantation of autologous myogenic progenitor cells genetically modified to express dystrophin. The use of this approach is challenged by the difficulty in maintaining these cells ex vivo while keeping their myogenic potential, and ensuring sufficient transgene expression following their transplantation and myogenic differentiation in vivo. We investigated the use of the piggyBac transposon system to achieve stable gene expression when transferred to cultured mesoangioblasts and into murine muscles. Without selection, up to 8% of the mesoangioblasts expressed the transgene from 1 to 2 genomic copies of the piggyBac vector. Integration occurred mostly in intergenic genomic DNA and transgene expression was stable in vitro. Intramuscular transplantation of mouse Tibialis anterior muscles with mesoangioblasts containing the transposon led to sustained myofiber GFP expression in vivo. In contrast, the direct electroporation of the transposon-donor plasmids in the mouse Tibialis muscles in vivo did not lead to sustained transgene expression despite molecular evidence of piggyBac transposition in vivo. Together these findings provide a proof-of-principle that piggyBac transposon may be considered for mesoangioblast cell-based therapies of muscular dystrophies.

  1. A New Two-Step Approach for Hands-On Teaching of Gene Technology: Effects on Students' Activities During Experimentation in an Outreach Gene Technology Lab

    Science.gov (United States)

    Scharfenberg, Franz-Josef; Bogner, Franz X.

    2011-08-01

    Emphasis on improving higher level biology education continues. A new two-step approach to the experimental phases within an outreach gene technology lab, derived from cognitive load theory, is presented. We compared our approach using a quasi-experimental design with the conventional one-step mode. The difference consisted of additional focused discussions combined with students writing down their ideas (step one) prior to starting any experimental procedure (step two). We monitored students' activities during the experimental phases by continuously videotaping 20 work groups within each approach ( N = 131). Subsequent classification of students' activities yielded 10 categories (with well-fitting intra- and inter-observer scores with respect to reliability). Based on the students' individual time budgets, we evaluated students' roles during experimentation from their prevalent activities (by independently using two cluster analysis methods). Independently of the approach, two common clusters emerged, which we labeled as `all-rounders' and as `passive students', and two clusters specific to each approach: `observers' as well as `high-experimenters' were identified only within the one-step approach whereas under the two-step conditions `managers' and `scribes' were identified. Potential changes in group-leadership style during experimentation are discussed, and conclusions for optimizing science teaching are drawn.

  2. A data mining approach for classifying DNA repair genes into ageing-related or non-ageing-related

    Directory of Open Access Journals (Sweden)

    Vasieva Olga

    2011-01-01

    Full Text Available Abstract Background The ageing of the worldwide population means there is a growing need for research on the biology of ageing. DNA damage is likely a key contributor to the ageing process and elucidating the role of different DNA repair systems in ageing is of great interest. In this paper we propose a data mining approach, based on classification methods (decision trees and Naive Bayes, for analysing data about human DNA repair genes. The goal is to build classification models that allow us to discriminate between ageing-related and non-ageing-related DNA repair genes, in order to better understand their different properties. Results The main patterns discovered by the classification methods are as follows: (a the number of protein-protein interactions was a predictor of DNA repair proteins being ageing-related; (b the use of predictor attributes based on protein-protein interactions considerably increased predictive accuracy of attributes based on Gene Ontology (GO annotations; (c GO terms related to "response to stimulus" seem reasonably good predictors of ageing-relatedness for DNA repair genes; (d interaction with the XRCC5 (Ku80 protein is a strong predictor of ageing-relatedness for DNA repair genes; and (e DNA repair genes with a high expression in T lymphocytes are more likely to be ageing-related. Conclusions The above patterns are broadly integrated in an analysis discussing relations between Ku, the non-homologous end joining DNA repair pathway, ageing and lymphocyte development. These patterns and their analysis support non-homologous end joining double strand break repair as central to the ageing-relatedness of DNA repair genes. Our work also showcases the use of protein interaction partners to improve accuracy in data mining methods and our approach could be applied to other ageing-related pathways.

  3. Gene therapy and its implications in Periodontics

    Science.gov (United States)

    Mahale, Swapna; Dani, Nitin; Ansari, Shumaila S.; Kale, Triveni

    2009-01-01

    Gene therapy is a field of Biomedicine. With the advent of gene therapy in dentistry, significant progress has been made in the control of periodontal diseases and reconstruction of dento-alveolar apparatus. Implementation in periodontics include: -As a mode of tissue engineering with three approaches: cell, protein-based and gene delivery approach. -Genetic approach to Biofilm Antibiotic Resistance. Future strategies of gene therapy in preventing periodontal diseases: -Enhances host defense mechanism against infection by transfecting host cells with an antimicrobial peptide protein-encoding gene. -Periodontal vaccination. Gene therapy is one of the recent entrants and its applications in the field of periodontics are reviewed in general here. PMID:20376232

  4. Different approaches in the molecular analysis of the SHOX gene dysfunctions.

    Science.gov (United States)

    Stuppia, L; Gatta, V; Antonucci, I; Giuliani, R; Palka, G

    2010-06-01

    Deficit of the short stature homeobox containing gene (SHOX) accounts for 2.15% of cases of idiopathic short stature (ISS) and 50-100% of cases of Leri-Weill dyschondrosteosis (LWD). It has been demonstrated that patients with SHOX deficit show a good response to treatment with GH. Thus, the early identification of SHOX alterations is a crucial point in order to choose the best treatment for ISS and LWD patients. In this study, we analyze the most commonly used molecular techniques for the detection of SHOX gene alterations. multiple ligation-dependent probe amplification analysis appears to represent the gold standard for the detection of deletion involving the SHOX gene or the enhancer region, being able to show both alterations in a single assay.

  5. Variants of the HNF1α gene: a molecular approach concerning diabetic patients from southern Brazil

    Directory of Open Access Journals (Sweden)

    Naieli Bonatto

    2012-01-01

    Full Text Available Maturity Onset Diabetes of the Young (MODY presents monogenic inheritance and mutation factors which have already been identified in six different genes. Given the wide molecular variation present in the hepatocyte nuclear factor-1α gene (HNF1α MODY3, the aimof this study was to amplify and sequence the coding regions of this gene in seven patients from the Campos Gerais region, Paraná State, Brazil, presenting clinical MODY3 features. Besides the synonymous variations, A15A, L17L, Q141Q, G288G and T515T, two missense mutations, I27L and A98V, were also detected. Clinical and laboratory data obtained from patients were compared with the molecular findings, including the I27L polymorphism that was revealed in some overweight/obese diabetic patients of this study, this corroborating with the literature. We found certain DNA variations that could explain the hyperglycemic phenotype of the patients.

  6. HisB as novel selection marker for gene targeting approaches in Aspergillus niger.

    Science.gov (United States)

    Fiedler, Markus R M; Gensheimer, Tarek; Kubisch, Christin; Meyer, Vera

    2017-03-08

    For Aspergillus niger, a broad set of auxotrophic and dominant resistance markers is available. However, only few offer targeted modification of a gene of interest into or at a genomic locus of choice, which hampers functional genomics studies. We thus aimed to extend the available set by generating a histidine auxotrophic strain with a characterized hisB locus for targeted gene integration and deletion in A. niger. A histidine-auxotrophic strain was established via disruption of the A. niger hisB gene by using the counterselectable pyrG marker. After curing, a hisB - , pyrG - strain was obtained, which served as recipient strain for further studies. We show here that both hisB orthologs from A. nidulans and A. niger can be used to reestablish histidine prototrophy in this recipient strain. Whereas the hisB gene from A. nidulans was suitable for efficient gene targeting at different loci in A. niger, the hisB gene from A. niger allowed efficient integration of a Tet-on driven luciferase reporter construct at the endogenous non-functional hisB locus. Subsequent analysis of the luciferase activity revealed that the hisB locus is tight under non-inducing conditions and allows even higher luciferase expression levels compared to the pyrG integration locus. Taken together, we provide here an alternative selection marker for A. niger, hisB, which allows efficient homologous integration rates as well as high expression levels which compare favorably to the well-established pyrG selection marker.

  7. Feminizing Wolbachia: a transcriptomics approach with insights on the immune response genes in Armadillidium vulgare

    Directory of Open Access Journals (Sweden)

    Chevalier Frédéric

    2012-01-01

    Full Text Available Abstract Background Wolbachia are vertically transmitted bacteria known to be the most widespread endosymbiont in arthropods. They induce various alterations of the reproduction of their host, including feminization of genetic males in isopod crustaceans. In the pill bug Armadillidium vulgare, the presence of Wolbachia is also associated with detrimental effects on host fertility and lifespan. Deleterious effects have been demonstrated on hemocyte density, phenoloxidase activity, and natural hemolymph septicemia, suggesting that infected individuals could have defective immune capacities. Since nothing is known about the molecular mechanisms involved in Wolbachia-A. vulgare interactions and its secondary immunocompetence modulation, we developed a transcriptomics strategy and compared A. vulgare gene expression between Wolbachia-infected animals (i.e., “symbiotic” animals and uninfected ones (i.e., “asymbiotic” animals as well as between animals challenged or not challenged by a pathogenic bacteria. Results Since very little genetic data is available on A. vulgare, we produced several EST libraries and generated a total of 28 606 ESTs. Analyses of these ESTs revealed that immune processes were over-represented in most experimental conditions (responses to a symbiont and to a pathogen. Considering canonical crustacean immune pathways, these genes encode antimicrobial peptides or are involved in pathogen recognition, detoxification, and autophagy. By RT-qPCR, we demonstrated a general trend towards gene under-expression in symbiotic whole animals and ovaries whereas the same gene set tends to be over-expressed in symbiotic immune tissues. Conclusion This study allowed us to generate the first reference transcriptome ever obtained in the Isopoda group and to identify genes involved in the major known crustacean immune pathways encompassing cellular and humoral responses. Expression of immune-related genes revealed a modulation of host

  8. Keratinocyte Growth Factor Gene Electroporation into Skeletal Muscle as a Novel Gene Therapeutic Approach for Elastase-Induced Pulmonary Emphysema in Mice

    International Nuclear Information System (INIS)

    Tobinaga, Shuichi; Matsumoto, Keitaro; Nagayasu, Takeshi; Furukawa, Katsuro; Abo, Takafumi; Yamasaki, Naoya; Tsuchiya, Tomoshi; Miyazaki, Takuro; Koji, Takehiko

    2015-01-01

    Pulmonary emphysema is a progressive disease with airspace destruction and an effective therapy is needed. Keratinocyte growth factor (KGF) promotes pulmonary epithelial proliferation and has the potential to induce lung regeneration. The aim of this study was to determine the possibility of using KGF gene therapy for treatment of a mouse emphysema model induced by porcine pancreatic elastase (PPE). Eight-week-old BALB/c male mice treated with intra-tracheal PPE administration were transfected with 80 μg of a recombinant human KGF (rhKGF)-expressing FLAG-CMV14 plasmid (pKGF-FLAG gene), or with the pFLAG gene expressing plasmid as a control, into the quadriceps muscle by electroporation. In the lung, the expression of proliferating cell nuclear antigen (PCNA) was augmented, and surfactant protein A (SP-A) and KGF receptor (KGFR) were co-expressed in PCNA-positive cells. Moreover, endogenous KGF and KGFR gene expression increased significantly by pKGF-FLAG gene transfection. Arterial blood gas analysis revealed that the PaO 2 level was not significantly reduced on day 14 after PPE instillation with pKGF-FLAG gene transfection compared to that of normal mice. These results indicated that KGF gene therapy with electroporation stimulated lung epithelial proliferation and protected depression of pulmonary function in a mouse emphysema model, suggesting a possible method of treating pulmonary emphysema

  9. Synthetic sustained gene delivery systems.

    Science.gov (United States)

    Agarwal, Ankit; Mallapragada, Surya K

    2008-01-01

    Gene therapy today is hampered by the need of a safe and efficient gene delivery system that can provide a sustained therapeutic effect without cytotoxicity or unwanted immune responses. Bolus gene delivery in solution results in the loss of delivered factors via lymphatic system and may cause undesired effects by the escape of bioactive molecules to distant sites. Controlled gene delivery systems, acting as localized depot of genes, provide an extended sustained release of genes, giving prolonged maintenance of the therapeutic level of encoded proteins. They also limit the DNA degradation in the nuclease rich extra-cellular environment. While attempts have been made to adapt existing controlled drug delivery technologies, more novel approaches are being investigated for controlled gene delivery. DNA encapsulated in nano/micro spheres of polymers have been administered systemically/orally to be taken up by the targeted tissues and provide sustained release once internalized. Alternatively, DNA entrapped in hydrogels or scaffolds have been injected/implanted in tissues/cavities as platforms for gene delivery. The present review examines these different modalities for sustained delivery of viral and non-viral gene-delivery vectors. Design parameters and release mechanisms of different systems made with synthetic or natural polymers are presented along with their prospective applications and opportunities for continuous development.

  10. Gene Therapy for Parkinson's Disease

    Directory of Open Access Journals (Sweden)

    Rachel Denyer

    2012-01-01

    Full Text Available Current pharmacological and surgical treatments for Parkinson's disease offer symptomatic improvements to those suffering from this incurable degenerative neurological disorder, but none of these has convincingly shown effects on disease progression. Novel approaches based on gene therapy have several potential advantages over conventional treatment modalities. These could be used to provide more consistent dopamine supplementation, potentially providing superior symptomatic relief with fewer side effects. More radically, gene therapy could be used to correct the imbalances in basal ganglia circuitry associated with the symptoms of Parkinson's disease, or to preserve or restore dopaminergic neurons lost during the disease process itself. The latter neuroprotective approach is the most exciting, as it could theoretically be disease modifying rather than simply symptom alleviating. Gene therapy agents using these approaches are currently making the transition from the laboratory to the bedside. This paper summarises the theoretical approaches to gene therapy for Parkinson's disease and the findings of clinical trials in this rapidly changing field.

  11. 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 ...

  12. Bioinformatic approach in the identification of arabidopsis gene homologous in amaranthus

    Directory of Open Access Journals (Sweden)

    Jana Žiarovská

    2015-05-01

    Full Text Available Bioinfomatics offers an efficient tool for molecular genetics applications and sequence homology search algorithms became an inevitable part for many different research strategies. Appropriate managing of known data that are stored in public available databases can be used in many ways in the research. Here, we report the identification of RmlC-like cupins superfamily protein DNA sequence than is known in Arabidopsis genome for the Amaranthus - plant specie where this sequence was still not sequenced. A BLAST based approach was used to identify the homologous sequences in the nucleotide database and to find suitable parts of the Arabidopsis sequence were primers can be designed. In total, 64 hits were found in nucleotide database for Arabidopsis RmlC-like cupins sequence. A query cover ranged from 10% up to the 100% among RmlC-like cupins nucleotides and its homologues that are actually stored in public nucleotide databases. The most conserved region was identified for matches that posses nucleotides in the range of 1506 up to the 1925 bp of RmlC-like cupins DNA sequence stored in the database. The in silico approach was subsequently used in PCR analysis where the specifity of designed primers was approved. A unique, 250 bp long fragment was obtained for Amaranthus cruentus and a hybride Amaranthus hypochondriacus x hybridus in our analysis. Bioinformatic based analysis of unknown parts of the plant genomes as showed in this study is a very good additional tool in PCR based analysis of plant variability. This approach is suitable in the case for plants, where concrete genomic data are still missing for the appropriate genes, as was demonstrated for Amaranthus. 

  13. Primetime for Learning Genes.

    Science.gov (United States)

    Keifer, Joyce

    2017-02-11

    Learning genes in mature neurons are uniquely suited to respond rapidly to specific environmental stimuli. Expression of individual learning genes, therefore, requires regulatory mechanisms that have the flexibility to respond with transcriptional activation or repression to select appropriate physiological and behavioral responses. Among the mechanisms that equip genes to respond adaptively are bivalent domains. These are specific histone modifications localized to gene promoters that are characteristic of both gene activation and repression, and have been studied primarily for developmental genes in embryonic stem cells. In this review, studies of the epigenetic regulation of learning genes in neurons, particularly the brain-derived neurotrophic factor gene ( BDNF ), by methylation/demethylation and chromatin modifications in the context of learning and memory will be highlighted. Because of the unique function of learning genes in the mature brain, it is proposed that bivalent domains are a characteristic feature of the chromatin landscape surrounding their promoters. This allows them to be "poised" for rapid response to activate or repress gene expression depending on environmental stimuli.

  14. A systems biology approach to construct the gene regulatory network of systemic inflammation via microarray and databases mining

    Directory of Open Access Journals (Sweden)

    Lan Chung-Yu

    2008-09-01

    Full Text Available Abstract Background Inflammation is a hallmark of many human diseases. Elucidating the mechanisms underlying systemic inflammation has long been an important topic in basic and clinical research. When primary pathogenetic events remains unclear due to its immense complexity, construction and analysis of the gene regulatory network of inflammation at times becomes the best way to understand the detrimental effects of disease. However, it is difficult to recognize and evaluate relevant biological processes from the huge quantities of experimental data. It is hence appealing to find an algorithm which can generate a gene regulatory network of systemic inflammation from high-throughput genomic studies of human diseases. Such network will be essential for us to extract valuable information from the complex and chaotic network under diseased conditions. Results In this study, we construct a gene regulatory network of inflammation using data extracted from the Ensembl and JASPAR databases. We also integrate and apply a number of systematic algorithms like cross correlation threshold, maximum likelihood estimation method and Akaike Information Criterion (AIC on time-lapsed microarray data to refine the genome-wide transcriptional regulatory network in response to bacterial endotoxins in the context of dynamic activated genes, which are regulated by transcription factors (TFs such as NF-κB. This systematic approach is used to investigate the stochastic interaction represented by the dynamic leukocyte gene expression profiles of human subject exposed to an inflammatory stimulus (bacterial endotoxin. Based on the kinetic parameters of the dynamic gene regulatory network, we identify important properties (such as susceptibility to infection of the immune system, which may be useful for translational research. Finally, robustness of the inflammatory gene network is also inferred by analyzing the hubs and "weak ties" structures of the gene network

  15. Integrating Ontological Knowledge and Textual Evidence in Estimating Gene and Gene Product Similarity

    Energy Technology Data Exchange (ETDEWEB)

    Sanfilippo, Antonio P.; Posse, Christian; Gopalan, Banu; Tratz, Stephen C.; Gregory, Michelle L.

    2006-06-08

    With the rising influence of the Gene On-tology, new approaches have emerged where the similarity between genes or gene products is obtained by comparing Gene Ontology code annotations associ-ated with them. So far, these approaches have solely relied on the knowledge en-coded in the Gene Ontology and the gene annotations associated with the Gene On-tology database. The goal of this paper is to demonstrate that improvements to these approaches can be obtained by integrating textual evidence extracted from relevant biomedical literature.

  16. A simple but highly effective approach to evaluate the prognostic performance of gene expression signatures.

    Directory of Open Access Journals (Sweden)

    Maud H W Starmans

    Full Text Available BACKGROUND: Highly parallel analysis of gene expression has recently been used to identify gene sets or 'signatures' to improve patient diagnosis and risk stratification. Once a signature is generated, traditional statistical testing is used to evaluate its prognostic performance. However, due to the dimensionality of microarrays, this can lead to false interpretation of these signatures. PRINCIPAL FINDINGS: A method was developed to test batches of a user-specified number of randomly chosen signatures in patient microarray datasets. The percentage of random generated signatures yielding prognostic value was assessed using ROC analysis by calculating the area under the curve (AUC in six public available cancer patient microarray datasets. We found that a signature consisting of randomly selected genes has an average 10% chance of reaching significance when assessed in a single dataset, but can range from 1% to ∼40% depending on the dataset in question. Increasing the number of validation datasets markedly reduces this number. CONCLUSIONS: We have shown that the use of an arbitrary cut-off value for evaluation of signature significance is not suitable for this type of research, but should be defined for each dataset separately. Our method can be used to establish and evaluate signature performance of any derived gene signature in a dataset by comparing its performance to thousands of randomly generated signatures. It will be of most interest for cases where few data are available and testing in multiple datasets is limited.

  17. Predictive minimum description length principle approach to inferring gene regulatory networks.

    Science.gov (United States)

    Chaitankar, Vijender; Zhang, Chaoyang; Ghosh, Preetam; Gong, Ping; Perkins, Edward J; Deng, Youping

    2011-01-01

    Reverse engineering of gene regulatory networks using information theory models has received much attention due to its simplicity, low computational cost, and capability of inferring large networks. One of the major problems with information theory models is to determine the threshold that defines the regulatory relationships between genes. The minimum description length (MDL) principle has been implemented to overcome this problem. The description length of the MDL principle is the sum of model length and data encoding length. A user-specified fine tuning parameter is used as control mechanism between model and data encoding, but it is difficult to find the optimal parameter. In this work, we propose a new inference algorithm that incorporates mutual information (MI), conditional mutual information (CMI), and predictive minimum description length (PMDL) principle to infer gene regulatory networks from DNA microarray data. In this algorithm, the information theoretic quantities MI and CMI determine the regulatory relationships between genes and the PMDL principle method attempts to determine the best MI threshold without the need of a user-specified fine tuning parameter. The performance of the proposed algorithm is evaluated using both synthetic time series data sets and a biological time series data set (Saccharomyces cerevisiae). The results show that the proposed algorithm produced fewer false edges and significantly improved the precision when compared to existing MDL algorithm.

  18. Genetic Susceptibility to Vitiligo: GWAS Approaches for Identifying Vitiligo Susceptibility Genes and Loci

    Science.gov (United States)

    Shen, Changbing; Gao, Jing; Sheng, Yujun; Dou, Jinfa; Zhou, Fusheng; Zheng, Xiaodong; Ko, Randy; Tang, Xianfa; Zhu, Caihong; Yin, Xianyong; Sun, Liangdan; Cui, Yong; Zhang, Xuejun

    2016-01-01

    Vitiligo is an autoimmune disease with a strong genetic component, characterized by areas of depigmented skin resulting from loss of epidermal melanocytes. Genetic factors are known to play key roles in vitiligo through discoveries in association studies and family studies. Previously, vitiligo susceptibility genes were mainly revealed through linkage analysis and candidate gene studies. Recently, our understanding of the genetic basis of vitiligo has been rapidly advancing through genome-wide association study (GWAS). More than 40 robust susceptible loci have been identified and confirmed to be associated with vitiligo by using GWAS. Most of these associated genes participate in important pathways involved in the pathogenesis of vitiligo. Many susceptible loci with unknown functions in the pathogenesis of vitiligo have also been identified, indicating that additional molecular mechanisms may contribute to the risk of developing vitiligo. In this review, we summarize the key loci that are of genome-wide significance, which have been shown to influence vitiligo risk. These genetic loci may help build the foundation for genetic diagnosis and personalize treatment for patients with vitiligo in the future. However, substantial additional studies, including gene-targeted and functional studies, are required to confirm the causality of the genetic variants and their biological relevance in the development of vitiligo. PMID:26870082

  19. Functional Associations by Response Overlap (FARO), a functional genomics approach matching gene expression phenotypes

    DEFF Research Database (Denmark)

    Nielsen, Henrik Bjørn; Mundy, J.; Willenbrock, Hanni

    2007-01-01

    The systematic comparison of transcriptional responses of organisms is a powerful tool in functional genomics. For example, mutants may be characterized by comparing their transcript profiles to those obtained in other experiments querying the effects on gene expression of many experimental facto...

  20. Using the gene ontology to scan multilevel gene sets for associations in genome wide association studies.

    Science.gov (United States)

    Schaid, Daniel J; Sinnwell, Jason P; Jenkins, Gregory D; McDonnell, Shannon K; Ingle, James N; Kubo, Michiaki; Goss, Paul E; Costantino, Joseph P; Wickerham, D Lawrence; Weinshilboum, Richard M

    2012-01-01

    Gene-set analyses have been widely used in gene expression studies, and some of the developed methods have been extended to genome wide association studies (GWAS). Yet, complications due to linkage disequilibrium (LD) among single nucleotide polymorphisms (SNPs), and variable numbers of SNPs per gene and genes per gene-set, have plagued current approaches, often leading to ad hoc "fixes." To overcome some of the current limitations, we developed a general approach to scan GWAS SNP data for both gene-level and gene-set analyses, building on score statistics for generalized linear models, and taking advantage of the directed acyclic graph structure of the gene ontology when creating gene-sets. However, other types of gene-set structures can be used, such as the popular Kyoto Encyclopedia of Genes and Genomes (KEGG). Our approach combines SNPs into genes, and genes into gene-sets, but assures that positive and negative effects of genes on a trait do not cancel. To control for multiple testing of many gene-sets, we use an efficient computational strategy that accounts for LD and provides accurate step-down adjusted P-values for each gene-set. Application of our methods to two different GWAS provide guidance on the potential strengths and weaknesses of our proposed gene-set analyses. © 2011 Wiley Periodicals, Inc.

  1. Gene therapy for hemophilia

    Science.gov (United States)

    Rogers, Geoffrey L.; Herzog, Roland W.

    2015-01-01

    Hemophilia is an X-linked inherited bleeding disorder consisting of two classifications, hemophilia A and hemophilia B, depending on the underlying mutation. Although the disease is currently treatable with intravenous delivery of replacement recombinant clotting factor, this approach represents a significant cost both monetarily and in terms of quality of life. Gene therapy is an attractive alternative approach to the treatment of hemophilia that would ideally provide life-long correction of clotting activity with a single injection. In this review, we will discuss the multitude of approaches that have been explored for the treatment of both hemophilia A and B, including both in vivo and ex vivo approaches with viral and nonviral delivery vectors. PMID:25553466

  2. Test of critical steps towards a combined cell and gene therapy approach for the treatment of Duchenne muscular dystrophy

    DEFF Research Database (Denmark)

    Kajhøj, Tine Qvistgaard; Duch, Mogens R.; Pedersen, Finn Skou

    2015-01-01

    Background: Therapies for muscular dystrophies remain a major challenge in spite of advanced strategies using either cell or gene therapy. We here propose a combined approach of cell and gene therapy. As gene delivery vehicles with specific homing potential we have chosen mesoangioblasts which...... for myogenic properties in coculture. Survival and in situ myogenic differentiation were studied upon injection into degenerating M. gastrocnemius of athymic mice. In situ participation in muscle regeneration was confirmed on cryo-sections using EGFP fluorescence as marker. The ability of mesoangioblasts...... to serve as retroviral packaging cells was tested using the murine cell line NIH 3T3 fibroblasts as recipients in vitro and evaluation of transduction by fluorescence microscopy. Results: EGFP-MA retained the ability to differentiate into skeletal muscle myotubes upon co-culture with C2C12 cells. In vivo...

  3. 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.

  4. A multianalytical approach to evaluate the association of 55 SNPs in 28 genes with obesity risk in North Indian adults.

    Science.gov (United States)

    Srivastava, Apurva; Mittal, Balraj; Prakash, Jai; Srivastava, Pranjal; Srivastava, Nimisha; Srivastava, Neena

    2017-03-01

    The aim of the study was to investigate the association of 55 SNPs in 28 genes with obesity risk in a North Indian population using a multianalytical approach. Overall, 480 subjects from the North Indian population were studied using strict inclusion/exclusion criteria. SNP Genotyping was carried out by Sequenom Mass ARRAY platform (Sequenom, San Diego, CA) and validated Taqman ® allelic discrimination (Applied Biosystems ® ). Statistical analyses were performed using SPSS software version 19.0, SNPStats, GMDR software (version 6) and GENEMANIA. Logistic regression analysis of 55 SNPs revealed significant associations (P obesity risk whereas the remaining 6 SNPs revealed no association (P > .05). The pathway-wise G-score revealed the significant role (P = .0001) of food intake-energy expenditure pathway genes. In CART analysis, the combined genotypes of FTO rs9939609 and TCF7L2 rs7903146 revealed the highest risk for BMI linked obesity. The analysis of the FTO-IRX3 locus revealed high LD and high order gene-gene interactions for BMI linked obesity. The interaction network of all of the associated genes in the present study generated by GENEMANIA revealed direct and indirect connections. In addition, the analysis with centralized obesity revealed that none of the SNPs except for FTO rs17818902 were significantly associated (P obesity risk in the North Indian population. © 2016 Wiley Periodicals, Inc.

  5. Identification and Cloning of Differentially Expressed SOUL and ELIP Genes in Saffron Stigmas Using a Subtractive Hybridization Approach.

    Directory of Open Access Journals (Sweden)

    Oussama Ahrazem

    Full Text Available Using a subtractive hybridization approach, differentially expressed genes involved in the light response in saffron stigmas were identified. Twenty-two differentially expressed transcript-derived fragments were cloned and sequenced. Two of them were highly induced by light and had sequence similarity to early inducible proteins (ELIP and SOUL heme-binding proteins. Using these sequences, we searched for other family members expressed in saffron stigma. ELIP and SOUL are represented by small gene families in saffron, with four and five members, respectively. The expression of these genes was analyzed during the development of the stigma and in light and dark conditions. ELIP transcripts were detected in all the developmental stages showing much higher expression levels in the developed stigmas of saffron and all were up-regulated by light but at different levels. By contrast, only one SOUL gene was up-regulated by light and was highly expressed in the stigma at anthesis. Both the ELIP and SOUL genes induced by light in saffron stigmas might be associated with the structural changes affecting the chromoplast of the stigma, as a result of light exposure, which promotes the development and increases the number of plastoglobules, specialized in the recruitment of specific proteins, which enables them to act in metabolite synthesis and disposal under changing environmental conditions and developmental stages.

  6. Prodrug encapsulated albumin nanoparticles as an alternative approach to manifest anti-proliferative effects of suicide gene therapy

    International Nuclear Information System (INIS)

    Tirkey, Bulbul; Bhushan, Bharat; Uday Kumar, S.; Gopinath, P.

    2017-01-01

    Conventional anticancer agents are associated with limited therapeutic efficacy and substantial nonspecific cytotoxicity. Thus, there is an imminent need for an alternative approach that can specifically annihilate the cancer cells with minimal side effects. Among such alternative approaches, CD::UPRT (cytosine deaminase uracil phosphoribosyl transferase) suicide gene therapy has tremendous potential due to its high efficacy. Prodrug 5-Fluorocytosine (5-FC) used in combination with CD::UPRT suicide gene suffers from limited solubility which subsequently leads to decline in therapeutic efficacy. In order to overcome this, 5-FC encapsulated bovine serum albumin nanoparticles (BSA-5-FC NPs) were prepared in this work by desolvation method. Physico-chemical characterizations studies revealed amorphous nature of BSA-5-FC NPs with uniform spherical morphology. Apart from increase in solubility, encapsulated 5-FC followed slow and sustained release profile. Suicide gene expressing stable clone of L-132 cells were adapted for investigating therapeutic potential of BSA-5-FC NPs. These nanoparticles were readily taken up by the cells in a concentration dependent manner and subsequently manifested apoptosis, which was further confirmed by morphological examination and gene expression analysis. These findings clearly illustrate that CD::UPRT suicide gene therapy can be efficiently utilized in combination with this nanosystem for improved suicide gene therapy and tumor eradication. - Highlights: • In this work, BSA-5-FC NPs has been prepared to achieve its sustained release and also facilitate its uptake by cells. • A protein based system has been realized for the first time to deliver prodrug for cancer therapy. • Physico-chemical characterizations further validate the formation of spherical, monodispersed and stable nanoparticles. • The therapeutic efficacy of BSA-5-FC NPs has been validated against CD::UPRT expressing stable cells.

  7. Prodrug encapsulated albumin nanoparticles as an alternative approach to manifest anti-proliferative effects of suicide gene therapy

    Energy Technology Data Exchange (ETDEWEB)

    Tirkey, Bulbul [Nanobiotechnology Laboratory, Department of Biotechnology, Indian Institute of Technology Roorkee, Roorkee, Uttarakhand 247667 (India); Bhushan, Bharat; Uday Kumar, S. [Nanobiotechnology Laboratory, Centre for Nanotechnology, Indian Institute of Technology Roorkee, Roorkee, Uttarakhand 247667 (India); Gopinath, P., E-mail: pgopifnt@iitr.ernet.in [Nanobiotechnology Laboratory, Centre for Nanotechnology, Indian Institute of Technology Roorkee, Roorkee, Uttarakhand 247667 (India); Nanobiotechnology Laboratory, Department of Biotechnology, Indian Institute of Technology Roorkee, Roorkee, Uttarakhand 247667 (India)

    2017-04-01

    Conventional anticancer agents are associated with limited therapeutic efficacy and substantial nonspecific cytotoxicity. Thus, there is an imminent need for an alternative approach that can specifically annihilate the cancer cells with minimal side effects. Among such alternative approaches, CD::UPRT (cytosine deaminase uracil phosphoribosyl transferase) suicide gene therapy has tremendous potential due to its high efficacy. Prodrug 5-Fluorocytosine (5-FC) used in combination with CD::UPRT suicide gene suffers from limited solubility which subsequently leads to decline in therapeutic efficacy. In order to overcome this, 5-FC encapsulated bovine serum albumin nanoparticles (BSA-5-FC NPs) were prepared in this work by desolvation method. Physico-chemical characterizations studies revealed amorphous nature of BSA-5-FC NPs with uniform spherical morphology. Apart from increase in solubility, encapsulated 5-FC followed slow and sustained release profile. Suicide gene expressing stable clone of L-132 cells were adapted for investigating therapeutic potential of BSA-5-FC NPs. These nanoparticles were readily taken up by the cells in a concentration dependent manner and subsequently manifested apoptosis, which was further confirmed by morphological examination and gene expression analysis. These findings clearly illustrate that CD::UPRT suicide gene therapy can be efficiently utilized in combination with this nanosystem for improved suicide gene therapy and tumor eradication. - Highlights: • In this work, BSA-5-FC NPs has been prepared to achieve its sustained release and also facilitate its uptake by cells. • A protein based system has been realized for the first time to deliver prodrug for cancer therapy. • Physico-chemical characterizations further validate the formation of spherical, monodispersed and stable nanoparticles. • The therapeutic efficacy of BSA-5-FC NPs has been validated against CD::UPRT expressing stable cells.

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

    Directory of Open Access Journals (Sweden)

    Mohammad Manir Hossain Mollah

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

  9. Genes and Social Behavior

    OpenAIRE

    Robinson, Gene E.; Fernald, Russell D.; Clayton, David F.

    2008-01-01

    What specific genes and regulatory sequences contribute to the organization and functioning of brain circuits that support social behavior? How does social experience interact with information in the genome to modulate these brain circuits? Here we address these questions by highlighting progress that has been made in identifying and understanding two key “vectors of influence” that link genes, brain, and social behavior: 1) social information alters gene readout in the brain to influence beh...

  10. Gene doping: possibilities and practicalities.

    Science.gov (United States)

    Wells, Dominic J

    2009-01-01

    Our ever-increasing understanding of the genetic control of cardiovascular and musculoskeletal function together with recent technical improvements in genetic manipulation generates mounting concern over the possibility of such technology being abused by athletes in their quest for improved performance. Genetic manipulation in the context of athletic performance is commonly referred to as gene doping. A review of the literature was performed to identify the genes and methodologies most likely to be used for gene doping and the technologies that might be used to identify such doping. A large number of candidate performance-enhancing genes have been identified from animal studies, many of them using transgenic mice. Only a limited number have been shown to be effective following gene transfer into adults. Those that seem most likely to be abused are genes that exert their effects locally and leave little, if any, trace in blood or urine. There is currently no evidence that gene doping has yet been undertaken in competitive athletes but the anti-doping authorities will need to remain vigilant in reviewing this rapidly emerging technology. The detection of gene doping involves some different challenges from other agents and a number of promising approaches are currently being explored. 2009 S. Karger AG, Basel

  11. A novel gene network inference algorithm using predictive minimum description length approach.

    Science.gov (United States)

    Chaitankar, Vijender; Ghosh, Preetam; Perkins, Edward J; Gong, Ping; Deng, Youping; Zhang, Chaoyang

    2010-05-28

    Reverse engineering of gene regulatory networks using information theory models has received much attention due to its simplicity, low computational cost, and capability of inferring large networks. One of the major problems with information theory models is to determine the threshold which defines the regulatory relationships between genes. The minimum description length (MDL) principle has been implemented to overcome this problem. The description length of the MDL principle is the sum of model length and data encoding length. A user-specified fine tuning parameter is used as control mechanism between model and data encoding, but it is difficult to find the optimal parameter. In this work, we proposed a new inference algorithm which incorporated mutual information (MI), conditional mutual information (CMI) and predictive minimum description length (PMDL) principle to infer gene regulatory networks from DNA microarray data. In this algorithm, the information theoretic quantities MI and CMI determine the regulatory relationships between genes and the PMDL principle method attempts to determine the best MI threshold without the need of a user-specified fine tuning parameter. The performance of the proposed algorithm was evaluated using both synthetic time series data sets and a biological time series data set for the yeast Saccharomyces cerevisiae. The benchmark quantities precision and recall were used as performance measures. The results show that the proposed algorithm produced less false edges and significantly improved the precision, as compared to the existing algorithm. For further analysis the performance of the algorithms was observed over different sizes of data. We have proposed a new algorithm that implements the PMDL principle for inferring gene regulatory networks from time series DNA microarray data that eliminates the need of a fine tuning parameter. The evaluation results obtained from both synthetic and actual biological data sets show that the

  12. Therapeutic genes for anti-HIV/AIDS gene therapy.

    Science.gov (United States)

    Bovolenta, Chiara; Porcellini, Simona; Alberici, Luca

    2013-01-01

    The multiple therapeutic approaches developed so far to cope HIV-1 infection, such as anti-retroviral drugs, germicides and several attempts of therapeutic vaccination have provided significant amelioration in terms of life-quality and survival rate of AIDS patients. Nevertheless, no approach has demonstrated efficacy in eradicating this lethal, if untreated, infection. The curative power of gene therapy has been proven for the treatment of monogenic immunodeficiensies, where permanent gene modification of host cells is sufficient to correct the defect for life-time. No doubt, a similar concept is not applicable for gene therapy of infectious immunodeficiensies as AIDS, where there is not a single gene to be corrected; rather engineered cells must gain immunotherapeutic or antiviral features to grant either short- or long-term efficacy mostly by acquisition of antiviral genes or payloads. Anti-HIV/AIDS gene therapy is one of the most promising strategy, although challenging, to eradicate HIV-1 infection. In fact, genetic modification of hematopoietic stem cells with one or multiple therapeutic genes is expected to originate blood cell progenies resistant to viral infection and thereby able to prevail on infected unprotected cells. Ultimately, protected cells will re-establish a functional immune system able to control HIV-1 replication. More than hundred gene therapy clinical trials against AIDS employing different viral vectors and transgenes have been approved or are currently ongoing worldwide. This review will overview anti-HIV-1 infection gene therapy field evaluating strength and weakness of the transgenes and payloads used in the past and of those potentially exploitable in the future.

  13. Genome-wide local ancestry approach identifies genes and variants associated with chemotherapeutic susceptibility in African Americans.

    Directory of Open Access Journals (Sweden)

    Heather E Wheeler

    Full Text Available Chemotherapeutic agents are used in the treatment of many cancers, yet variable resistance and toxicities among individuals limit successful outcomes. Several studies have indicated outcome differences associated with ancestry among patients with various cancer types. Using both traditional SNP-based and newly developed gene-based genome-wide approaches, we investigated the genetics of chemotherapeutic susceptibility in lymphoblastoid cell lines derived from 83 African Americans, a population for which there is a disparity in the number of genome-wide studies performed. To account for population structure in this admixed population, we incorporated local ancestry information into our association model. We tested over 2 million SNPs and identified 325, 176, 240, and 190 SNPs that were suggestively associated with cytarabine-, 5'-deoxyfluorouridine (5'-DFUR-, carboplatin-, and cisplatin-induced cytotoxicity, respectively (p≤10(-4. Importantly, some of these variants are found only in populations of African descent. We also show that cisplatin-susceptibility SNPs are enriched for carboplatin-susceptibility SNPs. Using a gene-based genome-wide association approach, we identified 26, 11, 20, and 41 suggestive candidate genes for association with cytarabine-, 5'-DFUR-, carboplatin-, and cisplatin-induced cytotoxicity, respectively (p≤10(-3. Fourteen of these genes showed evidence of association with their respective chemotherapeutic phenotypes in the Yoruba from Ibadan, Nigeria (p<0.05, including TP53I11, COPS5 and GAS8, which are known to be involved in tumorigenesis. Although our results require further study, we have identified variants and genes associated with chemotherapeutic susceptibility in African Americans by using an approach that incorporates local ancestry information.

  14. Linking Genes and Brain Development of Honeybee Workers: A Whole-Transcriptome Approach

    OpenAIRE

    Vleurinck, Christina; Raub, Stephan; Sturgill, David; Oliver, Brian; Beye, Martin

    2016-01-01

    Honeybees live in complex societies whose capabilities far exceed those of the sum of their single members. This social synergism is achieved mainly by the worker bees, which form a female caste. The worker bees display diverse collaborative behaviors and engage in different behavioral tasks, which are controlled by the central nervous system (CNS). The development of the worker brain is determined by the female sex and the worker caste determination signal. Here, we report on genes that are ...

  15. A Social Network Approach Reveals Associations between Mouse Social Dominance and Brain Gene Expression

    Science.gov (United States)

    So, Nina; Franks, Becca; Lim, Sean; Curley, James P.

    2015-01-01

    Modelling complex social behavior in the laboratory is challenging and requires analyses of dyadic interactions occurring over time in a physically and socially complex environment. In the current study, we approached the analyses of complex social interactions in group-housed male CD1 mice living in a large vivarium. Intensive observations of social interactions during a 3-week period indicated that male mice form a highly linear and steep dominance hierarchy that is maintained by fighting and chasing behaviors. Individual animals were classified as dominant, sub-dominant or subordinate according to their David’s Scores and I& SI ranking. Using a novel dynamic temporal Glicko rating method, we ascertained that the dominance hierarchy was stable across time. Using social network analyses, we characterized the behavior of individuals within 66 unique relationships in the social group. We identified two individual network metrics, Kleinberg’s Hub Centrality and Bonacich’s Power Centrality, as accurate predictors of individual dominance and power. Comparing across behaviors, we establish that agonistic, grooming and sniffing social networks possess their own distinctive characteristics in terms of density, average path length, reciprocity out-degree centralization and out-closeness centralization. Though grooming ties between individuals were largely independent of other social networks, sniffing relationships were highly predictive of the directionality of agonistic relationships. Individual variation in dominance status was associated with brain gene expression, with more dominant individuals having higher levels of corticotropin releasing factor mRNA in the medial and central nuclei of the amygdala and the medial preoptic area of the hypothalamus, as well as higher levels of hippocampal glucocorticoid receptor and brain-derived neurotrophic factor mRNA. This study demonstrates the potential and significance of combining complex social housing and intensive

  16. 3D printed hyperelastic "bone" scaffolds and regional gene therapy: A novel approach to bone healing.

    Science.gov (United States)

    Alluri, Ram; Jakus, Adam; Bougioukli, Sofia; Pannell, William; Sugiyama, Osamu; Tang, Amy; Shah, Ramille; Lieberman, Jay R

    2018-04-01

    The purpose of this study was to evaluate the viability of human adipose-derived stem cells (ADSCs) transduced with a lentiviral (LV) vector to overexpress bone morphogenetic protein-2 (BMP-2) loaded onto a novel 3D printed scaffold. Human ADSCs were transduced with a LV vector carrying the cDNA for BMP-2. The transduced cells were loaded onto a 3D printed Hyperelastic "Bone" (HB) scaffold. In vitro BMP-2 production was assessed using enzyme-linked immunosorbent assay analysis. The ability of ADSCs loaded on the HB scaffold to induce in vivo bone formation in a hind limb muscle pouch model was assessed in the following groups: ADSCs transduced with LV-BMP-2, LV-green fluorescent protein, ADSCs alone, and empty HB scaffolds. Bone formation was assessed using radiographs, histology and histomorphometry. Transduced ADSCs BMP-2 production on the HB scaffold at 24 hours was similar on 3D printed HB scaffolds versus control wells with transduced cells alone, and continued to increase after 1 and 2 weeks of culture. Bone formation was noted in LV-BMP-2 animals on plain radiographs at 2 and 4 weeks after implantation; no bone formation was noted in the other groups. Histology demonstrated that the LV-BMP-2 group was the only group that formed woven bone and the mean bone area/tissue area was significantly greater when compared with the other groups. 3D printed HB scaffolds are effective carriers for transduced ADSCs to promote bone repair. The combination of gene therapy and tissue engineered scaffolds is a promising multidisciplinary approach to bone repair with significant clinical potential. © 2018 Wiley Periodicals, Inc. J Biomed Mater Res Part A: 106A: 1104-1110, 2018. © 2018 Wiley Periodicals, Inc.

  17. A Kalman-filter based approach to identification of time-varying gene regulatory networks.

    Directory of Open Access Journals (Sweden)

    Jie Xiong

    Full Text Available MOTIVATION: Conventional identification methods for gene regulatory networks (GRNs have overwhelmingly adopted static topology models, which remains unchanged over time to represent the underlying molecular interactions of a biological system. However, GRNs are dynamic in response to physiological and environmental changes. Although there is a rich literature in modeling static or temporally invariant networks, how to systematically recover these temporally changing networks remains a major and significant pressing challenge. The purpose of this study is to suggest a two-step strategy that recovers time-varying GRNs. RESULTS: It is suggested in this paper to utilize a switching auto-regressive model to describe the dynamics of time-varying GRNs, and a two-step strategy is proposed to recover the structure of time-varying GRNs. In the first step, the change points are detected by a Kalman-filter based method. The observed time series are divided into several segments using these detection results; and each time series segment belonging to two successive demarcating change points is associated with an individual static regulatory network. In the second step, conditional network structure identification methods are used to reconstruct the topology for each time interval. This two-step strategy efficiently decouples the change point detection problem and the topology inference problem. Simulation results show that the proposed strategy can detect the change points precisely and recover each individual topology structure effectively. Moreover, computation results with the developmental data of Drosophila Melanogaster show that the proposed change point detection procedure is also able to work effectively in real world applications and the change point estimation accuracy exceeds other existing approaches, which means the suggested strategy may also be helpful in solving actual GRN reconstruction problem.

  18. A Social Network Approach Reveals Associations between Mouse Social Dominance and Brain Gene Expression.

    Directory of Open Access Journals (Sweden)

    Nina So

    Full Text Available Modelling complex social behavior in the laboratory is challenging and requires analyses of dyadic interactions occurring over time in a physically and socially complex environment. In the current study, we approached the analyses of complex social interactions in group-housed male CD1 mice living in a large vivarium. Intensive observations of social interactions during a 3-week period indicated that male mice form a highly linear and steep dominance hierarchy that is maintained by fighting and chasing behaviors. Individual animals were classified as dominant, sub-dominant or subordinate according to their David's Scores and I& SI ranking. Using a novel dynamic temporal Glicko rating method, we ascertained that the dominance hierarchy was stable across time. Using social network analyses, we characterized the behavior of individuals within 66 unique relationships in the social group. We identified two individual network metrics, Kleinberg's Hub Centrality and Bonacich's Power Centrality, as accurate predictors of individual dominance and power. Comparing across behaviors, we establish that agonistic, grooming and sniffing social networks possess their own distinctive characteristics in terms of density, average path length, reciprocity out-degree centralization and out-closeness centralization. Though grooming ties between individuals were largely independent of other social networks, sniffing relationships were highly predictive of the directionality of agonistic relationships. Individual variation in dominance status was associated with brain gene expression, with more dominant individuals having higher levels of corticotropin releasing factor mRNA in the medial and central nuclei of the amygdala and the medial preoptic area of the hypothalamus, as well as higher levels of hippocampal glucocorticoid receptor and brain-derived neurotrophic factor mRNA. This study demonstrates the potential and significance of combining complex social housing

  19. 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

  20. May I Cut in? Gene Editing Approaches in Human Induced Pluripotent Stem Cells.

    Science.gov (United States)

    Brookhouser, Nicholas; Raman, Sreedevi; Potts, Christopher; Brafman, David A

    2017-02-06

    In the decade since Yamanaka and colleagues described methods to reprogram somatic cells into a pluripotent state, human induced pluripotent stem cells (hiPSCs) have demonstrated tremendous promise in numerous disease modeling, drug discovery, and regenerative medicine applications. More recently, the development and refinement of advanced gene transduction and editing technologies have further accelerated the potential of hiPSCs. In this review, we discuss the various gene editing technologies that are being implemented with hiPSCs. Specifically, we describe the emergence of technologies including zinc-finger nuclease (ZFN), transcription activator-like effector nuclease (TALEN), and clustered regularly interspaced short palindromic repeats (CRISPR)/Cas9 that can be used to edit the genome at precise locations, and discuss the strengths and weaknesses of each of these technologies. In addition, we present the current applications of these technologies in elucidating the mechanisms of human development and disease, developing novel and effective therapeutic molecules, and engineering cell-based therapies. Finally, we discuss the emerging technological advances in targeted gene editing methods.

  1. Intraspecific relationship within the genus convolvulus l. inferred by rbcl gene using different phylogenetic approaches

    International Nuclear Information System (INIS)

    Kausar, S.; Qamarunnisa, S.

    2016-01-01

    A molecular systematics analysis was conducted using sequence data of chloroplast rbcL gene for the genus Convolvulus L., by distance and character based phylogenetic methods. Fifteen representative members from genus Convolvulus L., were included as in group whereas two members from a sister family Solanaceae were taken as out group to root the tree. Intraspecific relationships within Convolvulus were inferred by distance matrix, maximum parsimony and bayesian analysis. Transition/transversion ratio was also calculated and it was revealed that in the investigated Convolvulus species, transitional changes were more prevalent in rbcL gene. The nature of rbcL gene in the present study was observed to be conserved, as it does not show major variations between examined species. Distance matrix represented the minimal genetic variations between some species (C. glomeratus and C. pyrrhotrichus), thus exhibiting them as close relatives. The result of parsimonious and bayesian analysis revealed almost similar clades however maximum parsimony based tree was unable to establish relationship between some Convolvulus species. The bayesian inference method was found to be the method of choice for establishing intraspecific associations between Convolvulus species using rbcL data as it clearly defined the connections supported by posterior probability values. (author)

  2. New Markov Model Approaches to Deciphering Microbial Genome Function and Evolution: Comparative Genomics of Laterally Transferred Genes

    Energy Technology Data Exchange (ETDEWEB)

    Borodovsky, M.

    2013-04-11

    Algorithmic methods for gene prediction have been developed and successfully applied to many different prokaryotic genome sequences. As the set of genes in a particular genome is not homogeneous with respect to DNA sequence composition features, the GeneMark.hmm program utilizes two Markov models representing distinct classes of protein coding genes denoted "typical" and "atypical". Atypical genes are those whose DNA features deviate significantly from those classified as typical and they represent approximately 10% of any given genome. In addition to the inherent interest of more accurately predicting genes, the atypical status of these genes may also reflect their separate evolutionary ancestry from other genes in that genome. We hypothesize that atypical genes are largely comprised of those genes that have been relatively recently acquired through lateral gene transfer (LGT). If so, what fraction of atypical genes are such bona fide LGTs? We have made atypical gene predictions for all fully completed prokaryotic genomes; we have been able to compare these results to other "surrogate" methods of LGT prediction.

  3. Your Genes, Your Choices

    Science.gov (United States)

    Table of Contents Your Genes, Your Choices describes the Human Genome Project, the science behind it, and the ethical, legal, and social issues that are ... Nothing could be further from the truth. Your Genes, Your Choices points out how the progress of ...

  4. DNA repair genes

    International Nuclear Information System (INIS)

    Morimyo, Mitsuoki

    1995-01-01

    Fission yeast S. pombe is assumed to be a good model for cloning of human DNA repair genes, because human gene is normally expressed in S. pombe and has a very similar protein sequence to yeast protein. We have tried to elucidate the DNA repair mechanisms of S. pombe as a model system for those of mammals. (J.P.N.)

  5. Antisense gene silencing

    DEFF Research Database (Denmark)

    Nielsen, Troels T; Nielsen, Jørgen E

    2013-01-01

    Since the first reports that double-stranded RNAs can efficiently silence gene expression in C. elegans, the technology of RNA interference (RNAi) has been intensively exploited as an experimental tool to study gene function. With the subsequent discovery that RNAi could also be applied...

  6. Machine Learning-Assisted Network Inference Approach to Identify a New Class of Genes that Coordinate the Functionality of Cancer Networks.

    Science.gov (United States)

    Ghanat Bari, Mehrab; Ung, Choong Yong; Zhang, Cheng; Zhu, Shizhen; Li, Hu

    2017-08-01

    Emerging evidence indicates the existence of a new class of cancer genes that act as "signal linkers" coordinating oncogenic signals between mutated and differentially expressed genes. While frequently mutated oncogenes and differentially expressed genes, which we term Class I cancer genes, are readily detected by most analytical tools, the new class of cancer-related genes, i.e., Class II, escape detection because they are neither mutated nor differentially expressed. Given this hypothesis, we developed a Machine Learning-Assisted Network Inference (MALANI) algorithm, which assesses all genes regardless of expression or mutational status in the context of cancer etiology. We used 8807 expression arrays, corresponding to 9 cancer types, to build more than 2 × 10 8 Support Vector Machine (SVM) models for reconstructing a cancer network. We found that ~3% of ~19,000 not differentially expressed genes are Class II cancer gene candidates. Some Class II genes that we found, such as SLC19A1 and ATAD3B, have been recently reported to associate with cancer outcomes. To our knowledge, this is the first study that utilizes both machine learning and network biology approaches to uncover Class II cancer genes in coordinating functionality in cancer networks and will illuminate our understanding of how genes are modulated in a tissue-specific network contribute to tumorigenesis and therapy development.

  7. Radionuclide reporter gene imaging

    International Nuclear Information System (INIS)

    Min, Jung Joon

    2004-01-01

    Recent progress in the development of non-invasive imaging technologies continues to strengthen the role of molecular imaging biological research. These tools have been validated recently in variety of research models, and have been shown to provide continuous quantitative monitoring of the location(s), magnitude, and time-variation of gene expression. This article reviews the principles, characteristics, categories and the use of radionuclide reporter gene imaging technologies as they have been used in imaging cell trafficking, imaging gene therapy, imaging endogenous gene expression and imaging molecular interactions. The studies published to date demonstrate that reporter gene imaging technologies will help to accelerate model validation as well as allow for clinical monitoring of human diseases

  8. Radionuclide reporter gene imaging

    Energy Technology Data Exchange (ETDEWEB)

    Min, Jung Joon [School of Medicine, Chonnam National Univ., Gwangju (Korea, Republic of)

    2004-04-01

    Recent progress in the development of non-invasive imaging technologies continues to strengthen the role of molecular imaging biological research. These tools have been validated recently in variety of research models, and have been shown to provide continuous quantitative monitoring of the location(s), magnitude, and time-variation of gene expression. This article reviews the principles, characteristics, categories and the use of radionuclide reporter gene imaging technologies as they have been used in imaging cell trafficking, imaging gene therapy, imaging endogenous gene expression and imaging molecular interactions. The studies published to date demonstrate that reporter gene imaging technologies will help to accelerate model validation as well as allow for clinical monitoring of human diseases.

  9. Approaching the axiomatic enrichment of the Gene Ontology from a lexical perspective.

    Science.gov (United States)

    Quesada-Martínez, Manuel; Mikroyannidi, Eleni; Fernández-Breis, Jesualdo Tomás; Stevens, Robert

    2015-09-01

    The main goal of this work is to measure how lexical regularities in biomedical ontology labels can be used for the automatic creation of formal relationships between classes, and to evaluate the results of applying our approach to the Gene Ontology (GO). In recent years, we have developed a method for the lexical analysis of regularities in biomedical ontology labels, and we showed that the labels can present a high degree of regularity. In this work, we extend our method with a cross-products extension (CPE) metric, which estimates the potential interest of a specific regularity for axiomatic enrichment in the lexical analysis, using information on exact matches in external ontologies. The GO consortium recently enriched the GO by using so-called cross-product extensions. Cross-products are generated by establishing axioms that relate a given GO class with classes from the GO or other biomedical ontologies. We apply our method to the GO and study how its lexical analysis can identify and reconstruct the cross-products that are defined by the GO consortium. The label of the classes of the GO are highly regular in lexical terms, and the exact matches with labels of external ontologies affect 80% of the GO classes. The CPE metric reveals that 31.48% of the classes that exhibit regularities have fragments that are classes into two external ontologies that are selected for our experiment, namely, the Cell Ontology and the Chemical Entities of Biological Interest ontology, and 18.90% of them are fully decomposable into smaller parts. Our results show that the CPE metric permits our method to detect GO cross-product extensions with a mean recall of 62% and a mean precision of 28%. The study is completed with an analysis of false positives to explain this precision value. We think that our results support the claim that our lexical approach can contribute to the axiomatic enrichment of biomedical ontologies and that it can provide new insights into the engineering of

  10. 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...

  11. Research progress in machine learning methods for gene-gene interaction detection.

    Science.gov (United States)

    Peng, Zhe-Ye; Tang, Zi-Jun; Xie, Min-Zhu

    2018-03-20

    Complex diseases are results of gene-gene and gene-environment interactions. However, the detection of high-dimensional gene-gene interactions is computationally challenging. In the last two decades, machine-learning approaches have been developed to detect gene-gene interactions with some successes. In this review, we summarize the progress in research on machine learning methods, as applied to gene-gene interaction detection. It systematically examines the principles and limitations of the current machine learning methods used in genome wide association studies (GWAS) to detect gene-gene interactions, such as neural networks (NN), random forest (RF), support vector machines (SVM) and multifactor dimensionality reduction (MDR), and provides some insights on the future research directions in the field.

  12. The AERO system: a 3D-like approach for recording gene expression patterns in the whole mouse embryo.

    Directory of Open Access Journals (Sweden)

    Hirohito Shimizu

    Full Text Available We have recently constructed a web-based database of gene expression in the mouse whole embryo, EMBRYS (http://embrys.jp/embrys/html/MainMenu.html. To allow examination of gene expression patterns to the fullest extent possible, this database provides both photo images and annotation data. However, since embryos develop via an intricate process of morphogenesis, it would be of great value to track embryonic gene expression from a three dimensional perspective. In fact, several methods have been developed to achieve this goal, but highly laborious procedures and specific operational skills are generally required. We utilized a novel microscopic technique that enables the easy capture of rotational, 3D-like images of the whole embryo. In this method, a rotary head equipped with two mirrors that are designed to obtain an image tilted at 45 degrees to the microscope stage captures serial images at 2-degree intervals. By a simple operation, 180 images are automatically collected. These 2D images obtained at multiple angles are then used to reconstruct 3D-like images, termed AERO images. By means of this system, over 800 AERO images of 191 gene expression patterns were captured. These images can be easily rotated on the computer screen using the EMBRYS database so that researchers can view an entire embryo by a virtual viewing on a computer screen in an unbiased or non-predetermined manner. The advantages afforded by this approach make it especially useful for generating data viewed in public databases.

  13. The Zebrafish GenomeWiki: a crowdsourcing approach to connect the long tail for zebrafish gene annotation

    OpenAIRE

    Singh, Meghna; Bhartiya, Deeksha; Maini, Jayant; Sharma, Meenakshi; Singh, Angom Ramcharan; Kadarkaraisamy, Subburaj; Rana, Rajiv; Sabharwal, Ankit; Nanda, Srishti; Ramachandran, Aravindhakshan; Mittal, Ashish; Kapoor, Shruti; Sehgal, Paras; Asad, Zainab; Kaushik, Kriti

    2014-01-01

    A large repertoire of gene-centric data has been generated in the field of zebrafish biology. Although the bulk of these data are available in the public domain, most of them are not readily accessible or available in nonstandard formats. One major challenge is to unify and integrate these widely scattered data sources. We tested the hypothesis that active community participation could be a viable option to address this challenge. We present here our approach to create standards for assimilat...

  14. A systems biology approach using transcriptomic data reveals genes and pathways in porcine skeletal muscle affected by dietary lysine

    Science.gov (United States)

    Meeting the increasing market demands for pork products requires improvement of the feed efficiency of growing pigs. The use of Affymetrix Porcine Gene 1.0 ST array containing 19,211 genes in this study provides a comprehensive gene expression profile of skeletal muscle of finishing pigs in response...

  15. Exploration of structural stability in deleterious nsSNPs of the XPA gene: A molecular dynamics approach

    Directory of Open Access Journals (Sweden)

    N NagaSundaram

    2011-01-01

    Full Text Available Background: Distinguishing the deleterious from the massive number of non-functional nsSNPs that occur within a single genome is a considerable challenge in mutation research. In this approach, we have used the existing in silico methods to explore the mutation-structure-function relationship in the XPA gene. Materials and Methods: We used the Sorting Intolerant From Tolerant (SIFT, Polymorphism Phenotyping (PolyPhen, I-Mutant 2.0, and the Protein Analysis THrough Evolutionary Relationships methods to predict the effects of deleterious nsSNPs on protein function and evaluated the impact of mutation on protein stability by Molecular Dynamics simulations. Results: By comparing the scores of all the four in silico methods, nsSNP with an ID rs104894131 at position C108F was predicted to be highly deleterious. We extended our Molecular dynamics approach to gain insight into the impact of this non-synonymous polymorphism on structural changes that may affect the activity of the XPA gene. Conclusion: Based on the in silico methods score, potential energy, root-mean-square deviation, and root-mean-square fluctuation, we predict that deleterious nsSNP at position C108F would play a significant role in causing disease by the XPA gene. Our approach would present the application of in silico tools in understanding the functional variation from the perspective of structure, evolution, and phenotype.

  16. Problem-Solving Test: Targeted Gene Disruption

    Science.gov (United States)

    Szeberenyi, Jozsef

    2008-01-01

    Mutational inactivation of a specific gene is the most powerful technique to analyze the biological function of the gene. This approach has been used for a long time in viruses, bacteria, yeast, and fruit fly, but looked quite hopeless in more complex organisms. Targeted inactivation of specific genes (also known as knock-out mutation) in mice is…

  17. 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.

  18. Gene amplification in carcinogenesis

    Directory of Open Access Journals (Sweden)

    Lucimari Bizari

    2006-01-01

    Full Text Available Gene amplification increases the number of genes in a genome and can give rise to karyotype abnormalities called double minutes (DM and homogeneously staining regions (HSR, both of which have been widely observed in human tumors but are also known to play a major role during embryonic development due to the fact that they are responsible for the programmed increase of gene expression. The etiology of gene amplification during carcinogenesis is not yet completely understood but can be considered a result of genetic instability. Gene amplification leads to an increase in protein expression and provides a selective advantage during cell growth. Oncogenes such as CCND1, c-MET, c-MYC, ERBB2, EGFR and MDM2 are amplified in human tumors and can be associated with increased expression of their respective proteins or not. In general, gene amplification is associated with more aggressive tumors, metastases, resistance to chemotherapy and a decrease in the period during which the patient stays free of the disease. This review discusses the major role of gene amplification in the progression of carcinomas, formation of genetic markers and as possible therapeutic targets for the development of drugs for the treatment of some types of tumors.

  19. The animal sialyltransferases and sialyltransferase-related genes: a phylogenetic approach.

    Science.gov (United States)

    Harduin-Lepers, Anne; Mollicone, Rosella; Delannoy, Philippe; Oriol, Rafael

    2005-08-01

    The animal sialyltransferases are Golgi type II transmembrane glycosyltransferases. Twenty distinct sialyltransferases have been identified in both human and murine genomes. These enzymes catalyze transfer of sialic acid from CMP-Neu5Ac to the glycan moiety of glycoconjugates. Despite low overall identities, they share four conserved peptide motifs [L (large), S (small), motif III, and motif VS (very small)] that are hallmarks for sialyltransferase identification. We have identified 155 new putative genes in 25 animal species, and we have exploited two lines of evidence: (1) sequence comparisons and (2) exon-intron organization of the genes. An ortholog to the ancestor present before the split of ST6Gal I and II subfamilies was detected in arthropods. An ortholog to the ancestor present before the split of ST6GalNAc III, IV, V, and VI subfamilies was detected in sea urchin. An ortholog to the ancestor present before the split of ST3Gal I and II subfamilies was detected in ciona, and an ortholog to the ancestor of all the ST8Sia was detected in amphioxus. Therefore, single examples of the four families (ST3Gal, ST6Gal, ST6GalNAc, and ST8Sia) have appeared in invertebrates, earlier than previously thought, whereas the four families were all detected in bony fishes, amphibians, birds, and mammals. As previously hypothesized, sequence similarities among sialyltransferases suggest a common genetic origin, by successive duplications of an ancestral gene, followed by divergent evolution. Finally, we propose predictions on these invertebrates sialyltransferase-related activities that have not previously been demonstrated and that will ultimately need to be substantiated by protein expression and enzymatic activity assays.

  20. From the Cover: A polymer library approach to suicide gene therapy for cancer

    Science.gov (United States)

    Anderson, Daniel G.; Peng, Weidan; Akinc, Akin; Hossain, Naushad; Kohn, Anat; Padera, Robert; Langer, Robert; Sawicki, Janet A.

    2004-11-01

    Optimal gene therapy for cancer must (i) deliver DNA to tumor cells with high efficiency, (ii) induce minimal toxicity, and (iii) avoid gene expression in healthy tissues. To this end, we generated a library of >500 degradable, poly(-amino esters) for potential use as nonviral DNA vectors. Using high-throughput methods, we screened this library in vitro for transfection efficiency and cytotoxicity. We tested the best performing polymer, C32, in mice for toxicity and DNA delivery after intratumor and i.m. injection. C32 delivered DNA intratumorally 4-fold better than one of the best commercially available reagents, jetPEI (polyethyleneimine), and 26-fold better than naked DNA. Conversely, the highest transfection levels after i.m. administration were achieved with naked DNA, followed by polyethyleneimine; transfection was rarely observed with C32. Additionally, polyethyleneimine induced significant local toxicity after i.m. injection, whereas C32 demonstrated no toxicity. Finally, we used C32 to deliver a DNA construct encoding the A chain of diphtheria toxin (DT-A) to xenografts derived from LNCaP human prostate cancer cells. This construct regulates toxin expression both at the transcriptional level by the use of a chimeric-modified enhancer/promoter sequence of the human prostate-specific antigen gene and by DNA recombination mediated by Flp recombinase. C32 delivery of the A chain of diphtheria toxin DNA to LNCaP xenografts suppressed tumor growth and even caused 40% of tumors to regress in size. Because C32 transfects tumors locally at high levels, transfects healthy muscle poorly, and displays no toxicity, it may provide a vehicle for the local treatment of cancer. prostate | cationic polymers

  1. A Chinese Herbal Decoction, Danggui Buxue Tang, Stimulates Proliferation, Differentiation and Gene Expression of Cultured Osteosarcoma Cells: Genomic Approach to Reveal Specific Gene Activation

    Directory of Open Access Journals (Sweden)

    Roy C. Y. Choi

    2011-01-01

    Full Text Available Danggui Buxue Tang (DBT, a Chinese herbal decoction used to treat ailments in women, contains Radix Astragali (Huangqi; RA and Radix Angelicae Sinensis (Danggui; RAS. When DBT was applied onto cultured MG-63 cells, an increase of cell proliferation and differentiation of MG-63 cell were revealed: both of these effects were significantly higher in DBT than RA or RAS extract. To search for the biological markers that are specifically regulated by DBT, DNA microarray was used to reveal the gene expression profiling of DBT in MG-63 cells as compared to that of RA- or RAS-treated cells. Amongst 883 DBT-regulated genes, 403 of them are specifically regulated by DBT treatment, including CCL-2, CCL-7, CCL-8, and galectin-9. The signaling cascade of this DBT-regulated gene expression was also elucidated in cultured MG-63 cells. The current results reveal the potential usage of this herbal decoction in treating osteoporosis and suggest the uniqueness of Chinese herbal decoction that requires a well-defined formulation. The DBT-regulated genes in the culture could serve as biological responsive markers for quality assurance of the herbal preparation.

  2. Genomic Imbalances in Rhabdomyosarcoma Cell Lines Affect Expression of Genes Frequently Altered in Primary Tumors: An Approach to Identify Candidate Genes Involved in Tumor Development

    NARCIS (Netherlands)

    Missiaglia, Edoardo; Selfe, Joanna; Hamdi, Mohamed; Williamson, Daniel; Schaaf, Gerben; Fang, Cheng; Koster, Jan; Summersgill, Brenda; Messahel, Boo; Versteeg, Rogier; Pritchard-Jones, Kathy; Kool, Marcel; Shipley, Janet

    2009-01-01

    Rhabdomyosarcomas (RMS) are the most common pediatric soft tissue sarcomas. They resemble developing skeletal muscle and are histologically divided into two main subtypes; alveolar and embryonal RMS. Characteristic genomic aberrations, including the PAX3- and PAX7-FOXO1 fusion genes in alveolar

  3. Methanogenesis and methane genes

    International Nuclear Information System (INIS)

    Reeve, J.N.; Shref, B.A.

    1991-01-01

    An overview of the pathways leading to methane biosynthesis is presented. The steps investigated to date by gene cloning and DNA sequencing procedures are identified and discussed. The primary structures of component C of methyl coenzyme M reductase encoded by mcr operons in different methanogens are compared. Experiments to detect the primary structure of the genes encoding F420 reducing hydrogenase (frhABG) and methyl hydrogen reducing hydrogenase (mvhDGA) in methanobacterium thermoautotrophicum strain H are compared with each other and with eubacterial hydrogenase encoding genes. A biotechnological use for hydrogenases from hypermorphillic archaebacteria is suggested. (author)

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

    Directory of Open Access Journals (Sweden)

    Marzieh Kafeshani

    2015-01-01

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

  5. Isolation and Manipulation of Quantitative Tra it Loci for DIsease Resistance in Rice Using a Candid ate Gene Approach

    Institute of Scientific and Technical Information of China (English)

    Ke-Ming Hu; De-Yun Qiu; Xiang-Ling Shen; Xiang-Hua Li; Shi-Ping Wang

    2008-01-01

    Bacterial blight caused by Xanthomonas oryzae pv.oryzae and fungal blast caused by Magnaporthe grisea result in heavy production losses in rice,a main staple food for approximately 50%of the world's population.Application of host resistance to these pathogens iS the most economical and environment-friendly approach to solve this problem.Quantitative trait loci(QTLs)controlling quantitative resistance are valuable sources for broad.spectrum and durable disease resistance.Although large numbers of QTLs for bacteriaI blight and blast resistance have been identified.these sources have not been used effectively in rice improvement because of the complex genetic controI of quantitative resistance and because the genes underlying resistance QTLs are unknown.To isolate disease resistance QTLs,we established a candidate gene strategy that integrates linkage map,expression profile,and functionaI complementation analyses.This strategy has proven to be applicable for identifying the genes underlying minor resistance QTLs in rice-Xoo and rice-M grisea systems and it may also help to shed light on disease resistance QTLs of other cereals.Our results also suggest that a single minor QTL can be used in rice improvement by modulating the expression of the gene underlying the QTL.Pyramiding two or three minor QTL genes,whose expression can be managed and that function in different defense signaI transduction pathways,may allow the breeding of rice cultivars that are highly resistant to bacteriaI blight and blast.

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

    Directory of Open Access Journals (Sweden)

    Christian Müller

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

  7. Prediction of regulatory gene pairs using dynamic time warping and gene ontology.

    Science.gov (United States)

    Yang, Andy C; Hsu, Hui-Huang; Lu, Ming-Da; Tseng, Vincent S; Shih, Timothy K

    2014-01-01

    Selecting informative genes is the most important task for data analysis on microarray gene expression data. In this work, we aim at identifying regulatory gene pairs from microarray gene expression data. However, microarray data often contain multiple missing expression values. Missing value imputation is thus needed before further processing for regulatory gene pairs becomes possible. We develop a novel approach to first impute missing values in microarray time series data by combining k-Nearest Neighbour (KNN), Dynamic Time Warping (DTW) and Gene Ontology (GO). After missing values are imputed, we then perform gene regulation prediction based on our proposed DTW-GO distance measurement of gene pairs. Experimental results show that our approach is more accurate when compared with existing missing value imputation methods on real microarray data sets. Furthermore, our approach can also discover more regulatory gene pairs that are known in the literature than other methods.

  8. 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

  9. Approaches to gene pool conservation of medicinal plant Oxytropis lanata (Pall. DC. (Fabaceae

    Directory of Open Access Journals (Sweden)

    A. B. Kholina

    2015-05-01

    Full Text Available In order to preserve the gene pool of medicinal plant Oxytropis lanata (Pall. DC. we analyzed allozyme polymorphism and identified reliable and informative marker enzyme systems of this species; also we studied the response of seeds to deep freezing in liquid nitrogen (–196 ºС. Population has an average level of polymorphism (P95 = 41,2 %, P99 = 52,9 %, A = 1,58, Ho = 0,158, He = 0,171 in general typical for herbaceous legumes, and can serve as a source of material for gene pool conservation of the species. Deep freezing has not led to the death of the seeds; it was marked stimulatory effect of ultralow temperatures, expressed as an acceleration of germination and sharp increase of germinability (98,6 ± 2,3 % compared to the control (12,0 ± 3,5 % that is associated with overcoming physical dormancy. There were no abnormalities in the development of seedlings from seeds passed cryopreservation.

  10. Gene set analysis using variance component tests.

    Science.gov (United States)

    Huang, Yen-Tsung; Lin, Xihong

    2013-06-28

    Gene set analyses have become increasingly important in genomic research, as many complex diseases are contributed jointly by alterations of numerous genes. Genes often coordinate together as a functional repertoire, e.g., a biological pathway/network and are highly correlated. However, most of the existing gene set analysis methods do not fully account for the correlation among the genes. Here we propose to tackle this important feature of a gene set to improve statistical power in gene set analyses. We propose to model the effects of an independent variable, e.g., exposure/biological status (yes/no), on multiple gene expression values in a gene set using a multivariate linear regression model, where the correlation among the genes is explicitly modeled using a working covariance matrix. We develop TEGS (Test for the Effect of a Gene Set), a variance component test for the gene set effects by assuming a common distribution for regression coefficients in multivariate linear regression models, and calculate the p-values using permutation and a scaled chi-square approximation. We show using simulations that type I error is protected under different choices of working covariance matrices and power is improved as the working covariance approaches the true covariance. The global test is a special case of TEGS when correlation among genes in a gene set is ignored. Using both simulation data and a published diabetes dataset, we show that our test outperforms the commonly used approaches, the global test and gene set enrichment analysis (GSEA). We develop a gene set analyses method (TEGS) under the multivariate regression framework, which directly models the interdependence of the expression values in a gene set using a working covariance. TEGS outperforms two widely used methods, GSEA and global test in both simulation and a diabetes microarray data.

  11. Gene Expression Omnibus (GEO)

    Data.gov (United States)

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

  12. A new physical mapping approach refines the sex-determining gene positions on the Silene latifolia Y-chromosome

    Science.gov (United States)

    Kazama, Yusuke; Ishii, Kotaro; Aonuma, Wataru; Ikeda, Tokihiro; Kawamoto, Hiroki; Koizumi, Ayako; Filatov, Dmitry A.; Chibalina, Margarita; Bergero, Roberta; Charlesworth, Deborah; Abe, Tomoko; Kawano, Shigeyuki

    2016-01-01

    Sex chromosomes are particularly interesting regions of the genome for both molecular genetics and evolutionary studies; yet, for most species, we lack basic information, such as the gene order along the chromosome. Because they lack recombination, Y-linked genes cannot be mapped genetically, leaving physical mapping as the only option for establishing the extent of synteny and homology with the X chromosome. Here, we developed a novel and general method for deletion mapping of non-recombining regions by solving “the travelling salesman problem”, and evaluate its accuracy using simulated datasets. Unlike the existing radiation hybrid approach, this method allows us to combine deletion mutants from different experiments and sources. We applied our method to a set of newly generated deletion mutants in the dioecious plant Silene latifolia and refined the locations of the sex-determining loci on its Y chromosome map.

  13. Recent development of antiSMASH and other computational approaches to mine secondary metabolite biosynthetic gene clusters

    DEFF Research Database (Denmark)

    Blin, Kai; Kim, Hyun Uk; Medema, Marnix H.

    2017-01-01

    Many drugs are derived from small molecules produced by microorganisms and plants, so-called natural products. Natural products have diverse chemical structures, but the biosynthetic pathways producing those compounds are often organized as biosynthetic gene clusters (BGCs) and follow a highly...... conserved biosynthetic logic. This allows for the identification of core biosynthetic enzymes using genome mining strategies that are based on the sequence similarity of the involved enzymes/genes. However, mining for a variety of BGCs quickly approaches a complexity level where manual analyses...... are no longer possible and require the use of automated genome mining pipelines, such as the antiSMASH software. In this review, we discuss the principles underlying the predictions of antiSMASH and other tools and provide practical advice for their application. Furthermore, we discuss important caveats...

  14. Efficient strategy for detecting gene × gene joint action and its application in schizophrenia

    NARCIS (Netherlands)

    Won, Sungho; Kwon, Min-Seok; Mattheisen, Manuel; Park, Suyeon; Park, Changsoon; Kihara, Daisuke; Cichon, Sven; Ophoff, Roel; Nöthen, Markus M.; Rietschel, Marcella; Baur, Max; Uitterlinden, Andre G.; Hofmann, A.; Lange, Christoph; Kahn, René S.; Linszen, Don H.; van Os, Jim; Wiersma, Durk; Bruggeman, Richard; Cahn, Wiepke; de Haan, Lieuwe; Krabbendam, Lydia; Myin-Germeys, Inez

    2014-01-01

    We propose a new approach to detect gene × gene joint action in genome-wide association studies (GWASs) for case-control designs. This approach offers an exhaustive search for all two-way joint action (including, as a special case, single gene action) that is computationally feasible at the

  15. Establishing gene models from the Pinus pinaster genome using gene capture and BAC sequencing.

    Science.gov (United States)

    Seoane-Zonjic, Pedro; Cañas, Rafael A; Bautista, Rocío; Gómez-Maldonado, Josefa; Arrillaga, Isabel; Fernández-Pozo, Noé; Claros, M Gonzalo; Cánovas, Francisco M; Ávila, Concepción

    2016-02-27

    In the era of DNA throughput sequencing, assembling and understanding gymnosperm mega-genomes remains a challenge. Although drafts of three conifer genomes have recently been published, this number is too low to understand the full complexity of conifer genomes. Using techniques focused on specific genes, gene models can be established that can aid in the assembly of gene-rich regions, and this information can be used to compare genomes and understand functional evolution. In this study, gene capture technology combined with BAC isolation and sequencing was used as an experimental approach to establish de novo gene structures without a reference genome. Probes were designed for 866 maritime pine transcripts to sequence genes captured from genomic DNA. The gene models were constructed using GeneAssembler, a new bioinformatic pipeline, which reconstructed over 82% of the gene structures, and a high proportion (85%) of the captured gene models contained sequences from the promoter regulatory region. In a parallel experiment, the P. pinaster BAC library was screened to isolate clones containing genes whose cDNA sequence were already available. BAC clones containing the asparagine synthetase, sucrose synthase and xyloglucan endotransglycosylase gene sequences were isolated and used in this study. The gene models derived from the gene capture approach were compared with the genomic sequences derived from the BAC clones. This combined approach is a particularly efficient way to capture the genomic structures of gene families with a small number of members. The experimental approach used in this study is a valuable combined technique to study genomic gene structures in species for which a reference genome is unavailable. It can be used to establish exon/intron boundaries in unknown gene structures, to reconstruct incomplete genes and to obtain promoter sequences that can be used for transcriptional studies. A bioinformatics algorithm (GeneAssembler) is also provided as a

  16. Finding Genes for Schizophrenia

    OpenAIRE

    Åberg, Karolina

    2005-01-01

    Schizophrenia is one of our most common psychiatric diseases. It severely affects all aspects of psychological functions and results in loss of contact with reality. No cure exists and the treatments available today produce only partial relief for disease symptoms. The aim of this work is to better understand the etiology of schizophrenia by identification of candidate genes and gene pathways involved in the development of the disease. In a preliminarily study, the effects of medication and g...

  17. Epigenetics: beyond genes

    CSIR Research Space (South Africa)

    Fossey, A

    2009-06-01

    Full Text Available in forestry breeding. Keywords Gene regulation; chromatin; histone code hyporthesis; RNA silencing; post transcriptional gene silencing; forestry. Introduction to epigenetic phenomena Most living organisms share a vast amount of genetic information... (Rapp and Wendel, 2005). Epigenetic phenomena pervade all aspects of cell proliferation and plant development and are often in conflict with Mendelian models of genetics (Grant-Downton and Dickinson, 2005). A key element in many epigenetic effects...

  18. Novel approach to abuse the hyperactive K-Ras pathway for adenoviral gene therapy of colorectal cancer

    International Nuclear Information System (INIS)

    Naumov, Inna; Kazanov, Dina; Lisiansky, Victoria; Starr, Alex; Aroch, Ilan; Shapira, Shiran; Kraus, Sarah; Arber, Nadir

    2012-01-01

    Background: Functional activation of oncogenic K-Ras signaling pathway plays an important role in the early events of colorectal carcinogenesis (CRC). K-Ras proto-oncogene is involved in 35–40% of CRC cases. Mutations in the Ras gene trigger the transduction of proliferative and anti-apoptotic signals, even in the absence of extra cellular stimuli. The objective of the current study was to use a gene-targeting approach to kill human CRC cells selectively harboring mutated K-Ras. Results: A recombinant adenovirus that carries a lethal gene, PUMA, under the control of a Ras responsive promoter (Ad-Py4-SV40-PUMA) was used selectively to target CRC cells (HCT116, SW480, DLD1 and RIE-Ras) that possess a hyperactive Ras pathway while using HT29 and RIE cells as a control that harbors wild type Ras and exhibit very low Ras activity. Control vector, without the Ras responsive promoter elements was used to assess the specificity of our “gene therapy” approach. Both adenoviral vectors were assed in vitro and in xenograft model in vivo. Ad-Py4-SV40-PUMA showed high potency to induce ∼ 50% apoptosis in vitro, to abolish completely tumor formation by infecting cells with the Ad-Py4-SV40-PUMA prior xenografting them in nude mice and high ability to suppress by ∼ 35% tumor progression in vivo in already established tumors. Conclusions: Selective targeting of CRC cells with the activated Ras pathway may be a novel and effective therapy in CRC. The high potency of this adenoviral vector may help to overcome an undetectable micro metastasis that is the major hurdle in challenging with CRC.

  19. Novel approach to abuse the hyperactive K-Ras pathway for adenoviral gene therapy of colorectal cancer

    Energy Technology Data Exchange (ETDEWEB)

    Naumov, Inna [Integrated Cancer Prevention Center, Tel Aviv (Israel); Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv (Israel); Kazanov, Dina [Integrated Cancer Prevention Center, Tel Aviv (Israel); Lisiansky, Victoria [Integrated Cancer Prevention Center, Tel Aviv (Israel); Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv (Israel); Starr, Alex [Lung and Allergy Institute, Tel Aviv Sourasky Medical Center, Tel Aviv (Israel); Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv (Israel); Aroch, Ilan; Shapira, Shiran; Kraus, Sarah [Integrated Cancer Prevention Center, Tel Aviv (Israel); Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv (Israel); Arber, Nadir, E-mail: narber@post.tau.ac.il [Integrated Cancer Prevention Center, Tel Aviv (Israel); Department of Gastroenterology, Tel Aviv Sourasky Medical Center, Tel Aviv (Israel); Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv (Israel)

    2012-01-15

    Background: Functional activation of oncogenic K-Ras signaling pathway plays an important role in the early events of colorectal carcinogenesis (CRC). K-Ras proto-oncogene is involved in 35-40% of CRC cases. Mutations in the Ras gene trigger the transduction of proliferative and anti-apoptotic signals, even in the absence of extra cellular stimuli. The objective of the current study was to use a gene-targeting approach to kill human CRC cells selectively harboring mutated K-Ras. Results: A recombinant adenovirus that carries a lethal gene, PUMA, under the control of a Ras responsive promoter (Ad-Py4-SV40-PUMA) was used selectively to target CRC cells (HCT116, SW480, DLD1 and RIE-Ras) that possess a hyperactive Ras pathway while using HT29 and RIE cells as a control that harbors wild type Ras and exhibit very low Ras activity. Control vector, without the Ras responsive promoter elements was used to assess the specificity of our 'gene therapy' approach. Both adenoviral vectors were assed in vitro and in xenograft model in vivo. Ad-Py4-SV40-PUMA showed high potency to induce {approx} 50% apoptosis in vitro, to abolish completely tumor formation by infecting cells with the Ad-Py4-SV40-PUMA prior xenografting them in nude mice and high ability to suppress by {approx} 35% tumor progression in vivo in already established tumors. Conclusions: Selective targeting of CRC cells with the activated Ras pathway may be a novel and effective therapy in CRC. The high potency of this adenoviral vector may help to overcome an undetectable micro metastasis that is the major hurdle in challenging with CRC.

  20. Gene-Gene and Gene-Environment Interactions in the Etiology of Breast Cancer

    National Research Council Canada - National Science Library

    Adegoke, Olufemi

    2003-01-01

    The objective of this CDA is to evaluate the gene-gene and gene-environment interactions in the etiology of breast cancer in two ongoing case-control studies, the Shanghai Breast Cancer Study (SBCS...

  1. Radiosensitivity and genes

    Energy Technology Data Exchange (ETDEWEB)

    Qiyue, Hu; Mingyue, Lun [Suzhou Medical Coll., JS (China)

    1995-07-01

    Reported effects of some oncogenes, tumour suppressor genes and DNA repair genes on sensitivity of cells to ionizing radiation are reviewed. The role of oncogenes in cellular response to irradiation is discussed, especially the extensively studied oncogenes such as the ras gene family. For tumour suppressor genes, mainly the p53, which is increasingly implicated as a gene affecting radiosensitivity, is reviewed. It is considered that there is a cell cycle checkpoint determinant which is postulated to be able to arrest the irradiated cells in G{sub 1} phase to allow them to repair damage before they undergo DNA synthesis. So far there are six DNA repair genes which have been cloned in mammalian cells, but only one, XRCC1, appears to be involved in repair of human X-ray damage. XRCC1 can correct high sisterchromatid exchange levels when transferred into EM{sub 9} cells, but its expression seems to have no correlation with radiosensitivity of human neck and head tumour cells. Radiosensitivity is an intricate issue which may involve many factors. A scheme of cellular reactions after exposure to irradiation is proposed to indicate a possible sequence of events initiated by ionizing radiation.

  2. Radiosensitivity and genes

    International Nuclear Information System (INIS)

    Hu Qiyue; Lun Mingyue

    1995-07-01

    Reported effects of some oncogenes, tumour suppressor genes and DNA repair genes on sensitivity of cells to ionizing radiation are reviewed. The role of oncogenes in cellular response to irradiation is discussed, especially the extensively studied oncogenes such as the ras gene family. For tumour suppressor genes, mainly the p53, which is increasingly implicated as a gene affecting radiosensitivity, is reviewed. It is considered that there is a cell cycle checkpoint determinant which is postulated to be able to arrest the irradiated cells in G 1 phase to allow them to repair damage before they undergo DNA synthesis. So far there are six DNA repair genes which have been cloned in mammalian cells, but only one, XRCC1, appears to be involved in repair of human X-ray damage. XRCC1 can correct high sisterchromatid exchange levels when transferred into EM 9 cells, but its expression seems to have no correlation with radiosensitivity of human neck and head tumour cells. Radiosensitivity is an intricate issue which may involve many factors. A scheme of cellular reactions after exposure to irradiation is proposed to indicate a possible sequence of events initiated by ionizing radiation

  3. Evidence for homosexuality gene

    Energy Technology Data Exchange (ETDEWEB)

    Pool, R.

    1993-07-16

    A genetic analysis of 40 pairs of homosexual brothers has uncovered a region on the X chromosome that appears to contain a gene or genes for homosexuality. When analyzing the pedigrees of homosexual males, the researcheres found evidence that the trait has a higher likelihood of being passed through maternal genes. This led them to search the X chromosome for genes predisposing to homosexuality. The researchers examined the X chromosomes of pairs of homosexual brothers for regions of DNA that most or all had in common. Of the 40 sets of brothers, 33 shared a set of five markers in the q28 region of the long arm of the X chromosome. The linkage has a LOD score of 4.0, which translates into a 99.5% certainty that there is a gene or genes in this area that predispose males to homosexuality. The chief researcher warns, however, that this one site cannot explain all instances of homosexuality, since there were some cases where the trait seemed to be passed paternally. And even among those brothers where there was no evidence that the trait was passed paternally, seven sets of brothers did not share the Xq28 markers. It seems likely that homosexuality arises from a variety of causes.

  4. Cationic Bolaamphiphiles for Gene Delivery

    Science.gov (United States)

    Tan, Amelia Li Min; Lim, Alisa Xue Ling; Zhu, Yiting; Yang, Yi Yan; Khan, Majad

    2014-05-01

    Advances in medical research have shed light on the genetic cause of many human diseases. Gene therapy is a promising approach which can be used to deliver therapeutic genes to treat genetic diseases at its most fundamental level. In general, nonviral vectors are preferred due to reduced risk of immune response, but they are also commonly associated with low transfection efficiency and high cytotoxicity. In contrast to viral vectors, nonviral vectors do not have a natural mechanism to overcome extra- and intracellular barriers when delivering the therapeutic gene into cell. Hence, its design has been increasingly complex to meet challenges faced in targeting of, penetration of and expression in a specific host cell in achieving more satisfactory transfection efficiency. Flexibility in design of the vector is desirable, to enable a careful and controlled manipulation of its properties and functions. This can be met by the use of bolaamphiphile, a special class of lipid. Unlike conventional lipids, bolaamphiphiles can form asymmetric complexes with the therapeutic gene. The advantage of having an asymmetric complex lies in the different purposes served by the interior and exterior of the complex. More effective gene encapsulation within the interior of the complex can be achieved without triggering greater aggregation of serum proteins with the exterior, potentially overcoming one of the great hurdles faced by conventional single-head cationic lipids. In this review, we will look into the physiochemical considerations as well as the biological aspects of a bolaamphiphile-based gene delivery system.

  5. Developing strategies for detection of gene doping.

    Science.gov (United States)

    Baoutina, Anna; Alexander, Ian E; Rasko, John E J; Emslie, Kerry R

    2008-01-01

    It is feared that the use of gene transfer technology to enhance athletic performance, the practice that has received the term 'gene doping', may soon become a real threat to the world of sport. As recognised by the anti-doping community, gene doping, like doping in any form, undermines principles of fair play in sport and most importantly, involves major health risks to athletes who partake in gene doping. One attraction of gene doping for such athletes and their entourage lies in the apparent difficulty of detecting its use. Since the realisation of the threat of gene doping to sport in 2001, the anti-doping community and scientists from different disciplines concerned with potential misuse of gene therapy technologies for performance enhancement have focused extensive efforts on developing robust methods for gene doping detection which could be used by the World Anti-Doping Agency to monitor athletes and would meet the requirements of a legally defensible test. Here we review the approaches and technologies which are being evaluated for the detection of gene doping, as well as for monitoring the efficacy of legitimate gene therapy, in relation to the detection target, the type of sample required for analysis and detection methods. We examine the accumulated knowledge on responses of the body, at both cellular and systemic levels, to gene transfer and evaluate strategies for gene doping detection based on current knowledge of gene technology, immunology, transcriptomics, proteomics, biochemistry and physiology. (c) 2008 John Wiley & Sons, Ltd.

  6. The Mycoplasma hominis vaa gene displays a mosaic gene structure

    DEFF Research Database (Denmark)

    Boesen, Thomas; Emmersen, Jeppe M. G.; Jensen, Lise T.

    1998-01-01

    Mycoplasma hominis contains a variable adherence-associated (vaa) gene. To classify variants of the vaa genes, we examined 42 M. hominis isolated by PCR, DNA sequencing and immunoblotting. This uncovered the existence of five gene categories. Comparison of the gene types revealed a modular...

  7. Boolean Dynamic Modeling Approaches to Study Plant Gene Regulatory Networks: Integration, Validation, and Prediction.

    Science.gov (United States)

    Velderraín, José Dávila; Martínez-García, Juan Carlos; Álvarez-Buylla, Elena R

    2017-01-01

    Mathematical models based on dynamical systems theory are well-suited tools for the integration of available molecular experimental data into coherent frameworks in order to propose hypotheses about the cooperative regulatory mechanisms driving developmental processes. Computational analysis of the proposed models using well-established methods enables testing the hypotheses by contrasting predictions with observations. Within such framework, Boolean gene regulatory network dynamical models have been extensively used in modeling plant development. Boolean models are simple and intuitively appealing, ideal tools for collaborative efforts between theorists and experimentalists. In this chapter we present protocols used in our group for the study of diverse plant developmental processes. We focus on conceptual clarity and practical implementation, providing directions to the corresponding technical literature.

  8. Genome Wide Association Study of SNP-, Gene-, and Pathway-based Approaches to Identify Genes Influencing Susceptibility to Staphylococcus aureus Infections

    Directory of Open Access Journals (Sweden)

    Zhan eYe

    2014-05-01

    Full Text Available Background: We conducted a genome-wide association study (GWAS to identify specific genetic variants that underlie susceptibility to disease caused by Staphylococcus aureus in humans. Methods: Cases (n=309 and controls (n=2,925 were genotyped at 508,921 single nucleotide polymorphisms (SNPs. Cases had at least one laboratory and clinician confirmed disease caused by S. aureus whereas controls did not. R-package (for SNP association, EIGENSOFT (to estimate and adjust for population stratification and gene- (VEGAS and pathway-based (DAVID, PANTHER, and Ingenuity Pathway Analysis analyses were performed.Results: No SNP reached genome-wide significance. Four SNPs exceeded the pConclusion: We identified potential susceptibility genes for S. aureus diseases in this preliminary study but confirmation by other studies is needed. The observed associations could be relevant given the complexity of S. aureus as a pathogen and its ability to exploit multiple biological pathways to cause infections in humans.

  9. Gene therapy for lipid disorders

    Directory of Open Access Journals (Sweden)

    Rader Daniel J

    2000-10-01

    Full Text Available Abstract Lipid disorders are associated with atherosclerotic vascular disease, and therapy is associated with a substantial reduction in cardiovascular events. Current approaches to the treatment of lipid disorders are ineffective in a substantial number of patients. New therapies for refractory hypercholesterolemia, severe hypertriglyceridemia, and low levels of high-density lipoprotein cholesterol are needed: somatic gene therapy is one viable approach. The molecular etiology and pathophysiology of most of the candidate diseases are well understood. Animal models exist for the diseases and in many cases preclinical proof-of-principle studies have already been performed. There has been progress in the development of vectors that provide long-term gene expression. New clinical gene therapy trials for lipid disorders are likely to be initiated within the next few years.

  10. Evolutionary approaches for the reverse-engineering of gene regulatory networks: A study on a biologically realistic dataset

    Directory of Open Access Journals (Sweden)

    Gidrol Xavier

    2008-02-01

    Full Text Available Abstract Background Inferring gene regulatory networks from data requires the development of algorithms devoted to structure extraction. When only static data are available, gene interactions may be modelled by a Bayesian Network (BN that represents the presence of direct interactions from regulators to regulees by conditional probability distributions. We used enhanced evolutionary algorithms to stochastically evolve a set of candidate BN structures and found the model that best fits data without prior knowledge. Results We proposed various evolutionary strategies suitable for the task and tested our choices using simulated data drawn from a given bio-realistic network of 35 nodes, the so-called insulin network, which has been used in the literature for benchmarking. We assessed the inferred models against this reference to obtain statistical performance results. We then compared performances of evolutionary algorithms using two kinds of recombination operators that operate at different scales in the graphs. We introduced a niching strategy that reinforces diversity through the population and avoided trapping of the algorithm in one local minimum in the early steps of learning. We show the limited effect of the mutation operator when niching is applied. Finally, we compared our best evolutionary approach with various well known learning algorithms (MCMC, K2, greedy search, TPDA, MMHC devoted to BN structure learning. Conclusion We studied the behaviour of an evolutionary approach enhanced by niching for the learning of gene regulatory networks with BN. We show that this approach outperforms classical structure learning methods in elucidating the original model. These results were obtained for the learning of a bio-realistic network and, more importantly, on various small datasets. This is a suitable approach for learning transcriptional regulatory networks from real datasets without prior knowledge.

  11. Inducing indel mutation in the SOX6 gene by zinc finger nuclease for gamma reactivation: An approach towards gene therapy of beta thalassemia.

    Science.gov (United States)

    Modares Sadeghi, Mehran; Shariati, Laleh; Hejazi, Zahra; Shahbazi, Mansoureh; Tabatabaiefar, Mohammad Amin; Khanahmad, Hossein

    2018-03-01

    β-thalassemia is a common autosomal recessive disorder characterized by a deficiency in the synthesis of β-chains. Evidences show that increased HbF levels improve the symptoms in patients with β-thalassemia or sickle cell anemia. In this study, ZFN technology was applied to induce a mutation in the binding domain region of SOX6 to reactivate γ-globin expression. The sequences coding for ZFP arrays were designed and sub cloned in TDH plus as a transfer vector. The ZFN expression was confirmed using Western blot analysis. In the next step, using the site-directed mutagenesis strategy through the overlap PCR, a missense mutation (D64V) was induced in the catalytic domain of the integrase gene in the packaging plasmid and verified using DNA sequencing. Then, the integrase minus lentivirus containing ZFN cassette was packaged. Transduction of K562 cells with this virus was performed. Mutation detection assay was performed. The indel percentage of the cells transducted with lenti virus containing ZFN was 31%. After 5 days of erythroid differentiation with 15 μg/mL cisplatin, the levels of γ-globin mRNA were sixfold in the cells treated with ZFN compared to untreated cells. In the meantime, the measurement of HbF expression levels was carried out using hemoglobin electrophoresis and showed the same results. Integrase minus lentivirus can provide a useful tool for efficient transient gene expression and helps avoid disadvantages of gene targeting using the native virus. The ZFN strategy applied here to induce indel on SOX6 gene in adult erythroid progenitors may provide a method to activate fetal hemoglobin expression in individuals with β-thalassemia. © 2017 Wiley Periodicals, Inc.

  12. Cross-species multiple environmental stress responses: An integrated approach to identify candidate genes for multiple stress tolerance in sorghum (Sorghum bicolor (L. Moench and related model species.

    Directory of Open Access Journals (Sweden)

    Adugna Abdi Woldesemayat

    Full Text Available Crop response to the changing climate and unpredictable effects of global warming with adverse conditions such as drought stress has brought concerns about food security to the fore; crop yield loss is a major cause of concern in this regard. Identification of genes with multiple responses across environmental stresses is the genetic foundation that leads to crop adaptation to environmental perturbations.In this paper, we introduce an integrated approach to assess candidate genes for multiple stress responses across-species. The approach combines ontology based semantic data integration with expression profiling, comparative genomics, phylogenomics, functional gene enrichment and gene enrichment network analysis to identify genes associated with plant stress phenotypes. Five different ontologies, viz., Gene Ontology (GO, Trait Ontology (TO, Plant Ontology (PO, Growth Ontology (GRO and Environment Ontology (EO were used to semantically integrate drought related information.Target genes linked to Quantitative Trait Loci (QTLs controlling yield and stress tolerance in sorghum (Sorghum bicolor (L. Moench and closely related species were identified. Based on the enriched GO terms of the biological processes, 1116 sorghum genes with potential responses to 5 different stresses, such as drought (18%, salt (32%, cold (20%, heat (8% and oxidative stress (25% were identified to be over-expressed. Out of 169 sorghum drought responsive QTLs associated genes that were identified based on expression datasets, 56% were shown to have multiple stress responses. On the other hand, out of 168 additional genes that have been evaluated for orthologous pairs, 90% were conserved across species for drought tolerance. Over 50% of identified maize and rice genes were responsive to drought and salt stresses and were co-located within multifunctional QTLs. Among the total identified multi-stress responsive genes, 272 targets were shown to be co-localized within QTLs

  13. Systems biology approach to transplant tolerance: proof of concept experiments using RNA interference (RNAi) to knock down hub genes in Jurkat and HeLa cells in vitro.

    Science.gov (United States)

    Lwin, Wint Wah; Park, Ken; Wauson, Matthew; Gao, Qin; Finn, Patricia W; Perkins, David; Khanna, Ajai

    2012-07-01

    Systems biology is gaining importance in studying complex systems such as the functional interconnections of human genes [1]. To investigate the molecular interactions involved in T cell immune responses, we used databases of physical gene-gene interactions to constructed molecular interaction networks (interconnections) with R language algorithms. This helped to identify highly interconnected "hub" genes AT(1)P5C1, IL6ST, PRKCZ, MYC, FOS, JUN, and MAPK1. We hypothesized that suppression of these hub genes in the gene network would result in significant phenotypic effects on T cells and examined this in vitro. The molecular interaction networks were then analyzed and visualized with Cytoscape. Jurkat and HeLa cells were transfected with siRNA for the selected hub genes. Cell proliferation was measured using ATP luminescence and BrdU labeling, which were measured 36, 72, and 96 h after activation. Following T cell stimulation, we found a significant decrease in ATP production (P cells. However, HeLa cells showed a significant (P cell proliferation when the genes MAPK1, IL6ST, ATP5C1, JUN, and FOS were knocked down. In both Jurkat and HeLa cells, targeted gene knockdown using siRNA showed decreased cell proliferation and ATP production in both Jurkat and HeLa cells. However, Jurkat T cells and HELA cells use different hub genes to regulate activation responses. This experiment provides proof of principle of applying siRNA knockdown of T cell hub genes to evaluate their proliferative capacity and ATP production. This novel concept outlines a systems biology approach to identify hub genes for targeted therapeutics. Published by Elsevier Inc.

  14. A biology-driven approach identifies the hypoxia gene signature as a predictor of the outcome of neuroblastoma patients

    Directory of Open Access Journals (Sweden)

    Fardin Paolo

    2010-07-01

    Full Text Available Abstract Background Hypoxia is a condition of low oxygen tension occurring in the tumor microenvironment and it is related to poor prognosis in human cancer. To examine the relationship between hypoxia and neuroblastoma, we generated and tested an in vitro derived hypoxia gene signature for its ability to predict patients' outcome. Results We obtained the gene expression profile of 11 hypoxic neuroblastoma cell lines and we derived a robust 62 probesets signature (NB-hypo taking advantage of the strong discriminating power of the l1-l2 feature selection technique combined with the analysis of differential gene expression. We profiled gene expression of the tumors of 88 neuroblastoma patients and divided them according to the NB-hypo expression values by K-means clustering. The NB-hypo successfully stratifies the neuroblastoma patients into good and poor prognosis groups. Multivariate Cox analysis revealed that the NB-hypo is a significant independent predictor after controlling for commonly used risk factors including the amplification of MYCN oncogene. NB-hypo increases the resolution of the MYCN stratification by dividing patients with MYCN not amplified tumors in good and poor outcome suggesting that hypoxia is associated with the aggressiveness of neuroblastoma tumor independently from MYCN amplification. Conclusions Our results demonstrate that the NB-hypo is a novel and independent prognostic factor for neuroblastoma and support the view that hypoxia is negatively correlated with tumors' outcome. We show the power of the biology-driven approach in defining hypoxia as a critical molecular program in neuroblastoma and the potential for improvement in the current criteria for risk stratification.

  15. 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...

  16. Gene transfer technology and genetic radioisotope targeting therapy

    International Nuclear Information System (INIS)

    Wang Jiaqiong; Wang Zizheng

    2004-01-01

    With deeper cognition about mechanisms of disease at the cellular and molecular level, gene therapy has become one of the most important research fields in medical molecular biology at present. Gene transfer technology plays an important role during the course of gene therapy, and further improvement should be made about vectors carrying target gene sequences. Also, gene survey is needed during gene therapy, and gene imaging is the most effective method. The combination of gene therapy and targeted radiotherapy, that is, 'Genetic Radioisotope Targeting Therapy', will be a novel approach to tumor gene therapy

  17. Newer Gene Editing Technologies toward HIV Gene Therapy

    Directory of Open Access Journals (Sweden)

    Premlata Shankar

    2013-11-01

    Full Text Available Despite the great success of highly active antiretroviral therapy (HAART in ameliorating the course of HIV infection, alternative therapeutic approaches are being pursued because of practical problems associated with life-long therapy. The eradication of HIV in the so-called “Berlin patient” who received a bone marrow transplant from a CCR5-negative donor has rekindled interest in genome engineering strategies to achieve the same effect. Precise gene editing within the cells is now a realistic possibility with recent advances in understanding the DNA repair mechanisms, DNA interaction with transcription factors and bacterial defense mechanisms. Within the past few years, four novel technologies have emerged that can be engineered for recognition of specific DNA target sequences to enable site-specific gene editing: Homing Endonuclease, ZFN, TALEN, and CRISPR/Cas9 system. The most recent CRISPR/Cas9 system uses a short stretch of complementary RNA bound to Cas9 nuclease to recognize and cleave target DNA, as opposed to the previous technologies that use DNA binding motifs of either zinc finger proteins or transcription activator-like effector molecules fused to an endonuclease to mediate sequence-specific DNA cleavage. Unlike RNA interference, which requires the continued presence of effector moieties to maintain gene silencing, the newer technologies allow permanent disruption of the targeted gene after a single treatment. Here, we review the applications, limitations and future prospects of novel gene-editing strategies for use as HIV therapy.

  18. FunGene: the functional gene pipeline and repository.

    Science.gov (United States)

    Fish, Jordan A; Chai, Benli; Wang, Qiong; Sun, Yanni; Brown, C Titus; Tiedje, James M; Cole, James R

    2013-01-01

    Ribosomal RNA genes have become the standard molecular markers for microbial community analysis for good reasons, including universal occurrence in cellular organisms, availability of large databases, and ease of rRNA gene region amplification and analysis. As markers, however, rRNA genes have some significant limitations. The rRNA genes are often present in multiple copies, unlike most protein-coding genes. The slow rate of change in rRNA genes means that multiple species sometimes share identical 16S rRNA gene sequences, while many more species share identical sequences in the short 16S rRNA regions commonly analyzed. In addition, the genes involved in many important processes are not distributed in a phylogenetically coherent manner, potentially due to gene loss or horizontal gene transfer. While rRNA genes remain the most commonly used markers, key genes in ecologically important pathways, e.g., those involved in carbon and nitrogen cycling, can provide important insights into community composition and function not obtainable through rRNA analysis. However, working with ecofunctional gene data requires some tools beyond those required for rRNA analysis. To address this, our Functional Gene Pipeline and Repository (FunGene; http://fungene.cme.msu.edu/) offers databases of many common ecofunctional genes and proteins, as well as integrated tools that allow researchers to browse these collections and choose subsets for further analysis, build phylogenetic trees, test primers and probes for coverage, and download aligned sequences. Additional FunGene tools are specialized to process coding gene amplicon data. For example, FrameBot produces frameshift-corrected protein and DNA sequences from raw reads while finding the most closely related protein reference sequence. These tools can help provide better insight into microbial communities by directly studying key genes involved in important ecological processes.

  19. FunGene: the Functional Gene Pipeline and Repository

    Directory of Open Access Journals (Sweden)

    Jordan A. Fish

    2013-10-01

    Full Text Available Ribosomal RNA genes have become the standard molecular markers for microbial community analysis for good reasons, including universal occurrence in cellular organisms, availability of large databases, and ease of rRNA gene region amplification and analysis. As markers, however, rRNA genes have some significant limitations. The rRNA genes are often present in multiple copies, unlike most protein-coding genes. The slow rate of change in rRNA genes means that multiple species sometimes share identical 16S rRNA gene sequences, while many more species share identical sequences in the short 16S rRNA regions commonly analyzed. In addition, the genes involved in many important processes are not distributed in a phylogenetically coherent manner, potentially due to gene loss or horizontal gene transfer.While rRNA genes remain the most commonly used markers, key genes in ecologically important pathways, e.g., those involved in carbon and nitrogen cycling, can provide important insights into community composition and function not obtainable through rRNA analysis. However, working with ecofunctional gene data requires some tools beyond those required for rRNA analysis. To address this, our Functional Gene Pipeline and Repository (FunGene; http://fungene.cme.msu.edu/ offers databases of many common ecofunctional genes and proteins, as well as integrated tools that allow researchers to browse these collections and choose subsets for further analysis, build phylogenetic trees, test primers and probes for coverage, and download aligned sequences. Additional FunGene tools are specialized to process coding gene amplicon data. For example, FrameBot produces frameshift-corrected protein and DNA sequences from raw reads while finding the most closely related protein reference sequence. These tools can help provide better insight into microbial communities by directly studying key genes involved in important ecological processes.

  20. Gene therapy prospects--intranasal delivery of therapeutic genes.

    Science.gov (United States)

    Podolska, Karolina; Stachurska, Anna; Hajdukiewicz, Karolina; Małecki, Maciej

    2012-01-01

    Gene therapy is recognized to be a novel method for the treatment of various disorders. Gene therapy strategies involve gene manipulation on broad biological processes responsible for the spreading of diseases. Cancer, monogenic diseases, vascular and infectious diseases are the main targets of gene therapy. In order to obtain valuable experimental and clinical results, sufficient gene transfer methods are required. Therapeutic genes can be administered into target tissues via gene carriers commonly defined as vectors. The retroviral, adenoviral and adeno-associated virus based vectors are most frequently used in the clinic. So far, gene preparations may be administered directly into target organs or by intravenous, intramuscular, intratumor or intranasal injections. It is common knowledge that the number of gene therapy clinical trials has rapidly increased. However, some limitations such as transfection efficiency and stable and long-term gene expression are still not resolved. Consequently, great effort is focused on the evaluation of new strategies of gene delivery. There are many expectations associated with intranasal delivery of gene preparations for the treatment of diseases. Intranasal delivery of therapeutic genes is regarded as one of the most promising forms of pulmonary gene therapy research. Gene therapy based on inhalation of gene preparations offers an alternative way for the treatment of patients suffering from such lung diseases as cystic fibrosis, alpha-1-antitrypsin defect, or cancer. Experimental and first clinical trials based on plasmid vectors or recombinant viruses have revealed that gene preparations can effectively deliver therapeutic or marker genes to the cells of the respiratory tract. The noninvasive intranasal delivery of gene preparations or conventional drugs seems to be very encouraging, although basic scientific research still has to continue.

  1. GoGene: gene annotation in the fast lane.

    Science.gov (United States)

    Plake, Conrad; Royer, Loic; Winnenburg, Rainer; Hakenberg, Jörg; Schroeder, Michael

    2009-07-01

    High-throughput screens such as microarrays and RNAi screens produce huge amounts of data. They typically result in hundreds of genes, which are often further explored and clustered via enriched GeneOntology terms. The strength of such analyses is that they build on high-quality manual annotations provided with the GeneOntology. However, the weakness is that annotations are restricted to process, function and location and that they do not cover all known genes in model organisms. GoGene addresses this weakness by complementing high-quality manual annotation with high-throughput text mining extracting co-occurrences of genes and ontology terms from literature. GoGene contains over 4,000,000 associations between genes and gene-related terms for 10 model organisms extracted from more than 18,000,000 PubMed entries. It does not cover only process, function and location of genes, but also biomedical categories such as diseases, compounds, techniques and mutations. By bringing it all together, GoGene provides the most recent and most complete facts about genes and can rank them according to novelty and importance. GoGene accepts keywords, gene lists, gene sequences and protein sequences as input and supports search for genes in PubMed, EntrezGene and via BLAST. Since all associations of genes to terms are supported by evidence in the literature, the results are transparent and can be verified by the user. GoGene is available at http://gopubmed.org/gogene.

  2. Introduction: Cancer Gene Networks.

    Science.gov (United States)

    Clarke, Robert

    2017-01-01

    Constructing, evaluating, and interpreting gene networks generally sits within the broader field of systems biology, which continues to emerge rapidly, particular with respect to its application to understanding the complexity of signaling in the context of cancer biology. For the purposes of this volume, we take a broad definition of systems biology. Considering an organism or disease within an organism as a system, systems biology is the study of the integrated and coordinated interactions of the network(s) of genes, their variants both natural and mutated (e.g., polymorphisms, rearrangements, alternate splicing, mutations), their proteins and isoforms, and the organic and inorganic molecules with which they interact, to execute the biochemical reactions (e.g., as enzymes, substrates, products) that reflect the function of that system. Central to systems biology, and perhaps the only approach that can effectively manage the complexity of such systems, is the building of quantitative multiscale predictive models. The predictions of the models can vary substantially depending on the nature of the model and its inputoutput relationships. For example, a model may predict the outcome of a specific molecular reaction(s), a cellular phenotype (e.g., alive, dead, growth arrest, proliferation, and motility), a change in the respective prevalence of cell or subpopulations, a patient or patient subgroup outcome(s). Such models necessarily require computers. Computational modeling can be thought of as using machine learning and related tools to integrate the very high dimensional data generated from modern, high throughput omics technologies including genomics (next generation sequencing), transcriptomics (gene expression microarrays; RNAseq), metabolomics and proteomics (ultra high performance liquid chromatography, mass spectrometry), and "subomic" technologies to study the kinome, methylome, and others. Mathematical modeling can be thought of as the use of ordinary

  3. Gene therapy in animal models of autosomal dominant retinitis pigmentosa

    Science.gov (United States)

    Rossmiller, Brian; Mao, Haoyu

    2012-01-01

    Gene therapy for dominantly inherited genetic disease is more difficult than gene-based therapy for recessive disorders, which can be treated with gene supplementation. Treatment of dominant disease may require gene supplementation partnered with suppression of the expression of the mutant gene either at the DNA level, by gene repair, or at the RNA level by RNA interference or transcriptional repression. In this review, we examine some of the gene delivery approaches used to treat animal models of autosomal dominant retinitis pigmentosa, focusing on those models associated with mutations in the gene for rhodopsin. We conclude that combinatorial approaches have the greatest promise for success. PMID:23077406

  4. Global Transcriptome Analysis of Combined Abiotic Stress Signaling Genes Unravels Key Players in Oryza sativa L.: An In silico Approach

    Directory of Open Access Journals (Sweden)

    Pandiyan Muthuramalingam

    2017-05-01

    Full Text Available Combined abiotic stress (CAbS affects the field grown plants simultaneously. The multigenic and quantitative nature of uncontrollable abiotic stresses complicates the process of understanding the stress response by plants. Considering this, we analyzed the CAbS response of C3 model plant, Oryza sativa by meta-analysis. The datasets of commonly expressed genes by drought, salinity, submergence, metal, natural expression, biotic, and abiotic stresses were data mined through publically accessible transcriptomic abiotic stress (AbS responsive datasets. Of which 1,175, 12,821, and 42,877 genes were commonly expressed in meta differential, individual differential, and unchanged expressions respectively. Highly regulated 100 differentially expressed AbS genes were derived through integrative meta-analysis of expression data (INMEX. Of this 30 genes were identified from AbS gene families through expression atlas that were computationally analyzed for their physicochemical properties. All AbS genes were physically mapped against O. sativa genome. Comparative mapping of these genes demonstrated the orthologous relationship with related C4 panicoid genome. In silico expression analysis of these genes showed differential expression patterns in different developmental tissues. Protein–protein interaction of these genes, represented the complexity of AbS. Computational expression profiling of candidate genes in response to multiple stresses suggested the putative involvement of OS05G0350900, OS02G0612700, OS05G0104200, OS03G0596200, OS12G0225900, OS07G0152000, OS08G0119500, OS06G0594700, and Os01g0393100 in CAbS. These potential candidate genes need to be studied further to decipher their functional roles in AbS dynamics.

  5. Genes and inheritance.

    Science.gov (United States)

    Middelton, L A; Peters, K F

    2001-10-01

    The information gained from the Human Genome Project and related genetic research will undoubtedly create significant changes in healthcare practice. It is becoming increasingly clear that nurses in all areas of clinical practice will require a fundamental understanding of basic genetics. This article provides the oncology nurse with an overview of basic genetic concepts, including inheritance patterns of single gene conditions, pedigree construction, chromosome aberrations, and the multifactorial basis underlying the common diseases of adulthood. Normal gene structure and function are introduced and the biochemistry of genetic errors is described.

  6. Inactivation of tumor suppressor genes and cancer therapy: An evolutionary game theory approach.

    Science.gov (United States)

    Khadem, Heydar; Kebriaei, Hamed; Veisi, Zahra

    2017-06-01

    Inactivation of alleles in tumor suppressor genes (TSG) is one of the important issues resulting in evolution of cancerous cells. In this paper, the evolution of healthy, one and two missed allele cells is modeled using the concept of evolutionary game theory and replicator dynamics. The proposed model also takes into account the interaction rates of the cells as designing parameters of the system. Different combinations of the equilibrium points of the parameterized nonlinear system is studied and categorized into some cases. In each case, the interaction rates' values are suggested in a way that the equilibrium points of the replicator dynamics are located on an appropriate region of the state space. Based on the suggested interaction rates, it is proved that the system doesn't have any undesirable interior equilibrium point as well. Therefore, the system will converge to the desirable region, where there is a scanty level of cancerous cells. In addition, the proposed conditions for interaction rates guarantee that, when a trajectory of the system reaches the boundaries, then it will stay there forever which is a desirable property since the equilibrium points have been already located on the boundaries, appropriately. The simulation results show the effectiveness of the suggestions in the elimination of the cancerous cells in different scenarios. Copyright © 2017 Elsevier Inc. All rights reserved.

  7. 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

  8. Candidate genes in panic disorder

    DEFF Research Database (Denmark)

    Howe, A. S.; Buttenschön, Henriette N; Bani-Fatemi, A.

    2016-01-01

    The utilization of molecular genetics approaches in examination of panic disorder (PD) has implicated several variants as potential susceptibility factors for panicogenesis. However, the identification of robust PD susceptibility genes has been complicated by phenotypic diversity, underpowered...... association studies and ancestry-specific effects. In the present study, we performed a succinct review of case-control association studies published prior to April 2015. Meta-analyses were performed for candidate gene variants examined in at least three studies using the Cochrane Mantel-Haenszel fixed......-effect model. Secondary analyses were also performed to assess the influences of sex, agoraphobia co-morbidity and ancestry-specific effects on panicogenesis. Meta-analyses were performed on 23 variants in 20 PD candidate genes. Significant associations after correction for multiple testing were observed...

  9. Screening for single nucleotide variants, small indels and exon deletions with a next-generation sequencing based gene panel approach for Usher syndrome.

    Science.gov (United States)

    Krawitz, Peter M; Schiska, Daniela; Krüger, Ulrike; Appelt, Sandra; Heinrich, Verena; Parkhomchuk, Dmitri; Timmermann, Bernd; Millan, Jose M; Robinson, Peter N; Mundlos, Stefan; Hecht, Jochen; Gross, Manfred

    2014-09-01

    Usher syndrome is an autosomal recessive disorder characterized both by deafness and blindness. For the three clinical subtypes of Usher syndrome causal mutations in altogether 12 genes and a modifier gene have been identified. Due to the genetic heterogeneity of Usher syndrome, the molecular analysis is predestined for a comprehensive and parallelized analysis of all known genes by next-generation sequencing (NGS) approaches. We describe here the targeted enrichment and deep sequencing for exons of Usher genes and compare the costs and workload of this approach compared to Sanger sequencing. We also present a bioinformatics analysis pipeline that allows us to detect single-nucleotide variants, short insertions and deletions, as well as copy number variations of one or more exons on the same sequence data. Additionally, we present a flexible in silico gene panel for the analysis of sequence variants, in which newly identified genes can easily be included. We applied this approach to a cohort of 44 Usher patients and detected biallelic pathogenic mutations in 35 individuals and monoallelic mutations in eight individuals of our cohort. Thirty-nine of the sequence variants, including two heterozygous deletions comprising several exons of USH2A, have not been reported so far. Our NGS-based approach allowed us to assess single-nucleotide variants, small indels, and whole exon deletions in a single test. The described diagnostic approach is fast and cost-effective with a high molecular diagnostic yield.

  10. Gene replacement in Penicillium roqueforti.

    Science.gov (United States)

    Goarin, Anne; Silar, Philippe; Malagnac, Fabienne

    2015-05-01

    Most cheese-making filamentous fungi lack suitable molecular tools to improve their biotechnology potential. Penicillium roqueforti, a species of high industrial importance, would benefit from functional data yielded by molecular genetic approaches. This work provides the first example of gene replacement by homologous recombination in P. roqueforti, demonstrating that knockout experiments can be performed in this fungus. To do so, we improved the existing transformation method to integrate transgenes into P. roqueforti genome. In the meantime, we cloned the PrNiaD gene, which encodes a NADPH-dependent nitrate reductase that reduces nitrate to nitrite. Then, we performed a deletion of the PrNiaD gene from P. roqueforti strain AGO. The ΔPrNiaD mutant strain is more resistant to chlorate-containing medium than the wild-type strain, but did not grow on nitrate-containing medium. Because genomic data are now available, we believe that generating selective deletions of candidate genes will be a key step to open the way for a comprehensive exploration of gene function in P. roqueforti.

  11. Detection of EPO gene doping in blood.

    Science.gov (United States)

    Neuberger, Elmo W I; Jurkiewicz, Magdalena; Moser, Dirk A; Simon, Perikles

    2012-11-01

    Gene doping--or the abuse of gene therapy--will continue to threaten the sports world. History has shown that progress in medical research is likely to be abused in order to enhance human performance. In this review, we critically discuss the progress and the risks associated with the field of erythropoietin (EPO) gene therapy and its applicability to EPO gene doping. We present typical vector systems that are employed in ex vivo and in vivo gene therapy trials. Due to associated risks, gene doping is not a feasible alternative to conventional EPO or blood doping at this time. Nevertheless, it is well described that about half of the elite athlete population is in principle willing to risk its health to gain a competitive advantage. This includes the use of technologies that lack safety approval. Sophisticated detection approaches are a prerequisite for prevention of unapproved and uncontrolled use of gene therapy technology. In this review, we present current detection approaches for EPO gene doping, with a focus on blood-based direct and indirect approaches. Gene doping is detectable in principle, and recent DNA-based detection strategies enable long-term detection of transgenic DNA (tDNA) following in vivo gene transfer. Copyright © 2012 John Wiley & Sons, Ltd.

  12. Twenty Years of European Union Support to Gene Therapy and Gene Transfer.

    Science.gov (United States)

    Gancberg, David

    2017-11-01

    For 20 years and throughout its research programmes, the European Union has supported the entire innovation chain for gene transfer and gene therapy. The fruits of this investment are ripening as gene therapy products are reaching the European market and as clinical trials are demonstrating the safety of this approach to treat previously untreatable diseases.

  13. Mining disease genes using integrated protein-protein interaction and gene-gene co-regulation information.

    Science.gov (United States)

    Li, Jin; Wang, Limei; Guo, Maozu; Zhang, Ruijie; Dai, Qiguo; Liu, Xiaoyan; Wang, Chunyu; Teng, Zhixia; Xuan, Ping; Zhang, Mingming

    2015-01-01

    In humans, despite the rapid increase in disease-associated gene discovery, a large proportion of disease-associated genes are still unknown. Many network-based approaches have been used to prioritize disease genes. Many networks, such as the protein-protein interaction (PPI), KEGG, and gene co-expression networks, have been used. Expression quantitative trait loci (eQTLs) have been successfully applied for the determination of genes associated with several diseases. In this study, we constructed an eQTL-based gene-gene co-regulation network (GGCRN) and used it to mine for disease genes. We adopted the random walk with restart (RWR) algorithm to mine for genes associated with Alzheimer disease. Compared to the Human Protein Reference Database (HPRD) PPI network alone, the integrated HPRD PPI and GGCRN networks provided faster convergence and revealed new disease-related genes. Therefore, using the RWR algorithm for integrated PPI and GGCRN is an effective method for disease-associated gene mining.

  14. Norrie disease gene is distinct from the monoamine oxidase genes

    OpenAIRE

    Sims, Katherine B.; Ozelius, Laurie; Corey, Timothy; Rinehart, William B.; Liberfarb, Ruth; Haines, Jonathan; Chen, Wei Jane; Norio, Reijo; Sankila, Eeva; de la Chapelle, Albert; Murphy, Dennis L.; Gusella, James; Breakefield, Xandra O.

    1989-01-01

    The genes for MAO-A and MAO-B appear to be very close to the Norrie disease gene, on the basis of loss and /or disruption of the MAO genes and activities in atypical Norrie disease patients deleted for the DXS7 locus; linkage among the MAO genes, the Norrie disease gene, and the DXS7 locus; and mapping of all these loci to the chromosomal region Xp11. The present study provides evidence that the MAO genes are not disrupted in “classic” Norrie disease patients. Genomic DNA from these “nondelet...

  15. Comparative Genomic Analysis of Soybean Flowering Genes

    Science.gov (United States)

    Jung, Chol-Hee; Wong, Chui E.; Singh, Mohan B.; Bhalla, Prem L.

    2012-01-01

    Flowering is an important agronomic trait that determines crop yield. Soybean is a major oilseed legume crop used for human and animal feed. Legumes have unique vegetative and floral complexities. Our understanding of the molecular basis of flower initiation and development in legumes is limited. Here, we address this by using a computational approach to examine flowering regulatory genes in the soybean genome in comparison to the most studied model plant, Arabidopsis. For this comparison, a genome-wide analysis of orthologue groups was performed, followed by an in silico gene expression analysis of the identified soybean flowering genes. Phylogenetic analyses of the gene families highlighted the evolutionary relationships among these candidates. Our study identified key flowering genes in soybean and indicates that the vernalisation and the ambient-temperature pathways seem to be the most variant in soybean. A comparison of the orthologue groups containing flowering genes indicated that, on average, each Arabidopsis flowering gene has 2-3 orthologous copies in soybean. Our analysis highlighted that the CDF3, VRN1, SVP, AP3 and PIF3 genes are paralogue-rich genes in soybean. Furthermore, the genome mapping of the soybean flowering genes showed that these genes are scattered randomly across the genome. A paralogue comparison indicated that the soybean genes comprising the largest orthologue group are clustered in a 1.4 Mb region on chromosome 16 of soybean. Furthermore, a comparison with the undomesticated soybean (Glycine soja) revealed that there are hundreds of SNPs that are associated with putative soybean flowering genes and that there are structural variants that may affect the genes of the light-signalling and ambient-temperature pathways in soybean. Our study provides a framework for the soybean flowering pathway and insights into the relationship and evolution of flowering genes between a short-day soybean and the long-day plant, Arabidopsis. PMID:22679494

  16. A Candidate Gene Approach to ANCA-Associated Vasculitis Reveals Links to the C3 and CTLA-4 Genes but not to the IL1-Ra And Fcγ-RIIa Genes.

    OpenAIRE

    Persson, Ulf; Gullstrand, Birgitta; Pettersson, Åsa; Sturfelt, Gunnar; Truedsson, Lennart; Segelmark, Mårten

    2013-01-01

    Background/Aims: The aim of the study is to search for associations between Antineutrophil cytoplasm antibody (ANCA)-associated vasculitis (AAV) and polymorphisms in the genes of four key molecules possibly involved in different pathogenic pathways; complement C3, CTLA-4, Fcγ-RIIa and IL1-Ra. Patients and Methods: Patients with AAV (n=105) subgrouped as microscopic polyangiitis or granulomatosis with polyangiitis (Wegener's granulomatosis) and myeloperoxidase (MPO) or proteinase 3 (PR3) A...

  17. Hidden genes in birds

    Czech Academy of Sciences Publication Activity Database

    Hron, Tomáš; Pajer, Petr; Pačes, Jan; Bartůněk, Petr; Elleder, Daniel

    2015-01-01

    Roč. 16, August 18 (2015) ISSN 1465-6906 R&D Projects: GA MŠk(CZ) LK11215; GA MŠk LO1419 Grant - others:GA MŠk(CZ) LM2010005 Institutional support: RVO:68378050 Keywords : REPETITIVE SEQUENCES * G/C stretches * avian genes Subject RIV: EB - Genetics ; Molecular Biology Impact factor: 11.313, year: 2015

  18. Rhabdovirus accessory genes.

    Science.gov (United States)

    Walker, Peter J; Dietzgen, Ralf G; Joubert, D Albert; Blasdell, Kim R

    2011-12-01

    The Rhabdoviridae is one of the most ecologically diverse families of RNA viruses with members infecting a wide range of organisms including placental mammals, marsupials, birds, reptiles, fish, insects and plants. The availability of complete nucleotide sequences for an increasing number of rhabdoviruses has revealed that their ecological diversity is reflected in the diversity and complexity of their genomes. The five canonical rhabdovirus structural protein genes (N, P, M, G and L) that are shared by all rhabdoviruses are overprinted, overlapped and interspersed with a multitude of novel and diverse accessory genes. Although not essential for replication in cell culture, several of these genes have been shown to have roles associated with pathogenesis and apoptosis in animals, and cell-to-cell movement in plants. Others appear to be secreted or have the characteristics of membrane-anchored glycoproteins or viroporins. However, most encode proteins of unknown function that are unrelated to any other known proteins. Understanding the roles of these accessory genes and the strategies by which rhabdoviruses use them to engage, divert and re-direct cellular processes will not only present opportunities to develop new anti-viral therapies but may also reveal aspects of cellar function that have broader significance in biology, agriculture and medicine. Crown Copyright © 2011. Published by Elsevier B.V. All rights reserved.

  19. Targeting fumonisin biosynthetic genes

    Science.gov (United States)

    The fungus Fusarium is an agricultural problem because it can cause disease on most crop plants and can contaminate crops with mycotoxins. There is considerable variation in the presence/absence and genomic location of gene clusters responsible for synthesis of mycotoxins and other secondary metabol...

  20. Radio-induced genes

    International Nuclear Information System (INIS)

    Rigaud, O.; Kazmaier, M.

    2000-01-01

    The monitoring system of the DNA integrity of an irradiated cell does not satisfy oneself to recruit the enzymes allowing the repair of detected damages. It sends an alarm signal whom transmission leads to the activation of specific genes in charge of stopping the cell cycle, the time to make the repair works, or to lead to the elimination of a too much damaged cell. Among the numerous genes participating to the monitoring of cell response to irradiation, the target genes of the mammalian P53 protein are particularly studied. Caretaker of the genome, this protein play a central part in the cell response to ionizing radiations. this response is less studied among plants. A way to tackle it is to be interested in the radioinduced genes identification in the vegetal cell, while taking advantage of knowledge got in the animal field. The knowledge of the complete genome of the arabette (arabidopsis thaliana), the model plant and the arising of new techniques allow to lead this research at a previously unknown rhythm in vegetal biology. (N.C.)

  1. The Gene Guessing Game

    OpenAIRE

    Dunham, Ian

    2000-01-01

    A recent flurry of publications and media attention has revived interest in the question of how many genes exist in the human genome. Here, I review the estimates and use genomic sequence data from human chromosomes 21 and 22 to establish my own prediction.

  2. Targeting trichothecene biosynthetic genes

    NARCIS (Netherlands)

    Wei, Songhong; Lee, van der Theo; Verstappen, Els; Gent, van Marga; Waalwijk, Cees

    2017-01-01

    Biosynthesis of trichothecenes requires the involvement of at least 15 genes, most of which have been targeted for PCR. Qualitative PCRs are used to assign chemotypes to individual isolates, e.g., the capacity to produce type A and/or type B trichothecenes. Many regions in the core cluster

  3. Silence of the Genes

    Indian Academy of Sciences (India)

    Srimath

    a gene in the opposite orientation in a cultured plant cell line and observed that the ..... started emerging in early 1990s from the work carried out by the. It is believed that ... cause human diseases such as cervical cancer, hepatitis, measles.

  4. Silence of the Genes

    Indian Academy of Sciences (India)

    Home; Journals; Resonance – Journal of Science Education; Volume 12; Issue 4. Silence of the Genes - 2006 Nobel Prize in Physiology or Medicine. Utpal Nath Saumitra Das. General Article Volume 12 Issue 4 April 2007 pp 6-18. Fulltext. Click here to view fulltext PDF. Permanent link:

  5. Integrative microRNA and proteomic approaches identify novel osteoarthritis genes and their collaborative metabolic and inflammatory networks.

    Directory of Open Access Journals (Sweden)

    Dimitrios Iliopoulos

    Full Text Available BACKGROUND: Osteoarthritis is a multifactorial disease characterized by destruction of the articular cartilage due to genetic, mechanical and environmental components affecting more than 100 million individuals all over the world. Despite the high prevalence of the disease, the absence of large-scale molecular studies limits our ability to understand the molecular pathobiology of osteoathritis and identify targets for drug development. METHODOLOGY/PRINCIPAL FINDINGS: In this study we integrated genetic, bioinformatic and proteomic approaches in order to identify new genes and their collaborative networks involved in osteoarthritis pathogenesis. MicroRNA profiling of patient-derived osteoarthritic cartilage in comparison to normal cartilage, revealed a 16 microRNA osteoarthritis gene signature. Using reverse-phase protein arrays in the same tissues we detected 76 differentially expressed proteins between osteoarthritic and normal chondrocytes. Proteins such as SOX11, FGF23, KLF6, WWOX and GDF15 not implicated previously in the genesis of osteoarthritis were identified. Integration of microRNA and proteomic data with microRNA gene-target prediction algorithms, generated a potential "interactome" network consisting of 11 microRNAs and 58 proteins linked by 414 potential functional associations. Comparison of the molecular and clinical data, revealed specific microRNAs (miR-22, miR-103 and proteins (PPARA, BMP7, IL1B to be highly correlated with Body Mass Index (BMI. Experimental validation revealed that miR-22 regulated PPARA and BMP7 expression and its inhibition blocked inflammatory and catabolic changes in osteoarthritic chondrocytes. CONCLUSIONS/SIGNIFICANCE: Our findings indicate that obesity and inflammation are related to osteoarthritis, a metabolic disease affected by microRNA deregulation. Gene network approaches provide new insights for elucidating the complexity of diseases such as osteoarthritis. The integration of microRNA, proteomic

  6. A dual transcript-discovery approach to improve the delimitation of gene features from RNA-seq data in the chicken model

    Directory of Open Access Journals (Sweden)

    Mickael Orgeur

    2018-01-01

    Full Text Available The sequence of the chicken genome, like several other draft genome sequences, is presently not fully covered. Gaps, contigs assigned with low confidence and uncharacterized chromosomes result in gene fragmentation and imprecise gene annotation. Transcript abundance estimation from RNA sequencing (RNA-seq data relies on read quality, library complexity and expression normalization. In addition, the quality of the genome sequence used to map sequencing reads, and the gene annotation that defines gene features, must also be taken into account. A partially covered genome sequence causes the loss of sequencing reads from the mapping step, while an inaccurate definition of gene features induces imprecise read counts from the assignment step. Both steps can significantly bias interpretation of RNA-seq data. Here, we describe a dual transcript-discovery approach combining a genome-guided gene prediction and a de novo transcriptome assembly. This dual approach enabled us to increase the assignment rate of RNA-seq data by nearly 20% as compared to when using only the chicken reference annotation, contributing therefore to a more accurate estimation of transcript abundance. More generally, this strategy could be applied to any organism with partial genome sequence and/or lacking a manually-curated reference annotation in order to improve the accuracy of gene expression studies.

  7. Experimental estimation of mutation rates in a wheat population with a gene genealogy approach.

    Science.gov (United States)

    Raquin, Anne-Laure; Depaulis, Frantz; Lambert, Amaury; Galic, Nathalie; Brabant, Philippe; Goldringer, Isabelle

    2008-08-01

    Microsatellite markers are extensively used to evaluate genetic diversity in natural or experimental evolving populations. Their high degree of polymorphism reflects their high mutation rates. Estimates of the mutation rates are therefore necessary when characterizing diversity in populations. As a complement to the classical experimental designs, we propose to use experimental populations, where the initial state is entirely known and some intermediate states have been thoroughly surveyed, thus providing a short timescale estimation together with a large number of cumulated meioses. In this article, we derived four original gene genealogy-based methods to assess mutation rates with limited bias due to relevant model assumptions incorporating the initial state, the number of new alleles, and the genetic effective population size. We studied the evolution of genetic diversity at 21 microsatellite markers, after 15 generations in an experimental wheat population. Compared to the parents, 23 new alleles were found in generation 15 at 9 of the 21 loci studied. We provide evidence that they arose by mutation. Corresponding estimates of the mutation rates ranged from 0 to 4.97 x 10(-3) per generation (i.e., year). Sequences of several alleles revealed that length polymorphism was only due to variation in the core of the microsatellite. Among different microsatellite characteristics, both the motif repeat number and an independent estimation of the Nei diversity were correlated with the novel diversity. Despite a reduced genetic effective size, global diversity at microsatellite markers increased in this population, suggesting that microsatellite diversity should be used with caution as an indicator in biodiversity conservation issues.

  8. COGNATE: comparative gene annotation characterizer.

    Science.gov (United States)

    Wilbrandt, Jeanne; Misof, Bernhard; Niehuis, Oliver

    2017-07-17

    The comparison of gene and genome structures across species has the potential to reveal major trends of genome evolution. However, such a comparative approach is currently hampered by a lack of standardization (e.g., Elliott TA, Gregory TR, Philos Trans Royal Soc B: Biol Sci 370:20140331, 2015). For example, testing the hypothesis that the total amount of coding sequences is a reliable measure of potential proteome diversity (Wang M, Kurland CG, Caetano-Anollés G, PNAS 108:11954, 2011) requires the application of standardized definitions of coding sequence and genes to create both comparable and comprehensive data sets and corresponding summary statistics. However, such standard definitions either do not exist or are not consistently applied. These circumstances call for a standard at the descriptive level using a minimum of parameters as well as an undeviating use of standardized terms, and for software that infers the required data under these strict definitions. The acquisition of a comprehensive, descriptive, and standardized set of parameters and summary statistics for genome publications and further analyses can thus greatly benefit from the availability of an easy to use standard tool. We developed a new open-source command-line tool, COGNATE (Comparative Gene Annotation Characterizer), which uses a given genome assembly and its annotation of protein-coding genes for a detailed description of the respective gene and genome structure parameters. Additionally, we revised the standard definitions of gene and genome structures and provide the definitions used by COGNATE as a working draft suggestion for further reference. Complete parameter lists and summary statistics are inferred using this set of definitions to allow down-stream analyses and to provide an overview of the genome and gene repertoire characteristics. COGNATE is written in Perl and freely available at the ZFMK homepage ( https://www.zfmk.de/en/COGNATE ) and on github ( https

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

    International Nuclear Information System (INIS)

    Belov, O.V.

    2006-01-01

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

  10. Genes2FANs: connecting genes through functional association networks

    Science.gov (United States)

    2012-01-01

    Background Protein-protein, cell signaling, metabolic, and transcriptional interaction networks are useful for identifying connections between lists of experimentally identified genes/proteins. However, besides physical or co-expression interactions there are many ways in which pairs of genes, or their protein products, can be associated. By systematically incorporating knowledge on shared properties of genes from diverse sources to build functional association networks (FANs), researchers may be able to identify additional functional interactions between groups of genes that are not readily apparent. Results Genes2FANs is a web based tool and a database that utilizes 14 carefully constructed FANs and a large-scale protein-protein interaction (PPI) network to build subnetworks that connect lists of human and mouse genes. The FANs are created from mammalian gene set libraries where mouse genes are converted to their human orthologs. The tool takes as input a list of human or mouse Entrez gene symbols to produce a subnetwork and a ranked list of intermediate genes that are used to connect the query input list. In addition, users can enter any PubMed search term and then the system automatically converts the returned results to gene lists using GeneRIF. This gene list is then used as input to generate a subnetwork from the user’s PubMed query. As a case study, we applied Genes2FANs to connect disease genes from 90 well-studied disorders. We find an inverse correlation between the counts of links connecting disease genes through PPI and links connecting diseases genes through FANs, separating diseases into two categories. Conclusions Genes2FANs is a useful tool for interpreting the relationships between gene/protein lists in the context of their various functions and networks. Combining functional association interactions with physical PPIs can be useful for revealing new biology and help form hypotheses for further experimentation. Our finding that disease genes in

  11. Progress in Gene Therapy for Prostate Cancer

    Energy Technology Data Exchange (ETDEWEB)

    Ahmed, Kamran A.; Davis, Brian J. [Department of Radiation Oncology, Mayo Clinic, Rochester, MN (United States); Wilson, Torrence M. [Department of Urology, Mayo Clinic, Rochester, MN (United States); Wiseman, Gregory A. [Division of Nuclear Medicine, Mayo Clinic, Rochester, MN (United States); Federspiel, Mark J. [Department of Molecular Medicine, Mayo Clinic, Rochester, MN (United States); Morris, John C., E-mail: davis.brian@mayo.edu [Division of Endocrinology, Mayo Clinic, Rochester, MN (United States)

    2012-11-19

    Gene therapy has held promise to correct various disease processes. Prostate cancer represents the second leading cause of cancer death in American men. A number of clinical trials involving gene therapy for the treatment of prostate cancer have been reported. The ability to efficiently transduce tumors with effective levels of therapeutic genes has been identified as a fundamental barrier to effective cancer gene therapy. The approach utilizing gene therapy in prostate cancer patients at our institution attempts to address this deficiency. The sodium-iodide symporter (NIS) is responsible for the ability of the thyroid gland to transport and concentrate iodide. The characteristics of the NIS gene suggest that it could represent an ideal therapeutic gene for cancer therapy. Published results from Mayo Clinic researchers have indicated several important successes with the use of the NIS gene and prostate gene therapy. Studies have demonstrated that transfer of the human NIS gene into prostate cancer using adenovirus vectors in vitro and in vivo results in efficient uptake of radioactive iodine and significant tumor growth delay with prolongation of survival. Preclinical successes have culminated in the opening of a phase I trial for patients with advanced prostate disease which is currently accruing patients. Further study will reveal the clinical promise of NIS gene therapy in the treatment of prostate as well as other malignancies.

  12. Progress in Gene Therapy for Prostate Cancer

    International Nuclear Information System (INIS)

    Ahmed, Kamran A.; Davis, Brian J.; Wilson, Torrence M.; Wiseman, Gregory A.; Federspiel, Mark J.; Morris, John C.

    2012-01-01

    Gene therapy has held promise to correct various disease processes. Prostate cancer represents the second leading cause of cancer death in American men. A number of clinical trials involving gene therapy for the treatment of prostate cancer have been reported. The ability to efficiently transduce tumors with effective levels of therapeutic genes has been identified as a fundamental barrier to effective cancer gene therapy. The approach utilizing gene therapy in prostate cancer patients at our institution attempts to address this deficiency. The sodium-iodide symporter (NIS) is responsible for the ability of the thyroid gland to transport and concentrate iodide. The characteristics of the NIS gene suggest that it could represent an ideal therapeutic gene for cancer therapy. Published results from Mayo Clinic researchers have indicated several important successes with the use of the NIS gene and prostate gene therapy. Studies have demonstrated that transfer of the human NIS gene into prostate cancer using adenovirus vectors in vitro and in vivo results in efficient uptake of radioactive iodine and significant tumor growth delay with prolongation of survival. Preclinical successes have culminated in the opening of a phase I trial for patients with advanced prostate disease which is currently accruing patients. Further study will reveal the clinical promise of NIS gene therapy in the treatment of prostate as well as other malignancies.

  13. Industrial scale gene synthesis.

    Science.gov (United States)

    Notka, Frank; Liss, Michael; Wagner, Ralf

    2011-01-01

    The most recent developments in the area of deep DNA sequencing and downstream quantitative and functional analysis are rapidly adding a new dimension to understanding biochemical pathways and metabolic interdependencies. These increasing insights pave the way to designing new strategies that address public needs, including environmental applications and therapeutic inventions, or novel cell factories for sustainable and reconcilable energy or chemicals sources. Adding yet another level is building upon nonnaturally occurring networks and pathways. Recent developments in synthetic biology have created economic and reliable options for designing and synthesizing genes, operons, and eventually complete genomes. Meanwhile, high-throughput design and synthesis of extremely comprehensive DNA sequences have evolved into an enabling technology already indispensable in various life science sectors today. Here, we describe the industrial perspective of modern gene synthesis and its relationship with synthetic biology. Gene synthesis contributed significantly to the emergence of synthetic biology by not only providing the genetic material in high quality and quantity but also enabling its assembly, according to engineering design principles, in a standardized format. Synthetic biology on the other hand, added the need for assembling complex circuits and large complexes, thus fostering the development of appropriate methods and expanding the scope of applications. Synthetic biology has also stimulated interdisciplinary collaboration as well as integration of the broader public by addressing socioeconomic, philosophical, ethical, political, and legal opportunities and concerns. The demand-driven technological achievements of gene synthesis and the implemented processes are exemplified by an industrial setting of large-scale gene synthesis, describing production from order to delivery. Copyright © 2011 Elsevier Inc. All rights reserved.

  14. Direct Detection and Differentiation of Pathogenic Leptospira Species Using a Multi-Gene Targeted Real Time PCR Approach

    Science.gov (United States)

    Ferreira, Ana Sofia; Costa, Pedro; Rocha, Teresa; Amaro, Ana; Vieira, Maria Luísa; Ahmed, Ahmed; Thompson, Gertrude; Hartskeerl, Rudy A.; Inácio, João

    2014-01-01

    Leptospirosis is a growing public and veterinary health concern caused by pathogenic species of Leptospira. Rapid and reliable laboratory tests for the direct detection of leptospiral infections in animals are in high demand not only to improve diagnosis but also for understanding the epidemiology of the disease. In this work we describe a novel and simple TaqMan-based multi-gene targeted real-time PCR approach able to detect and differentiate Leptospira interrogans, L. kirschneri, L. borgpeteresenii and L. noguchii, which constitute the veterinary most relevant pathogenic species of Leptospira. The method uses sets of species-specific probes, and respective flanking primers, designed from ompL1 and secY gene sequences. To monitor the presence of inhibitors, a duplex amplification assay targeting both the mammal β-actin and the leptospiral lipL32 genes was implemented. The analytical sensitivity of all primer and probe sets was estimated to be <10 genome equivalents (GE) in the reaction mixture. Application of the amplification reactions on genomic DNA from a variety of pathogenic and non-pathogenic Leptospira strains and other non-related bacteria revealed a 100% analytical specificity. Additionally, pathogenic leptospires were successfully detected in five out of 29 tissue samples from animals (Mus spp., Rattus spp., Dolichotis patagonum and Sus domesticus). Two samples were infected with L. borgpetersenii, two with L. interrogans and one with L. kirschneri. The possibility to detect and identify these pathogenic agents to the species level in domestic and wildlife animals reinforces the diagnostic information and will enhance our understanding of the epidemiology of leptopirosis. PMID:25398140

  15. Population density approach for discrete mRNA distributions in generalized switching models for stochastic gene expression.

    Science.gov (United States)

    Stinchcombe, Adam R; Peskin, Charles S; Tranchina, Daniel

    2012-06-01

    We present a generalization of a population density approach for modeling and analysis of stochastic gene expression. In the model, the gene of interest fluctuates stochastically between an inactive state, in which transcription cannot occur, and an active state, in which discrete transcription events occur; and the individual mRNA molecules are degraded stochastically in an independent manner. This sort of model in simplest form with exponential dwell times has been used to explain experimental estimates of the discrete distribution of random mRNA copy number. In our generalization, the random dwell times in the inactive and active states, T_{0} and T_{1}, respectively, are independent random variables drawn from any specified distributions. Consequently, the probability per unit time of switching out of a state depends on the time since entering that state. Our method exploits a connection between the fully discrete random process and a related continuous process. We present numerical methods for computing steady-state mRNA distributions and an analytical derivation of the mRNA autocovariance function. We find that empirical estimates of the steady-state mRNA probability mass function from Monte Carlo simulations of laboratory data do not allow one to distinguish between underlying models with exponential and nonexponential dwell times in some relevant parameter regimes. However, in these parameter regimes and where the autocovariance function has negative lobes, the autocovariance function disambiguates the two types of models. Our results strongly suggest that temporal data beyond the autocovariance function is required in general to characterize gene switching.

  16. Genes contributing to prion pathogenesis

    DEFF Research Database (Denmark)

    Tamgüney, Gültekin; Giles, Kurt; Glidden, David V

    2008-01-01

    incubation times, indicating that the conversion reaction may be influenced by other gene products. To identify genes that contribute to prion pathogenesis, we analysed incubation times of prions in mice in which the gene product was inactivated, knocked out or overexpressed. We tested 20 candidate genes...... show that many genes previously implicated in prion replication have no discernible effect on the pathogenesis of prion disease. While most genes tested did not significantly affect survival times, ablation of the amyloid beta (A4) precursor protein (App) or interleukin-1 receptor, type I (Il1r1...

  17. 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.

  18. 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

  19. A comprehensive approach to identify reliable reference gene candidates to investigate the link between alcoholism and endocrinology in Sprague-Dawley rats.

    Directory of Open Access Journals (Sweden)

    Faten A Taki

    Full Text Available Gender and hormonal differences are often correlated with alcohol dependence and related complications like addiction and breast cancer. Estrogen (E2 is an important sex hormone because it serves as a key protein involved in organism level signaling pathways. Alcoholism has been reported to affect estrogen receptor signaling; however, identifying the players involved in such multi-faceted syndrome is complex and requires an interdisciplinary approach. In many situations, preliminary investigations included a straight forward, yet informative biotechniques such as gene expression analyses using quantitative real time PCR (qRT-PCR. The validity of qRT-PCR-based conclusions is affected by the choice of reliable internal controls. With this in mind, we compiled a list of 15 commonly used housekeeping genes (HKGs as potential reference gene candidates in rat biological models. A comprehensive comparison among 5 statistical approaches (geNorm, dCt method, NormFinder, BestKeeper, and RefFinder was performed to identify the minimal number as well the most stable reference genes required for reliable normalization in experimental rat groups that comprised sham operated (SO, ovariectomized rats in the absence (OVX or presence of E2 (OVXE2. These rat groups were subdivided into subgroups that received alcohol in liquid diet or isocalroic control liquid diet for 12 weeks. Our results showed that U87, 5S rRNA, GAPDH, and U5a were the most reliable gene candidates for reference genes in heart and brain tissue. However, different gene stability ranking was specific for each tissue input combination. The present preliminary findings highlight the variability in reference gene rankings across different experimental conditions and analytic methods and constitute a fundamental step for gene expression assays.

  20. Patenting human genes: Chinese academic articles' portrayal of gene patents.

    Science.gov (United States)

    Du, Li

    2018-04-24

    The patenting of human genes has been the subject of debate for decades. While China has gradually come to play an important role in the global genomics-based testing and treatment market, little is known about Chinese scholars' perspectives on patent protection for human genes. A content analysis of academic literature was conducted to identify Chinese scholars' concerns regarding gene patents, including benefits and risks of patenting human genes, attitudes that researchers hold towards gene patenting, and any legal and policy recommendations offered for the gene patent regime in China. 57.2% of articles were written by law professors, but scholars from health sciences, liberal arts, and ethics also participated in discussions on gene patent issues. While discussions of benefits and risks were relatively balanced in the articles, 63.5% of the articles favored gene patenting in general and, of the articles (n = 41) that explored gene patents in the Chinese context, 90.2% supported patent protections for human genes in China. The patentability of human genes was discussed in 33 articles, and 75.8% of these articles reached the conclusion that human genes are patentable. Chinese scholars view the patent regime as an important legal tool to protect the interests of inventors and inventions as well as the genetic resources of China. As such, many scholars support a gene patent system in China. These attitudes towards gene patents remain unchanged following the court ruling in the Myriad case in 2013, but arguments have been raised about the scope of gene patents, in particular that the increasing numbers of gene patents may negatively impact public health in China.

  1. 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

  2. Two Distinct Approaches for CRISPR-Cas9-Mediated Gene Editing in Cryptococcus neoformans and Related Species.

    Science.gov (United States)

    Wang, Ping

    2018-06-27

    Cryptococcus neoformans and related species are encapsulated basidiomycetous fungi that cause meningoencephalitis in individuals with immune deficiency. This pathogen has a tractable genetic system; however, gene disruption via electroporation remains difficult, while biolistic transformation is often limited by lack of multiple genetic markers and the high initial cost of equipment. The approach using clustered regularly interspaced short palindromic repeats (CRISPR) and CRISPR-associated protein 9 (Cas9) has become the technology of choice for gene editing in many organisms due to its simplicity, efficiency, and versatility. The technique has been successfully demonstrated in C. neoformans and Cryptococcus deneoformans in which two DNA plasmids expressing either the Streptococcus pyogenes CAS9 gene or the guide RNA (gRNA) were employed. However, potential adverse effects due to constitutive expression and the time-consuming process of constructing vectors to express each gRNA remain as a primary barrier for wide adaptation. This report describes the delivery of preassembled CRISPR-Cas9-gRNA ribonucleoproteins (RNPs) via electroporation that is able to generate edited mutant alleles. RNP-mediated CRISPR-Cas9 was used to replace the wild-type GIB2 gene encoding a Gβ-like/RACK1 Gib2 protein with a gib2 :: NAT allele via homologous recombination in both C. neoformans and C. deneoformans In addition, a DNA plasmid (pCnCas9:U6-gRNA) that expresses both Cas9 and gRNA, allowing for convenient yet low-cost DNA-mediated gene editing, is described. pCnCas9:U6-gRNA contains an endogenous U6 promoter for gRNA expression and restriction sites for one-step insertion of a gRNA. These approaches and resources provide new opportunities to accelerate genetic studies of Cryptococcus species. IMPORTANCE For genetic studies of the Cryptococcus genus, generation of mutant strains is often hampered by a limited number of selectable genetic markers, the tedious process of vector

  3. Differential distribution and abundance of diazotrophic bacterial communities across different soil niches using a gene-targeted clone library approach.

    Science.gov (United States)

    Yousuf, Basit; Kumar, Raghawendra; Mishra, Avinash; Jha, Bhavanath

    2014-11-01

    Diazotrophs are key players of the globally important biogeochemical nitrogen cycle, having a significant role in maintaining ecosystem sustainability. Saline soils are pristine and unexplored habitats representing intriguing ecosystems expected to harbour potential diazotrophs capable of adapting in extreme conditions, and these implicated organisms are largely obscure. Differential occurrence of diazotrophs was studied by the nifH gene-targeted clone library approach. Four nifH gene clone libraries were constructed from different soil niches, that is saline soils (low and high salinity; EC 3.8 and 7.1 ds m(-1) ), and agricultural and rhizosphere soil. Additionally, the abundance of diazotrophic community members was assessed using quantitative PCR. Results showed environment-dependent metabolic versatility and the presence of nitrogen-fixing bacteria affiliated with a range of taxa, encompassing members of the Alphaproteobacteria, Betaproteobacteria, Deltaproteobacteria, Gammaproteobacteria, Cyanobacteria and Firmicutes. The analyses unveiled the dominance of Alphaproteobacteria and Gammaproteobacteria (Pseudomonas, Halorhodospira, Ectothiorhodospira, Bradyrhizobium, Agrobacterium, Amorphomonas) as nitrogen fixers in coastal-saline soil ecosystems, and Alphaproteobacteria and Betaproteobacteria (Bradyrhizobium, Azohydromonas, Azospirillum, Ideonella) in agricultural/rhizosphere ecosystems. The results revealed a repertoire of novel nitrogen-fixing bacterial guilds particularly in saline soil ecosystems. © 2014 Federation of European Microbiological Societies. Published by John Wiley & Sons Ltd. All rights reserved.

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

    Directory of Open Access Journals (Sweden)

    Je-Hyuk Lee

    2009-11-01

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

  5. Spectral Analysis on Time-Course Expression Data: Detecting Periodic Genes Using a Real-Valued Iterative Adaptive Approach

    Directory of Open Access Journals (Sweden)

    Kwadwo S. Agyepong

    2013-01-01

    Full Text Available Time-course expression profiles and methods for spectrum analysis have been applied for detecting transcriptional periodicities, which are valuable patterns to unravel genes associated with cell cycle and circadian rhythm regulation. However, most of the proposed methods suffer from restrictions and large false positives to a certain extent. Additionally, in some experiments, arbitrarily irregular sampling times as well as the presence of high noise and small sample sizes make accurate detection a challenging task. A novel scheme for detecting periodicities in time-course expression data is proposed, in which a real-valued iterative adaptive approach (RIAA, originally proposed for signal processing, is applied for periodogram estimation. The inferred spectrum is then analyzed using Fisher’s hypothesis test. With a proper -value threshold, periodic genes can be detected. A periodic signal, two nonperiodic signals, and four sampling strategies were considered in the simulations, including both bursts and drops. In addition, two yeast real datasets were applied for validation. The simulations and real data analysis reveal that RIAA can perform competitively with the existing algorithms. The advantage of RIAA is manifested when the expression data are highly irregularly sampled, and when the number of cycles covered by the sampling time points is very reduced.

  6. Genes, stress, and depression.

    Science.gov (United States)

    Wurtman, Richard J

    2005-05-01

    A relationship between genetic makeup and susceptibility to major depressive disorder (MDD) has long been suspected on the basis of family and twin studies. A metaanalysis of reports on the basis of twin studies has estimated MDD's degree of heritability to be 0.33 (confidence interval, 0.26-0.39). Among families exhibiting an increased prevalence of MDD, risk of developing the illness was enhanced in members exposed to a highly stressful environment. Aberrant genes can predispose to depression in a number of ways, for example, by diminishing production of growth factors that act during brain development. An aberrant gene could also increase or decrease a neurotransmitter's release into synapses, its actions, or its duration of activity. The gene products of greatest interest at present are those involved in the synthesis and actions of serotonin; among them, the serotonin-uptake protein localized within the terminals and dendrites of serotonin-releasing neurons. It has been found that the Vmax of platelet serotonin uptake is low in some patients with MDD; also, Vmax is highly correlated in twins. Antidepressant drugs such as the selective serotonin reuptake inhibitors act on this uptake protein. The specific genetic locus causing serotonin uptake to be lower in some patients with major depression involves a polymorphic region (5-HTTLPR) in the promoter region of the gene for the uptake protein. The gene itself exists as several alleles, the short "S" allele and the long "L" allele. The S variant is associated with less, and the L variant with more, of the uptake protein. The effect of stressful life events on depressive symptoms in young adults was found to be significantly stronger among SS or SL subjects than among LL subjects. Neuroimaging studies showed that people with the SS or SL alleles exhibited a greater activation of the amygdala in response to fearful stimuli than those with LL. It has been reported recently that mutations in the gene that controls

  7. The silencing effect of miR-30a on ITGA4 gene expression in vitro: an approach for gene therapy.

    Science.gov (United States)

    Darzi, Leila; Boshtam, Maryam; Shariati, Laleh; Kouhpayeh, Shirin; Gheibi, Azam; Mirian, Mina; Rahimmanesh, Ilnaz; Khanahmad, Hossein; Tabatabaiefar, Mohammad Amin

    2017-12-01

    Integrins are adhesion molecules which play crucial roles in cell-cell and cell-extracellular matrix interactions. Very late antigen-4 or α4β1 and lymphocyte Peyer's patch adhesion molecule-1 or α4β7, are key factors in the invasion of tumor cells and metastasis. Based on the previous reports, integrin α4 ( ITGA4 ) is overexpressed in some immune disorders and cancers. Thus, inhibition of ITGA4 could be a therapeutic strategy. In the present study, miR-30a was selected in order to suppress ITGA4 expression. The ITGA4 3' UTR was amplified, cloned in the Z2827-M67-( ITGA4 ) plasmid and named as Z2827-M67/3'UTR. HeLa cells were divided into five groups; (1) untreated without any transfection, (2) mock with Z2827-M67/3'UTR transfection and X-tremeGENE reagent, (3) negative control with Z2827-M67/3'UTR transfection alone, (4) test with miR-30a mimic and Z2827-M67/3'UTR transfection and (5) scramble with miR-30a scramble and Z2827-M67/3'UTR transfection. The MTT assay was performed to evaluate cell survival and cytotoxicity in each group. Real-time RT-PCR was applied for the ITGA4 expression analysis. The findings of this study showed that miR-30a downregulated ITGA4 expression and had no effect on the cell survival. Due to the silencing effect of miR-30a on the ITGA4 gene expression, this agent could be considered as a potential tool for cancer and immune disorders therapy.

  8. Vertebrate gene predictions and the problem of large genes

    DEFF Research Database (Denmark)

    Wang, Jun; Li, ShengTing; Zhang, Yong

    2003-01-01

    To find unknown protein-coding genes, annotation pipelines use a combination of ab initio gene prediction and similarity to experimentally confirmed genes or proteins. Here, we show that although the ab initio predictions have an intrinsically high false-positive rate, they also have a consistent...

  9. Models of gene gain and gene loss for probabilistic reconstruction of gene content in the last universal common ancestor of life

    OpenAIRE

    Kannan, Lavanya; Li, Hua; Rubinstein, Boris; Mushegian, Arcady

    2013-01-01

    Background The problem of probabilistic inference of gene content in the last common ancestor of several extant species with completely sequenced genomes is: for each gene that is conserved in all or some of the genomes, assign the probability that its ancestral gene was present in the genome of their last common ancestor. Results We have developed a family of models of gene gain and gene loss in evolution, and applied the maximum-likelihood approach that uses phylogenetic tree of prokaryotes...

  10. Effect of the absolute statistic on gene-sampling gene-set analysis methods.

    Science.gov (United States)

    Nam, Dougu

    2017-06-01

    Gene-set enrichment analysis and its modified versions have commonly been used for identifying altered functions or pathways in disease from microarray data. In particular, the simple gene-sampling gene-set analysis methods have been heavily used for datasets with only a few sample replicates. The biggest problem with this approach is the highly inflated false-positive rate. In this paper, the effect of absolute gene statistic on gene-sampling gene-set analysis methods is systematically investigated. Thus far, the absolute gene statistic has merely been regarded as a supplementary method for capturing the bidirectional changes in each gene set. Here, it is shown that incorporating the absolute gene statistic in gene-sampling gene-set analysis substantially reduces the false-positive rate and improves the overall discriminatory ability. Its effect was investigated by power, false-positive rate, and receiver operating curve for a number of simulated and real datasets. The performances of gene-set analysis methods in one-tailed (genome-wide association study) and two-tailed (gene expression data) tests were also compared and discussed.

  11. Plant gene technology: social considerations

    African Journals Online (AJOL)

    Administrator

    The genetic modification of plants by gene technology is of immense potential benefits, but there may be possible risks. ... As a new endeavour, however, people have a mixed ... reality by gene biotechnology (Watson, 1997). Industrial ...

  12. Brains, Genes and Primates

    Science.gov (United States)

    Belmonte, Juan Carlos Izpisua; Callaway, Edward M.; Churchland, Patricia; Caddick, Sarah J.; Feng, Guoping; Homanics, Gregg E.; Lee, Kuo-Fen; Leopold, David A.; Miller, Cory T.; Mitchell, Jude F.; Mitalipov, Shoukhrat; Moutri, Alysson R.; Movshon, J. Anthony; Okano, Hideyuki; Reynolds, John H.; Ringach, Dario; Sejnowski, Terrence J.; Silva, Afonso C.; Strick, Peter L.; Wu, Jun; Zhang, Feng

    2015-01-01

    One of the great strengths of the mouse model is the wide array of genetic tools that have been developed. Striking examples include methods for directed modification of the genome, and for regulated expression or inactivation of genes. Within neuroscience, it is now routine to express reporter genes, neuronal activity indicators and opsins in specific neuronal types in the mouse. However, there are considerable anatomical, physiological, cognitive and behavioral differences between the mouse and the human that, in some areas of inquiry, limit the degree to which insights derived from the mouse can be applied to understanding human neurobiology. Several recent advances have now brought into reach the goal of applying these tools to understanding the primate brain. Here we describe these advances, consider their potential to advance our understanding of the human brain and brain disorders, discuss bioethical considerations, and describe what will be needed to move forward. PMID:25950631

  13. An integrated and comparative approach towards identification, characterization and functional annotation of candidate genes for drought tolerance in sorghum (Sorghum bicolor (L.) Moench).

    Science.gov (United States)

    Woldesemayat, Adugna Abdi; Van Heusden, Peter; Ndimba, Bongani K; Christoffels, Alan

    2017-12-22

    Drought is the most disastrous abiotic stress that severely affects agricultural productivity worldwide. Understanding the biological basis of drought-regulated traits, requires identification and an in-depth characterization of genetic determinants using model organisms and high-throughput technologies. However, studies on drought tolerance have generally been limited to traditional candidate gene approach that targets only a single gene in a pathway that is related to a trait. In this study, we used sorghum, one of the model crops that is well adapted to arid regions, to mine genes and define determinants for drought tolerance using drought expression libraries and RNA-seq data. We provide an integrated and comparative in silico candidate gene identification, characterization and annotation approach, with an emphasis on genes playing a prominent role in conferring drought tolerance in sorghum. A total of 470 non-redundant functionally annotated drought responsive genes (DRGs) were identified using experimental data from drought responses by employing pairwise sequence similarity searches, pathway and interpro-domain analysis, expression profiling and orthology relation. Comparison of the genomic locations between these genes and sorghum quantitative trait loci (QTLs) showed that 40% of these genes were co-localized with QTLs known for drought tolerance. The genome reannotation conducted using the Program to Assemble Spliced Alignment (PASA), resulted in 9.6% of existing single gene models being updated. In addition, 210 putative novel genes were identified using AUGUSTUS and PASA based analysis on expression dataset. Among these, 50% were single exonic, 69.5% represented drought responsive and 5.7% were complete gene structure models. Analysis of biochemical metabolism revealed 14 metabolic pathways that are related to drought tolerance and also had a strong biological network, among categories of genes involved. Identification of these pathways, signifies the

  14. Gene Porter Bridwell

    Science.gov (United States)

    1994-01-01

    Gene Porter Bridwell served as the director of the Marshall Space Flight Center from January 6, 1994 until February 3, 1996, when he retired from NASA after thirty-four years service. Bridwell, a Marshall employee since 1962, had been Marshall's Space Shuttle Projects Office Director and Space Station Redesign Team deputy manager. Under Bridwell, Marshall worked to develop its role as a Center of Excellence for propulsion and for providing access to space.

  15. Mutant genes in pea breeding

    International Nuclear Information System (INIS)

    Swiecicki, W.K.

    1990-01-01

    Full text: Mutations of genes Dpo (dehiscing pods) and A (anthocyanin synthesis) played a role in pea domestication. A number of other genes were important in cultivar development for 3 types of usage (dry seeds, green vegetable types, fodder), e.g. fn, fna, le, p, v, fas and af. New genes (induced and spontaneous), are important for present ideotypes and are registered by the Pisum Genetics Association (PGA). Comparison of a pea variety ideotype with the variation available in gene banks shows that breeders need 'new' features. In mutation induction experiments, genotype, mutagen and method of treatment (e.g. combined or fractionated doses) are varied for broadening the mutation spectrum and selecting more genes of agronomic value. New genes are genetically analysed. In Poland, some mutant varieties with the gene afila were registered, controlling lodging by a shorter stem and a higher number of internodes. Really non-lodging pea varieties could strongly increase seed yield. But the probability of detecting a major gene for lodging resistance is low. Therefore, mutant genes with smaller influence on plant architecture are sought, to combine their effect by crossing. Promising seem to be the genes rogue, reductus and arthritic as well as a number of mutant genes not yet genetically identified. The gene det for terminal inflorescence - similarly to Vicia faba - changes plant development. Utilisation of assimilates and ripening should be better. Improvement of harvest index should give higher seed yield. A number of genes controlling disease resistance are well known (eg. Fw, Fnw, En, mo and sbm). Important in mass screening of resistance are closely linked gene markers. Pea gene banks collect respective lines, but mutants induced in highly productive cultivars would be better. Inducing gene markers sometimes seems to be easier than transfer by crossing. Mutation induction in pea breeding is probably more important because a high number of monogenic features are

  16. Gene doping in modern sport.

    OpenAIRE

    MAREK SAWCZUK; AGNIESZKA MACIEJEWSKA; PAWEL CIESZCZYK,

    2009-01-01

    Background: The subject of this paper is gene doping, which should be understood as "he non-therapeutic use of cells, genes, genetic elements, or of the modulation of gene expression, having the capacity to improve athletic performance". The authors of this work, based on the review of literature and previous research, make an attempt at wider characterization of gene doping and the discussion of related potential threats.Methods: This is a comprehensive survey of literature on the latest app...

  17. 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.

  18. Genealogy and gene trees.

    Science.gov (United States)

    Rasmuson, Marianne

    2008-02-01

    Heredity can be followed in persons or in genes. Persons can be identified only a few generations back, but simplified models indicate that universal ancestors to all now living persons have occurred in the past. Genetic variability can be characterized as variants of DNA sequences. Data are available only from living persons, but from the pattern of variation gene trees can be inferred by means of coalescence models. The merging of lines backwards in time leads to a MRCA (most recent common ancestor). The time and place of living for this inferred person can give insights in human evolutionary history. Demographic processes are incorporated in the model, but since culture and customs are known to influence demography the models used ought to be tested against available genealogy. The Icelandic data base offers a possibility to do so and points to some discrepancies. Mitochondrial DNA and Y chromosome patterns give a rather consistent view of human evolutionary history during the latest 100 000 years but the earlier epochs of human evolution demand gene trees with longer branches. The results of such studies reveal as yet unsolved problems about the sources of our genome.

  19. Gene therapy of cancer and development of therapeutic target gene

    Energy Technology Data Exchange (ETDEWEB)

    Kim, Chang Min; Kwon, Hee Chung

    1998-04-01

    We applied HSV-tk/GCV strategy to orthotopic rat hepatoma model and showed anticancer effects of hepatoma. The increased expression of Lac Z gene after adenovirus-mediated gene delivery throughout hepatic artery was thought that is increased the possibility of gene therapy for curing hepatoma. With the construction of kGLP-laboratory, it is possible to produce a good quantity and quality of adenovirus in lage-scale production and purification of adenovirus vector. Also, the analysis of hepatoma related genes by PCR-LOH could be used for the diagnosis of patients and the development of therapeutic gene.

  20. Gene therapy of cancer and development of therapeutic target gene

    International Nuclear Information System (INIS)

    Kim, Chang Min; Kwon, Hee Chung

    1998-04-01

    We applied HSV-tk/GCV strategy to orthotopic rat hepatoma model and showed anticancer effects of hepatoma. The increased expression of Lac Z gene after adenovirus-mediated gene delivery throughout hepatic artery was thought that is increased the possibility of gene therapy for curing hepatoma. With the construction of kGLP-laboratory, it is possible to produce a good quantity and quality of adenovirus in lage-scale production and purification of adenovirus vector. Also, the analysis of hepatoma related genes by PCR-LOH could be used for the diagnosis of patients and the development of therapeutic gene

  1. Evaluating historical candidate genes for schizophrenia

    DEFF Research Database (Denmark)

    Farrell, M S; Werge, T; Sklar, P

    2015-01-01

    Prior to the genome-wide association era, candidate gene studies were a major approach in schizophrenia genetics. In this invited review, we consider the current status of 25 historical candidate genes for schizophrenia (for example, COMT, DISC1, DTNBP1 and NRG1). The initial study for 24 of thes...

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

    DEFF Research Database (Denmark)

    Hagedorn, Peter

    To understand how complex systems, such as cells, function, comprehensive Measurements of their constituent parts must be made. This can be achieved by combining methods that are each optimized to measure specific parts of the system. Four such methods,each covering a different area, are presented...... from such measurements allows models of the system to be developed and tested. For each of the methods, such analysis and modelling approaches have beenapplied and are presented: Differentially regulated genes are identified and classified according to function; cell-specfic motility models...... are developed that can distinguish between different surfaces; a method for selecting repertoires of antigens thatseparate mice based on their response to treatment is developed; and the observed concentrations of free and bound NADH is used to build and test a basic model of respiratory metabolism...

  3. Advances in combining gene therapy with cell and tissue engineering-based approaches to enhance healing of the meniscus.

    Science.gov (United States)

    Cucchiarini, M; McNulty, A L; Mauck, R L; Setton, L A; Guilak, F; Madry, H

    2016-08-01

    Meniscal lesions are common problems in orthopaedic surgery and sports medicine, and injury or loss of the meniscus accelerates the onset of knee osteoarthritis (OA). Despite a variety of therapeutic options in the clinics, there is a critical need for improved treatments to enhance meniscal repair. In this regard, combining gene-, cell-, and tissue engineering-based approaches is an attractive strategy to generate novel, effective therapies to treat meniscal lesions. In the present work, we provide an overview of the tools currently available to improve meniscal repair and discuss the progress and remaining challenges for potential future translation in patients. Copyright © 2016 Osteoarthritis Research Society International. Published by Elsevier Ltd. All rights reserved.

  4. Gene electrotransfer in clinical trials

    DEFF Research Database (Denmark)

    Gehl, Julie

    2014-01-01

    Electroporation is increasingly being used for delivery of chemotherapy to tumors. Likewise, gene delivery by electroporation is rapidly gaining momentum for both vaccination purposes and for delivery of genes coding for other therapeutic molecules, such as chronic diseases or cancer. This chapter...... describes how gene therapy may be performed using electric pulses to enhance uptake and expression....

  5. Gene probes: principles and protocols

    National Research Council Canada - National Science Library

    Aquino de Muro, Marilena; Rapley, Ralph

    2002-01-01

    ... of labeled DNA has allowed genes to be mapped to single chromosomes and in many cases to a single chromosome band, promoting significant advance in human genome mapping. Gene Probes: Principles and Protocols presents the principles for gene probe design, labeling, detection, target format, and hybridization conditions together with detailed protocols, accom...

  6. Compositional gradients in Gramineae genes

    DEFF Research Database (Denmark)

    Wong, Gane Ka-Shu; Wang, Jun; Tao, Lin

    2002-01-01

    In this study, we describe a property of Gramineae genes, and perhaps all monocot genes, that is not observed in eudicot genes. Along the direction of transcription, beginning at the junction of the 5'-UTR and the coding region, there are gradients in GC content, codon usage, and amino-acid usage...

  7. Independent Gene Discovery and Testing

    Science.gov (United States)

    Palsule, Vrushalee; Coric, Dijana; Delancy, Russell; Dunham, Heather; Melancon, Caleb; Thompson, Dennis; Toms, Jamie; White, Ashley; Shultz, Jeffry

    2010-01-01

    A clear understanding of basic gene structure is critical when teaching molecular genetics, the central dogma and the biological sciences. We sought to create a gene-based teaching project to improve students' understanding of gene structure and to integrate this into a research project that can be implemented by instructors at the secondary level…

  8. Virulence-associated and antibiotic resistance genes of microbial populations in cattle feces analyzed using a metagenomic approach.

    Science.gov (United States)

    Durso, Lisa M; Harhay, Gregory P; Bono, James L; Smith, Timothy P L

    2011-02-01

    The bovine fecal microbiota impacts human food safety as well as animal health. Although the bacteria of cattle feces have been well characterized using culture-based and culture-independent methods, techniques have been lacking to correlate total community composition with community function. We used high throughput sequencing of total DNA extracted from fecal material to characterize general community composition and examine the repertoire of microbial genes present in beef cattle feces, including genes associated with antibiotic resistance and bacterial virulence. Results suggest that traditional 16S sequencing using "universal" primers to generate full-length sequence may under represent Acitinobacteria and Proteobacteria. Over eight percent (8.4%) of the sequences from our beef cattle fecal pool sample could be categorized as virulence genes, including a suite of genes associated with resistance to antibiotic and toxic compounds (RATC). This is a higher proportion of virulence genes found in Sargasso sea, chicken cecum, and cow rumen samples, but comparable to the proportion found in Antarctic marine derived lake, human fecal, and farm soil samples. The quantitative nature of metagenomic data, combined with the large number of RATC classes represented in samples from widely different habitats indicates that metagenomic data can be used to track relative amounts of antibiotic resistance genes in individual animals over time. Consequently, these data can be used to generate sample-specific and temporal antibiotic resistance gene profiles to facilitate an understanding of the ecology of the microbial communities in each habitat as well as the epidemiology of antibiotic resistant gene transport between and among habitats. Published by Elsevier B.V.

  9. Allele-specific expression in the germline of patients with familial pancreatic cancer: An unbiased approach to cancer gene discovery

    OpenAIRE

    Tan, Aik Choon; Fan, Jian-Bing; Karikari, Collins; Bibikova, Marina; Garcia, Eliza Wickham; Zhou, Lixin; Barker, David; Serre, David; Feldmann, Georg; Hruban, Ralph H.; Klein, Alison P.; Goggins, Michael; Couch, Fergus J.; Hudson, Thomas J.; Winslow, Raimond L.

    2007-01-01

    Physiologic allele-specific expression (ASE) in germline tissues occurs during random X-chromosome inactivation1 and in genomic imprinting,2 wherein the two alleles of a gene in a heterozygous individual are not expressed equally. Recent studies have confirmed the existence of ASE in apparently non-imprinted autosomal genes;3–14 however, the extent of ASE in the human genome is unknown. We explored ASE in lymphoblastoid cell lines of 145 individuals using an oligonucleotide array based assay....

  10. Bayesian Computational Approaches for Gene Regulation Studies of Bioethanol and Biohydrogen Production. Final Scientific/Technical Report

    Energy Technology Data Exchange (ETDEWEB)

    Newberg, Lee; McCue, Lee Anne; Van Roey, Patrick

    2014-04-17

    The project developed mathematical models and first-version software tools for the understanding of gene regulation across multiple related species. The project lays the foundation for understanding how certain alpha-proteobacterial species control their own genes for bioethanol and biohydrogen production, and sets the stage for exploiting bacteria for the production of fuels. Enabling such alternative sources of fuel is a high priority for the Department of Energy and the public.

  11. Novel candidate genes important for asthma and hypertension comorbidity revealed from associative gene networks.

    Science.gov (United States)

    Saik, Olga V; Demenkov, Pavel S; Ivanisenko, Timofey V; Bragina, Elena Yu; Freidin, Maxim B; Goncharova, Irina A; Dosenko, Victor E; Zolotareva, Olga I; Hofestaedt, Ralf; Lavrik, Inna N; Rogaev, Evgeny I; Ivanisenko, Vladimir A

    2018-02-13

    Hypertension and bronchial asthma are a major issue for people's health. As of 2014, approximately one billion adults, or ~ 22% of the world population, have had hypertension. As of 2011, 235-330 million people globally have been affected by asthma and approximately 250,000-345,000 people have died each year from the disease. The development of the effective treatment therapies against these diseases is complicated by their comorbidity features. This is often a major problem in diagnosis and their treatment. Hence, in this study the bioinformatical methodology for the analysis of the comorbidity of these two diseases have been developed. As such, the search for candidate genes related to the comorbid conditions of asthma and hypertension can help in elucidating the molecular mechanisms underlying the comorbid condition of these two diseases, and can also be useful for genotyping and identifying new drug targets. Using ANDSystem, the reconstruction and analysis of gene networks associated with asthma and hypertension was carried out. The gene network of asthma included 755 genes/proteins and 62,603 interactions, while the gene network of hypertension - 713 genes/proteins and 45,479 interactions. Two hundred and five genes/proteins and 9638 interactions were shared between asthma and hypertension. An approach for ranking genes implicated in the comorbid condition of two diseases was proposed. The approach is based on nine criteria for ranking genes by their importance, including standard methods of gene prioritization (Endeavor, ToppGene) as well as original criteria that take into account the characteristics of an associative gene network and the presence of known polymorphisms in the analysed genes. According to the proposed approach, the genes IL10, TLR4, and CAT had the highest priority in the development of comorbidity of these two diseases. Additionally, it was revealed that the list of top genes is enriched with apoptotic genes and genes involved in

  12. 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

  13. The ethics of gene therapy.

    Science.gov (United States)

    Chan, Sarah; Harris, John

    2006-10-01

    Recent developments have progressed in areas of science that pertain to gene therapy and its ethical implications. This review discusses the current state of therapeutic gene technologies, including stem cell therapies and genetic modification, and identifies ethical issues of concern in relation to the science of gene therapy and its application, including the ethics of embryonic stem cell research and therapeutic cloning, the risks associated with gene therapy, and the ethics of clinical research in developing new therapeutic technologies. Additionally, ethical issues relating to genetic modification itself are considered: the significance of the human genome, the distinction between therapy and enhancement, and concerns regarding gene therapy as a eugenic practice.

  14. Genes with minimal phylogenetic information are problematic for coalescent analyses when gene tree estimation is biased.

    Science.gov (United States)

    Xi, Zhenxiang; Liu, Liang; Davis, Charles C

    2015-11-01

    The development and application of coalescent methods are undergoing rapid changes. One little explored area that bears on the application of gene-tree-based coalescent methods to species tree estimation is gene informativeness. Here, we investigate the accuracy of these coalescent methods when genes have minimal phylogenetic information, including the implementation of the multilocus bootstrap approach. Using simulated DNA sequences, we demonstrate that genes with minimal phylogenetic information can produce unreliable gene trees (i.e., high error in gene tree estimation), which may in turn reduce the accuracy of species tree estimation using gene-tree-based coalescent methods. We demonstrate that this problem can be alleviated by sampling more genes, as is commonly done in large-scale phylogenomic analyses. This applies even when these genes are minimally informative. If gene tree estimation is biased, however, gene-tree-based coalescent analyses will produce inconsistent results, which cannot be remedied by increasing the number of genes. In this case, it is not the gene-tree-based coalescent methods that are flawed, but rather the input data (i.e., estimated gene trees). Along these lines, the commonly used program PhyML has a tendency to infer one particular bifurcating topology even though it is best represented as a polytomy. We additionally corroborate these findings by analyzing the 183-locus mammal data set assembled by McCormack et al. (2012) using ultra-conserved elements (UCEs) and flanking DNA. Lastly, we demonstrate that when employing the multilocus bootstrap approach on this 183-locus data set, there is no strong conflict between species trees estimated from concatenation and gene-tree-based coalescent analyses, as has been previously suggested by Gatesy and Springer (2014). Copyright © 2015 Elsevier Inc. All rights reserved.

  15. Identification of Hematopoietic Stem Cell Engraftment Genes in Gene Therapy Studies.

    Science.gov (United States)

    Powers, John M; Trobridge, Grant D

    2013-09-01

    Hematopoietic stem cell (HSC) therapy using replication-incompetent retroviral vectors is a promising approach to provide life-long correction for genetic defects. HSC gene therapy clinical studies have resulted in functional cures for several diseases, but in some studies clonal expansion or leukemia has occurred. This is due to the dyregulation of endogenous host gene expression from vector provirus insertional mutagenesis. Insertional mutagenesis screens using replicating retroviruses have been used extensively to identify genes that influence oncogenesis. However, retroviral mutagenesis screens can also be used to determine the role of genes in biological processes such as stem cell engraftment. The aim of this review is to describe the potential for vector insertion site data from gene therapy studies to provide novel insights into mechanisms of HSC engraftment. In HSC gene therapy studies dysregulation of host genes by replication-incompetent vector proviruses may lead to enrichment of repopulating clones with vector integrants near genes that influence engraftment. Thus, data from HSC gene therapy studies can be used to identify novel candidate engraftment genes. As HSC gene therapy use continues to expand, the vector insertion site data collected will be of great interest to help identify novel engraftment genes and may ultimately lead to new therapies to improve engraftment.

  16. Integrative characterization of germ cell-specific genes from mouse spermatocyte UniGene library

    Directory of Open Access Journals (Sweden)

    Eddy Edward M

    2007-07-01

    Full Text Available Abstract Background The primary regulator of spermatogenesis, a highly ordered and tightly regulated developmental process, is an intrinsic genetic program involving male germ cell-specific genes. Results We analyzed the mouse spermatocyte UniGene library containing 2155 gene-oriented transcript clusters. We predict that 11% of these genes are testis-specific and systematically identified 24 authentic genes specifically and abundantly expressed in the testis via in silico and in vitro approaches. Northern blot analysis disclosed various transcript characteristics, such as expression level, size and the presence of isoform. Expression analysis revealed developmentally regulated and stage-specific expression patterns in all of the genes. We further analyzed the genes at the protein and cellular levels. Transfection assays performed using GC-2 cells provided information on the cellular characteristics of the gene products. In addition, antibodies were generated against proteins encoded by some of the genes to facilitate their identification and characterization in spermatogenic cells and sperm. Our data suggest that a number of the gene products are implicated in transcriptional regulation, nuclear integrity, sperm structure and motility, and fertilization. In particular, we found for the first time that Mm.333010, predicted to contain a trypsin-like serine protease domain, is a sperm acrosomal protein. Conclusion We identify 24 authentic genes with spermatogenic cell-specific expression, and provide comprehensive information about the genes. Our findings establish a new basis for future investigation into molecular mechanisms underlying male reproduction.

  17. Induction of angiogenesis in tissue-engineered scaffolds designed for bone repair: a combined gene therapy-cell transplantation approach.

    Science.gov (United States)

    Jabbarzadeh, Ehsan; Starnes, Trevor; Khan, Yusuf M; Jiang, Tao; Wirtel, Anthony J; Deng, Meng; Lv, Qing; Nair, Lakshmi S; Doty, Steven B; Laurencin, Cato T

    2008-08-12

    One of the fundamental principles underlying tissue engineering approaches is that newly formed tissue must maintain sufficient vascularization to support its growth. Efforts to induce vascular growth into tissue-engineered scaffolds have recently been dedicated to developing novel strategies to deliver specific biological factors that direct the recruitment of endothelial cell (EC) progenitors and their differentiation. The challenge, however, lies in orchestration of the cells, appropriate biological factors, and optimal factor doses. This study reports an approach as a step forward to resolving this dilemma by combining an ex vivo gene transfer strategy and EC transplantation. The utility of this approach was evaluated by using 3D poly(lactide-co-glycolide) (PLAGA) sintered microsphere scaffolds for bone tissue engineering applications. Our goal was achieved by isolation and transfection of adipose-derived stromal cells (ADSCs) with adenovirus encoding the cDNA of VEGF. We demonstrated that the combination of VEGF releasing ADSCs and ECs results in marked vascular growth within PLAGA scaffolds. We thereby delineate the potential of ADSCs to promote vascular growth into biomaterials.

  18. Induction of angiogenesis in tissue-engineered scaffolds designed for bone repair: A combined gene therapy–cell transplantation approach

    Science.gov (United States)

    Jabbarzadeh, Ehsan; Starnes, Trevor; Khan, Yusuf M.; Jiang, Tao; Wirtel, Anthony J.; Deng, Meng; Lv, Qing; Nair, Lakshmi S.; Doty, Steven B.; Laurencin, Cato T.

    2008-01-01

    One of the fundamental principles underlying tissue engineering approaches is that newly formed tissue must maintain sufficient vascularization to support its growth. Efforts to induce vascular growth into tissue-engineered scaffolds have recently been dedicated to developing novel strategies to deliver specific biological factors that direct the recruitment of endothelial cell (EC) progenitors and their differentiation. The challenge, however, lies in orchestration of the cells, appropriate biological factors, and optimal factor doses. This study reports an approach as a step forward to resolving this dilemma by combining an ex vivo gene transfer strategy and EC transplantation. The utility of this approach was evaluated by using 3D poly(lactide-co-glycolide) (PLAGA) sintered microsphere scaffolds for bone tissue engineering applications. Our goal was achieved by isolation and transfection of adipose-derived stromal cells (ADSCs) with adenovirus encoding the cDNA of VEGF. We demonstrated that the combination of VEGF releasing ADSCs and ECs results in marked vascular growth within PLAGA scaffolds. We thereby delineate the potential of ADSCs to promote vascular growth into biomaterials. PMID:18678895

  19. Identification of Single Nucleotide Polymorphisms and analysis of Linkage Disequilibrium in sunflower elite inbred lines using the candidate gene approach

    Directory of Open Access Journals (Sweden)

    Heinz Ruth A

    2008-01-01

    Full Text Available Abstract Background Association analysis is a powerful tool to identify gene loci that may contribute to phenotypic variation. This includes the estimation of nucleotide diversity, the assessment of linkage disequilibrium structure (LD and the evaluation of selection processes. Trait mapping by allele association requires a high-density map, which could be obtained by the addition of Single Nucleotide Polymorphisms (SNPs and short insertion and/or deletions (indels to SSR and AFLP genetic maps. Nucleotide diversity analysis of randomly selected candidate regions is a promising approach for the success of association analysis and fine mapping in the sunflower genome. Moreover, knowledge of the distance over which LD persists, in agronomically meaningful sunflower accessions, is important to establish the density of markers and the experimental design for association analysis. Results A set of 28 candidate genes related to biotic and abiotic stresses were studied in 19 sunflower inbred lines. A total of 14,348 bp of sequence alignment was analyzed per individual. In average, 1 SNP was found per 69 nucleotides and 38 indels were identified in the complete data set. The mean nucleotide polymorphism was moderate (θ = 0.0056, as expected for inbred materials. The number of haplotypes per region ranged from 1 to 9 (mean = 3.54 ± 1.88. Model-based population structure analysis allowed detection of admixed individuals within the set of accessions examined. Two putative gene pools were identified (G1 and G2, with a large proportion of the inbred lines being assigned to one of them (G1. Consistent with the absence of population sub-structuring, LD for G1 decayed more rapidly (r2 = 0.48 at 643 bp; trend line, pooled data than the LD trend line for the entire set of 19 individuals (r2 = 0.64 for the same distance. Conclusion Knowledge about the patterns of diversity and the genetic relationships between breeding materials could be an invaluable aid in crop

  20. [Approach to Spodoptera (Lepidoptera: Noctuidae) phylogeny based on the sequence of the cytocrhome oxydase I (COI) mitochondrial gene].

    Science.gov (United States)

    Saldamando, Clara Inés; Marquez, Edna Judith

    2012-09-01

    The genus Spodoptera includes 30 species of moths considered important pests worldwide, with a great representation in the Western Hemisphere. In general, Noctuidae species have morphological similarities that have caused some difficulties for assertive species identification by conventional methods. The purpose of this work was to generate an approach to the genus phylogeny from several species of the genus Spodoptera and the species Bombyx mori as an out group, with the use of molecular tools. For this, a total of 102 S. frugiperda larvae were obtained at random in corn, cotton, rice, grass and sorghum, during late 2006 and early 2009, from Colombia. We took ADN samples from the larval posterior part and we analyzed a fragment of 451 base pairs of the mitochondrial gene cytochrome oxydase I (COI), to produce a maximum likelihood (ML) tree by using 62 sequences (29 Colombian haplotypes were used). Our results showed a great genetic differentiation (K2 distances) amongst S. frugiperda haplotypes from Colombia and the United States, condition supported by the estimators obtained for haplotype diversity and polymorphism. The obtained ML tree clustered most of the species with bootstrapping values from 73-99% in the interior branches; with low values also observed in some of the branches. In addition, this tree clustered two species of the Eastern hemisphere (S littoralis and S. litura) and eight species of the Western hemisphere (S. androgea, S. dolichos, S. eridania, S. exigua, S. frugiperda, S. latifascia, S. ornithogalli and S. pulchella). In Colombia, S. frugiperda, S. ornithogalli and S. albula represent a group of species referred as "the Spodoptera complex" of cotton crops, and our work demonstrated that sequencing a fragment of the COI gene, allows researchers to differentiate the first two species, and thus it can be used as an alternative method to taxonomic keys based on morphology. Finally, the ML tree did not cluster S. frugiperda with S. ornithogalli

  1. Novel approach to select genes from RMA normalized microarray data using functional hearing tests in aging mice

    Science.gov (United States)

    D'Souza, Mary; Zhu, Xiaoxia; Frisina, Robert D.

    2008-01-01

    Presbycusis – age-related hearing loss – is the number one communicative disorder and one of the top three chronic medical condition of our aged population. High-throughput technologies potentially can be used to identify differentially expressed genes that may be better diagnostic and therapeutic targets for sensory and neural disorders. Here we analyzed gene expression for a set of GABA receptors in the cochlea of aging CBA mice using the Affymetrix GeneChip MOE430A. Functional phenotypic hearing measures were made, including auditory brainstem response (ABR) thresholds and distortion-product otoacoustic emission (DPOAE) amplitudes (four age groups). Four specific criteria were used to assess gene expression changes from RMA normalized microarray data (40 replicates). Linear regression models were used to fit the neurophysiological hearing measurements to probe-set expression profiles. These data were first subjected to one-way ANOVA, and then linear regression was performed. In addition, the log signal ratio was converted to fold change, and selected gene expression changes were confirmed by relative real-time PCR. Major findings: expression of GABA-A receptor subunit α6 was upregulated with age and hearing loss, whereas subunit α1 was repressed. In addition, GABA-A receptor associated protein like-1 and GABA-A receptor associated protein like-2 were strongly downregulated with age and hearing impairment. Lastly, gene expression measures were correlated with pathway/network relationships relevant to the inner ear using Pathway Architect, to identify key pathways consistent with the gene expression changes observed. PMID:18455804

  2. Multiple analytical approaches reveal distinct gene-environment interactions in smokers and non smokers in lung cancer.

    Directory of Open Access Journals (Sweden)

    Rakhshan Ihsan

    Full Text Available Complex disease such as cancer results from interactions of multiple genetic and environmental factors. Studying these factors singularly cannot explain the underlying pathogenetic mechanism of the disease. Multi-analytical approach, including logistic regression (LR, classification and regression tree (CART and multifactor dimensionality reduction (MDR, was applied in 188 lung cancer cases and 290 controls to explore high order interactions among xenobiotic metabolizing genes and environmental risk factors. Smoking was identified as the predominant risk factor by all three analytical approaches. Individually, CYP1A1*2A polymorphism was significantly associated with increased lung cancer risk (OR = 1.69;95%CI = 1.11-2.59,p = 0.01, whereas EPHX1 Tyr113His and SULT1A1 Arg213His conferred reduced risk (OR = 0.40;95%CI = 0.25-0.65,p<0.001 and OR = 0.51;95%CI = 0.33-0.78,p = 0.002 respectively. In smokers, EPHX1 Tyr113His and SULT1A1 Arg213His polymorphisms reduced the risk of lung cancer, whereas CYP1A1*2A, CYP1A1*2C and GSTP1 Ile105Val imparted increased risk in non-smokers only. While exploring non-linear interactions through CART analysis, smokers carrying the combination of EPHX1 113TC (Tyr/His, SULT1A1 213GG (Arg/Arg or AA (His/His and GSTM1 null genotypes showed the highest risk for lung cancer (OR = 3.73;95%CI = 1.33-10.55,p = 0.006, whereas combined effect of CYP1A1*2A 6235CC or TC, SULT1A1 213GG (Arg/Arg and betel quid chewing showed maximum risk in non-smokers (OR = 2.93;95%CI = 1.15-7.51,p = 0.01. MDR analysis identified two distinct predictor models for the risk of lung cancer in smokers (tobacco chewing, EPHX1 Tyr113His, and SULT1A1 Arg213His and non-smokers (CYP1A1*2A, GSTP1 Ile105Val and SULT1A1 Arg213His with testing balance accuracy (TBA of 0.6436 and 0.6677 respectively. Interaction entropy interpretations of MDR results showed non-additive interactions of tobacco chewing with

  3. Gene-based interaction analysis shows GABAergic genes interacting with parenting in adolescent depressive symptoms

    NARCIS (Netherlands)

    Van Assche, Evelien; Moons, Tim; Cinar, Ozan; Viechtbauer, Wolfgang; Oldehinkel, Albertine J.; Van Leeuwen, Karla; Verschueren, Karine; Colpin, Hilde; Lambrechts, Diether; Van den Noortgate, Wim; Goossens, Luc; Claes, Stephan; van Winkel, Ruud

    2017-01-01

    BACKGROUND: Most gene-environment interaction studies (G × E) have focused on single candidate genes. This approach is criticized for its expectations of large effect sizes and occurrence of spurious results. We describe an approach that accounts for the polygenic nature of most psychiatric

  4. The Caenorhabditis chemoreceptor gene families

    Directory of Open Access Journals (Sweden)

    Robertson Hugh M

    2008-10-01

    Full Text Available Abstract Background Chemoreceptor proteins mediate the first step in the transduction of environmental chemical stimuli, defining the breadth of detection and conferring stimulus specificity. Animal genomes contain families of genes encoding chemoreceptors that mediate taste, olfaction, and pheromone responses. The size and diversity of these families reflect the biology of chemoperception in specific species. Results Based on manual curation and sequence comparisons among putative G-protein-coupled chemoreceptor genes in the nematode Caenorhabditis elegans, we identified approximately 1300 genes and 400 pseudogenes in the 19 largest gene families, most of which fall into larger superfamilies. In the related species C. briggsae and C. remanei, we identified most or all genes in each of the 19 families. For most families, C. elegans has the largest number of genes and C. briggsae the smallest number, suggesting changes in the importance of chemoperception among the species. Protein trees reveal family-specific and species-specific patterns of gene duplication and gene loss. The frequency of strict orthologs varies among the families, from just over 50% in two families to less than 5% in three families. Several families include large species-specific expansions, mostly in C. elegans and C. remanei. Conclusion Chemoreceptor gene families in Caenorhabditis species are large and evolutionarily dynamic as a result of gene duplication and gene loss. These dynamics shape the chemoreceptor gene complements in Caenorhabditis species and define the receptor space available for chemosensory responses. To explain these patterns, we propose the gray pawn hypothesis: individual genes are of little significance, but the aggregate of a large number of diverse genes is required to cover a large phenotype space.

  5. The Caenorhabditis chemoreceptor gene families.

    Science.gov (United States)

    Thomas, James H; Robertson, Hugh M

    2008-10-06

    Chemoreceptor proteins mediate the first step in the transduction of environmental chemical stimuli, defining the breadth of detection and conferring stimulus specificity. Animal genomes contain families of genes encoding chemoreceptors that mediate taste, olfaction, and pheromone responses. The size and diversity of these families reflect the biology of chemoperception in specific species. Based on manual curation and sequence comparisons among putative G-protein-coupled chemoreceptor genes in the nematode Caenorhabditis elegans, we identified approximately 1300 genes and 400 pseudogenes in the 19 largest gene families, most of which fall into larger superfamilies. In the related species C. briggsae and C. remanei, we identified most or all genes in each of the 19 families. For most families, C. elegans has the largest number of genes and C. briggsae the smallest number, suggesting changes in the importance of chemoperception among the species. Protein trees reveal family-specific and species-specific patterns of gene duplication and gene loss. The frequency of strict orthologs varies among the families, from just over 50% in two families to less than 5% in three families. Several families include large species-specific expansions, mostly in C. elegans and C. remanei. Chemoreceptor gene families in Caenorhabditis species are large and evolutionarily dynamic as a result of gene duplication and gene loss. These dynamics shape the chemoreceptor gene complements in Caenorhabditis species and define the receptor space available for chemosensory responses. To explain these patterns, we propose the gray pawn hypothesis: individual genes are of little significance, but the aggregate of a large number of diverse genes is required to cover a large phenotype space.

  6. Maximum Gene-Support Tree

    Directory of Open Access Journals (Sweden)

    Yunfeng Shan

    2008-01-01

    Full Text Available Genomes and genes diversify during evolution; however, it is unclear to what extent genes still retain the relationship among species. Model species for molecular phylogenetic studies include yeasts and viruses whose genomes were sequenced as well as plants that have the fossil-supported true phylogenetic trees available. In this study, we generated single gene trees of seven yeast species as well as single gene trees of nine baculovirus species using all the orthologous genes among the species compared. Homologous genes among seven known plants were used for validation of the finding. Four algorithms—maximum parsimony (MP, minimum evolution (ME, maximum likelihood (ML, and neighbor-joining (NJ—were used. Trees were reconstructed before and after weighting the DNA and protein sequence lengths among genes. Rarely a gene can always generate the “true tree” by all the four algorithms. However, the most frequent gene tree, termed “maximum gene-support tree” (MGS tree, or WMGS tree for the weighted one, in yeasts, baculoviruses, or plants was consistently found to be the “true tree” among the species. The results provide insights into the overall degree of divergence of orthologous genes of the genomes analyzed and suggest the following: 1 The true tree relationship among the species studied is still maintained by the largest group of orthologous genes; 2 There are usually more orthologous genes with higher similarities between genetically closer species than between genetically more distant ones; and 3 The maximum gene-support tree reflects the phylogenetic relationship among species in comparison.

  7. 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.

  8. 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

  9. MUTATIONS IN CALMODULIN GENES

    DEFF Research Database (Denmark)

    2013-01-01

    The present invention relates to an isolated polynucleotide encoding at least a part of calmodulin and an isolated polypeptide comprising at least a part of a calmodulin protein, wherein the polynucleotide and the polypeptide comprise at least one mutation associated with a cardiac disorder. The ...... the binding of calmodulin to ryanodine receptor 2 and use of such compound in a treatment of an individual having a cardiac disorder. The invention further provides a kit that can be used to detect specific mutations in calmodulin encoding genes....

  10. Identification of Gene Biomarkers for Distinguishing Small-Cell Lung Cancer from Non-Small-Cell Lung Cancer Using a Network-Based Approach

    Directory of Open Access Journals (Sweden)

    Fei Long

    2015-01-01

    Full Text Available Lung cancer consists of two main subtypes: small-cell lung cancer (SCLC and non-small-cell lung cancer (NSCLC that are classified according to their physiological phenotypes. In this study, we have developed a network-based approach to identify molecular biomarkers that can distinguish SCLC from NSCLC. By identifying positive and negative coexpression gene pairs in normal lung tissues, SCLC, or NSCLC samples and using functional association information from the STRING network, we first construct a lung cancer-specific gene association network. From the network, we obtain gene modules in which genes are highly functionally associated with each other and are either positively or negatively coexpressed in the three conditions. Then, we identify gene modules that not only are differentially expressed between cancer and normal samples, but also show distinctive expression patterns between SCLC and NSCLC. Finally, we select genes inside those modules with discriminating coexpression patterns between the two lung cancer subtypes and predict them as candidate biomarkers that are of diagnostic use.

  11. Genes and Disease: Prader-Willi Syndrome

    Science.gov (United States)

    ... MD): National Center for Biotechnology Information (US); 1998-. Genes and Disease [Internet]. Show details National Center for ... 45K) PDF version of this title (3.8M) Gene sequence Genome view see gene locations Entrez Gene ...

  12. Gene Therapy and Children (For Parents)

    Science.gov (United States)

    ... Staying Safe Videos for Educators Search English Español Gene Therapy and Children KidsHealth / For Parents / Gene Therapy ... that don't respond to conventional therapies. About Genes Our genes help make us unique. Inherited from ...

  13. Combinatorial gene regulation in Plasmodium falciparum.

    NARCIS (Netherlands)

    Noort, V. van; Huynen, M.A.

    2006-01-01

    The malaria parasite Plasmodium falciparum has a complicated life cycle with large variations in its gene expression pattern, but it contains relatively few specific transcriptional regulators. To elucidate this paradox, we identified regulatory sequences, using an approach that integrates the

  14. Association of Protein Translation and Extracellular Matrix Gene Sets with Breast Cancer Metastasis: Findings Uncovered on Analysis of Multiple Publicly Available Datasets Using Individual Patient Data Approach.

    Directory of Open Access Journals (Sweden)

    Nilotpal Chowdhury

    Full Text Available Microarray analysis has revolutionized the role of genomic prognostication in breast cancer. However, most studies are single series studies, and suffer from methodological problems. We sought to use a meta-analytic approach in combining multiple publicly available datasets, while correcting for batch effects, to reach a more robust oncogenomic analysis.The aim of the present study was to find gene sets associated with distant metastasis free survival (DMFS in systemically untreated, node-negative breast cancer patients, from publicly available genomic microarray datasets.Four microarray series (having 742 patients were selected after a systematic search and combined. Cox regression for each gene was done for the combined dataset (univariate, as well as multivariate - adjusted for expression of Cell cycle related genes and for the 4 major molecular subtypes. The centre and microarray batch effects were adjusted by including them as random effects variables. The Cox regression coefficients for each analysis were then ranked and subjected to a Gene Set Enrichment Analysis (GSEA.Gene sets representing protein translation were independently negatively associated with metastasis in the Luminal A and Luminal B subtypes, but positively associated with metastasis in Basal tumors. Proteinaceous extracellular matrix (ECM gene set expression was positively associated with metastasis, after adjustment for expression of cell cycle related genes on the combined dataset. Finally, the positive association of the proliferation-related genes with metastases was confirmed.To the best of our knowledge, the results depicting mixed prognostic significance of protein translation in breast cancer subtypes are being reported for the first time. We attribute this to our study combining multiple series and performing a more robust meta-analytic Cox regression modeling on the combined dataset, thus discovering 'hidden' associations. This methodology seems to yield new and

  15. Association of Protein Translation and Extracellular Matrix Gene Sets with Breast Cancer Metastasis: Findings Uncovered on Analysis of Multiple Publicly Available Datasets Using Individual Patient Data Approach.

    Science.gov (United States)

    Chowdhury, Nilotpal; Sapru, Shantanu

    2015-01-01

    Microarray analysis has revolutionized the role of genomic prognostication in breast cancer. However, most studies are single series studies, and suffer from methodological problems. We sought to use a meta-analytic approach in combining multiple publicly available datasets, while correcting for batch effects, to reach a more robust oncogenomic analysis. The aim of the present study was to find gene sets associated with distant metastasis free survival (DMFS) in systemically untreated, node-negative breast cancer patients, from publicly available genomic microarray datasets. Four microarray series (having 742 patients) were selected after a systematic search and combined. Cox regression for each gene was done for the combined dataset (univariate, as well as multivariate - adjusted for expression of Cell cycle related genes) and for the 4 major molecular subtypes. The centre and microarray batch effects were adjusted by including them as random effects variables. The Cox regression coefficients for each analysis were then ranked and subjected to a Gene Set Enrichment Analysis (GSEA). Gene sets representing protein translation were independently negatively associated with metastasis in the Luminal A and Luminal B subtypes, but positively associated with metastasis in Basal tumors. Proteinaceous extracellular matrix (ECM) gene set expression was positively associated with metastasis, after adjustment for expression of cell cycle related genes on the combined dataset. Finally, the positive association of the proliferation-related genes with metastases was confirmed. To the best of our knowledge, the results depicting mixed prognostic significance of protein translation in breast cancer subtypes are being reported for the first time. We attribute this to our study combining multiple series and performing a more robust meta-analytic Cox regression modeling on the combined dataset, thus discovering 'hidden' associations. This methodology seems to yield new and interesting

  16. Meta-analysis of Cancer Gene Profiling Data.

    Science.gov (United States)

    Roy, Janine; Winter, Christof; Schroeder, Michael

    2016-01-01

    The simultaneous measurement of thousands of genes gives the opportunity to personalize and improve cancer therapy. In addition, the integration of meta-data such as protein-protein interaction (PPI) information into the analyses helps in the identification and prioritization of genes from these screens. Here, we describe a computational approach that identifies genes prognostic for outcome by combining gene profiling data from any source with a network of known relationships between genes.

  17. 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.

  18. Network Diffusion-Based Prioritization of Autism Risk Genes Identifies Significantly Connected Gene Modules

    Directory of Open Access Journals (Sweden)

    Ettore Mosca

    2017-09-01

    Full Text Available Autism spectrum disorder (ASD is marked by a strong genetic heterogeneity, which is underlined by the low overlap between ASD risk gene lists proposed in different studies. In this context, molecular networks can be used to analyze the results of several genome-wide studies in order to underline those network regions harboring genetic variations associated with ASD, the so-called “disease modules.” In this work, we used a recent network diffusion-based approach to jointly analyze multiple ASD risk gene lists. We defined genome-scale prioritizations of human genes in relation to ASD genes from multiple studies, found significantly connected gene modules associated with ASD and predicted genes functionally related to ASD risk genes. Most of them play a role in synapsis and neuronal development and function; many are related to syndromes that can be in comorbidity with ASD and the remaining are involved in epigenetics, cell cycle, cell adhesion and cancer.

  19. Gene therapy for Stargardt disease associated with ABCA4 gene.

    Science.gov (United States)

    Han, Zongchao; Conley, Shannon M; Naash, Muna I

    2014-01-01

    Mutations in the photoreceptor-specific flippase ABCA4 lead to accumulation of the toxic bisretinoid A2E, resulting in atrophy of the retinal pigment epithelium (RPE) and death of the photoreceptor cells. Many blinding diseases are associated with these mutations including Stargardt's disease (STGD1), cone-rod dystrophy, retinitis pigmentosa (RP), and increased susceptibility to age-related macular degeneration. There are no curative treatments for any of these dsystrophies. While the monogenic nature of many of these conditions makes them amenable to treatment with gene therapy, the ABCA4 cDNA is 6.8 kb and is thus too large for the AAV vectors which have been most successful for other ocular genes. Here we review approaches to ABCA4 gene therapy including treatment with novel AAV vectors, lentiviral vectors, and non-viral compacted DNA nanoparticles. Lentiviral and compacted DNA nanoparticles in particular have a large capacity and have been successful in improving disease phenotypes in the Abca4 (-/-) murine model. Excitingly, two Phase I/IIa clinical trials are underway to treat patients with ABCA4-associated Startgardt's disease (STGD1). As a result of the development of these novel technologies, effective therapies for ABCA4-associated diseases may finally be within reach.

  20. VIGS approach reveals the modulation of anthocyanin biosynthetic genes by CaMYB in Chili pepper leaves

    Directory of Open Access Journals (Sweden)

    zhen ezhang

    2015-07-01

    Full Text Available The purple coloration of pepper leaves arises from the accumulation of anthocyanin. Three regulatory and 12 structural genes have been characterized for their involvement in the anthocyanin biosynthesis. Examination of the abundance of these genes in leaves showed that the majority of them differed between anthocyanin pigmented line Z1 and non-pigmented line A3. Silencing of the R2R3-MYB transcription factor CaMYB in pepper leaves of Z1 resulted in the loss of anthocyanin accumulation. Moreover, the expression of multiple genes was altered in the silenced leaves. The expression of MYC was significantly lower in CaMYB-silenced leaves, whereas WD40 showed the opposite pattern. Most structural genes including CHS, CHI, F3H, F3’5’H, DFR, ANS, UFGT, ANP and GST were repressed in CaMYB-silenced foliage with the exception of PAL, C4H and 4CL. These results indicated that MYB plays an important role in the regulation of anthocyanin biosynthetic related genes. Besides CaMYB silenced leaves rendered more sporulation of Phytophthora capsici Leonian indicating that CaMYB might be involved in the defense response to pathogens.

  1. Novel Approach for Coexpression Analysis of E2F1–3 and MYC Target Genes in Chronic Myelogenous Leukemia

    Directory of Open Access Journals (Sweden)

    Fengfeng Wang

    2014-01-01

    Full Text Available Background. Chronic myelogenous leukemia (CML is characterized by tremendous amount of immature myeloid cells in the blood circulation. E2F1–3 and MYC are important transcription factors that form positive feedback loops by reciprocal regulation in their own transcription processes. Since genes regulated by E2F1–3 or MYC are related to cell proliferation and apoptosis, we wonder if there exists difference in the coexpression patterns of genes regulated concurrently by E2F1–3 and MYC between the normal and the CML states. Results. We proposed a method to explore the difference in the coexpression patterns of those candidate target genes between the normal and the CML groups. A disease-specific cutoff point for coexpression levels that classified the coexpressed gene pairs into strong and weak coexpression classes was identified. Our developed method effectively identified the coexpression pattern differences from the overall structure. Moreover, we found that genes related to the cell adhesion and angiogenesis properties were more likely to be coexpressed in the normal group when compared to the CML group. Conclusion. Our findings may be helpful in exploring the underlying mechanisms of CML and provide useful information in cancer treatment.

  2. Multiple-endpoints gene alteration-based (MEGA) assay: A toxicogenomics approach for water quality assessment of wastewater effluents.

    Science.gov (United States)

    Fukushima, Toshikazu; Hara-Yamamura, Hiroe; Nakashima, Koji; Tan, Lea Chua; Okabe, Satoshi

    2017-12-01

    Wastewater effluents contain a significant number of toxic contaminants, which, even at low concentrations, display a wide variety of toxic actions. In this study, we developed a multiple-endpoints gene alteration-based (MEGA) assay, a real-time PCR-based transcriptomic analysis, to assess the water quality of wastewater effluents for human health risk assessment and management. Twenty-one genes from the human hepatoblastoma cell line (HepG2), covering the basic health-relevant stress responses such as response to xenobiotics, genotoxicity, and cytotoxicity, were selected and incorporated into the MEGA assay. The genes related to the p53-mediated DNA damage response and cytochrome P450 were selected as markers for genotoxicity and response to xenobiotics, respectively. Additionally, the genes that were dose-dependently regulated by exposure to the wastewater effluents were chosen as markers for cytotoxicity. The alterations in the expression of an individual gene, induced by exposure to the wastewater effluents, were evaluated by real-time PCR and the results were validated by genotoxicity (e.g., comet assay) and cell-based cytotoxicity tests. In summary, the MEGA assay is a real-time PCR-based assay that targets cellular responses to contaminants present in wastewater effluents at the transcriptional level; it is rapid, cost-effective, and high-throughput and can thus complement any chemical analysis for water quality assessment and management. Copyright © 2017 Elsevier Ltd. All rights reserved.

  3. Gene-knockdown in the honey bee mite Varroa destructor by a non-invasive approach: studies on a glutathione S-transferase

    Directory of Open Access Journals (Sweden)

    Campbell Ewan M

    2010-08-01

    Full Text Available Abstract Background The parasitic mite Varroa destructor is considered the major pest of the European honey bee (Apis mellifera and responsible for declines in honey bee populations worldwide. Exploiting the full potential of gene sequences becoming available for V. destructor requires adaptation of modern molecular biology approaches to this non-model organism. Using a mu-class glutathione S-transferase (VdGST-mu1 as a candidate gene we investigated the feasibility of gene knockdown in V. destructor by double-stranded RNA-interference (dsRNAi. Results Intra-haemocoelic injection of dsRNA-VdGST-mu1 resulted in 97% reduction in VdGST-mu1 transcript levels 48 h post-injection compared to mites injected with a bolus of irrelevant dsRNA (LacZ. This gene suppression was maintained to, at least, 72 h. Total GST catalytic activity was reduced by 54% in VdGST-mu1 gene knockdown mites demonstrating the knockdown was effective at the translation step as well as the transcription steps. Although near total gene knockdown was achieved by intra-haemocoelic injection, only half of such treated mites survived this traumatic method of dsRNA administration and less invasive methods were assessed. V. destructor immersed overnight in 0.9% NaCl solution containing dsRNA exhibited excellent reduction in VdGST-mu1 transcript levels (87% compared to mites immersed in dsRNA-LacZ. Importantly, mites undergoing the immersion approach had greatly improved survival (75-80% over 72 h, approaching that of mites not undergoing any treatment. Conclusions Our findings on V. destructor are the first report of gene knockdown in any mite species and demonstrate that the small size of such organisms is not a major impediment to applying gene knockdown approaches to the study of such parasitic pests. The immersion in dsRNA solution method provides an easy, inexpensive, relatively high throughput method of gene silencing suitable for studies in V. destructor, other small mites and

  4. Linking genes to microbial growth kinetics: an integrated biochemical systems engineering approach

    NARCIS (Netherlands)

    Koutinas, M.; Kiparissides, A.; Silva-Rocha, R.; Lam, M.C.; Martins Dos Santos, V.A.P.; Lorenzo, de V.; Pistikopoulos, E.N.; Mantalaris, A.

    2011-01-01

    The majority of models describing the kinetic properties of a microorganism for a given substrate are unstructured and empirical. They are formulated in this manner so that the complex mechanism of cell growth is simplified. Herein, a novel approach for modelling microbial growth kinetics is

  5. When genome-based approach meets the ‘old but good’: revealing genes involved in the antibacterial activity of Pseudomonas sp. P482 against soft rot pathogens.

    Directory of Open Access Journals (Sweden)

    Dorota Magdalena Krzyżanowska

    2016-05-01

    illustrates that mining of microbial genomes is a powerful approach for predicting the presence of novel secondary-metabolite encoding genes especially when coupled with transposon mutagenesis.

  6. Mapping of repair genes

    International Nuclear Information System (INIS)

    Hori, Tadaaki

    1985-01-01

    Chromosome mapping of repair genes involved in U.V. sensitivity is reported. Twenty-three of 25 hybrid cells were resistant to U.V. light. Survival curves of 2 U.V.-resistant cell strains, which possessed mouse chromosomes and human chromosome No.7 - 16, were similar to those of wild strain (L5178Y). On the other hand, survival curves of U.V.-sensitive hybrid cells was analogous to those of Q31. There was a definitive difference in the frequency of inducible chromosome aberrations between U.V. resistant and sensitive mouse-human hybrid cells. U.V.-resistant cell strains possessed the ability of excision repair. Analysis of karyotype in hybrid cells showed that the difference in U.V. sensitivity is dependent upon whether or not human chromosome No.13 is present. Synteny test on esterase D-determining locus confirmed that there is an agreement between the presence of chromosome No.13 and the presence of human esterase D activity. These results led to a conclusion that human genes which compensate recessive character of U.V.-sensitive mutant strain, Q31, with mouse-human hybrid cells are located on the locus of chromosome No.13. (Namekawa, K.)

  7. Gene therapy for ocular diseases.

    Science.gov (United States)

    Liu, Melissa M; Tuo, Jingsheng; Chan, Chi-Chao

    2011-05-01

    The eye is an easily accessible, highly compartmentalised and immune-privileged organ that offers unique advantages as a gene therapy target. Significant advancements have been made in understanding the genetic pathogenesis of ocular diseases, and gene replacement and gene silencing have been implicated as potentially efficacious therapies. Recent improvements have been made in the safety and specificity of vector-based ocular gene transfer methods. Proof-of-concept for vector-based gene therapies has also been established in several experimental models of human ocular diseases. After nearly two decades of ocular gene therapy research, preliminary successes are now being reported in phase 1 clinical trials for the treatment of Leber congenital amaurosis. This review describes current developments and future prospects for ocular gene therapy. Novel methods are being developed to enhance the performance and regulation of recombinant adeno-associated virus- and lentivirus-mediated ocular gene transfer. Gene therapy prospects have advanced for a variety of retinal disorders, including retinitis pigmentosa, retinoschisis, Stargardt disease and age-related macular degeneration. Advances have also been made using experimental models for non-retinal diseases, such as uveitis and glaucoma. These methodological advancements are critical for the implementation of additional gene-based therapies for human ocular diseases in the near future.

  8. A Proteomic Approach to Investigating Gene Cluster Expression and Secondary Metabolite Functionality in Aspergillus fumigatus

    Science.gov (United States)

    Owens, Rebecca A.; Hammel, Stephen; Sheridan, Kevin J.; Jones, Gary W.; Doyle, Sean

    2014-01-01

    A combined proteomics and metabolomics approach was utilised to advance the identification and characterisation of secondary metabolites in Aspergillus fumigatus. Here, implementation of a shotgun proteomic strategy led to the identification of non-redundant mycelial proteins (n = 414) from A. fumigatus including proteins typically under-represented in 2-D proteome maps: proteins with multiple transmembrane regions, hydrophobic proteins and proteins with extremes of molecular mass and pI. Indirect identification of secondary metabolite cluster expression was also achieved, with proteins (n = 18) from LaeA-regulated clusters detected, including GliT encoded within the gliotoxin biosynthetic cluster. Biochemical analysis then revealed that gliotoxin significantly attenuates H2O2-induced oxidative stress in A. fumigatus (p>0.0001), confirming observations from proteomics data. A complementary 2-D/LC-MS/MS approach further elucidated significantly increased abundance (pproteome and experimental strategies, plus mechanistic data pertaining to gliotoxin functionality in the organism. PMID:25198175

  9. Constructing an integrated gene similarity network for the identification of disease genes.

    Science.gov (United States)

    Tian, Zhen; Guo, Maozu; Wang, Chunyu; Xing, LinLin; Wang, Lei; Zhang, Yin

    2017-09-20

    Discovering novel genes that are involved human diseases is a challenging task in biomedical research. In recent years, several computational approaches have been proposed to prioritize candidate disease genes. Most of these methods are mainly based on protein-protein interaction (PPI) networks. However, since these PPI networks contain false positives and only cover less half of known human genes, their reliability and coverage are very low. Therefore, it is highly necessary to fuse multiple genomic data to construct a credible gene similarity network and then infer disease genes on the whole genomic scale. We proposed a novel method, named RWRB, to infer causal genes of interested diseases. First, we construct five individual gene (protein) similarity networks based on multiple genomic data of human genes. Then, an integrated gene similarity network (IGSN) is reconstructed based on similarity network fusion (SNF) method. Finally, we employee the random walk with restart algorithm on the phenotype-gene bilayer network, which combines phenotype similarity network, IGSN as well as phenotype-gene association network, to prioritize candidate disease genes. We investigate the effectiveness of RWRB through leave-one-out cross-validation methods in inferring phenotype-gene relationships. Results show that RWRB is more accurate than state-of-the-art methods on most evaluation metrics. Further analysis shows that the success of RWRB is benefited from IGSN which has a wider coverage and higher reliability comparing with current PPI networks. Moreover, we conduct a comprehensive case study for Alzheimer's disease and predict some novel disease genes that supported by literature. RWRB is an effective and reliable algorithm in prioritizing candidate disease genes on the genomic scale. Software and supplementary information are available at http://nclab.hit.edu.cn/~tianzhen/RWRB/ .

  10. A proteomic approach to investigating gene cluster expression and secondary metabolite functionality in Aspergillus fumigatus.

    OpenAIRE

    Owens, RA; Hammel, S; Sheridan, KJ; Jones, GW; Doyle, S

    2014-01-01

    A combined proteomics and metabolomics approach was utilised to advance the identification and characterisation of secondary metabolites in Aspergillus fumigatus. Here, implementation of a shotgun proteomic strategy led to the identification of non-redundant mycelial proteins (n = 414) from A. fumigatus including proteins typically under-represented in 2-D proteome maps: proteins with multiple transmembrane regions, hydrophobic proteins and proteins with extremes of molecular mass and pI. Ind...

  11. Models of gene gain and gene loss for probabilistic reconstruction of gene content in the last universal common ancestor of life.

    Science.gov (United States)

    Kannan, Lavanya; Li, Hua; Rubinstein, Boris; Mushegian, Arcady

    2013-12-19

    The problem of probabilistic inference of gene content in the last common ancestor of several extant species with completely sequenced genomes is: for each gene that is conserved in all or some of the genomes, assign the probability that its ancestral gene was present in the genome of their last common ancestor. We have developed a family of models of gene gain and gene loss in evolution, and applied the maximum-likelihood approach that uses phylogenetic tree of prokaryotes and the record of orthologous relationships between their genes to infer the gene content of LUCA, the Last Universal Common Ancestor of all currently living cellular organisms. The crucial parameter, the ratio of gene losses and gene gains, was estimated from the data and was higher in models that take account of the number of in-paralogs in genomes than in models that treat gene presences and absences as a binary trait. While the numbers of genes that are placed confidently into LUCA are similar in the ML methods and in previously published methods that use various parsimony-based approaches, the identities of genes themselves are different. Most of the models of either kind treat the genes found in many existing genomes in a similar way, assigning to them high probabilities of being ancestral ("high ancestrality"). The ML models are more likely than others to assign high ancestrality to the genes that are relatively rare in the present-day genomes.

  12. Evolving chromosomes and gene regulatory networks

    Indian Academy of Sciences (India)

    Aswin

    Genes under H NS control can be. (a) regulated by H NS. (b) regulated by H NS and StpA. Because backup by StpA is partial. Page 19. Gene expression level. H NS regulated xenogenes. Other genes. Page 20 ... recollect: H&NS silences highl transcribable genes. Gene expression level unilateral. Other genes epistatic ...

  13. An Integrated Approach Identifies Nhlh1 and Insm1 as Sonic Hedgehog-regulated Genes in Developing Cerebellum and Medulloblastoma

    Directory of Open Access Journals (Sweden)

    Enrico De Smaele

    2008-01-01

    Full Text Available Medulloblastoma (MB is the most common malignant brain tumor of childhood arising from deregulated cerebellar development. Sonic Hedgehog (Shh pathway plays a critical role in cerebellar development and its aberrant expression has been identified in MB. Gene expression profiling of cerebella from 1- to 14-day-old mice unveiled a cluster of genes whose expression correlates with the levels of Hedgehog (HH activity. From this cluster, we identified Insm1 and Nhlh1/NSCL1 as novel HH targets induced by Shh treatment in cultured cerebellar granule cell progenitors. Nhlh1 promoter was found to be bound and activated by Gli1 transcription factor. Remarkably, the expression of these genes is also upregulated in mouse and human HH-dependent MBs, suggesting that they may be either a part of the HH-induced tumorigenic process or a specific trait of HH-dependent tumor cells.

  14. Deciphering the genomic architecture of the stickleback brain with a novel multilocus gene-mapping approach.

    Science.gov (United States)

    Li, Zitong; Guo, Baocheng; Yang, Jing; Herczeg, Gábor; Gonda, Abigél; Balázs, Gergely; Shikano, Takahito; Calboli, Federico C F; Merilä, Juha

    2017-03-01

    Quantitative traits important to organismal function and fitness, such as brain size, are presumably controlled by many small-effect loci. Deciphering the genetic architecture of such traits with traditional quantitative trait locus (QTL) mapping methods is challenging. Here, we investigated the genetic architecture of brain size (and the size of five different brain parts) in nine-spined sticklebacks (Pungitius pungitius) with the aid of novel multilocus QTL-mapping approaches based on a de-biased LASSO method. Apart from having more statistical power to detect QTL and reduced rate of false positives than conventional QTL-mapping approaches, the developed methods can handle large marker panels and provide estimates of genomic heritability. Single-locus analyses of an F 2 interpopulation cross with 239 individuals and 15 198, fully informative single nucleotide polymorphisms (SNPs) uncovered 79 QTL associated with variation in stickleback brain size traits. Many of these loci were in strong linkage disequilibrium (LD) with each other, and consequently, a multilocus mapping of individual SNPs, accounting for LD structure in the data, recovered only four significant QTL. However, a multilocus mapping of SNPs grouped by linkage group (LG) identified 14 LGs (1-6 depending on the trait) that influence variation in brain traits. For instance, 17.6% of the variation in relative brain size was explainable by cumulative effects of SNPs distributed over six LGs, whereas 42% of the variation was accounted for by all 21 LGs. Hence, the results suggest that variation in stickleback brain traits is influenced by many small-effect loci. Apart from suggesting moderately heritable (h 2  ≈ 0.15-0.42) multifactorial genetic architecture of brain traits, the results highlight the challenges in identifying the loci contributing to variation in quantitative traits. Nevertheless, the results demonstrate that the novel QTL-mapping approach developed here has distinctive advantages

  15. Maximizing biomarker discovery by minimizing gene signatures

    Directory of Open Access Journals (Sweden)

    Chang Chang

    2011-12-01

    Full Text Available Abstract Background The use of gene signatures can potentially be of considerable value in the field of clinical diagnosis. However, gene signatures defined with different methods can be quite various even when applied the same disease and the same endpoint. Previous studies have shown that the correct selection of subsets of genes from microarray data is key for the accurate classification of disease phenotypes, and a number of methods have been proposed for the purpose. However, these methods refine the subsets by only considering each single feature, and they do not confirm the association between the genes identified in each gene signature and the phenotype of the disease. We proposed an innovative new method termed Minimize Feature's Size (MFS based on multiple level similarity analyses and association between the genes and disease for breast cancer endpoints by comparing classifier models generated from the second phase of MicroArray Quality Control (MAQC-II, trying to develop effective meta-analysis strategies to transform the MAQC-II signatures into a robust and reliable set of biomarker for clinical applications. Results We analyzed the similarity of the multiple gene signatures in an endpoint and between the two endpoints of breast cancer at probe and gene levels, the results indicate that disease-related genes can be preferably selected as the components of gene signature, and that the gene signatures for the two endpoints could be interchangeable. The minimized signatures were built at probe level by using MFS for each endpoint. By applying the approach, we generated a much smaller set of gene signature with the similar predictive power compared with those gene signatures from MAQC-II. Conclusions Our results indicate that gene signatures of both large and small sizes could perform equally well in clinical applications. Besides, consistency and biological significances can be detected among different gene signatures, reflecting the

  16. Simple Comparative Analyses of Differentially Expressed Gene Lists May Overestimate Gene Overlap.

    Science.gov (United States)

    Lawhorn, Chelsea M; Schomaker, Rachel; Rowell, Jonathan T; Rueppell, Olav

    2018-04-16

    Comparing the overlap between sets of differentially expressed genes (DEGs) within or between transcriptome studies is regularly used to infer similarities between biological processes. Significant overlap between two sets of DEGs is usually determined by a simple test. The number of potentially overlapping genes is compared to the number of genes that actually occur in both lists, treating every gene as equal. However, gene expression is controlled by transcription factors that bind to a variable number of transcription factor binding sites, leading to variation among genes in general variability of their expression. Neglecting this variability could therefore lead to inflated estimates of significant overlap between DEG lists. With computer simulations, we demonstrate that such biases arise from variation in the control of gene expression. Significant overlap commonly arises between two lists of DEGs that are randomly generated, assuming that the control of gene expression is variable among genes but consistent between corresponding experiments. More overlap is observed when transcription factors are specific to their binding sites and when the number of genes is considerably higher than the number of different transcription factors. In contrast, overlap between two DEG lists is always lower than expected when the genetic architecture of expression is independent between the two experiments. Thus, the current methods for determining significant overlap between DEGs are potentially confounding biologically meaningful overlap with overlap that arises due to variability in control of expression among genes, and more sophisticated approaches are needed.

  17. Mapping of HKT1;5 Gene in Barley Using GWAS Approach and Its Implication in Salt Tolerance Mechanism

    Science.gov (United States)

    Hazzouri, Khaled M.; Khraiwesh, Basel; Amiri, Khaled M. A.; Pauli, Duke; Blake, Tom; Shahid, Mohammad; Mullath, Sangeeta K.; Nelson, David; Mansour, Alain L.; Salehi-Ashtiani, Kourosh; Purugganan, Michael; Masmoudi, Khaled

    2018-01-01

    Sodium (Na+) accumulation in the cytosol will result in ion homeostasis imbalance and toxicity of transpiring leaves. Studies of salinity tolerance in the diploid wheat ancestor Triticum monococcum showed that HKT1;5-like gene was a major gene in the QTL for salt tolerance, named Nax2. In the present study, we were interested in investigating the molecular mechanisms underpinning the role of the HKT1;5 gene in salt tolerance in barley (Hordeum vulgare). A USDA mini-core collection of 2,671 barley lines, part of a field trial was screened for salinity tolerance, and a Genome Wide Association Study (GWAS) was performed. Our results showed important SNPs that are correlated with salt tolerance that mapped to a region where HKT1;5 ion transporter located on chromosome four. Furthermore, sodium (Na+) and potassium (K+) content analysis revealed that tolerant lines accumulate more sodium in roots and leaf sheaths, than in the sensitive ones. In contrast, sodium concentration was reduced in leaf blades of the tolerant lines under salt stress. In the absence of NaCl, the concentration of Na+ and K+ were the same in the roots, leaf sheaths and leaf blades between the tolerant and the sensitive lines. In order to study the molecular mechanism behind that, alleles of the HKT1;5 gene from five tolerant and five sensitive barley lines were cloned and sequenced. Sequence analysis did not show the presence of any polymorphism that distinguishes between the tolerant and sensitive alleles. Our real-time RT-PCR experiments, showed that the expression of HKT1;5 gene in roots of the tolerant line was significantly induced after challenging the plants with salt stress. In contrast, in leaf sheaths the expression was decreased after salt treatment. In sensitive lines, there was no difference in the expression of HKT1;5 gene in leaf sheath under control and saline conditions, while a slight increase in the expression was observed in roots after salt treatment. These results provide

  18. Mapping of HKT1;5 Gene in Barley Using GWAS Approach and Its Implication in Salt Tolerance Mechanism

    Directory of Open Access Journals (Sweden)

    Khaled M. Hazzouri

    2018-02-01

    Full Text Available Sodium (Na+ accumulation in the cytosol will result in ion homeostasis imbalance and toxicity of transpiring leaves. Studies of salinity tolerance in the diploid wheat ancestor Triticum monococcum showed that HKT1;5-like gene was a major gene in the QTL for salt tolerance, named Nax2. In the present study, we were interested in investigating the molecular mechanisms underpinning the role of the HKT1;5 gene in salt tolerance in barley (Hordeum vulgare. A USDA mini-core collection of 2,671 barley lines, part of a field trial was screened for salinity tolerance, and a Genome Wide Association Study (GWAS was performed. Our results showed important SNPs that are correlated with salt tolerance that mapped to a region where HKT1;5 ion transporter located on chromosome four. Furthermore, sodium (Na+ and potassium (K+ content analysis revealed that tolerant lines accumulate more sodium in roots and leaf sheaths, than in the sensitive ones. In contrast, sodium concentration was reduced in leaf blades of the tolerant lines under salt stress. In the absence of NaCl, the concentration of Na+ and K+ were the same in the roots, leaf sheaths and leaf blades between the tolerant and the sensitive lines. In order to study the molecular mechanism behind that, alleles of the HKT1;5 gene from five tolerant and five sensitive barley lines were cloned and sequenced. Sequence analysis did not show the presence of any polymorphism that distinguishes between the tolerant and sensitive alleles. Our real-time RT-PCR experiments, showed that the expression of HKT1;5 gene in roots of the tolerant line was significantly induced after challenging the plants with salt stress. In contrast, in leaf sheaths the expression was decreased after salt treatment. In sensitive lines, there was no difference in the expression of HKT1;5 gene in leaf sheath under control and saline conditions, while a slight increase in the expression was observed in roots after salt treatment. These

  19. A proteomic approach to investigating gene cluster expression and secondary metabolite functionality in Aspergillus fumigatus.

    Directory of Open Access Journals (Sweden)

    Rebecca A Owens

    Full Text Available A combined proteomics and metabolomics approach was utilised to advance the identification and characterisation of secondary metabolites in Aspergillus fumigatus. Here, implementation of a shotgun proteomic strategy led to the identification of non-redundant mycelial proteins (n = 414 from A. fumigatus including proteins typically under-represented in 2-D proteome maps: proteins with multiple transmembrane regions, hydrophobic proteins and proteins with extremes of molecular mass and pI. Indirect identification of secondary metabolite cluster expression was also achieved, with proteins (n = 18 from LaeA-regulated clusters detected, including GliT encoded within the gliotoxin biosynthetic cluster. Biochemical analysis then revealed that gliotoxin significantly attenuates H2O2-induced oxidative stress in A. fumigatus (p>0.0001, confirming observations from proteomics data. A complementary 2-D/LC-MS/MS approach further elucidated significantly increased abundance (p<0.05 of proliferating cell nuclear antigen (PCNA, NADH-quinone oxidoreductase and the gliotoxin oxidoreductase GliT, along with significantly attenuated abundance (p<0.05 of a heat shock protein, an oxidative stress protein and an autolysis-associated chitinase, when gliotoxin and H2O2 were present, compared to H2O2 alone. Moreover, gliotoxin exposure significantly reduced the abundance of selected proteins (p<0.05 involved in de novo purine biosynthesis. Significantly elevated abundance (p<0.05 of a key enzyme, xanthine-guanine phosphoribosyl transferase Xpt1, utilised in purine salvage, was observed in the presence of H2O2 and gliotoxin. This work provides new insights into the A. fumigatus proteome and experimental strategies, plus mechanistic data pertaining to gliotoxin functionality in the organism.

  20. Conditional RNAi: towards a silent gene therapy.

    Science.gov (United States)

    Lee, Sang-Kyung; Kumar, Priti

    2009-07-02

    RNA interference (RNAi) has the potential to permit the downregulation of virtually any gene. While transgenic RNAi enables stable propagation of the resulting phenotype to progeny, the dominant nature of RNAi limits its use to applications where the continued suppression of gene expression does not disturb normal cell functioning. This is of particular importance when the target gene product is essential for cell survival, development or differentiation. It is therefore desirable that knockdown be externally regulatable. This review is aimed at providing an overview of the approaches for conditional RNAi in mammalian systems, with a special mention of studies employing these approaches to target therapeutically/biologically relevant molecules, their advantages and disadvantages, and a pointer towards approaches best suited for RNAi-based gene therapy.

  1. 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.

  2. Generalist genes and learning disabilities.

    Science.gov (United States)

    Plomin, Robert; Kovas, Yulia

    2005-07-01

    The authors reviewed recent quantitative genetic research on learning disabilities that led to the conclusion that genetic diagnoses differ from traditional diagnoses in that the effects of relevant genes are largely general rather than specific. This research suggests that most genes associated with common learning disabilities--language impairment, reading disability, and mathematics disability--are generalists in 3 ways. First, genes that affect common learning disabilities are largely the same genes responsible for normal variation in learning abilities. Second, genes that affect any aspect of a learning disability affect other aspects of the disability. Third, genes that affect one learning disability are also likely to affect other learning disabilities. These quantitative genetic findings have far-reaching implications for molecular genetics and neuroscience as well as psychology. Copyright 2005 APA, all rights reserved.

  3. Rooted triple consensus and anomalous gene trees

    Directory of Open Access Journals (Sweden)

    Schmidt Heiko A

    2008-04-01

    Full Text Available Abstract Background Anomalous gene trees (AGTs are gene trees with a topology different from a species tree that are more probable to observe than congruent gene trees. In this paper we propose a rooted triple approach to finding the correct species tree in the presence of AGTs. Results Based on simulated data we show that our method outperforms the extended majority rule consensus strategy, while still resolving the species tree. Applying both methods to a metazoan data set of 216 genes, we tested whether AGTs substantially interfere with the reconstruction of the metazoan phylogeny. Conclusion Evidence of AGTs was not found in this data set, suggesting that erroneously reconstructed gene trees are the most significant challenge in the reconstruction of phylogenetic relationships among species with current data. The new method does however rule out the erroneous reconstruction of deep or poorly resolved splits in the presence of lineage sorting.

  4. Gene-wide analysis detects two new susceptibility genes for Alzheimer's Disease

    OpenAIRE

    Escott-Price, Valentina; Bellenguez, Céline; Wang, Li-San; Choi, Seung-Hoan; Harold, Denise; Jones, Lesley; Holmans, Peter Alan; Gerrish, Amy; Vedernikov, Alexey; Richards, Alexander; DeStefano, Anita L.; Lambert, Jean-Charles; Ibrahim-Verbaas, Carla A.; Naj, Adam C.; Sims, Rebecca

    2014-01-01

    PUBLISHED BACKGROUND: Alzheimer's disease is a common debilitating dementia with known heritability, for which 20 late onset susceptibility loci have been identified, but more remain to be discovered. This study sought to identify new susceptibility genes, using an alternative gene-wide analytical approach which tests for patterns of association within genes, in the powerful genome-wide association dataset of the International Genomics of Alzheimer's Project Consortium, comprising over...

  5. Gene-gene interactions and gene polymorphisms of VEGFA and EG-VEGF gene systems in recurrent pregnancy loss.

    Science.gov (United States)

    Su, Mei-Tsz; Lin, Sheng-Hsiang; Chen, Yi-Chi; Kuo, Pao-Lin

    2014-06-01

    Both vascular endothelial growth factor A (VEGFA) and endocrine gland-derived vascular endothelial growth factor (EG-VEGF) systems play major roles in angiogenesis. A body of evidence suggests VEGFs regulate critical processes during pregnancy and have been associated with recurrent pregnancy loss (RPL). However, little information is available regarding the interaction of these two major major angiogenesis-related systems in early human pregnancy. This study was conducted to investigate the association of gene polymorphisms and gene-gene interaction among genes in VEGFA and EG-VEGF systems and idiopathic RPL. A total of 98 women with history of idiopathic RPL and 142 controls were included, and 5 functional SNPs selected from VEGFA, KDR, EG-VEGF (PROK1), PROKR1 and PROKR2 were genotyped. We used multifactor dimensionality reduction (MDR) analysis to choose a best model and evaluate gene-gene interactions. Ingenuity pathways analysis (IPA) was introduced to explore possible complex interactions. Two receptor gene polymorphisms [KDR (Q472H) and PROKR2 (V331M)] were significantly associated with idiopathic RPL (P<0.01). The MDR test revealed that the KDR (Q472H) polymorphism was the best loci to be associated with RPL (P=0.02). IPA revealed EG-VEGF and VEGFA systems shared several canonical signaling pathways that may contribute to gene-gene interactions, including the Akt, IL-8, EGFR, MAPK, SRC, VHL, HIF-1A and STAT3 signaling pathways. Two receptor gene polymorphisms [KDR (Q472H) and PROKR2 (V331M)] were significantly associated with idiopathic RPL. EG-VEGF and VEGFA systems shared several canonical signaling pathways that may contribute to gene-gene interactions, including the Akt, IL-8, EGFR, MAPK, SRC, VHL, HIF-1A and STAT3.

  6. A comparative study of mutation screening of sarcomeric genes ...

    African Journals Online (AJOL)

    , TNNT2) using single gene approach versus targeted gene panel next generation sequencing in a cohort of HCM patients in Egypt. Heba Sh. Kassem, Roddy Walsh, Paul J. Barton, Besra S. Abdelghany, Remon S. Azer, Rachel Buchan, ...

  7. Identification of housekeeping genes as references for quantitative ...

    Indian Academy of Sciences (India)

    Navya

    2017-01-20

    Jan 20, 2017 ... approach to identify genes suited for normalization, applied to bladder and colon cancer ... Cloning of Atlantic halibut growth hormone receptor genes and .... messenger and ribosomal RNA content in rat mammary tumors.

  8. Genes, evolution and intelligence.

    Science.gov (United States)

    Bouchard, Thomas J

    2014-11-01

    I argue that the g factor meets the fundamental criteria of a scientific construct more fully than any other conception of intelligence. I briefly discuss the evidence regarding the relationship of brain size to intelligence. A review of a large body of evidence demonstrates that there is a g factor in a wide range of species and that, in the species studied, it relates to brain size and is heritable. These findings suggest that many species have evolved a general-purpose mechanism (a general biological intelligence) for dealing with the environments in which they evolved. In spite of numerous studies with considerable statistical power, we know of very few genes that influence g and the effects are very small. Nevertheless, g appears to be highly polygenic. Given the complexity of the human brain, it is not surprising that that one of its primary faculties-intelligence-is best explained by the near infinitesimal model of quantitative genetics.

  9. Gene therapy and reproductive medicine.

    Science.gov (United States)

    Stribley, John M; Rehman, Khurram S; Niu, Hairong; Christman, Gregory M

    2002-04-01

    To review the literature on the principles of gene therapy and its potential application in reproductive medicine. Literature review. Gene therapy involves transfer of genetic material to target cells using a delivery system, or vector. Attention has primarily focused on viral vectors. Significant problems remain to be overcome including low efficacy of gene transfer, the transient expression of some vectors, safety issues with modified adenoviruses and retroviruses, and ethical concerns. If these issues can be resolved, gene therapy will be applicable to an increasing spectrum of single and multiple gene disorders, as the Human Genome Project data are analyzed, and the genetic component of human disease becomes better understood. Gynecologic gene therapy has advanced to human clinical trials for ovarian carcinoma, and shows potential for the treatment of uterine leiomyomata. Obstetric applications of gene therapy, including fetal gene therapy, remain more distant goals. Concerns about the safety of human gene therapy research are being actively addressed, and remarkable progress in improving DNA transfer has been made. The first treatment success for a genetic disease (severe combined immunodeficiency disease) has been achieved, and ongoing research efforts will eventually yield clinical applications in many spheres of reproductive medicine.

  10. Efficient strategy for detecting gene × gene joint action and its application in schizophrenia.

    Science.gov (United States)

    Won, Sungho; Kwon, Min-Seok; Mattheisen, Manuel; Park, Suyeon; Park, Changsoon; Kihara, Daisuke; Cichon, Sven; Ophoff, Roel; Nöthen, Markus M; Rietschel, Marcella; Baur, Max; Uitterlinden, Andre G; Hofmann, A; Lange, Christoph

    2014-01-01

    We propose a new approach to detect gene × gene joint action in genome-wide association studies (GWASs) for case-control designs. This approach offers an exhaustive search for all two-way joint action (including, as a special case, single gene action) that is computationally feasible at the genome-wide level and has reasonable statistical power under most genetic models. We found that the presence of any gene × gene joint action may imply differences in three types of genetic components: the minor allele frequencies and the amounts of Hardy-Weinberg disequilibrium may differ between cases and controls, and between the two genetic loci the degree of linkage disequilibrium may differ between cases and controls. Using Fisher's method, it is possible to combine the different sources of genetic information in an overall test for detecting gene × gene joint action. The proposed statistical analysis is efficient and its simplicity makes it applicable to GWASs. In the current study, we applied the proposed approach to a GWAS on schizophrenia and found several potential gene × gene interactions. Our application illustrates the practical advantage of the proposed method. © 2013 WILEY PERIODICALS, INC.

  11. Time-Course Gene Set Analysis for Longitudinal Gene Expression Data.

    Directory of Open Access Journals (Sweden)

    Boris P Hejblum

    2015-06-01

    Full Text Available Gene set analysis methods, which consider predefined groups of genes in the analysis of genomic data, have been successfully applied for analyzing gene expression data in cross-sectional studies. The time-course gene set analysis (TcGSA introduced here is an extension of gene set analysis to longitudinal data. The proposed method relies on random effects modeling with maximum likelihood estimates. It allows to use all available repeated measurements while dealing with unbalanced data due to missing at random (MAR measurements. TcGSA is a hypothesis driven method that identifies a priori defined gene sets with significant expression variations over time, taking into account the potential heterogeneity of expression within gene sets. When biological conditions are compared, the method indicates if the time patterns of gene sets significantly differ according to these conditions. The interest of the method is illustrated by its application to two real life datasets: an HIV therapeutic vaccine trial (DALIA-1 trial, and data from a recent study on influenza and pneumococcal vaccines. In the DALIA-1 trial TcGSA revealed a significant change in gene expression over time within 69 gene sets during vaccination, while a standard univariate individual gene analysis corrected for multiple testing as well as a standard a Gene Set Enrichment Analysis (GSEA for time series both failed to detect any significant pattern change over time. When applied to the second illustrative data set, TcGSA allowed the identification of 4 gene sets finally found to be linked with the influenza vaccine too although they were found to be associated to the pneumococcal vaccine only in previous analyses. In our simulation study TcGSA exhibits good statistical properties, and an increased power compared to other approaches for analyzing time-course expression patterns of gene sets. The method is made available for the community through an R package.

  12. Human gene therapy and imaging: cardiology

    International Nuclear Information System (INIS)

    Wu, Joseph C.; Yla-Herttuala, Seppo

    2005-01-01

    This review discusses the basics of cardiovascular gene therapy, the results of recent human clinical trials, and the rapid progress in imaging techniques in cardiology. Improved understanding of the molecular and genetic basis of coronary heart disease has made gene therapy a potential new alternative for the treatment of cardiovascular diseases. Experimental studies have established the proof-of-principle that gene transfer to the cardiovascular system can achieve therapeutic effects. First human clinical trials provided initial evidence of feasibility and safety of cardiovascular gene therapy. However, phase II/III clinical trials have so far been rather disappointing and one of the major problems in cardiovascular gene therapy has been the inability to verify gene expression in the target tissue. New imaging techniques could significantly contribute to the development of better gene therapeutic approaches. Although the exact choice of imaging modality will depend on the biological question asked, further improvement in image resolution and detection sensitivity will be needed for all modalities as we move from imaging of organs and tissues to imaging of cells and genes. (orig.)

  13. Characterization of the omlA gene from different serotypes of Actinobacillus pleuropneumoniae: a new insight into an old approach

    Directory of Open Access Journals (Sweden)

    Ciro César Rossi

    2013-01-01

    Full Text Available The OmlA protein is a virulence factor of Actinobacillus pleuropneumoniae, an important pathogen in pigs. The polymorphisms present in the omlA gene sequence of 15 reference serotypes of A. pleuropneumoniae and non-serotypable isolates were assessed to determine the possible evolutionary relationship among them and to validate the importance of this gene as a molecular marker for the characterization of this bacterium. Divergence among the 15 serotypes of A. pleuropneumoniae probably resulted initially from two major evolutionary events that led to subsequent differentiation into nine groups. This differentiation makes it possible to characterize most of the serotypes by using bionformatics, thereby avoiding problems with immunological cross-reactivity. A conserved α-helix common to all the serotypes was most likely involved in connecting the protein to the outer membrane and acting as a signal peptide. A previously unknown gene duplication was also identified and could contribute to the genetic variability that makes it difficult to serotype some isolates. Our data support the importance of the omlA gene in the biology of A. pleuropneumoniae and provide a new area of research into the OmlA protein.

  14. Bioinformatics Data Mining Approach Suggests Coexpression of AGTPBP1 with an ALS-linked Gene C9orf72

    Directory of Open Access Journals (Sweden)

    Shouta Kitano

    2015-01-01

    Full Text Available Background Expanded GGGGCC hexanucleotide repeats located in the noncoding region of the chromosome 9 open reading frame 72 ( C9orf72 gene represent the most common genetic abnormality for familial and sporadic amyotrophic lateral sclerosis (ALS and frontotemporal dementia (FTD. Formation of nuclear RNA foci, accumulation of repeat-associated non-ATG-translated dipeptide-repeat proteins, and haploinsufficiency of C9orf72 are proposed for pathological mechanisms of C9ALS/FTD. However, at present, the physiological function of C9orf72 remains largely unknown. Methods By searching on a bioinformatics database named COXPRESdb composed of the comprehensive gene coexpression data, we studied potential C9orf72 interactors. Results We identified the ATP/GTP binding protein 1 ( AGTPBP1 gene alternatively named NNA1 encoding a cytosolic carboxypeptidase whose mutation is causative of the degeneration of Purkinje cells and motor neurons as the most significant gene coexpressed with C9orf72. We verified coexpression and interaction of AGTPBP1 and C9orf72 in transfected cells by immunoprecipitation and in neurons of the human brain by double-labeling immunohistochemistry. Furthermore, we found a positive correlation between AGTPBP1 and C9orf72 mRNA expression levels in the set of 21 human brains examined. Conclusions These results suggest that AGTPBP1 serves as a C9orf72 interacting partner that plays a role in the regulation of neuronal function in a coordinated manner within the central nervous system.

  15. Comprehensive approach to study complement C4 in systemic lupus erythematosus: Gene polymorphisms, protein levels and functional activity

    NARCIS (Netherlands)

    Tsang-A-Sjoe, M. W. P.; Bultink, I. E. M.; Korswagen, L. A.; van der Horst, A. [=Anneke; Rensink, I.; de Boer, M.; Hamann, D.; Voskuyl, A. E.; Wouters, D.

    2017-01-01

    Genetic variation of the genes encoding complement component C4 is strongly associated with systemic lupus erythematosus (SLE), a chronic multi-organ auto-immune disease. This study examined C4 and its isotypes on a genetic, protein, and functional level in 140 SLE patients and 104 healthy controls.

  16. Discovering gene annotations in biomedical text databases

    Directory of Open Access Journals (Sweden)

    Ozsoyoglu Gultekin

    2008-03-01

    Full Text Available Abstract Background Genes and gene products are frequently annotated with Gene Ontology concepts based on the evidence provided in genomics articles. Manually locating and curating information about a genomic entity from the biomedical literature requires vast amounts of human effort. Hence, there is clearly a need forautomated computational tools to annotate the genes and gene products with Gene Ontology concepts by computationally capturing the related knowledge embedded in textual data. Results In this article, we present an automated genomic entity annotation system, GEANN, which extracts information about the characteristics of genes and gene products in article abstracts from PubMed, and translates the discoveredknowledge into Gene Ontology (GO concepts, a widely-used standardized vocabulary of genomic traits. GEANN utilizes textual "extraction patterns", and a semantic matching framework to locate phrases matching to a pattern and produce Gene Ontology annotations for genes and gene products. In our experiments, GEANN has reached to the precision level of 78% at therecall level of 61%. On a select set of Gene Ontology concepts, GEANN either outperforms or is comparable to two other automated annotation studies. Use of WordNet for semantic pattern matching improves the precision and recall by 24% and 15%, respectively, and the improvement due to semantic pattern matching becomes more apparent as the Gene Ontology terms become more general. Conclusion GEANN is useful for two distinct purposes: (i automating the annotation of genomic entities with Gene Ontology concepts, and (ii providing existing annotations with additional "evidence articles" from the literature. The use of textual extraction patterns that are constructed based on the existing annotations achieve high precision. The semantic pattern matching framework provides a more flexible pattern matching scheme with respect to "exactmatching" with the advantage of locating approximate

  17. Functional gene profiling through metaRNAseq approach reveals diet-dependent variation in rumen microbiota of buffalo (Bubalus bubalis).

    Science.gov (United States)

    Hinsu, Ankit T; Parmar, Nidhi R; Nathani, Neelam M; Pandit, Ramesh J; Patel, Anand B; Patel, Amrutlal K; Joshi, Chaitanya G

    2017-04-01

    Recent advances in next generation sequencing technology have enabled analysis of complex microbial community from genome to transcriptome level. In the present study, metatranscriptomic approach was applied to elucidate functionally active bacteria and their biological processes in rumen of buffalo (Bubalus bubalis) adapted to different dietary treatments. Buffaloes were adapted to a diet containing 50:50, 75:25 and 100:0 forage to concentrate ratio, each for 6 weeks, before ruminal content sample collection. Metatranscriptomes from rumen fiber adherent and fiber-free active bacteria were sequenced using Ion Torrent PGM platform followed by annotation using MG-RAST server and CAZYmes (Carbohydrate active enzymes) analysis toolkit. In all the samples Bacteroidetes was the most abundant phylum followed by Firmicutes. Functional analysis using KEGG Orthology database revealed Metabolism as the most abundant category at level 1 within which Carbohydrate metabolism was dominating. Diet treatments also exerted significant differences in proportion of enzymes involved in metabolic pathways for VFA production. Carbohydrate Active Enzyme(CAZy) analysis revealed the abundance of genes encoding glycoside hydrolases with the highest representation of GH13 CAZy family in all the samples. The findings provide an overview of the activities occurring in the rumen as well as active bacterial population and the changes occurring through different dietary treatments. Copyright © 2017 Elsevier Ltd. All rights reserved.

  18. 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) ...

  19. Are TMEM genes potential candidate genes for panic disorder?

    DEFF Research Database (Denmark)

    NO, Gregersen; Buttenschøn, Henriette Nørmølle; Hedemand, Anne

    2014-01-01

    We analysed single nucleotide polymorphisms in two transmembrane genes (TMEM98 and TMEM132E) in panic disorder (PD) patients and control individuals from the Faroe Islands, Denmark and Germany. The genes encode single-pass membrane proteins and are located within chromosome 17q11.2-q12...

  20. Synthesis of a wild-type and three mutant Cucurbita maxima trypsin inhibitor-encoding genes by a single-strand approach.

    Science.gov (United States)

    Botes, D P; Qobose, M D; Corfield, V A

    1991-09-15

    A single-strand approach to gene assembly, based on a modification of an in vitro complementary oligodeoxyribonucleotide template-directed ligation of the desired sequence to a linearized vector [Chen et al., Nucleic Acids Res. 18 (1990) 871-878], is described. The gene coding for the wild-type Cucurbita maxima trypsin inhibitor of 29 amino acid residues [Bode et al., FEBS Lett. 242 (1989) 285-292], as well as three mutant forms of the gene, in which two of the three disulfide bonds have been replaced singly or as a pair, have been synthesized in a single synthesis run with minimal manual intervention. Subsequent to ligation to pUC9 and in vivo gapped duplex repair by Escherichia coli, their sequences have been verified.

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

    International Nuclear Information System (INIS)

    Robson, T.; Yakkundi, A.; McCarthy, H.; McErlane, V.; Hughes, C.M.; Hirst, D.G.; McKeown, S.R.; Patterson, L.H.

    2003-01-01

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

  2. Affected pathways and transcriptional regulators in gene expression response to an ultra-marathon trail: Global and independent activity approaches.

    Directory of Open Access Journals (Sweden)

    Maria Maqueda

    Full Text Available Gene expression (GE analyses on blood samples from marathon and half-marathon runners have reported significant impacts on the immune and inflammatory systems. An ultra-marathon trail (UMT represents a greater effort due to its more testing conditions. For the first time, we report the genome-wide GE profiling in a group of 16 runners participating in an 82 km UMT competition. We quantified their differential GE profile before and after the race using HuGene2.0st microarrays (Affymetrix Inc., California, US. The results obtained were decomposed by means of an independent component analysis (ICA targeting independent expression modes. We observed significant differences in the expression levels of 5,084 protein coding genes resulting in an overrepresentation of 14% of the human biological pathways from the Kyoto Encyclopedia of Genes and Genomes database. These were mainly clustered on terms related with protein synthesis repression, altered immune system and infectious diseases related mechanisms. In a second analysis, 27 out of the 196 transcriptional regulators (TRs included in the Open Regulatory Annotation database were overrepresented. Among these TRs, we identified transcription factors from the hypoxia-inducible factors (HIF family EPAS1 (p< 0.01 and HIF1A (p<0.001, and others jointly described in the gluconeogenesis program such as HNF4 (p< 0.001, EGR1 (p<0.001, CEBPA (p< 0.001 and a highly specific TR, YY1 (p<0.01. The five independent components, obtained from ICA, further revealed a down-regulation of 10 genes distributed in the complex I, III and V from the electron transport chain. This mitochondrial activity reduction is compatible with HIF-1 system activation. The vascular endothelial growth factor (VEGF pathway, known to be regulated by HIF, also emerged (p<0.05. Additionally, and related to the brain rewarding circuit, the endocannabinoid signalling pathway was overrepresented (p<0.05.

  3. Principles of gene microarray data analysis.

    Science.gov (United States)

    Mocellin, Simone; Rossi, Carlo Riccardo

    2007-01-01

    The development of several gene expression profiling methods, such as comparative genomic hybridization (CGH), differential display, serial analysis of gene expression (SAGE), and gene microarray, together with the sequencing of the human genome, has provided an opportunity to monitor and investigate the complex cascade of molecular events leading to tumor development and progression. The availability of such large amounts of information has shifted the attention of scientists towards a nonreductionist approach to biological phenomena. High throughput technologies can be used to follow changing patterns of gene expression over time. Among them, gene microarray has become prominent because it is easier to use, does not require large-scale DNA sequencing, and allows for the parallel quantification of thousands of genes from multiple samples. Gene microarray technology is rapidly spreading worldwide and has the potential to drastically change the therapeutic approach to patients affected with tumor. Therefore, it is of paramount importance for both researchers and clinicians to know the principles underlying the analysis of the huge amount of data generated with microarray technology.

  4. Classifying genes to the correct Gene Ontology Slim term in Saccharomyces cerevisiae using neighbouring genes with classification learning

    Directory of Open Access Journals (Sweden)

    Tsatsoulis Costas

    2010-05-01

    Full Text Available Abstract Background There is increasing evidence that gene location and surrounding genes influence the functionality of genes in the eukaryotic genome. Knowing the Gene Ontology Slim terms associated with a gene gives us insight into a gene's functionality by informing us how its gene product behaves in a cellular context using three different ontologies: molecular function, biological process, and cellular component. In this study, we analyzed if we could classify a gene in Saccharomyces cerevisiae to its correct Gene Ontology Slim term using information about its location in the genome and information from its nearest-neighbouring genes using classification learning. Results We performed experiments to establish that the MultiBoostAB algorithm using the J48 classifier could correctly classify Gene Ontology Slim terms of a gene given information regarding the gene's location and information from its nearest-neighbouring genes for training. Different neighbourhood sizes were examined to determine how many nearest neighbours should be included around each gene to provide better classification rules. Our results show that by just incorporating neighbour information from each gene's two-nearest neighbours, the percentage of correctly classified genes to their correct Gene Ontology Slim term for each ontology reaches over 80% with high accuracy (reflected in F-measures over 0.80 of the classification rules produced. Conclusions We confirmed that in classifying genes to their correct Gene Ontology Slim term, the inclusion of neighbour information from those genes is beneficial. Knowing the location of a gene and the Gene Ontology Slim information from neighbouring genes gives us insight into that gene's functionality. This benefit is seen by just including information from a gene's two-nearest neighbouring genes.

  5. The roles of segmental and tandem gene duplication in the evolution of large gene families in Arabidopsis thaliana

    Directory of Open Access Journals (Sweden)

    Baumgarten Andrew

    2004-06-01

    Full Text Available Abstract Background Most genes in Arabidopsis thaliana are members of gene families. How do the members of gene families arise, and how are gene family copy numbers maintained? Some gene families may evolve primarily through tandem duplication and high rates of birth and death in clusters, and others through infrequent polyploidy or large-scale segmental duplications and subsequent losses. Results Our approach to understanding the mechanisms of gene family evolution was to construct phylogenies for 50 large gene families in Arabidopsis thaliana, identify large internal segmental duplications in Arabidopsis, map gene duplications onto the segmental duplications, and use this information to identify which nodes in each phylogeny arose due to segmental or tandem duplication. Examples of six gene families exemplifying characteristic modes are described. Distributions of gene family sizes and patterns of duplication by genomic distance are also described in order to characterize patterns of local duplication and copy number for large gene families. Both gene family size and duplication by distance closely follow power-law distributions. Conclusions Combining information about genomic segmental duplications, gene family phylogenies, and gene positions provides a method to evaluate contributions of tandem duplication and segmental genome duplication in the generation and maintenance of gene families. These differences appear to correspond meaningfully to differences in functional roles of the members of the gene families.

  6. Gene therapy for prostate cancer.

    LENUS (Irish Health Repository)

    Tangney, Mark

    2012-01-31

    Cancer remains a leading cause of morbidity and mortality. Despite advances in understanding, detection, and treatment, it accounts for almost one-fourth of all deaths per year in Western countries. Prostate cancer is currently the most commonly diagnosed noncutaneous cancer in men in Europe and the United States, accounting for 15% of all cancers in men. As life expectancy of individuals increases, it is expected that there will also be an increase in the incidence and mortality of prostate cancer. Prostate cancer may be inoperable at initial presentation, unresponsive to chemotherapy and radiotherapy, or recur following appropriate treatment. At the time of presentation, patients may already have metastases in their tissues. Preventing tumor recurrence requires systemic therapy; however, current modalities are limited by toxicity or lack of efficacy. For patients with such metastatic cancers, the development of alternative therapies is essential. Gene therapy is a realistic prospect for the treatment of prostate and other cancers, and involves the delivery of genetic information to the patient to facilitate the production of therapeutic proteins. Therapeutics can act directly (eg, by inducing tumor cells to produce cytotoxic agents) or indirectly by upregulating the immune system to efficiently target tumor cells or by destroying the tumor\\'s vasculature. However, technological difficulties must be addressed before an efficient and safe gene medicine is achieved (primarily by developing a means of delivering genes to the target cells or tissue safely and efficiently). A wealth of research has been carried out over the past 20 years, involving various strategies for the treatment of prostate cancer at preclinical and clinical trial levels. The therapeutic efficacy observed with many of these approaches in patients indicates that these treatment modalities will serve as an important component of urological malignancy treatment in the clinic, either in isolation or

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

    Science.gov (United States)

    Travella, Silvia; Keller, Beat

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

  8. Coexpression landscape in ATTED-II: usage of gene list and gene network for various types of pathways.

    Science.gov (United States)

    Obayashi, Takeshi; Kinoshita, Kengo

    2010-05-01

    Gene coexpression analyses are a powerful method to predict the function of genes and/or to identify genes that are functionally related to query genes. The basic idea of gene coexpression analyses is that genes with similar functions should have similar expression patterns under many different conditions. This approach is now widely used by many experimental researchers, especially in the field of plant biology. In this review, we will summarize recent successful examples obtained by using our gene coexpression database, ATTED-II. Specifically, the examples will describe the identification of new genes, such as the subunits of a complex protein, the enzymes in a metabolic pathway and transporters. In addition, we will discuss the discovery of a new intercellular signaling factor and new regulatory relationships between transcription factors and their target genes. In ATTED-II, we provide two basic views of gene coexpression, a gene list view and a gene network view, which can be used as guide gene approach and narrow-down approach, respectively. In addition, we will discuss the coexpression effectiveness for various types of gene sets.

  9. Analysis of multiplex gene expression maps obtained by voxelation.

    Science.gov (United States)

    An, Li; Xie, Hongbo; Chin, Mark H; Obradovic, Zoran; Smith, Desmond J; Megalooikonomou, Vasileios

    2009-04-29

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

  10. Analysis of multiplex gene expression maps obtained by voxelation

    Directory of Open Access Journals (Sweden)

    Smith Desmond J

    2009-04-01

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

  11. Determining Semantically Related Significant Genes.

    Science.gov (United States)

    Taha, Kamal

    2014-01-01

    GO relation embodies some aspects of existence dependency. If GO term xis existence-dependent on GO term y, the presence of y implies the presence of x. Therefore, the genes annotated with the function of the GO term y are usually functionally and semantically related to the genes annotated with the function of the GO term x. A large number of gene set enrichment analysis methods have been developed in recent years for analyzing gene sets enrichment. However, most of these methods overlook the structural dependencies between GO terms in GO graph by not considering the concept of existence dependency. We propose in this paper a biological search engine called RSGSearch that identifies enriched sets of genes annotated with different functions using the concept of existence dependency. We observe that GO term xcannot be existence-dependent on GO term y, if x- and y- have the same specificity (biological characteristics). After encoding into a numeric format the contributions of GO terms annotating target genes to the semantics of their lowest common ancestors (LCAs), RSGSearch uses microarray experiment to identify the most significant LCA that annotates the result genes. We evaluated RSGSearch experimentally and compared it with five gene set enrichment systems. Results showed marked improvement.

  12. Gene set analysis for GWAS

    DEFF Research Database (Denmark)

    Debrabant, Birgit; Soerensen, Mette

    2014-01-01

    Abstract We discuss the use of modified Kolmogorov-Smirnov (KS) statistics in the context of gene set analysis and review corresponding null and alternative hypotheses. Especially, we show that, when enhancing the impact of highly significant genes in the calculation of the test statistic, the co...

  13. On meme--gene coevolution.

    Science.gov (United States)

    Bull, L; Holland, O; Blackmore, S

    2000-01-01

    In this article we examine the effects of the emergence of a new replicator, memes, on the evolution of a pre-existing replicator, genes. Using a version of the NKCS model we examine the effects of increasing the rate of meme evolution in relation to the rate of gene evolution, for various degrees of interdependence between the two replicators. That is, the effects of memes' (suggested) more rapid rate of evolution in comparison to that of genes is investigated using a tunable model of coevolution. It is found that, for almost any degree of interdependence between the two replicators, as the rate of meme evolution increases, a phase transition-like dynamic occurs under which memes have a significantly detrimental effect on the evolution of genes, quickly resulting in the cessation of effective gene evolution. Conversely, the memes experience a sharp increase in benefit from increasing their rate of evolution. We then examine the effects of enabling genes to reduce the percentage of gene-detrimental evolutionary steps taken by memes. Here a critical region emerges as the comparative rate of meme evolution increases, such that if genes cannot effectively select memes a high percentage of the time, they suffer from meme evolution as if they had almost no selective capability.

  14. Susceptibility Genes in Thyroid Autoimmunity

    Directory of Open Access Journals (Sweden)

    Yoshiyuki Ban

    2005-01-01

    Full Text Available The autoimmune thyroid diseases (AITD are complex diseases which are caused by an interaction between susceptibility genes and environmental triggers. Genetic susceptibility in combination with external factors (e.g. dietary iodine is believed to initiate the autoimmune response to thyroid antigens. Abundant epidemiological data, including family and twin studies, point to a strong genetic influence on the development of AITD. Various techniques have been employed to identify the genes contributing to the etiology of AITD, including candidate gene analysis and whole genome screening. These studies have enabled the identification of several loci (genetic regions that are linked with AITD, and in some of these loci, putative AITD susceptibility genes have been identified. Some of these genes/loci are unique to Graves' disease (GD and Hashimoto's thyroiditis (HT and some are common to both the diseases, indicating that there is a shared genetic susceptibility to GD and HT. The putative GD and HT susceptibility genes include both immune modifying genes (e.g. HLA, CTLA-4 and thyroid specific genes (e.g. TSHR, Tg. Most likely, these loci interact and their interactions may influence disease phenotype and severity.

  15. Gene polymorphisms in chronic periodontitis

    NARCIS (Netherlands)

    Laine, M.L.; Loos, B.G.; Crielaard, W.

    2010-01-01

    We aimed to conduct a review of the literature for gene polymorphisms associated with chronic periodontitis (CP) susceptibility. A comprehensive search of the literature in English was performed using the keywords: periodontitis, periodontal disease, combined with the words genes, mutation, or

  16. Imaging after vascular gene therapy

    International Nuclear Information System (INIS)

    Manninen, Hannu I.; Yang, Xiaoming

    2005-01-01

    Targets for cardiovascular gene therapy currently include limiting restenosis after balloon angioplasty and stent placement, inhibiting vein bypass graft intimal hyperplasia/stenosis, therapeutic angiogenesis for cardiac and lower-limb ischemia, and prevention of thrombus formation. While catheter angiography is still standard method to follow-up vascular gene transfer, other modern imaging techniques, especially intravascular ultrasound (IVUS), magnetic resonance (MR), and positron emission tomography (PET) imaging provide complementary information about the therapeutic effect of vascular gene transfer in humans. Although molecular imaging of therapeutic gene expression in the vasculatures is still in its technical development phase, it has already offered basic medical science an extremely useful in vivo evaluation tool for non- or minimally invasive imaging of vascular gene therapy

  17. Function analysis of unknown genes

    DEFF Research Database (Denmark)

    Rogowska-Wrzesinska, A.

    2002-01-01

      This thesis entitled "Function analysis of unknown genes" presents the use of proteome analysis for the characterisation of yeast (Saccharomyces cerevisiae) genes and their products (proteins especially those of unknown function). This study illustrates that proteome analysis can be used...... to describe different aspects of molecular biology of the cell, to study changes that occur in the cell due to overexpression or deletion of a gene and to identify various protein modifications. The biological questions and the results of the described studies show the diversity of the information that can...... genes and proteins. It reports the first global proteome database collecting 36 yeast single gene deletion mutants and selecting over 650 differences between analysed mutants and the wild type strain. The obtained results show that two-dimensional gel electrophoresis and mass spectrometry based proteome...

  18. Tracking microorganisms and gene in the environment

    International Nuclear Information System (INIS)

    Atlas, R.M.; Sayler, G.S.

    1988-01-01

    Studies have been conducted to determine the sensitivities and limitations of various methods for determining the fate of genetically engineered microorganisms (GEMs) and their genes in the environment. Selective viable plate count procedures can be designed to detect the introduced organisms with high sensitivity; but they are restricted by potential mutations affecting the expression of the selective characteristic in the introduced organism, the occurrence of the particular selective characteristic in the indigenous organisms, and the need to culture the organism. The accuracy of this approach is greatly improved by colony hybridization procedures that use a specific gene probe to detect the introduced genes, but this approach is still only as sensitive as the plating procedure. Direct extraction of DNA from environmental samples, coupled with dot blot hybridization with radiolabeled probe DNA or solution hybridization, gives a high degree of both sensitivity and precision. This approach does not require culturing of the organism; and even if an introduced gene moves into a new organism or if the introduced organism is viable but nonculturable, the gene probe methods will detect the persistence of the introduced genes in the environment. Efficient direct DNA extraction methods have been developed and tested following in vitro experimental additions of GEMs to sediment and water samples

  19. 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.

  20. Exploring the Optimal Strategy to Predict Essential Genes in Microbes

    Directory of Open Access Journals (Sweden)

    Yao Lu

    2011-12-01

    Full Text Available Accurately predicting essential genes is important in many aspects of biology, medicine and bioengineering. In previous research, we have developed a machine learning based integrative algorithm to predict essential genes in bacterial species. This algorithm lends itself to two approaches for predicting essential genes: learning the traits from known essential genes in the target organism, or transferring essential gene annotations from a closely related model organism. However, for an understudied microbe, each approach has its potential limitations. The first is constricted by the often small number of known essential genes. The second is limited by the availability of model organisms and by evolutionary distance. In this study, we aim to determine the optimal strategy for predicting essential genes by examining four microbes with well-characterized essential genes. Our results suggest that, unless the known essential genes are few, learning from the known essential genes in the target organism usually outperforms transferring essential gene annotations from a related model organism. In fact, the required number of known essential genes is surprisingly small to make accurate predictions. In prokaryotes, when the number of known essential genes is greater than 2% of total genes, this approach already comes close to its optimal performance. In eukaryotes, achieving the same best performance requires over 4% of total genes, reflecting the increased complexity of eukaryotic organisms. Combining the two approaches resulted in an increased performance when the known essential genes are few. Our investigation thus provides key information on accurately predicting essential genes and will greatly facilitate annotations of microbial genomes.

  1. GeneTopics - interpretation of gene sets via literature-driven topic models

    Science.gov (United States)

    2013-01-01

    Background Annotation of a set of genes is often accomplished through comparison to a library of labelled gene sets such as biological processes or canonical pathways. However, this approach might fail if the employed libraries are not up to date with the latest research, don't capture relevant biological themes or are curated at a different level of granularity than is required to appropriately analyze the input gene set. At the same time, the vast biomedical literature offers an unstructured repository of the latest research findings that can be tapped to provide thematic sub-groupings for any input gene set. Methods Our proposed method relies on a gene-specific text corpus and extracts commonalities between documents in an unsupervised manner using a topic model approach. We automatically determine the number of topics summarizing the corpus and calculate a gene relevancy score for each topic allowing us to eliminate non-specific topics. As a result we obtain a set of literature topics in which each topic is associated with a subset of the input genes providing directly interpretable keywords and corresponding documents for literature research. Results We validate our method based on labelled gene sets from the KEGG metabolic pathway collection and the genetic association database (GAD) and show that the approach is able to detect topics consistent with the labelled annotation. Furthermore, we discuss the results on three different types of experimentally derived gene sets, (1) differentially expressed genes from a cardiac hypertrophy experiment in mice, (2) altered transcript abundance in human pancreatic beta cells, and (3) genes implicated by GWA studies to be associated with metabolite levels in a healthy population. In all three cases, we are able to replicate findings from the original papers in a quick and semi-automated manner. Conclusions Our approach provides a novel way of automatically generating meaningful annotations for gene sets that are directly

  2. 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

  3. 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

  4. [MVK gene abnormality and new approach to treatment of hyper IgD syndrome and periodic fever syndrome].

    Science.gov (United States)

    Naruto, Takuya

    2007-04-01

    Hyper IgD and periodic fever syndrome (HIDS; OMIM 260920) is one of the hereditary autoinflammatory syndromes characterized by recurrent episodes of fever and inflammation.. HIDS is an autosomal recessive disorder characterized by recurrent fever attacks in early childhood. HIDS caused by mevalonate kinase (MK) mutations, also that is the gene of mevalonic aciduria (OMIM 251170). During febrile episodes, urinary mevalonate concentrations were found to be significantly elevated in patients. Diagnosis of HIDS was retrieving gene or measurement of the enzyme activity in peripheral blood lymphocyte in general. This of HIDS is an activity decline of MK, and a complete deficiency of MK becomes a mevalonic aciduria with a nervous symptom. The relation between the fever and inflammation of mevalonate or isoprenoid products are uncertain. The therapy attempt with statins, which is inhibited the next enzyme after HMG-CoA reductase, or inhibit the proinflammatory cytokines.

  5. Gene prioritization for livestock diseases by data integration

    DEFF Research Database (Denmark)

    Jiang, Li; Sørensen, Peter; Thomsen, Bo Stjerne

    2012-01-01

    in bovine mastitis. Gene-associated phenome profile and transcriptome profile in response to Escherichia coli infection in the mammary gland were integrated to make a global inference of bovine genes involved in mastitis. The top ranked genes were highly enriched for pathways and biological processes...... underlying inflammation and immune responses, which supports the validity of our approach for identifying genes that are relevant to animal health and disease. These gene-associated phenotypes were used for a local prioritization of candidate genes located in a QTL affecting the susceptibility to mastitis...

  6. A Probabilistic Genome-Wide Gene Reading Frame Sequence Model

    DEFF Research Database (Denmark)

    Have, Christian Theil; Mørk, Søren

    We introduce a new type of probabilistic sequence model, that model the sequential composition of reading frames of genes in a genome. Our approach extends gene finders with a model of the sequential composition of genes at the genome-level -- effectively producing a sequential genome annotation...... as output. The model can be used to obtain the most probable genome annotation based on a combination of i: a gene finder score of each gene candidate and ii: the sequence of the reading frames of gene candidates through a genome. The model --- as well as a higher order variant --- is developed and tested...... and are evaluated by the effect on prediction performance. Since bacterial gene finding to a large extent is a solved problem it forms an ideal proving ground for evaluating the explicit modeling of larger scale gene sequence composition of genomes. We conclude that the sequential composition of gene reading frames...

  7. The Use of a Combined Bioinformatics Approach to Locate Antibiotic Resistance Genes on Plasmids From Whole Genome Sequences of Salmonella enterica Serovars From Humans in Ghana

    Directory of Open Access Journals (Sweden)

    Egle Kudirkiene

    2018-05-01

    Full Text Available In the current study, we identified plasmids carrying antimicrobial resistance genes in draft whole genome sequences of 16 selected Salmonella enterica isolates representing six different serovars from humans in Ghana. The plasmids and the location of resistance genes in the genomes were predicted using a combination of PlasmidFinder, ResFinder, plasmidSPAdes and BLAST genomic analysis tools. Subsequently, S1-PFGE was employed for analysis of plasmid profiles. Whole genome sequencing confirmed the presence of antimicrobial resistance genes in Salmonella isolates showing multidrug resistance phenotypically. ESBL, either blaTEM52−B or blaCTX−M15 were present in two cephalosporin resistant isolates of S. Virchow and S. Poona, respectively. The systematic genome analysis revealed the presence of different plasmids in different serovars, with or without insertion of antimicrobial resistance genes. In S. Enteritidis, resistance genes were carried predominantly on plasmids of IncN type, in S. Typhimurium on plasmids of IncFII(S/IncFIB(S/IncQ1 type. In S. Virchow and in S. Poona, resistance genes were detected on plasmids of IncX1 and TrfA/IncHI2/IncHI2A type, respectively. The latter two plasmids were described for the first time in these serovars. The combination of genomic analytical tools allowed nearly full mapping of the resistance plasmids in all Salmonella strains analyzed. The results suggest that the improved analytical approach used in the current study may be used to identify plasmids that are specifically associated with resistance phenotypes in whole genome sequences. Such knowledge would allow the development of rapid multidrug resistance tracking tools in Salmonella populations using WGS.

  8. Case-control approach application for finding a relationship between candidate genes and clinical mastitis in Holstein dairy cattle.

    Science.gov (United States)

    Bagheri, Masoumeh; Moradi-Sharhrbabak, M; Miraie-Ashtiani, R; Safdari-Shahroudi, M; Abdollahi-Arpanahi, R

    2016-02-01

    Mastitis is a major source of economic loss in dairy herds. The objective of this research was to evaluate the association between genotypes within SLC11A1 and CXCR1 candidate genes and clinical mastitis in Holstein dairy cattle using the selective genotyping method. The data set contained clinical mastitis records of 3,823 Holstein cows from two Holstein dairy herds located in two different regions in Iran. Data included the number of cases of clinical mastitis per lactation. Selective genotyping was based on extreme values for clinical mastitis residuals (CMR) from mixed model analyses. Two extreme groups consisting of 135 cows were formed (as cases and controls), and genotyped for the two candidate genes, namely, SLC11A1 and CXCR1, using polymerase chain reaction-single strand conformation polymorphism (PCR-SSCP) and polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP), respectively. Associations between single nucleotide polymorphism (SNP) genotypes with CMR and breeding values for milk and protein yield were carried out by applying logistic regression analyses, i.e. estimating the probability of the heterogeneous genotype in the dependency of values for CMR and breeding values (BVs). The sequencing results revealed a novel mutation in 1139 bp of exon 11 of the SLC11A1 gene and this SNP had a significant association with CMR (P G and these genotypes had significant relationships with CMR. Overall, the results showed that SLC11A1 and CXCR1 are valuable candidate genes for the improvement of mastitis resistance as well as production traits in dairy cattle populations.

  9. A recently transferred cluster of bacterial genes in Trichomonas vaginalis - lateral gene transfer and the fate of acquired genes

    Science.gov (United States)

    2014-01-01

    Background Lateral Gene Transfer (LGT) has recently gained recognition as an important contribut