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Sample records for gene selection method

  1. A Comparative Study of Feature Selection and Classification Methods for Gene Expression Data

    KAUST Repository

    Abusamra, Heba

    2013-01-01

    Different experiments have been applied to compare the performance of the classification methods with and without performing feature selection. Results revealed the important role of feature selection in classifying gene expression data. By performing feature selection, the classification accuracy can be significantly boosted by using a small number of genes. The relationship of features selected in different feature selection methods is investigated and the most frequent features selected in each fold among all methods for both datasets are evaluated.

  2. Ultrahigh-dimensional variable selection method for whole-genome gene-gene interaction analysis

    Directory of Open Access Journals (Sweden)

    Ueki Masao

    2012-05-01

    Full Text Available Abstract Background Genome-wide gene-gene interaction analysis using single nucleotide polymorphisms (SNPs is an attractive way for identification of genetic components that confers susceptibility of human complex diseases. Individual hypothesis testing for SNP-SNP pairs as in common genome-wide association study (GWAS however involves difficulty in setting overall p-value due to complicated correlation structure, namely, the multiple testing problem that causes unacceptable false negative results. A large number of SNP-SNP pairs than sample size, so-called the large p small n problem, precludes simultaneous analysis using multiple regression. The method that overcomes above issues is thus needed. Results We adopt an up-to-date method for ultrahigh-dimensional variable selection termed the sure independence screening (SIS for appropriate handling of numerous number of SNP-SNP interactions by including them as predictor variables in logistic regression. We propose ranking strategy using promising dummy coding methods and following variable selection procedure in the SIS method suitably modified for gene-gene interaction analysis. We also implemented the procedures in a software program, EPISIS, using the cost-effective GPGPU (General-purpose computing on graphics processing units technology. EPISIS can complete exhaustive search for SNP-SNP interactions in standard GWAS dataset within several hours. The proposed method works successfully in simulation experiments and in application to real WTCCC (Wellcome Trust Case–control Consortium data. Conclusions Based on the machine-learning principle, the proposed method gives powerful and flexible genome-wide search for various patterns of gene-gene interaction.

  3. Detection of biomarkers for Hepatocellular Carcinoma using a hybrid univariate gene selection methods

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    Abdel Samee Nagwan M

    2012-08-01

    Full Text Available Abstract Background Discovering new biomarkers has a great role in improving early diagnosis of Hepatocellular carcinoma (HCC. The experimental determination of biomarkers needs a lot of time and money. This motivates this work to use in-silico prediction of biomarkers to reduce the number of experiments required for detecting new ones. This is achieved by extracting the most representative genes in microarrays of HCC. Results In this work, we provide a method for extracting the differential expressed genes, up regulated ones, that can be considered candidate biomarkers in high throughput microarrays of HCC. We examine the power of several gene selection methods (such as Pearson’s correlation coefficient, Cosine coefficient, Euclidean distance, Mutual information and Entropy with different estimators in selecting informative genes. A biological interpretation of the highly ranked genes is done using KEGG (Kyoto Encyclopedia of Genes and Genomes pathways, ENTREZ and DAVID (Database for Annotation, Visualization, and Integrated Discovery databases. The top ten genes selected using Pearson’s correlation coefficient and Cosine coefficient contained six genes that have been implicated in cancer (often multiple cancers genesis in previous studies. A fewer number of genes were obtained by the other methods (4 genes using Mutual information, 3genes using Euclidean distance and only one gene using Entropy. A better result was obtained by the utilization of a hybrid approach based on intersecting the highly ranked genes in the output of all investigated methods. This hybrid combination yielded seven genes (2 genes for HCC and 5 genes in different types of cancer in the top ten genes of the list of intersected genes. Conclusions To strengthen the effectiveness of the univariate selection methods, we propose a hybrid approach by intersecting several of these methods in a cascaded manner. This approach surpasses all of univariate selection methods when

  4. 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.

  5. An Entropy-based gene selection method for cancer classification using microarray data

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    Krishnan Arun

    2005-03-01

    Full Text Available Abstract Background Accurate diagnosis of cancer subtypes remains a challenging problem. Building classifiers based on gene expression data is a promising approach; yet the selection of non-redundant but relevant genes is difficult. The selected gene set should be small enough to allow diagnosis even in regular clinical laboratories and ideally identify genes involved in cancer-specific regulatory pathways. Here an entropy-based method is proposed that selects genes related to the different cancer classes while at the same time reducing the redundancy among the genes. Results The present study identifies a subset of features by maximizing the relevance and minimizing the redundancy of the selected genes. A merit called normalized mutual information is employed to measure the relevance and the redundancy of the genes. In order to find a more representative subset of features, an iterative procedure is adopted that incorporates an initial clustering followed by data partitioning and the application of the algorithm to each of the partitions. A leave-one-out approach then selects the most commonly selected genes across all the different runs and the gene selection algorithm is applied again to pare down the list of selected genes until a minimal subset is obtained that gives a satisfactory accuracy of classification. The algorithm was applied to three different data sets and the results obtained were compared to work done by others using the same data sets Conclusion This study presents an entropy-based iterative algorithm for selecting genes from microarray data that are able to classify various cancer sub-types with high accuracy. In addition, the feature set obtained is very compact, that is, the redundancy between genes is reduced to a large extent. This implies that classifiers can be built with a smaller subset of genes.

  6. A Comparative Study of Feature Selection and Classification Methods for Gene Expression Data

    KAUST Repository

    Abusamra, Heba

    2013-05-01

    Microarray technology has enriched the study of gene expression in such a way that scientists are now able to measure the expression levels of thousands of genes in a single experiment. Microarray gene expression data gained great importance in recent years due to its role in disease diagnoses and prognoses which help to choose the appropriate treatment plan for patients. This technology has shifted a new era in molecular classification, interpreting gene expression data remains a difficult problem and an active research area due to their native nature of “high dimensional low sample size”. Such problems pose great challenges to existing classification methods. Thus, effective feature selection techniques are often needed in this case to aid to correctly classify different tumor types and consequently lead to a better understanding of genetic signatures as well as improve treatment strategies. This thesis aims on a comparative study of state-of-the-art feature selection methods, classification methods, and the combination of them, based on gene expression data. We compared the efficiency of three different classification methods including: support vector machines, k- nearest neighbor and random forest, and eight different feature selection methods, including: information gain, twoing rule, sum minority, max minority, gini index, sum of variances, t- statistics, and one-dimension support vector machine. Five-fold cross validation was used to evaluate the classification performance. Two publicly available gene expression data sets of glioma were used for this study. Different experiments have been applied to compare the performance of the classification methods with and without performing feature selection. Results revealed the important role of feature selection in classifying gene expression data. By performing feature selection, the classification accuracy can be significantly boosted by using a small number of genes. The relationship of features selected in

  7. A Comparative Study of Feature Selection and Classification Methods for Gene Expression Data of Glioma

    KAUST Repository

    Abusamra, Heba

    2013-11-01

    Microarray gene expression data gained great importance in recent years due to its role in disease diagnoses and prognoses which help to choose the appropriate treatment plan for patients. This technology has shifted a new era in molecular classification. Interpreting gene expression data remains a difficult problem and an active research area due to their native nature of “high dimensional low sample size”. Such problems pose great challenges to existing classification methods. Thus, effective feature selection techniques are often needed in this case to aid to correctly classify different tumor types and consequently lead to a better understanding of genetic signatures as well as improve treatment strategies. This paper aims on a comparative study of state-of-the- art feature selection methods, classification methods, and the combination of them, based on gene expression data. We compared the efficiency of three different classification methods including: support vector machines, k-nearest neighbor and random forest, and eight different feature selection methods, including: information gain, twoing rule, sum minority, max minority, gini index, sum of variances, t-statistics, and one-dimension support vector machine. Five-fold cross validation was used to evaluate the classification performance. Two publicly available gene expression data sets of glioma were used in the experiments. Results revealed the important role of feature selection in classifying gene expression data. By performing feature selection, the classification accuracy can be significantly boosted by using a small number of genes. The relationship of features selected in different feature selection methods is investigated and the most frequent features selected in each fold among all methods for both datasets are evaluated.

  8. A Comparative Study of Feature Selection and Classification Methods for Gene Expression Data of Glioma

    KAUST Repository

    Abusamra, Heba

    2013-01-01

    Microarray gene expression data gained great importance in recent years due to its role in disease diagnoses and prognoses which help to choose the appropriate treatment plan for patients. This technology has shifted a new era in molecular classification. Interpreting gene expression data remains a difficult problem and an active research area due to their native nature of “high dimensional low sample size”. Such problems pose great challenges to existing classification methods. Thus, effective feature selection techniques are often needed in this case to aid to correctly classify different tumor types and consequently lead to a better understanding of genetic signatures as well as improve treatment strategies. This paper aims on a comparative study of state-of-the- art feature selection methods, classification methods, and the combination of them, based on gene expression data. We compared the efficiency of three different classification methods including: support vector machines, k-nearest neighbor and random forest, and eight different feature selection methods, including: information gain, twoing rule, sum minority, max minority, gini index, sum of variances, t-statistics, and one-dimension support vector machine. Five-fold cross validation was used to evaluate the classification performance. Two publicly available gene expression data sets of glioma were used in the experiments. Results revealed the important role of feature selection in classifying gene expression data. By performing feature selection, the classification accuracy can be significantly boosted by using a small number of genes. The relationship of features selected in different feature selection methods is investigated and the most frequent features selected in each fold among all methods for both datasets are evaluated.

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

    Science.gov (United States)

    Kang, Suyeon; Song, Jongwoo

    2017-09-02

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

  10. Genetic Bee Colony (GBC) algorithm: A new gene selection method for microarray cancer classification.

    Science.gov (United States)

    Alshamlan, Hala M; Badr, Ghada H; Alohali, Yousef A

    2015-06-01

    Naturally inspired evolutionary algorithms prove effectiveness when used for solving feature selection and classification problems. Artificial Bee Colony (ABC) is a relatively new swarm intelligence method. In this paper, we propose a new hybrid gene selection method, namely Genetic Bee Colony (GBC) algorithm. The proposed algorithm combines the used of a Genetic Algorithm (GA) along with Artificial Bee Colony (ABC) algorithm. The goal is to integrate the advantages of both algorithms. The proposed algorithm is applied to a microarray gene expression profile in order to select the most predictive and informative genes for cancer classification. In order to test the accuracy performance of the proposed algorithm, extensive experiments were conducted. Three binary microarray datasets are use, which include: colon, leukemia, and lung. In addition, another three multi-class microarray datasets are used, which are: SRBCT, lymphoma, and leukemia. Results of the GBC algorithm are compared with our recently proposed technique: mRMR when combined with the Artificial Bee Colony algorithm (mRMR-ABC). We also compared the combination of mRMR with GA (mRMR-GA) and Particle Swarm Optimization (mRMR-PSO) algorithms. In addition, we compared the GBC algorithm with other related algorithms that have been recently published in the literature, using all benchmark datasets. The GBC algorithm shows superior performance as it achieved the highest classification accuracy along with the lowest average number of selected genes. This proves that the GBC algorithm is a promising approach for solving the gene selection problem in both binary and multi-class cancer classification. Copyright © 2015 Elsevier Ltd. All rights reserved.

  11. Locating disease genes using Bayesian variable selection with the Haseman-Elston method

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    He Qimei

    2003-12-01

    Full Text Available Abstract Background We applied stochastic search variable selection (SSVS, a Bayesian model selection method, to the simulated data of Genetic Analysis Workshop 13. We used SSVS with the revisited Haseman-Elston method to find the markers linked to the loci determining change in cholesterol over time. To study gene-gene interaction (epistasis and gene-environment interaction, we adopted prior structures, which incorporate the relationship among the predictors. This allows SSVS to search in the model space more efficiently and avoid the less likely models. Results In applying SSVS, instead of looking at the posterior distribution of each of the candidate models, which is sensitive to the setting of the prior, we ranked the candidate variables (markers according to their marginal posterior probability, which was shown to be more robust to the prior. Compared with traditional methods that consider one marker at a time, our method considers all markers simultaneously and obtains more favorable results. Conclusions We showed that SSVS is a powerful method for identifying linked markers using the Haseman-Elston method, even for weak effects. SSVS is very effective because it does a smart search over the entire model space.

  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. Confirming candidate genes for longevity in Drosophila melanogaster using two different genetic backgrounds and selection methods

    DEFF Research Database (Denmark)

    Wit, Janneke; Frydenberg, Jane; Sarup, Pernille Merete

    2013-01-01

    usually focussed on one sex and on flies originating from one genetic background, and results from different studies often do not overlap. Using D. melanogaster selected for increased longevity we aimed to find robust longevity related genes by examining gene expression in both sexes of flies originating......Elucidating genes that affect life span or that can be used as biomarkers for ageing has received attention in diverse studies in recent years. Using model organisms and various approaches several genes have been linked to the longevity phenotype. For Drosophila melanogaster those studies have...... from different genetic backgrounds. Further, we compared expression changes across three ages, when flies were young, middle aged or old, to examine how candidate gene expression changes with the onset of ageing. We selected 10 genes based on their expression differences in prior microarray studies...

  14. Robust variable selection method for nonparametric differential equation models with application to nonlinear dynamic gene regulatory network analysis.

    Science.gov (United States)

    Lu, Tao

    2016-01-01

    The gene regulation network (GRN) evaluates the interactions between genes and look for models to describe the gene expression behavior. These models have many applications; for instance, by characterizing the gene expression mechanisms that cause certain disorders, it would be possible to target those genes to block the progress of the disease. Many biological processes are driven by nonlinear dynamic GRN. In this article, we propose a nonparametric differential equation (ODE) to model the nonlinear dynamic GRN. Specially, we address following questions simultaneously: (i) extract information from noisy time course gene expression data; (ii) model the nonlinear ODE through a nonparametric smoothing function; (iii) identify the important regulatory gene(s) through a group smoothly clipped absolute deviation (SCAD) approach; (iv) test the robustness of the model against possible shortening of experimental duration. We illustrate the usefulness of the model and associated statistical methods through a simulation and a real application examples.

  15. Multiclass gene selection using Pareto-fronts.

    Science.gov (United States)

    Rajapakse, Jagath C; Mundra, Piyushkumar A

    2013-01-01

    Filter methods are often used for selection of genes in multiclass sample classification by using microarray data. Such techniques usually tend to bias toward a few classes that are easily distinguishable from other classes due to imbalances of strong features and sample sizes of different classes. It could therefore lead to selection of redundant genes while missing the relevant genes, leading to poor classification of tissue samples. In this manuscript, we propose to decompose multiclass ranking statistics into class-specific statistics and then use Pareto-front analysis for selection of genes. This alleviates the bias induced by class intrinsic characteristics of dominating classes. The use of Pareto-front analysis is demonstrated on two filter criteria commonly used for gene selection: F-score and KW-score. A significant improvement in classification performance and reduction in redundancy among top-ranked genes were achieved in experiments with both synthetic and real-benchmark data sets.

  16. Methods for selecting fixed-effect models for heterogeneous codon evolution, with comments on their application to gene and genome data.

    Science.gov (United States)

    Bao, Le; Gu, Hong; Dunn, Katherine A; Bielawski, Joseph P

    2007-02-08

    Models of codon evolution have proven useful for investigating the strength and direction of natural selection. In some cases, a priori biological knowledge has been used successfully to model heterogeneous evolutionary dynamics among codon sites. These are called fixed-effect models, and they require that all codon sites are assigned to one of several partitions which are permitted to have independent parameters for selection pressure, evolutionary rate, transition to transversion ratio or codon frequencies. For single gene analysis, partitions might be defined according to protein tertiary structure, and for multiple gene analysis partitions might be defined according to a gene's functional category. Given a set of related fixed-effect models, the task of selecting the model that best fits the data is not trivial. In this study, we implement a set of fixed-effect codon models which allow for different levels of heterogeneity among partitions in the substitution process. We describe strategies for selecting among these models by a backward elimination procedure, Akaike information criterion (AIC) or a corrected Akaike information criterion (AICc). We evaluate the performance of these model selection methods via a simulation study, and make several recommendations for real data analysis. Our simulation study indicates that the backward elimination procedure can provide a reliable method for model selection in this setting. We also demonstrate the utility of these models by application to a single-gene dataset partitioned according to tertiary structure (abalone sperm lysin), and a multi-gene dataset partitioned according to the functional category of the gene (flagellar-related proteins of Listeria). Fixed-effect models have advantages and disadvantages. Fixed-effect models are desirable when data partitions are known to exhibit significant heterogeneity or when a statistical test of such heterogeneity is desired. They have the disadvantage of requiring a priori

  17. Characteristic gene selection via weighting principal components by singular values.

    Directory of Open Access Journals (Sweden)

    Jin-Xing Liu

    Full Text Available Conventional gene selection methods based on principal component analysis (PCA use only the first principal component (PC of PCA or sparse PCA to select characteristic genes. These methods indeed assume that the first PC plays a dominant role in gene selection. However, in a number of cases this assumption is not satisfied, so the conventional PCA-based methods usually provide poor selection results. In order to improve the performance of the PCA-based gene selection method, we put forward the gene selection method via weighting PCs by singular values (WPCS. Because different PCs have different importance, the singular values are exploited as the weights to represent the influence on gene selection of different PCs. The ROC curves and AUC statistics on artificial data show that our method outperforms the state-of-the-art methods. Moreover, experimental results on real gene expression data sets show that our method can extract more characteristic genes in response to abiotic stresses than conventional gene selection methods.

  18. Gene selection heuristic algorithm for nutrigenomics studies.

    Science.gov (United States)

    Valour, D; Hue, I; Grimard, B; Valour, B

    2013-07-15

    Large datasets from -omics studies need to be deeply investigated. The aim of this paper is to provide a new method (LEM method) for the search of transcriptome and metabolome connections. The heuristic algorithm here described extends the classical canonical correlation analysis (CCA) to a high number of variables (without regularization) and combines well-conditioning and fast-computing in "R." Reduced CCA models are summarized in PageRank matrices, the product of which gives a stochastic matrix that resumes the self-avoiding walk covered by the algorithm. Then, a homogeneous Markov process applied to this stochastic matrix converges the probabilities of interconnection between genes, providing a selection of disjointed subsets of genes. This is an alternative to regularized generalized CCA for the determination of blocks within the structure matrix. Each gene subset is thus linked to the whole metabolic or clinical dataset that represents the biological phenotype of interest. Moreover, this selection process reaches the aim of biologists who often need small sets of genes for further validation or extended phenotyping. The algorithm is shown to work efficiently on three published datasets, resulting in meaningfully broadened gene networks.

  19. Reference gene selection for molecular studies of dormancy in wild oat (Avena fatua L. caryopses by RT-qPCR method.

    Directory of Open Access Journals (Sweden)

    Izabela Ruduś

    Full Text Available Molecular studies of primary and secondary dormancy in Avena fatua L., a serious weed of cereal and other crops, are intended to reveal the species-specific details of underlying molecular mechanisms which in turn may be useable in weed management. Among others, quantitative real-time PCR (RT-qPCR data of comparative gene expression analysis may give some insight into the involvement of particular wild oat genes in dormancy release, maintenance or induction by unfavorable conditions. To assure obtaining biologically significant results using this method, the expression stability of selected candidate reference genes in different data subsets was evaluated using four statistical algorithms i.e. geNorm, NormFinder, Best Keeper and ΔCt method. Although some discrepancies in their ranking outputs were noticed, evidently two ubiquitin-conjugating enzyme homologs, AfUBC1 and AfUBC2, as well as one homolog of glyceraldehyde 3-phosphate dehydrogenase AfGAPDH1 and TATA-binding protein AfTBP2 appeared as more stably expressed than AfEF1a (translation elongation factor 1α, AfGAPDH2 or the least stable α-tubulin homolog AfTUA1 in caryopses and seedlings of A. fatua. Gene expression analysis of a dormancy-related wild oat transcription factor VIVIPAROUS1 (AfVP1 allowed for a validation of candidate reference genes performance. Based on the obtained results it can be recommended that the normalization factor calculated as a geometric mean of Cq values of AfUBC1, AfUBC2 and AfGAPDH1 would be optimal for RT-qPCR results normalization in the experiments comprising A. fatua caryopses of different dormancy status.

  20. Reference gene selection for molecular studies of dormancy in wild oat (Avena fatua L.) caryopses by RT-qPCR method.

    Science.gov (United States)

    Ruduś, Izabela; Kępczyński, Jan

    2018-01-01

    Molecular studies of primary and secondary dormancy in Avena fatua L., a serious weed of cereal and other crops, are intended to reveal the species-specific details of underlying molecular mechanisms which in turn may be useable in weed management. Among others, quantitative real-time PCR (RT-qPCR) data of comparative gene expression analysis may give some insight into the involvement of particular wild oat genes in dormancy release, maintenance or induction by unfavorable conditions. To assure obtaining biologically significant results using this method, the expression stability of selected candidate reference genes in different data subsets was evaluated using four statistical algorithms i.e. geNorm, NormFinder, Best Keeper and ΔCt method. Although some discrepancies in their ranking outputs were noticed, evidently two ubiquitin-conjugating enzyme homologs, AfUBC1 and AfUBC2, as well as one homolog of glyceraldehyde 3-phosphate dehydrogenase AfGAPDH1 and TATA-binding protein AfTBP2 appeared as more stably expressed than AfEF1a (translation elongation factor 1α), AfGAPDH2 or the least stable α-tubulin homolog AfTUA1 in caryopses and seedlings of A. fatua. Gene expression analysis of a dormancy-related wild oat transcription factor VIVIPAROUS1 (AfVP1) allowed for a validation of candidate reference genes performance. Based on the obtained results it can be recommended that the normalization factor calculated as a geometric mean of Cq values of AfUBC1, AfUBC2 and AfGAPDH1 would be optimal for RT-qPCR results normalization in the experiments comprising A. fatua caryopses of different dormancy status.

  1. Selection of Phototransduction Genes in Homo sapiens.

    Science.gov (United States)

    Christopher, Mark; Scheetz, Todd E; Mullins, Robert F; Abràmoff, Michael D

    2013-08-13

    We investigated the evidence of recent positive selection in the human phototransduction system at single nucleotide polymorphism (SNP) and gene level. SNP genotyping data from the International HapMap Project for European, Eastern Asian, and African populations was used to discover differences in haplotype length and allele frequency between these populations. Numeric selection metrics were computed for each SNP and aggregated into gene-level metrics to measure evidence of recent positive selection. The level of recent positive selection in phototransduction genes was evaluated and compared to a set of genes shown previously to be under recent selection, and a set of highly conserved genes as positive and negative controls, respectively. Six of 20 phototransduction genes evaluated had gene-level selection metrics above the 90th percentile: RGS9, GNB1, RHO, PDE6G, GNAT1, and SLC24A1. The selection signal across these genes was found to be of similar magnitude to the positive control genes and much greater than the negative control genes. There is evidence for selective pressure in the genes involved in retinal phototransduction, and traces of this selective pressure can be demonstrated using SNP-level and gene-level metrics of allelic variation. We hypothesize that the selective pressure on these genes was related to their role in low light vision and retinal adaptation to ambient light changes. Uncovering the underlying genetics of evolutionary adaptations in phototransduction not only allows greater understanding of vision and visual diseases, but also the development of patient-specific diagnostic and intervention strategies.

  2. Statistical Redundancy Testing for Improved Gene Selection in Cancer Classification Using Microarray Data

    Directory of Open Access Journals (Sweden)

    J. Sunil Rao

    2007-01-01

    Full Text Available In gene selection for cancer classifi cation using microarray data, we define an eigenvalue-ratio statistic to measure a gene’s contribution to the joint discriminability when this gene is included into a set of genes. Based on this eigenvalueratio statistic, we define a novel hypothesis testing for gene statistical redundancy and propose two gene selection methods. Simulation studies illustrate the agreement between statistical redundancy testing and gene selection methods. Real data examples show the proposed gene selection methods can select a compact gene subset which can not only be used to build high quality cancer classifiers but also show biological relevance.

  3. Selective gas exhaustion method

    International Nuclear Information System (INIS)

    Hirano, Yoichi

    1998-01-01

    The present invention provides a method capable of evacuating gases at an exhaustion rate which varies depending on the kind of gases. For example, in a thermonuclear experimental device, a hydrogen gas exhaustion rate is determined to 0 and an exhaustion rate for other impure gases is made greater. Namely, a baffle plate is cooled to a temperature to a level at which the vapor pressure of gases to evacuate a baffle plate is required in a pump incorporating a baffle plate, for example, a cryopump or a sorption pump. In this case, the level of the vapor pressure required for evacuating the exhaustion gas ingredients is 1 x 10 -8 Torr or less, preferably, 1 x 10 -9 Torr. In a thermonuclear experimental device, a gas having a lower boiling point next to hydrogen is neon, but neon is scarcely present in natural world. Nitrogen has a lower boiling point next thereto, and if the temperature is lowered to such a level that the vapor pressure for evacuating gases such as nitrogen, and carbon monoxide, oxygen, fluorine, argon or methane having a boiling point at or lower than nitrogen is required. Then, evacuation rate sufficient for gases other than hydrogen gas can be obtained. (I.S.)

  4. Genes under positive selection in Escherichia coli

    DEFF Research Database (Denmark)

    Petersen, Lise; Bollback, Jonathan P; Dimmic, Matt

    2007-01-01

    We used a comparative genomics approach to identify genes that are under positive selection in six strains of Escherichia coli and Shigella flexneri, including five strains that are human pathogens. We find that positive selection targets a wide range of different functions in the E. coli genome......, including cell surface proteins such as beta barrel porins, presumably because of the involvement of these genes in evolutionary arms races with other bacteria, phages, and/or the host immune system. Structural mapping of positively selected sites on trans-membrane beta barrel porins reveals...... that the residues under positive selection occur almost exclusively in the extracellular region of the proteins that are enriched with sites known to be targets of phages, colicins, or the host immune system. More surprisingly, we also find a number of other categories of genes that show very strong evidence...

  5. A BAYESIAN NONPARAMETRIC MIXTURE MODEL FOR SELECTING GENES AND GENE SUBNETWORKS.

    Science.gov (United States)

    Zhao, Yize; Kang, Jian; Yu, Tianwei

    2014-06-01

    It is very challenging to select informative features from tens of thousands of measured features in high-throughput data analysis. Recently, several parametric/regression models have been developed utilizing the gene network information to select genes or pathways strongly associated with a clinical/biological outcome. Alternatively, in this paper, we propose a nonparametric Bayesian model for gene selection incorporating network information. In addition to identifying genes that have a strong association with a clinical outcome, our model can select genes with particular expressional behavior, in which case the regression models are not directly applicable. We show that our proposed model is equivalent to an infinity mixture model for which we develop a posterior computation algorithm based on Markov chain Monte Carlo (MCMC) methods. We also propose two fast computing algorithms that approximate the posterior simulation with good accuracy but relatively low computational cost. We illustrate our methods on simulation studies and the analysis of Spellman yeast cell cycle microarray data.

  6. Inspection methods and their selection

    International Nuclear Information System (INIS)

    Maier, H.J.

    1980-01-01

    First those nondestructive testing methods, which are used in quality assurance, are to be treated, e.g. - ultrasonics - radiography - magnetic particle testing - dye penetrant testing - eddy currents, and their capabilities and limitations are shown. Second the selection of optimal testing methods under the aspect of defect recognition in different materials and components are shown. (orig./RW)

  7. Selection Method for COTS Systems

    DEFF Research Database (Denmark)

    Hedman, Jonas; Andersson, Bo

    2014-01-01

    feature behind the method is that improved understanding of organizational ‘ends’ or goals should govern the selection of a COTS system. This can also be expressed as a match or fit between ‘ends’ (e.g. improved organizational effectiveness) and ‘means’ (e.g. implementing COTS systems). This way...

  8. A Selection Method That Succeeds!

    Science.gov (United States)

    Weitman, Catheryn J.

    Provided a structural selection method is carried out, it is possible to find quality early childhood personnel. The hiring process involves five definite steps, each of which establishes a base for the next. A needs assessment formulating basic minimal qualifications is the first step. The second step involves review of current job descriptions…

  9. Informative gene selection using Adaptive Analytic Hierarchy Process (A2HP

    Directory of Open Access Journals (Sweden)

    Abhishek Bhola

    2017-12-01

    Full Text Available Gene expression dataset derived from microarray experiments are marked by large number of genes, which contains the gene expression values at different sample conditions/time-points. Selection of informative genes from these large datasets is an issue of major concern for various researchers and biologists. In this study, we propose a gene selection and dimensionality reduction method called Adaptive Analytic Hierarchy Process (A2HP. Traditional analytic hierarchy process is a multiple-criteria based decision analysis method whose result depends upon the expert knowledge or decision makers. It is mainly used to solve the decision problems in different fields. On the other hand, A2HP is a fused method that combines the outcomes of five individual gene selection ranking methods t-test, chi-square variance test, z-test, wilcoxon test and signal-to-noise ratio (SNR. At first, the preprocessing of gene expression dataset is done and then the reduced number of genes obtained, will be fed as input for A2HP. A2HP utilizes both quantitative and qualitative factors to select the informative genes. Results demonstrate that A2HP selects efficient number of genes as compared to the individual gene selection methods. The percentage of deduction in number of genes and time complexity are taken as the performance measure for the proposed method. And it is shown that A2HP outperforms individual gene selection methods.

  10. An improved selective sampling method

    International Nuclear Information System (INIS)

    Miyahara, Hiroshi; Iida, Nobuyuki; Watanabe, Tamaki

    1986-01-01

    The coincidence methods which are currently used for the accurate activity standardisation of radio-nuclides, require dead time and resolving time corrections which tend to become increasingly uncertain as countrates exceed about 10 K. To reduce the dependence on such corrections, Muller, in 1981, proposed the selective sampling method using a fast multichannel analyser (50 ns ch -1 ) for measuring the countrates. It is, in many ways, more convenient and possibly potentially more reliable to replace the MCA with scalers and a circuit is described employing five scalers; two of them serving to measure the background correction. Results of comparisons using our new method and the coincidence method for measuring the activity of 60 Co sources yielded agree-ment within statistical uncertainties. (author)

  11. Parameters selection in gene selection using Gaussian kernel support vector machines by genetic algorithm

    Institute of Scientific and Technical Information of China (English)

    2005-01-01

    In microarray-based cancer classification, gene selection is an important issue owing to the large number of variables and small number of samples as well as its non-linearity. It is difficult to get satisfying results by using conventional linear statistical methods. Recursive feature elimination based on support vector machine (SVM RFE) is an effective algorithm for gene selection and cancer classification, which are integrated into a consistent framework. In this paper, we propose a new method to select parameters of the aforementioned algorithm implemented with Gaussian kernel SVMs as better alternatives to the common practice of selecting the apparently best parameters by using a genetic algorithm to search for a couple of optimal parameter. Fast implementation issues for this method are also discussed for pragmatic reasons. The proposed method was tested on two representative hereditary breast cancer and acute leukaemia datasets. The experimental results indicate that the proposed method performs well in selecting genes and achieves high classification accuracies with these genes.

  12. Prospective identification of malaria parasite genes under balancing selection.

    Directory of Open Access Journals (Sweden)

    Kevin K A Tetteh

    Full Text Available Endemic human pathogens are subject to strong immune selection, and interrogation of pathogen genome variation for signatures of balancing selection can identify important target antigens. Several major antigen genes in the malaria parasite Plasmodium falciparum have shown such signatures in polymorphism-versus-divergence indices (comparing with the chimpanzee parasite P. reichenowi, and in allele frequency based indices.To compare methods for prospective identification of genes under balancing selection, 26 additional genes known or predicted to encode surface-exposed proteins of the invasive blood stage merozoite were first sequenced from a panel of 14 independent P. falciparum cultured lines and P. reichenowi. Six genes at the positive extremes of one or both of the Hudson-Kreitman-Aguade (HKA and McDonald-Kreitman (MK indices were identified. Allele frequency based analysis was then performed on a Gambian P. falciparum population sample for these six genes and three others as controls. Tajima's D (TjD index was most highly positive for the msp3/6-like PF10_0348 (TjD = 1.96 as well as the positive control ama1 antigen gene (TjD = 1.22. Across the genes there was a strong correlation between population TjD values and the relative HKA indices (whether derived from the population or the panel of cultured laboratory isolates, but no correlation with the MK indices.Although few individual parasite genes show significant evidence of balancing selection, analysis of population genomic and comparative sequence data with the HKA and TjD indices should discriminate those that do, and thereby identify likely targets of immunity.

  13. Gene selection for cancer classification with the help of bees.

    Science.gov (United States)

    Moosa, Johra Muhammad; Shakur, Rameen; Kaykobad, Mohammad; Rahman, Mohammad Sohel

    2016-08-10

    Development of biologically relevant models from gene expression data notably, microarray data has become a topic of great interest in the field of bioinformatics and clinical genetics and oncology. Only a small number of gene expression data compared to the total number of genes explored possess a significant correlation with a certain phenotype. Gene selection enables researchers to obtain substantial insight into the genetic nature of the disease and the mechanisms responsible for it. Besides improvement of the performance of cancer classification, it can also cut down the time and cost of medical diagnoses. This study presents a modified Artificial Bee Colony Algorithm (ABC) to select minimum number of genes that are deemed to be significant for cancer along with improvement of predictive accuracy. The search equation of ABC is believed to be good at exploration but poor at exploitation. To overcome this limitation we have modified the ABC algorithm by incorporating the concept of pheromones which is one of the major components of Ant Colony Optimization (ACO) algorithm and a new operation in which successive bees communicate to share their findings. The proposed algorithm is evaluated using a suite of ten publicly available datasets after the parameters are tuned scientifically with one of the datasets. Obtained results are compared to other works that used the same datasets. The performance of the proposed method is proved to be superior. The method presented in this paper can provide subset of genes leading to more accurate classification results while the number of selected genes is smaller. Additionally, the proposed modified Artificial Bee Colony Algorithm could conceivably be applied to problems in other areas as well.

  14. Analysis of polymorphisms and selective pressures on ama1 gene ...

    Indian Academy of Sciences (India)

    Chuen Yang Chua

    2017-09-05

    Sep 5, 2017 ... The presence of purifying selection and low nucleotide diversity ... (2000) studied the gene substitution of ama1 ... in the gene coding for AMA-1 protein in Plasmodium ... Health Malaysia. ...... X. Asembo Bay Cohort Project.

  15. FiGS: a filter-based gene selection workbench for microarray data

    Directory of Open Access Journals (Sweden)

    Yun Taegyun

    2010-01-01

    Full Text Available Abstract Background The selection of genes that discriminate disease classes from microarray data is widely used for the identification of diagnostic biomarkers. Although various gene selection methods are currently available and some of them have shown excellent performance, no single method can retain the best performance for all types of microarray datasets. It is desirable to use a comparative approach to find the best gene selection result after rigorous test of different methodological strategies for a given microarray dataset. Results FiGS is a web-based workbench that automatically compares various gene selection procedures and provides the optimal gene selection result for an input microarray dataset. FiGS builds up diverse gene selection procedures by aligning different feature selection techniques and classifiers. In addition to the highly reputed techniques, FiGS diversifies the gene selection procedures by incorporating gene clustering options in the feature selection step and different data pre-processing options in classifier training step. All candidate gene selection procedures are evaluated by the .632+ bootstrap errors and listed with their classification accuracies and selected gene sets. FiGS runs on parallelized computing nodes that capacitate heavy computations. FiGS is freely accessible at http://gexp.kaist.ac.kr/figs. Conclusion FiGS is an web-based application that automates an extensive search for the optimized gene selection analysis for a microarray dataset in a parallel computing environment. FiGS will provide both an efficient and comprehensive means of acquiring optimal gene sets that discriminate disease states from microarray datasets.

  16. Positive selection on gene expression in the human brain

    DEFF Research Database (Denmark)

    Khaitovich, Philipp; Tang, Kun; Franz, Henriette

    2006-01-01

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

  17. 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

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

    Directory of Open Access Journals (Sweden)

    Alireza Mehridehnavi

    2013-01-01

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

  19. Selection of Reliable Reference Genes for Gene Expression Studies on Rhododendron molle G. Don.

    Science.gov (United States)

    Xiao, Zheng; Sun, Xiaobo; Liu, Xiaoqing; Li, Chang; He, Lisi; Chen, Shangping; Su, Jiale

    2016-01-01

    The quantitative real-time polymerase chain reaction (qRT-PCR) approach has become a widely used method to analyze expression patterns of target genes. The selection of an optimal reference gene is a prerequisite for the accurate normalization of gene expression in qRT-PCR. The present study constitutes the first systematic evaluation of potential reference genes in Rhododendron molle G. Don. Eleven candidate reference genes in different tissues and flowers at different developmental stages of R. molle were assessed using the following three software packages: GeNorm, NormFinder, and BestKeeper. The results showed that EF1- α (elongation factor 1-alpha), 18S (18s ribosomal RNA), and RPL3 (ribosomal protein L3) were the most stable reference genes in developing rhododendron flowers and, thus, in all of the tested samples, while tublin ( TUB ) was the least stable. ACT5 (actin), RPL3 , 18S , and EF1- α were found to be the top four choices for different tissues, whereas TUB was not found to favor qRT-PCR normalization in these tissues. Three stable reference genes are recommended for the normalization of qRT-PCR data in R. molle . Furthermore, the expression profiles of RmPSY (phytoene synthase) and RmPDS (phytoene dehydrogenase) were assessed using EF1- α, 18S , ACT5 , RPL3 , and their combination as internals. Similar trends were found, but these trends varied when the least stable reference gene TUB was used. The results further prove that it is necessary to validate the stability of reference genes prior to their use for normalization under different experimental conditions. This study provides useful information for reliable qRT-PCR data normalization in gene studies of R. molle .

  20. Selection of Reliable Reference Genes for Gene Expression Studies on Rhododendron molle G. Don

    Directory of Open Access Journals (Sweden)

    Zheng Xiao

    2016-10-01

    Full Text Available The quantitative real-time polymerase chain reaction (qRT-PCR approach has become a widely used method to analyze expression patterns of target genes. The selection of an optimal reference gene is a prerequisite for the accurate normalization of gene expression in qRT-PCR. The present study constitutes the first systematic evaluation of potential reference genes in Rhododendron molle G. Don. Eleven candidate reference genes in different tissues and flowers at different developmental stages of R. molle were assessed using the following three software packages: GeNorm, NormFinder and BestKeeper. The results showed that EF1-α (elongation factor 1-alpha, 18S (18s ribosomal RNA and RPL3 (ribosomal protein L3 were the most stable reference genes in developing rhododendron flowers and, thus, in all of the tested samples, while tublin (TUB was the least stable. ACT5 (actin, RPL3, 18S and EF1-α were found to be the top four choices for different tissues, whereas TUB was not found to favor qRT-PCR normalization in these tissues. Three stable reference genes are recommended for the normalization of qRT-PCR data in R. molle. Furthermore, the expression profiles of RmPSY (phytoene synthase and RmPDS (phytoene dehydrogenase were assessed using EF1-α, 18S, ACT5, and RPL3 and their combination as internals. Similar trends were found, but these trends varied when the least stable reference gene TUB was used. The results further prove that it is necessary to validate the stability of reference genes prior to their use for normalization under different experimental conditions. This study provides useful information for reliable qRT-PCR data normalization in gene studies of R. molle.

  1. Recent adaptive events in human brain revealed by meta-analysis of positively selected genes.

    Directory of Open Access Journals (Sweden)

    Yue Huang

    Full Text Available BACKGROUND AND OBJECTIVES: Analysis of positively-selected genes can help us understand how human evolved, especially the evolution of highly developed cognitive functions. However, previous works have reached conflicting conclusions regarding whether human neuronal genes are over-represented among genes under positive selection. METHODS AND RESULTS: We divided positively-selected genes into four groups according to the identification approaches, compiling a comprehensive list from 27 previous studies. We showed that genes that are highly expressed in the central nervous system are enriched in recent positive selection events in human history identified by intra-species genomic scan, especially in brain regions related to cognitive functions. This pattern holds when different datasets, parameters and analysis pipelines were used. Functional category enrichment analysis supported these findings, showing that synapse-related functions are enriched in genes under recent positive selection. In contrast, immune-related functions, for instance, are enriched in genes under ancient positive selection revealed by inter-species coding region comparison. We further demonstrated that most of these patterns still hold even after controlling for genomic characteristics that might bias genome-wide identification of positively-selected genes including gene length, gene density, GC composition, and intensity of negative selection. CONCLUSION: Our rigorous analysis resolved previous conflicting conclusions and revealed recent adaptation of human brain functions.

  2. Natural Selection in Virulence Genes of Francisella tularensis.

    Science.gov (United States)

    Gunnell, Mark K; Robison, Richard A; Adams, Byron J

    2016-06-01

    A fundamental tenet of evolution is that alleles that are under negative selection are often deleterious and confer no evolutionary advantage. Negatively selected alleles are removed from the gene pool and are eventually extinguished from the population. Conversely, alleles under positive selection do confer an evolutionary advantage and lead to an increase in the overall fitness of the organism. These alleles increase in frequency until they eventually become fixed in the population. Francisella tularensis is a zoonotic pathogen and a potential biothreat agent. The most virulent type of F. tularensis, Type A, is distributed across North America with Type A.I occurring mainly in the east and Type A.II appearing mainly in the west. F. tularensis is thought to be a genome in decay (losing genes) because of the relatively large number of pseudogenes present in its genome. We hypothesized that the observed frequency of gene loss/pseudogenes may be an artifact of evolution in response to a changing environment, and that genes involved in virulence should be under strong positive selection. To test this hypothesis, we sequenced and compared whole genomes of Type A.I and A.II isolates. We analyzed a subset of virulence and housekeeping genes from several F. tularensis subspecies genomes to ascertain the presence and extent of positive selection. Eleven previously identified virulence genes were screened for positive selection along with 10 housekeeping genes. Analyses of selection yielded one housekeeping gene and 7 virulence genes which showed significant evidence of positive selection at loci implicated in cell surface structures and membrane proteins, metabolism and biosynthesis, transcription, translation and cell separation, and substrate binding and transport. Our results suggest that while the loss of functional genes through disuse could be accelerated by negative selection, the genome decay in Francisella could also be the byproduct of adaptive evolution

  3. A Selection Method for COTS Systems

    DEFF Research Database (Denmark)

    Hedman, Jonas

    new skills and methods supporting the process of evaluating and selecting information systems. This paper presents a method for selecting COTS systems. The method includes the following phases: problem framing, requirements and appraisal, and selection of systems. The idea and distinguishing feature...... behind the method is that improved understanding of organizational' ends' or goals should govern the selection of a COTS system. This can also be expressed as a match or fit between ‘ends' (e.g. improved organizational effectiveness) and ‘means' (e.g. implementing COTS systems). This way of approaching...

  4. Cloning and selection of reference genes for gene expression ...

    African Journals Online (AJOL)

    Full length mRNA sequences of Ac-β-actin and Ac-gapdh, and partial mRNA sequences of Ac-18SrRNA and Ac-ubiquitin were cloned from pineapple in this study. The four genes were tested as housekeeping genes in three experimental sets. GeNorm and NormFinder analysis revealed that β-actin was the most ...

  5. Gene selection for microarray data classification via subspace learning and manifold regularization.

    Science.gov (United States)

    Tang, Chang; Cao, Lijuan; Zheng, Xiao; Wang, Minhui

    2017-12-19

    With the rapid development of DNA microarray technology, large amount of genomic data has been generated. Classification of these microarray data is a challenge task since gene expression data are often with thousands of genes but a small number of samples. In this paper, an effective gene selection method is proposed to select the best subset of genes for microarray data with the irrelevant and redundant genes removed. Compared with original data, the selected gene subset can benefit the classification task. We formulate the gene selection task as a manifold regularized subspace learning problem. In detail, a projection matrix is used to project the original high dimensional microarray data into a lower dimensional subspace, with the constraint that the original genes can be well represented by the selected genes. Meanwhile, the local manifold structure of original data is preserved by a Laplacian graph regularization term on the low-dimensional data space. The projection matrix can serve as an importance indicator of different genes. An iterative update algorithm is developed for solving the problem. Experimental results on six publicly available microarray datasets and one clinical dataset demonstrate that the proposed method performs better when compared with other state-of-the-art methods in terms of microarray data classification. Graphical Abstract The graphical abstract of this work.

  6. A metaheuristic optimization framework for informative gene selection

    Directory of Open Access Journals (Sweden)

    Kaberi Das

    Full Text Available This paper presents a metaheuristic framework using Harmony Search (HS with Genetic Algorithm (GA for gene selection. The internal architecture of the proposed model broadly works in two phases, in the first phase, the model allows the hybridization of HS with GA to compute and evaluate the fitness of the randomly selected solutions of binary strings and then HS ranks the solutions in descending order of their fitness. In the second phase, the offsprings are generated using crossover and mutation operations of GA and finally, those offsprings were selected for the next generation whose fitness value is more than their parents evaluated by SVM classifier. The accuracy of the final gene subsets obtained from this model has been evaluated using SVM classifiers. The merit of this approach is analyzed by experimental results on five benchmark datasets and the results showed an impressive accuracy over existing feature selection approaches. The occurrence of gene subsets selected from this model have also been computed and the most often selected gene subsets with the probability of [0.1–0.9] have been chosen as optimal sets of informative genes. Finally, the performance of those selected informative gene subsets have been measured and established through probabilistic measures. Keywords: Gene Selection, Metaheuristic, Harmony Search Algorithm, Genetic Algorithm, SVM

  7. Methods for monitoring multiple gene expression

    Energy Technology Data Exchange (ETDEWEB)

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

    2012-05-01

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

  8. Methods for monitoring multiple gene expression

    Energy Technology Data Exchange (ETDEWEB)

    Berka, Randy; Bachkirova, Elena; Rey, Michael

    2013-10-01

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

  9. When natural selection gives gene function the cold shoulder.

    Science.gov (United States)

    Cutter, Asher D; Jovelin, Richard

    2015-11-01

    It is tempting to invoke organismal selection as perpetually optimizing the function of any given gene. However, natural selection can drive genic functional change without improvement of biochemical activity, even to the extinction of gene activity. Detrimental mutations can creep in owing to linkage with other selectively favored loci. Selection can promote functional degradation, irrespective of genetic drift, when adaptation occurs by loss of gene function. Even stabilizing selection on a trait can lead to divergence of the underlying molecular constituents. Selfish genetic elements can also proliferate independent of any functional benefits to the host genome. Here we review the logic and evidence for these diverse processes acting in genome evolution. This collection of distinct evolutionary phenomena - while operating through easily understandable mechanisms - all contribute to the seemingly counterintuitive notion that maintenance or improvement of a gene's biochemical function sometimes do not determine its evolutionary fate. © 2015 WILEY Periodicals, Inc.

  10. Challenges in microarray class discovery: a comprehensive examination of normalization, gene selection and clustering

    Directory of Open Access Journals (Sweden)

    Landfors Mattias

    2010-10-01

    Full Text Available Abstract Background Cluster analysis, and in particular hierarchical clustering, is widely used to extract information from gene expression data. The aim is to discover new classes, or sub-classes, of either individuals or genes. Performing a cluster analysis commonly involve decisions on how to; handle missing values, standardize the data and select genes. In addition, pre-processing, involving various types of filtration and normalization procedures, can have an effect on the ability to discover biologically relevant classes. Here we consider cluster analysis in a broad sense and perform a comprehensive evaluation that covers several aspects of cluster analyses, including normalization. Result We evaluated 2780 cluster analysis methods on seven publicly available 2-channel microarray data sets with common reference designs. Each cluster analysis method differed in data normalization (5 normalizations were considered, missing value imputation (2, standardization of data (2, gene selection (19 or clustering method (11. The cluster analyses are evaluated using known classes, such as cancer types, and the adjusted Rand index. The performances of the different analyses vary between the data sets and it is difficult to give general recommendations. However, normalization, gene selection and clustering method are all variables that have a significant impact on the performance. In particular, gene selection is important and it is generally necessary to include a relatively large number of genes in order to get good performance. Selecting genes with high standard deviation or using principal component analysis are shown to be the preferred gene selection methods. Hierarchical clustering using Ward's method, k-means clustering and Mclust are the clustering methods considered in this paper that achieves the highest adjusted Rand. Normalization can have a significant positive impact on the ability to cluster individuals, and there are indications that

  11. Challenges in microarray class discovery: a comprehensive examination of normalization, gene selection and clustering

    Science.gov (United States)

    2010-01-01

    Background Cluster analysis, and in particular hierarchical clustering, is widely used to extract information from gene expression data. The aim is to discover new classes, or sub-classes, of either individuals or genes. Performing a cluster analysis commonly involve decisions on how to; handle missing values, standardize the data and select genes. In addition, pre-processing, involving various types of filtration and normalization procedures, can have an effect on the ability to discover biologically relevant classes. Here we consider cluster analysis in a broad sense and perform a comprehensive evaluation that covers several aspects of cluster analyses, including normalization. Result We evaluated 2780 cluster analysis methods on seven publicly available 2-channel microarray data sets with common reference designs. Each cluster analysis method differed in data normalization (5 normalizations were considered), missing value imputation (2), standardization of data (2), gene selection (19) or clustering method (11). The cluster analyses are evaluated using known classes, such as cancer types, and the adjusted Rand index. The performances of the different analyses vary between the data sets and it is difficult to give general recommendations. However, normalization, gene selection and clustering method are all variables that have a significant impact on the performance. In particular, gene selection is important and it is generally necessary to include a relatively large number of genes in order to get good performance. Selecting genes with high standard deviation or using principal component analysis are shown to be the preferred gene selection methods. Hierarchical clustering using Ward's method, k-means clustering and Mclust are the clustering methods considered in this paper that achieves the highest adjusted Rand. Normalization can have a significant positive impact on the ability to cluster individuals, and there are indications that background correction is

  12. HMM-Based Gene Annotation Methods

    Energy Technology Data Exchange (ETDEWEB)

    Haussler, David; Hughey, Richard; Karplus, Keven

    1999-09-20

    Development of new statistical methods and computational tools to identify genes in human genomic DNA, and to provide clues to their functions by identifying features such as transcription factor binding sites, tissue, specific expression and splicing patterns, and remove homologies at the protein level with genes of known function.

  13. An Efficient Ensemble Learning Method for Gene Microarray Classification

    Directory of Open Access Journals (Sweden)

    Alireza Osareh

    2013-01-01

    Full Text Available The gene microarray analysis and classification have demonstrated an effective way for the effective diagnosis of diseases and cancers. However, it has been also revealed that the basic classification techniques have intrinsic drawbacks in achieving accurate gene classification and cancer diagnosis. On the other hand, classifier ensembles have received increasing attention in various applications. Here, we address the gene classification issue using RotBoost ensemble methodology. This method is a combination of Rotation Forest and AdaBoost techniques which in turn preserve both desirable features of an ensemble architecture, that is, accuracy and diversity. To select a concise subset of informative genes, 5 different feature selection algorithms are considered. To assess the efficiency of the RotBoost, other nonensemble/ensemble techniques including Decision Trees, Support Vector Machines, Rotation Forest, AdaBoost, and Bagging are also deployed. Experimental results have revealed that the combination of the fast correlation-based feature selection method with ICA-based RotBoost ensemble is highly effective for gene classification. In fact, the proposed method can create ensemble classifiers which outperform not only the classifiers produced by the conventional machine learning but also the classifiers generated by two widely used conventional ensemble learning methods, that is, Bagging and AdaBoost.

  14. Detecting negative selection on recurrent mutations using gene genealogy

    Science.gov (United States)

    2013-01-01

    Background Whether or not a mutant allele in a population is under selection is an important issue in population genetics, and various neutrality tests have been invented so far to detect selection. However, detection of negative selection has been notoriously difficult, partly because negatively selected alleles are usually rare in the population and have little impact on either population dynamics or the shape of the gene genealogy. Recently, through studies of genetic disorders and genome-wide analyses, many structural variations were shown to occur recurrently in the population. Such “recurrent mutations” might be revealed as deleterious by exploiting the signal of negative selection in the gene genealogy enhanced by their recurrence. Results Motivated by the above idea, we devised two new test statistics. One is the total number of mutants at a recurrently mutating locus among sampled sequences, which is tested conditionally on the number of forward mutations mapped on the sequence genealogy. The other is the size of the most common class of identical-by-descent mutants in the sample, again tested conditionally on the number of forward mutations mapped on the sequence genealogy. To examine the performance of these two tests, we simulated recurrently mutated loci each flanked by sites with neutral single nucleotide polymorphisms (SNPs), with no recombination. Using neutral recurrent mutations as null models, we attempted to detect deleterious recurrent mutations. Our analyses demonstrated high powers of our new tests under constant population size, as well as their moderate power to detect selection in expanding populations. We also devised a new maximum parsimony algorithm that, given the states of the sampled sequences at a recurrently mutating locus and an incompletely resolved genealogy, enumerates mutation histories with a minimum number of mutations while partially resolving genealogical relationships when necessary. Conclusions With their

  15. A Bayesian variable selection procedure for ranking overlapping gene sets

    DEFF Research Database (Denmark)

    Skarman, Axel; Mahdi Shariati, Mohammad; Janss, Luc

    2012-01-01

    Background Genome-wide expression profiling using microarrays or sequence-based technologies allows us to identify genes and genetic pathways whose expression patterns influence complex traits. Different methods to prioritize gene sets, such as the genes in a given molecular pathway, have been de...

  16. Flies selected for longevity retain a young gene expression profile

    DEFF Research Database (Denmark)

    Sarup, Pernille Merete; Sørensen, Peter; Loeschcke, Volker

    2011-01-01

      We investigated correlated responses in the transcriptomes of longevity-selected lines of Drosophila melanogaster to identify pathways that affect life span in metazoan systems. We evaluated the gene expression profile in young, middle-aged, and old male flies, finding that 530 genes were...

  17. Translational selection in human: More pronounced in housekeeping genes

    KAUST Repository

    Ma, Lina

    2014-07-10

    Background: Translational selection is a ubiquitous and significant mechanism to regulate protein expression in prokaryotes and unicellular eukaryotes. Recent evidence has shown that translational selection is weakly operative in highly expressed genes in human and other vertebrates. However, it remains unclear whether translational selection acts differentially on human genes depending on their expression patterns.Results: Here we report that human housekeeping (HK) genes that are strictly defined as genes that are expressed ubiquitously and consistently in most or all tissues, are under stronger translational selection.Conclusions: These observations clearly show that translational selection is also closely associated with expression pattern. Our results suggest that human HK genes are more efficiently and/or accurately translated into proteins, which will inevitably open up a new understanding of HK genes and the regulation of gene expression.Reviewers: This article was reviewed by Yuan Yuan, Baylor College of Medicine; Han Liang, University of Texas MD Anderson Cancer Center (nominated by Dr Laura Landweber) Eugene Koonin, NCBI, NLM, NIH, United States of America Sandor Pongor, International Centre for Genetic Engineering and biotechnology (ICGEB), Italy. © 2014 Ma et al.; licensee BioMed Central Ltd.

  18. Quantitative Methods for Software Selection and Evaluation

    National Research Council Canada - National Science Library

    Bandor, Michael S

    2006-01-01

    ... (the ability of the product to meet the need) and the cost. The method used for the analysis and selection activities can range from the use of basic intuition to counting the number of requirements fulfilled, or something...

  19. Mining method selection by integrated AHP and PROMETHEE method.

    Science.gov (United States)

    Bogdanovic, Dejan; Nikolic, Djordje; Ilic, Ivana

    2012-03-01

    Selecting the best mining method among many alternatives is a multicriteria decision making problem. The aim of this paper is to demonstrate the implementation of an integrated approach that employs AHP and PROMETHEE together for selecting the most suitable mining method for the "Coka Marin" underground mine in Serbia. The related problem includes five possible mining methods and eleven criteria to evaluate them. Criteria are accurately chosen in order to cover the most important parameters that impact on the mining method selection, such as geological and geotechnical properties, economic parameters and geographical factors. The AHP is used to analyze the structure of the mining method selection problem and to determine weights of the criteria, and PROMETHEE method is used to obtain the final ranking and to make a sensitivity analysis by changing the weights. The results have shown that the proposed integrated method can be successfully used in solving mining engineering problems.

  20. 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.

  1. Combining gene prediction methods to improve metagenomic gene annotation

    Directory of Open Access Journals (Sweden)

    Rosen Gail L

    2011-01-01

    Full Text Available Abstract Background Traditional gene annotation methods rely on characteristics that may not be available in short reads generated from next generation technology, resulting in suboptimal performance for metagenomic (environmental samples. Therefore, in recent years, new programs have been developed that optimize performance on short reads. In this work, we benchmark three metagenomic gene prediction programs and combine their predictions to improve metagenomic read gene annotation. Results We not only analyze the programs' performance at different read-lengths like similar studies, but also separate different types of reads, including intra- and intergenic regions, for analysis. The main deficiencies are in the algorithms' ability to predict non-coding regions and gene edges, resulting in more false-positives and false-negatives than desired. In fact, the specificities of the algorithms are notably worse than the sensitivities. By combining the programs' predictions, we show significant improvement in specificity at minimal cost to sensitivity, resulting in 4% improvement in accuracy for 100 bp reads with ~1% improvement in accuracy for 200 bp reads and above. To correctly annotate the start and stop of the genes, we find that a consensus of all the predictors performs best for shorter read lengths while a unanimous agreement is better for longer read lengths, boosting annotation accuracy by 1-8%. We also demonstrate use of the classifier combinations on a real dataset. Conclusions To optimize the performance for both prediction and annotation accuracies, we conclude that the consensus of all methods (or a majority vote is the best for reads 400 bp and shorter, while using the intersection of GeneMark and Orphelia predictions is the best for reads 500 bp and longer. We demonstrate that most methods predict over 80% coding (including partially coding reads on a real human gut sample sequenced by Illumina technology.

  2. A comparative study of three different gene expression analysis methods.

    Science.gov (United States)

    Choe, Jae Young; Han, Hyung Soo; Lee, Seon Duk; Lee, Hanna; Lee, Dong Eun; Ahn, Jae Yun; Ryoo, Hyun Wook; Seo, Kang Suk; Kim, Jong Kun

    2017-12-04

    TNF-α regulates immune cells and acts as an endogenous pyrogen. Reverse transcription polymerase chain reaction (RT-PCR) is one of the most commonly used methods for gene expression analysis. Among the alternatives to PCR, loop-mediated isothermal amplification (LAMP) shows good potential in terms of specificity and sensitivity. However, few studies have compared RT-PCR and LAMP for human gene expression analysis. Therefore, in the present study, we compared one-step RT-PCR, two-step RT-LAMP and one-step RT-LAMP for human gene expression analysis. We compared three gene expression analysis methods using the human TNF-α gene as a biomarker from peripheral blood cells. Total RNA from the three selected febrile patients were subjected to the three different methods of gene expression analysis. In the comparison of three gene expression analysis methods, the detection limit of both one-step RT-PCR and one-step RT-LAMP were the same, while that of two-step RT-LAMP was inferior. One-step RT-LAMP takes less time, and the experimental result is easy to determine. One-step RT-LAMP is a potentially useful and complementary tool that is fast and reasonably sensitive. In addition, one-step RT-LAMP could be useful in environments lacking specialized equipment or expertise.

  3. Entropy-based gene ranking without selection bias for the predictive classification of microarray data

    Directory of Open Access Journals (Sweden)

    Serafini Maria

    2003-11-01

    Full Text Available Abstract Background We describe the E-RFE method for gene ranking, which is useful for the identification of markers in the predictive classification of array data. The method supports a practical modeling scheme designed to avoid the construction of classification rules based on the selection of too small gene subsets (an effect known as the selection bias, in which the estimated predictive errors are too optimistic due to testing on samples already considered in the feature selection process. Results With E-RFE, we speed up the recursive feature elimination (RFE with SVM classifiers by eliminating chunks of uninteresting genes using an entropy measure of the SVM weights distribution. An optimal subset of genes is selected according to a two-strata model evaluation procedure: modeling is replicated by an external stratified-partition resampling scheme, and, within each run, an internal K-fold cross-validation is used for E-RFE ranking. Also, the optimal number of genes can be estimated according to the saturation of Zipf's law profiles. Conclusions Without a decrease of classification accuracy, E-RFE allows a speed-up factor of 100 with respect to standard RFE, while improving on alternative parametric RFE reduction strategies. Thus, a process for gene selection and error estimation is made practical, ensuring control of the selection bias, and providing additional diagnostic indicators of gene importance.

  4. Positive-negative-selection-mediated gene targeting in rice

    Directory of Open Access Journals (Sweden)

    Zenpei eShimatani

    2015-01-01

    Full Text Available Gene targeting (GT refers to the designed modification of genomic sequence(s through homologous recombination (HR. GT is a powerful tool both for the study of gene function and for molecular breeding. However, in transformation of higher plants, non-homologous end joining (NHEJ occurs overwhelmingly in somatic cells, masking HR-mediated GT. Positive-negative selection (PNS is an approach for finding HR-mediated GT events because it can eliminate NHEJ effectively by expression of a negative-selection marker gene. In rice—a major crop worldwide—reproducible PNS-mediated GT of endogenous genes has now been successfully achieved. The procedure is based on strong PNS using diphtheria toxin A-fragment as a negative marker, and has succeeded in the directed modification of several endogenous rice genes in various ways. In addition to gene knock-outs and knock-ins, a nucleotide substitution in a target gene was also achieved recently. This review presents a summary of the development of the rice PNS system, highlighting its advantages. Different types of gene modification and gene editing aimed at developing new plant breeding technology (NPBT based on PNS are discussed.

  5. Equipment Selection by using Fuzzy TOPSIS Method

    Science.gov (United States)

    Yavuz, Mahmut

    2016-10-01

    In this study, Fuzzy TOPSIS method was performed for the selection of open pit truck and the optimal solution of the problem was investigated. Data from Turkish Coal Enterprises was used in the application of the method. This paper explains the Fuzzy TOPSIS approaches with group decision-making application in an open pit coal mine in Turkey. An algorithm of the multi-person multi-criteria decision making with fuzzy set approach was applied an equipment selection problem. It was found that Fuzzy TOPSIS with a group decision making is a method that may help decision-makers in solving different decision-making problems in mining.

  6. A large-scale benchmark of gene prioritization methods.

    Science.gov (United States)

    Guala, Dimitri; Sonnhammer, Erik L L

    2017-04-21

    In order to maximize the use of results from high-throughput experimental studies, e.g. GWAS, for identification and diagnostics of new disease-associated genes, it is important to have properly analyzed and benchmarked gene prioritization tools. While prospective benchmarks are underpowered to provide statistically significant results in their attempt to differentiate the performance of gene prioritization tools, a strategy for retrospective benchmarking has been missing, and new tools usually only provide internal validations. The Gene Ontology(GO) contains genes clustered around annotation terms. This intrinsic property of GO can be utilized in construction of robust benchmarks, objective to the problem domain. We demonstrate how this can be achieved for network-based gene prioritization tools, utilizing the FunCoup network. We use cross-validation and a set of appropriate performance measures to compare state-of-the-art gene prioritization algorithms: three based on network diffusion, NetRank and two implementations of Random Walk with Restart, and MaxLink that utilizes network neighborhood. Our benchmark suite provides a systematic and objective way to compare the multitude of available and future gene prioritization tools, enabling researchers to select the best gene prioritization tool for the task at hand, and helping to guide the development of more accurate methods.

  7. Gene selection and classification for cancer microarray data based on machine learning and similarity measures

    Directory of Open Access Journals (Sweden)

    Liu Qingzhong

    2011-12-01

    Full Text Available Abstract Background Microarray data have a high dimension of variables and a small sample size. In microarray data analyses, two important issues are how to choose genes, which provide reliable and good prediction for disease status, and how to determine the final gene set that is best for classification. Associations among genetic markers mean one can exploit information redundancy to potentially reduce classification cost in terms of time and money. Results To deal with redundant information and improve classification, we propose a gene selection method, Recursive Feature Addition, which combines supervised learning and statistical similarity measures. To determine the final optimal gene set for prediction and classification, we propose an algorithm, Lagging Prediction Peephole Optimization. By using six benchmark microarray gene expression data sets, we compared Recursive Feature Addition with recently developed gene selection methods: Support Vector Machine Recursive Feature Elimination, Leave-One-Out Calculation Sequential Forward Selection and several others. Conclusions On average, with the use of popular learning machines including Nearest Mean Scaled Classifier, Support Vector Machine, Naive Bayes Classifier and Random Forest, Recursive Feature Addition outperformed other methods. Our studies also showed that Lagging Prediction Peephole Optimization is superior to random strategy; Recursive Feature Addition with Lagging Prediction Peephole Optimization obtained better testing accuracies than the gene selection method varSelRF.

  8. Selective Constraints on Coding Sequences of Nervous System Genes Are a Major Determinant of Duplicate Gene Retention in Vertebrates.

    Science.gov (United States)

    Roux, Julien; Liu, Jialin; Robinson-Rechavi, Marc

    2017-11-01

    The evolutionary history of vertebrates is marked by three ancient whole-genome duplications: two successive rounds in the ancestor of vertebrates, and a third one specific to teleost fishes. Biased loss of most duplicates enriched the genome for specific genes, such as slow evolving genes, but this selective retention process is not well understood. To understand what drives the long-term preservation of duplicate genes, we characterized duplicated genes in terms of their expression patterns. We used a new method of expression enrichment analysis, TopAnat, applied to in situ hybridization data from thousands of genes from zebrafish and mouse. We showed that the presence of expression in the nervous system is a good predictor of a higher rate of retention of duplicate genes after whole-genome duplication. Further analyses suggest that purifying selection against the toxic effects of misfolded or misinteracting proteins, which is particularly strong in nonrenewing neural tissues, likely constrains the evolution of coding sequences of nervous system genes, leading indirectly to the preservation of duplicate genes after whole-genome duplication. Whole-genome duplications thus greatly contributed to the expansion of the toolkit of genes available for the evolution of profound novelties of the nervous system at the base of the vertebrate radiation. © The Author 2017. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.

  9. Variable selection by lasso-type methods

    Directory of Open Access Journals (Sweden)

    Sohail Chand

    2011-09-01

    Full Text Available Variable selection is an important property of shrinkage methods. The adaptive lasso is an oracle procedure and can do consistent variable selection. In this paper, we provide an explanation that how use of adaptive weights make it possible for the adaptive lasso to satisfy the necessary and almost sufcient condition for consistent variable selection. We suggest a novel algorithm and give an important result that for the adaptive lasso if predictors are normalised after the introduction of adaptive weights, it makes the adaptive lasso performance identical to the lasso.

  10. Recursive Cluster Elimination (RCE for classification and feature selection from gene expression data

    Directory of Open Access Journals (Sweden)

    Showe Louise C

    2007-05-01

    Full Text Available Abstract Background Classification studies using gene expression datasets are usually based on small numbers of samples and tens of thousands of genes. The selection of those genes that are important for distinguishing the different sample classes being compared, poses a challenging problem in high dimensional data analysis. We describe a new procedure for selecting significant genes as recursive cluster elimination (RCE rather than recursive feature elimination (RFE. We have tested this algorithm on six datasets and compared its performance with that of two related classification procedures with RFE. Results We have developed a novel method for selecting significant genes in comparative gene expression studies. This method, which we refer to as SVM-RCE, combines K-means, a clustering method, to identify correlated gene clusters, and Support Vector Machines (SVMs, a supervised machine learning classification method, to identify and score (rank those gene clusters for the purpose of classification. K-means is used initially to group genes into clusters. Recursive cluster elimination (RCE is then applied to iteratively remove those clusters of genes that contribute the least to the classification performance. SVM-RCE identifies the clusters of correlated genes that are most significantly differentially expressed between the sample classes. Utilization of gene clusters, rather than individual genes, enhances the supervised classification accuracy of the same data as compared to the accuracy when either SVM or Penalized Discriminant Analysis (PDA with recursive feature elimination (SVM-RFE and PDA-RFE are used to remove genes based on their individual discriminant weights. Conclusion SVM-RCE provides improved classification accuracy with complex microarray data sets when it is compared to the classification accuracy of the same datasets using either SVM-RFE or PDA-RFE. SVM-RCE identifies clusters of correlated genes that when considered together

  11. 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.

  12. Combinatorial Pooling Enables Selective Sequencing of the Barley Gene Space

    Science.gov (United States)

    Lonardi, Stefano; Duma, Denisa; Alpert, Matthew; Cordero, Francesca; Beccuti, Marco; Bhat, Prasanna R.; Wu, Yonghui; Ciardo, Gianfranco; Alsaihati, Burair; Ma, Yaqin; Wanamaker, Steve; Resnik, Josh; Bozdag, Serdar; Luo, Ming-Cheng; Close, Timothy J.

    2013-01-01

    For the vast majority of species – including many economically or ecologically important organisms, progress in biological research is hampered due to the lack of a reference genome sequence. Despite recent advances in sequencing technologies, several factors still limit the availability of such a critical resource. At the same time, many research groups and international consortia have already produced BAC libraries and physical maps and now are in a position to proceed with the development of whole-genome sequences organized around a physical map anchored to a genetic map. We propose a BAC-by-BAC sequencing protocol that combines combinatorial pooling design and second-generation sequencing technology to efficiently approach denovo selective genome sequencing. We show that combinatorial pooling is a cost-effective and practical alternative to exhaustive DNA barcoding when preparing sequencing libraries for hundreds or thousands of DNA samples, such as in this case gene-bearing minimum-tiling-path BAC clones. The novelty of the protocol hinges on the computational ability to efficiently compare hundred millions of short reads and assign them to the correct BAC clones (deconvolution) so that the assembly can be carried out clone-by-clone. Experimental results on simulated data for the rice genome show that the deconvolution is very accurate, and the resulting BAC assemblies have high quality. Results on real data for a gene-rich subset of the barley genome confirm that the deconvolution is accurate and the BAC assemblies have good quality. While our method cannot provide the level of completeness that one would achieve with a comprehensive whole-genome sequencing project, we show that it is quite successful in reconstructing the gene sequences within BACs. In the case of plants such as barley, this level of sequence knowledge is sufficient to support critical end-point objectives such as map-based cloning and marker-assisted breeding. PMID:23592960

  13. Combinatorial pooling enables selective sequencing of the barley gene space.

    Directory of Open Access Journals (Sweden)

    Stefano Lonardi

    2013-04-01

    Full Text Available For the vast majority of species - including many economically or ecologically important organisms, progress in biological research is hampered due to the lack of a reference genome sequence. Despite recent advances in sequencing technologies, several factors still limit the availability of such a critical resource. At the same time, many research groups and international consortia have already produced BAC libraries and physical maps and now are in a position to proceed with the development of whole-genome sequences organized around a physical map anchored to a genetic map. We propose a BAC-by-BAC sequencing protocol that combines combinatorial pooling design and second-generation sequencing technology to efficiently approach denovo selective genome sequencing. We show that combinatorial pooling is a cost-effective and practical alternative to exhaustive DNA barcoding when preparing sequencing libraries for hundreds or thousands of DNA samples, such as in this case gene-bearing minimum-tiling-path BAC clones. The novelty of the protocol hinges on the computational ability to efficiently compare hundred millions of short reads and assign them to the correct BAC clones (deconvolution so that the assembly can be carried out clone-by-clone. Experimental results on simulated data for the rice genome show that the deconvolution is very accurate, and the resulting BAC assemblies have high quality. Results on real data for a gene-rich subset of the barley genome confirm that the deconvolution is accurate and the BAC assemblies have good quality. While our method cannot provide the level of completeness that one would achieve with a comprehensive whole-genome sequencing project, we show that it is quite successful in reconstructing the gene sequences within BACs. In the case of plants such as barley, this level of sequence knowledge is sufficient to support critical end-point objectives such as map-based cloning and marker-assisted breeding.

  14. Combinatorial pooling enables selective sequencing of the barley gene space.

    Science.gov (United States)

    Lonardi, Stefano; Duma, Denisa; Alpert, Matthew; Cordero, Francesca; Beccuti, Marco; Bhat, Prasanna R; Wu, Yonghui; Ciardo, Gianfranco; Alsaihati, Burair; Ma, Yaqin; Wanamaker, Steve; Resnik, Josh; Bozdag, Serdar; Luo, Ming-Cheng; Close, Timothy J

    2013-04-01

    For the vast majority of species - including many economically or ecologically important organisms, progress in biological research is hampered due to the lack of a reference genome sequence. Despite recent advances in sequencing technologies, several factors still limit the availability of such a critical resource. At the same time, many research groups and international consortia have already produced BAC libraries and physical maps and now are in a position to proceed with the development of whole-genome sequences organized around a physical map anchored to a genetic map. We propose a BAC-by-BAC sequencing protocol that combines combinatorial pooling design and second-generation sequencing technology to efficiently approach denovo selective genome sequencing. We show that combinatorial pooling is a cost-effective and practical alternative to exhaustive DNA barcoding when preparing sequencing libraries for hundreds or thousands of DNA samples, such as in this case gene-bearing minimum-tiling-path BAC clones. The novelty of the protocol hinges on the computational ability to efficiently compare hundred millions of short reads and assign them to the correct BAC clones (deconvolution) so that the assembly can be carried out clone-by-clone. Experimental results on simulated data for the rice genome show that the deconvolution is very accurate, and the resulting BAC assemblies have high quality. Results on real data for a gene-rich subset of the barley genome confirm that the deconvolution is accurate and the BAC assemblies have good quality. While our method cannot provide the level of completeness that one would achieve with a comprehensive whole-genome sequencing project, we show that it is quite successful in reconstructing the gene sequences within BACs. In the case of plants such as barley, this level of sequence knowledge is sufficient to support critical end-point objectives such as map-based cloning and marker-assisted breeding.

  15. Personnel Selection Based on Fuzzy Methods

    Directory of Open Access Journals (Sweden)

    Lourdes Cañós

    2011-03-01

    Full Text Available The decisions of managers regarding the selection of staff strongly determine the success of the company. A correct choice of employees is a source of competitive advantage. We propose a fuzzy method for staff selection, based on competence management and the comparison with the valuation that the company considers the best in each competence (ideal candidate. Our method is based on the Hamming distance and a Matching Level Index. The algorithms, implemented in the software StaffDesigner, allow us to rank the candidates, even when the competences of the ideal candidate have been evaluated only in part. Our approach is applied in a numerical example.

  16. Selection on meiosis genes in diploid and tetraploid Arabidopsis arenosa.

    Science.gov (United States)

    Wright, Kevin M; Arnold, Brian; Xue, Katherine; Šurinová, Maria; O'Connell, Jeremy; Bomblies, Kirsten

    2015-04-01

    Meiotic chromosome segregation is critical for fertility across eukaryotes, and core meiotic processes are well conserved even between kingdoms. Nevertheless, recent work in animals has shown that at least some meiosis genes are highly diverse or strongly differentiated among populations. What drives this remains largely unknown. We previously showed that autotetraploid Arabidopsis arenosa evolved stable meiosis, likely through reduced crossover rates, and that associated with this there is strong evidence for selection in a subset of meiosis genes known to affect axis formation, synapsis, and crossover frequency. Here, we use genome-wide data to study the molecular evolution of 70 meiosis genes in a much wider sample of A. arenosa. We sample the polyploid lineage, a diploid lineage from the Carpathian Mountains, and a more distantly related diploid lineage from the adjacent, but biogeographically distinct Pannonian Basin. We find that not only did selection act on meiosis genes in the polyploid lineage but also independently on a smaller subset of meiosis genes in Pannonian diploids. Functionally related genes are targeted by selection in these distinct contexts, and in two cases, independent sweeps occurred in the same loci. The tetraploid lineage has sustained selection on more genes, has more amino acid changes in each, and these more often affect conserved or potentially functional sites. We hypothesize that Pannonian diploid and tetraploid A. arenosa experienced selection on structural proteins that mediate sister chromatid cohesion, the formation of meiotic chromosome axes, and synapsis, likely for different underlying reasons. © The Author 2014. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

  17. mRMR-ABC: A Hybrid Gene Selection Algorithm for Cancer Classification Using Microarray Gene Expression Profiling

    Directory of Open Access Journals (Sweden)

    Hala Alshamlan

    2015-01-01

    Full Text Available An artificial bee colony (ABC is a relatively recent swarm intelligence optimization approach. In this paper, we propose the first attempt at applying ABC algorithm in analyzing a microarray gene expression profile. In addition, we propose an innovative feature selection algorithm, minimum redundancy maximum relevance (mRMR, and combine it with an ABC algorithm, mRMR-ABC, to select informative genes from microarray profile. The new approach is based on a support vector machine (SVM algorithm to measure the classification accuracy for selected genes. We evaluate the performance of the proposed mRMR-ABC algorithm by conducting extensive experiments on six binary and multiclass gene expression microarray datasets. Furthermore, we compare our proposed mRMR-ABC algorithm with previously known techniques. We reimplemented two of these techniques for the sake of a fair comparison using the same parameters. These two techniques are mRMR when combined with a genetic algorithm (mRMR-GA and mRMR when combined with a particle swarm optimization algorithm (mRMR-PSO. The experimental results prove that the proposed mRMR-ABC algorithm achieves accurate classification performance using small number of predictive genes when tested using both datasets and compared to previously suggested methods. This shows that mRMR-ABC is a promising approach for solving gene selection and cancer classification problems.

  18. mRMR-ABC: A Hybrid Gene Selection Algorithm for Cancer Classification Using Microarray Gene Expression Profiling.

    Science.gov (United States)

    Alshamlan, Hala; Badr, Ghada; Alohali, Yousef

    2015-01-01

    An artificial bee colony (ABC) is a relatively recent swarm intelligence optimization approach. In this paper, we propose the first attempt at applying ABC algorithm in analyzing a microarray gene expression profile. In addition, we propose an innovative feature selection algorithm, minimum redundancy maximum relevance (mRMR), and combine it with an ABC algorithm, mRMR-ABC, to select informative genes from microarray profile. The new approach is based on a support vector machine (SVM) algorithm to measure the classification accuracy for selected genes. We evaluate the performance of the proposed mRMR-ABC algorithm by conducting extensive experiments on six binary and multiclass gene expression microarray datasets. Furthermore, we compare our proposed mRMR-ABC algorithm with previously known techniques. We reimplemented two of these techniques for the sake of a fair comparison using the same parameters. These two techniques are mRMR when combined with a genetic algorithm (mRMR-GA) and mRMR when combined with a particle swarm optimization algorithm (mRMR-PSO). The experimental results prove that the proposed mRMR-ABC algorithm achieves accurate classification performance using small number of predictive genes when tested using both datasets and compared to previously suggested methods. This shows that mRMR-ABC is a promising approach for solving gene selection and cancer classification problems.

  19. Evaluation of gene importance in microarray data based upon probability of selection

    Directory of Open Access Journals (Sweden)

    Fu Li M

    2005-03-01

    Full Text Available Abstract Background Microarray devices permit a genome-scale evaluation of gene function. This technology has catalyzed biomedical research and development in recent years. As many important diseases can be traced down to the gene level, a long-standing research problem is to identify specific gene expression patterns linking to metabolic characteristics that contribute to disease development and progression. The microarray approach offers an expedited solution to this problem. However, it has posed a challenging issue to recognize disease-related genes expression patterns embedded in the microarray data. In selecting a small set of biologically significant genes for classifier design, the nature of high data dimensionality inherent in this problem creates substantial amount of uncertainty. Results Here we present a model for probability analysis of selected genes in order to determine their importance. Our contribution is that we show how to derive the P value of each selected gene in multiple gene selection trials based on different combinations of data samples and how to conduct a reliability analysis accordingly. The importance of a gene is indicated by its associated P value in that a smaller value implies higher information content from information theory. On the microarray data concerning the subtype classification of small round blue cell tumors, we demonstrate that the method is capable of finding the smallest set of genes (19 genes with optimal classification performance, compared with results reported in the literature. Conclusion In classifier design based on microarray data, the probability value derived from gene selection based on multiple combinations of data samples enables an effective mechanism for reducing the tendency of fitting local data particularities.

  20. Multi-level gene/MiRNA feature selection using deep belief nets and active learning.

    Science.gov (United States)

    Ibrahim, Rania; Yousri, Noha A; Ismail, Mohamed A; El-Makky, Nagwa M

    2014-01-01

    Selecting the most discriminative genes/miRNAs has been raised as an important task in bioinformatics to enhance disease classifiers and to mitigate the dimensionality curse problem. Original feature selection methods choose genes/miRNAs based on their individual features regardless of how they perform together. Considering group features instead of individual ones provides a better view for selecting the most informative genes/miRNAs. Recently, deep learning has proven its ability in representing the data in multiple levels of abstraction, allowing for better discrimination between different classes. However, the idea of using deep learning for feature selection is not widely used in the bioinformatics field yet. In this paper, a novel multi-level feature selection approach named MLFS is proposed for selecting genes/miRNAs based on expression profiles. The approach is based on both deep and active learning. Moreover, an extension to use the technique for miRNAs is presented by considering the biological relation between miRNAs and genes. Experimental results show that the approach was able to outperform classical feature selection methods in hepatocellular carcinoma (HCC) by 9%, lung cancer by 6% and breast cancer by around 10% in F1-measure. Results also show the enhancement in F1-measure of our approach over recently related work in [1] and [2].

  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. Repeated adaptive introgression at a gene under multiallelic balancing selection.

    Directory of Open Access Journals (Sweden)

    Vincent Castric

    2008-08-01

    Full Text Available Recently diverged species typically have incomplete reproductive barriers, allowing introgression of genetic material from one species into the genomic background of the other. The role of natural selection in preventing or promoting introgression remains contentious. Because of genomic co-adaptation, some chromosomal fragments are expected to be selected against in the new background and resist introgression. In contrast, natural selection should favor introgression for alleles at genes evolving under multi-allelic balancing selection, such as the MHC in vertebrates, disease resistance, or self-incompatibility genes in plants. Here, we test the prediction that negative, frequency-dependent selection on alleles at the multi-allelic gene controlling pistil self-incompatibility specificity in two closely related species, Arabidopsis halleri and A. lyrata, caused introgression at this locus at a higher rate than the genomic background. Polymorphism at this gene is largely shared, and we have identified 18 pairs of S-alleles that are only slightly divergent between the two species. For these pairs of S-alleles, divergence at four-fold degenerate sites (K = 0.0193 is about four times lower than the genomic background (K = 0.0743. We demonstrate that this difference cannot be explained by differences in effective population size between the two types of loci. Rather, our data are most consistent with a five-fold increase of introgression rates for S-alleles as compared to the genomic background, making this study the first documented example of adaptive introgression facilitated by balancing selection. We suggest that this process plays an important role in the maintenance of high allelic diversity and divergence at the S-locus in flowering plant families. Because genes under balancing selection are expected to be among the last to stop introgressing, their comparison in closely related species provides a lower-bound estimate of the time since the

  3. A review of methods supporting supplier selection

    NARCIS (Netherlands)

    de Boer, L.; Labro, Eva; Morlacchi, Pierangela

    2001-01-01

    this paper we present a review of decision methods reported in the literature for supporting the supplier selection process. The review is based on an extensive search in the academic literature. We position the contributions in a framework that takes the diversity of procurement situations in terms

  4. Selecting and validating reference genes for quantitative real-time PCR in Plutella xylostella (L.).

    Science.gov (United States)

    You, Yanchun; Xie, Miao; Vasseur, Liette; You, Minsheng

    2018-05-01

    Gene expression analysis provides important clues regarding gene functions, and quantitative real-time PCR (qRT-PCR) is a widely used method in gene expression studies. Reference genes are essential for normalizing and accurately assessing gene expression. In the present study, 16 candidate reference genes (ACTB, CyPA, EF1-α, GAPDH, HSP90, NDPk, RPL13a, RPL18, RPL19, RPL32, RPL4, RPL8, RPS13, RPS4, α-TUB, and β-TUB) from Plutella xylostella were selected to evaluate gene expression stability across different experimental conditions using five statistical algorithms (geNorm, NormFinder, Delta Ct, BestKeeper, and RefFinder). The results suggest that different reference genes or combinations of reference genes are suitable for normalization in gene expression studies of P. xylostella according to the different developmental stages, strains, tissues, and insecticide treatments. Based on the given experimental sets, the most stable reference genes were RPS4 across different developmental stages, RPL8 across different strains and tissues, and EF1-α across different insecticide treatments. A comprehensive and systematic assessment of potential reference genes for gene expression normalization is essential for post-genomic functional research in P. xylostella, a notorious pest with worldwide distribution and a high capacity to adapt and develop resistance to insecticides.

  5. Optimization methods for activities selection problems

    Science.gov (United States)

    Mahad, Nor Faradilah; Alias, Suriana; Yaakop, Siti Zulaika; Arshad, Norul Amanina Mohd; Mazni, Elis Sofia

    2017-08-01

    Co-curriculum activities must be joined by every student in Malaysia and these activities bring a lot of benefits to the students. By joining these activities, the students can learn about the time management and they can developing many useful skills. This project focuses on the selection of co-curriculum activities in secondary school using the optimization methods which are the Analytic Hierarchy Process (AHP) and Zero-One Goal Programming (ZOGP). A secondary school in Negeri Sembilan, Malaysia was chosen as a case study. A set of questionnaires were distributed randomly to calculate the weighted for each activity based on the 3 chosen criteria which are soft skills, interesting activities and performances. The weighted was calculated by using AHP and the results showed that the most important criteria is soft skills. Then, the ZOGP model will be analyzed by using LINGO Software version 15.0. There are two priorities to be considered. The first priority which is to minimize the budget for the activities is achieved since the total budget can be reduced by RM233.00. Therefore, the total budget to implement the selected activities is RM11,195.00. The second priority which is to select the co-curriculum activities is also achieved. The results showed that 9 out of 15 activities were selected. Thus, it can concluded that AHP and ZOGP approach can be used as the optimization methods for activities selection problem.

  6. A dual selection based, targeted gene replacement tool for Magnaporthe grisea and Fusarium oxysporum.

    Science.gov (United States)

    Khang, Chang Hyun; Park, Sook-Young; Lee, Yong-Hwan; Kang, Seogchan

    2005-06-01

    Rapid progress in fungal genome sequencing presents many new opportunities for functional genomic analysis of fungal biology through the systematic mutagenesis of the genes identified through sequencing. However, the lack of efficient tools for targeted gene replacement is a limiting factor for fungal functional genomics, as it often necessitates the screening of a large number of transformants to identify the desired mutant. We developed an efficient method of gene replacement and evaluated factors affecting the efficiency of this method using two plant pathogenic fungi, Magnaporthe grisea and Fusarium oxysporum. This method is based on Agrobacterium tumefaciens-mediated transformation with a mutant allele of the target gene flanked by the herpes simplex virus thymidine kinase (HSVtk) gene as a conditional negative selection marker against ectopic transformants. The HSVtk gene product converts 5-fluoro-2'-deoxyuridine to a compound toxic to diverse fungi. Because ectopic transformants express HSVtk, while gene replacement mutants lack HSVtk, growing transformants on a medium amended with 5-fluoro-2'-deoxyuridine facilitates the identification of targeted mutants by counter-selecting against ectopic transformants. In addition to M. grisea and F. oxysporum, the method and associated vectors are likely to be applicable to manipulating genes in a broad spectrum of fungi, thus potentially serving as an efficient, universal functional genomic tool for harnessing the growing body of fungal genome sequence data to study fungal biology.

  7. Genomic Selection in Plant Breeding: Methods, Models, and Perspectives.

    Science.gov (United States)

    Crossa, José; Pérez-Rodríguez, Paulino; Cuevas, Jaime; Montesinos-López, Osval; Jarquín, Diego; de Los Campos, Gustavo; Burgueño, Juan; González-Camacho, Juan M; Pérez-Elizalde, Sergio; Beyene, Yoseph; Dreisigacker, Susanne; Singh, Ravi; Zhang, Xuecai; Gowda, Manje; Roorkiwal, Manish; Rutkoski, Jessica; Varshney, Rajeev K

    2017-11-01

    Genomic selection (GS) facilitates the rapid selection of superior genotypes and accelerates the breeding cycle. In this review, we discuss the history, principles, and basis of GS and genomic-enabled prediction (GP) as well as the genetics and statistical complexities of GP models, including genomic genotype×environment (G×E) interactions. We also examine the accuracy of GP models and methods for two cereal crops and two legume crops based on random cross-validation. GS applied to maize breeding has shown tangible genetic gains. Based on GP results, we speculate how GS in germplasm enhancement (i.e., prebreeding) programs could accelerate the flow of genes from gene bank accessions to elite lines. Recent advances in hyperspectral image technology could be combined with GS and pedigree-assisted breeding. Copyright © 2017 Elsevier Ltd. All rights reserved.

  8. Construction of human antibody gene libraries and selection of antibodies by phage display.

    Science.gov (United States)

    Frenzel, André; Kügler, Jonas; Wilke, Sonja; Schirrmann, Thomas; Hust, Michael

    2014-01-01

    Antibody phage display is the most commonly used in vitro selection technology and has yielded thousands of useful antibodies for research, diagnostics, and therapy.The prerequisite for successful generation and development of human recombinant antibodies using phage display is the construction of a high-quality antibody gene library. Here, we describe the methods for the construction of human immune and naive scFv gene libraries.The success also depends on the panning strategy for the selection of binders from these libraries. In this article, we describe a panning strategy that is high-throughput compatible and allows parallel selection in microtiter plates.

  9. Genomic consequences of selection on self-incompatibility genes

    DEFF Research Database (Denmark)

    Schierup, Mikkel Heide; Vekemans, Xavier

    2008-01-01

    closely related species. We review recent empirical studies demonstrating these features and relate the empirical findings to theoretical predictions. We show how these features are being exploited in searches for other genes under multi-allelic balancing selection and for inference on recent breakdown...

  10. Sexual selection, genetic conflict, selfish genes, and the atypical patterns of gene expression in spermatogenic cells.

    Science.gov (United States)

    Kleene, Kenneth C

    2005-01-01

    This review proposes that the peculiar patterns of gene expression in spermatogenic cells are the consequence of powerful evolutionary forces known as sexual selection. Sexual selection is generally characterized by intense competition of males for females, an enormous variety of the strategies to maximize male reproductive success, exaggerated male traits at all levels of biological organization, co-evolution of sexual traits in males and females, and conflict between the sexual advantage of the male trait and the reproductive fitness of females and the individual fitness of both sexes. In addition, spermatogenesis is afflicted by selfish genes that promote their transmission to progeny while causing deleterious effects. Sexual selection, selfish genes, and genetic conflict provide compelling explanations for many atypical features of gene expression in spermatogenic cells including the gross overexpression of certain mRNAs, transcripts encoding truncated proteins that cannot carry out basic functions of the proteins encoded by the same genes in somatic cells, the large number of gene families containing paralogous genes encoding spermatogenic cell-specific isoforms, the large number of testis-cancer-associated genes that are expressed only in spermatogenic cells and malignant cells, and the overbearing role of Sertoli cells in regulating the number and quality of spermatozoa.

  11. Reference gene selection for quantitative gene expression studies during biological invasions: A test on multiple genes and tissues in a model ascidian Ciona savignyi.

    Science.gov (United States)

    Huang, Xuena; Gao, Yangchun; Jiang, Bei; Zhou, Zunchun; Zhan, Aibin

    2016-01-15

    As invasive species have successfully colonized a wide range of dramatically different local environments, they offer a good opportunity to study interactions between species and rapidly changing environments. Gene expression represents one of the primary and crucial mechanisms for rapid adaptation to local environments. Here, we aim to select reference genes for quantitative gene expression analysis based on quantitative Real-Time PCR (qRT-PCR) for a model invasive ascidian, Ciona savignyi. We analyzed the stability of ten candidate reference genes in three tissues (siphon, pharynx and intestine) under two key environmental stresses (temperature and salinity) in the marine realm based on three programs (geNorm, NormFinder and delta Ct method). Our results demonstrated only minor difference for stability rankings among the three methods. The use of different single reference gene might influence the data interpretation, while multiple reference genes could minimize possible errors. Therefore, reference gene combinations were recommended for different tissues - the optimal reference gene combination for siphon was RPS15 and RPL17 under temperature stress, and RPL17, UBQ and TubA under salinity treatment; for pharynx, TubB, TubA and RPL17 were the most stable genes under temperature stress, while TubB, TubA and UBQ were the best under salinity stress; for intestine, UBQ, RPS15 and RPL17 were the most reliable reference genes under both treatments. Our results suggest that the necessity of selection and test of reference genes for different tissues under varying environmental stresses. The results obtained here are expected to reveal mechanisms of gene expression-mediated invasion success using C. savignyi as a model species. Copyright © 2015 Elsevier B.V. All rights reserved.

  12. Supplier Selection Using Weighted Utility Additive Method

    Science.gov (United States)

    Karande, Prasad; Chakraborty, Shankar

    2015-10-01

    Supplier selection is a multi-criteria decision-making (MCDM) problem which mainly involves evaluating a number of available suppliers according to a set of common criteria for choosing the best one to meet the organizational needs. For any manufacturing or service organization, selecting the right upstream suppliers is a key success factor that will significantly reduce purchasing cost, increase downstream customer satisfaction and improve competitive ability. The past researchers have attempted to solve the supplier selection problem employing different MCDM techniques which involve active participation of the decision makers in the decision-making process. This paper deals with the application of weighted utility additive (WUTA) method for solving supplier selection problems. The WUTA method, an extension of utility additive approach, is based on ordinal regression and consists of building a piece-wise linear additive decision model from a preference structure using linear programming (LP). It adopts preference disaggregation principle and addresses the decision-making activities through operational models which need implicit preferences in the form of a preorder of reference alternatives or a subset of these alternatives present in the process. The preferential preorder provided by the decision maker is used as a restriction of a LP problem, which has its own objective function, minimization of the sum of the errors associated with the ranking of each alternative. Based on a given reference ranking of alternatives, one or more additive utility functions are derived. Using these utility functions, the weighted utilities for individual criterion values are combined into an overall weighted utility for a given alternative. It is observed that WUTA method, having a sound mathematical background, can provide accurate ranking to the candidate suppliers and choose the best one to fulfill the organizational requirements. Two real time examples are illustrated to prove

  13. Selection of reference genes for gene expression studies in heart failure for left and right ventricles.

    Science.gov (United States)

    Li, Mengmeng; Rao, Man; Chen, Kai; Zhou, Jianye; Song, Jiangping

    2017-07-15

    Real-time quantitative reverse transcriptase-PCR (qRT-PCR) is a feasible tool for determining gene expression profiles, but the accuracy and reliability of the results depends on the stable expression of selected housekeeping genes in different samples. By far, researches on stable housekeeping genes in human heart failure samples are rare. Moreover the effect of heart failure on the expression of housekeeping genes in right and left ventricles is yet to be studied. Therefore we aim to provide stable housekeeping genes for both ventricles in heart failure and normal heart samples. In this study, we selected seven commonly used housekeeping genes as candidates. By using the qRT-PCR, the expression levels of ACTB, RAB7A, GAPDH, REEP5, RPL5, PSMB4 and VCP in eight heart failure and four normal heart samples were assessed. The stability of candidate housekeeping genes was evaluated by geNorm and Normfinder softwares. GAPDH showed the least variation in all heart samples. Results also indicated the difference of gene expression existed in heart failure left and right ventricles. GAPDH had the highest expression stability in both heart failure and normal heart samples. We also propose using different sets of housekeeping genes for left and right ventricles respectively. The combination of RPL5, GAPDH and PSMB4 is suitable for the right ventricle and the combination of GAPDH, REEP5 and RAB7A is suitable for the left ventricle. Copyright © 2017 Elsevier B.V. All rights reserved.

  14. Method for hydrometallurgical recovery of selected metals

    International Nuclear Information System (INIS)

    Lorenz, G.; Schaefer, B.; Balzat, W.

    1988-01-01

    The method for hydrometallurgical recovery of selected metals refers to ore dressing by means of milling and alkaline leaching of metals, preferably uranium. By adding CaO during wet milling, Na + or K + ions of clayey ores are replaced by Ca 2+ ions. Due to the ion exchange processes, the uranium bonded with clays becomes more accessible to the leaching solution. The uranium yield increases and the consumption of reagents decreases

  15. Global patterns of diversity and selection in human tyrosinase gene.

    Science.gov (United States)

    Hudjashov, Georgi; Villems, Richard; Kivisild, Toomas

    2013-01-01

    Global variation in skin pigmentation is one of the most striking examples of environmental adaptation in humans. More than two hundred loci have been identified as candidate genes in model organisms and a few tens of these have been found to be significantly associated with human skin pigmentation in genome-wide association studies. However, the evolutionary history of different pigmentation genes is rather complex: some loci have been subjected to strong positive selection, while others evolved under the relaxation of functional constraints in low UV environment. Here we report the results of a global study of the human tyrosinase gene, which is one of the key enzymes in melanin production, to assess the role of its variation in the evolution of skin pigmentation differences among human populations. We observe a higher rate of non-synonymous polymorphisms in the European sample consistent with the relaxation of selective constraints. A similar pattern was previously observed in the MC1R gene and concurs with UV radiation-driven model of skin color evolution by which mutations leading to lower melanin levels and decreased photoprotection are subject to purifying selection at low latitudes while being tolerated or even favored at higher latitudes because they facilitate UV-dependent vitamin D production. Our coalescent date estimates suggest that the non-synonymous variants, which are frequent in Europe and North Africa, are recent and have emerged after the separation of East and West Eurasian populations.

  16. Niewirusowy transfer genów do komórek skóry – wybrane metody = Non-viral gene transfer into skin cells – selected methods

    Directory of Open Access Journals (Sweden)

    Ewelina Wędrowska

    2016-01-01

    . Therefore, there is an urgent need for alternative, non-viral methods of gene transfer. Aim of the study: To present methods for non-viral gene transfer used in gene therapy of skin diseases. Short description of knowledge state: Gene therapy for skin diseases include the usage of plasmid vectors as a carrier for therapeutic genes and different methods for their delivery into cells such as: electroporation, microinjection, sonication, lipid carriers and cationic polymers. Summary: Non-viral gene transfer methods offer some advantages including lower toxicity, non-infectious properties, ease of production and low costs as compared to viral techniques. Non-viral approaches are the promising tool in gene therapy of skin diseases, in particular in skin cancer ceases.   Key words: plasmids, gene transfer, skin, viruses, gene therapy.

  17. Genetic signature of strong recent positive selection at interleukin-32 gene in goat

    Directory of Open Access Journals (Sweden)

    Akhtar Rasool Asif

    2017-07-01

    Full Text Available Objective Identification of the candidate genes that play key roles in phenotypic variations can provide new information about evolution and positive selection. Interleukin (IL-32 is involved in many biological processes, however, its role for the immune response against various diseases in mammals is poorly understood. Therefore, the current investigation was performed for the better understanding of the molecular evolution and the positive selection of single nucleotide polymorphisms in IL-32 gene. Methods By using fixation index (FST based method, IL-32 (9375 gene was found to be outlier and under significant positive selection with the provisional combined allocation of mean heterozygosity and FST. Using nucleotide sequences of 11 mammalian species from National Center for Biotechnology Information database, the evolutionary selection of IL-32 gene was determined using Maximum likelihood model method, through four models (M1a, M2a, M7, and M8 in Codeml program of phylogenetic analysis by maximum liklihood. Results IL-32 is detected under positive selection using the FST simulations method. The phylogenetic tree revealed that goat IL-32 was in close resemblance with sheep IL-32. The coding nucleotide sequences were compared among 11 species and it was found that the goat IL-32 gene shared identity with sheep (96.54%, bison (91.97%, camel (58.39%, cat (56.59%, buffalo (56.50%, human (56.13%, dog (50.97%, horse (54.04%, and rabbit (53.41% respectively. Conclusion This study provides evidence for IL-32 gene as under significant positive selection in goat.

  18. A comparative study of covariance selection models for the inference of gene regulatory networks.

    Science.gov (United States)

    Stifanelli, Patrizia F; Creanza, Teresa M; Anglani, Roberto; Liuzzi, Vania C; Mukherjee, Sayan; Schena, Francesco P; Ancona, Nicola

    2013-10-01

    The inference, or 'reverse-engineering', of gene regulatory networks from expression data and the description of the complex dependency structures among genes are open issues in modern molecular biology. In this paper we compared three regularized methods of covariance selection for the inference of gene regulatory networks, developed to circumvent the problems raising when the number of observations n is smaller than the number of genes p. The examined approaches provided three alternative estimates of the inverse covariance matrix: (a) the 'PINV' method is based on the Moore-Penrose pseudoinverse, (b) the 'RCM' method performs correlation between regression residuals and (c) 'ℓ(2C)' method maximizes a properly regularized log-likelihood function. Our extensive simulation studies showed that ℓ(2C) outperformed the other two methods having the most predictive partial correlation estimates and the highest values of sensitivity to infer conditional dependencies between genes even when a few number of observations was available. The application of this method for inferring gene networks of the isoprenoid biosynthesis pathways in Arabidopsis thaliana allowed to enlighten a negative partial correlation coefficient between the two hubs in the two isoprenoid pathways and, more importantly, provided an evidence of cross-talk between genes in the plastidial and the cytosolic pathways. When applied to gene expression data relative to a signature of HRAS oncogene in human cell cultures, the method revealed 9 genes (p-value<0.0005) directly interacting with HRAS, sharing the same Ras-responsive binding site for the transcription factor RREB1. This result suggests that the transcriptional activation of these genes is mediated by a common transcription factor downstream of Ras signaling. Software implementing the methods in the form of Matlab scripts are available at: http://users.ba.cnr.it/issia/iesina18/CovSelModelsCodes.zip. Copyright © 2013 The Authors. Published by

  19. Feature Genes Selection Using Supervised Locally Linear Embedding and Correlation Coefficient for Microarray Classification.

    Science.gov (United States)

    Xu, Jiucheng; Mu, Huiyu; Wang, Yun; Huang, Fangzhou

    2018-01-01

    The selection of feature genes with high recognition ability from the gene expression profiles has gained great significance in biology. However, most of the existing methods have a high time complexity and poor classification performance. Motivated by this, an effective feature selection method, called supervised locally linear embedding and Spearman's rank correlation coefficient (SLLE-SC 2 ), is proposed which is based on the concept of locally linear embedding and correlation coefficient algorithms. Supervised locally linear embedding takes into account class label information and improves the classification performance. Furthermore, Spearman's rank correlation coefficient is used to remove the coexpression genes. The experiment results obtained on four public tumor microarray datasets illustrate that our method is valid and feasible.

  20. Sexual selection and magic traits in speciation with gene flow

    Directory of Open Access Journals (Sweden)

    Maria R. SERVEDIO, Michael KOPP

    2012-06-01

    Full Text Available The extent to which sexual selection is involved in speciation with gene flow remains an open question and the subject of much research. Here, we propose that some insight can be gained from considering the concept of magic traits (i.e., traits involved in both reproductive isolation and ecological divergence. Both magic traits and other, “non-magic”, traits can contribute to speciation via a number of specific mechanisms. We argue that many of these mechanisms are likely to differ widely in the extent to which they involve sexual selection. Furthermore, in some cases where sexual selection is present, it may be prone to inhibit rather than drive speciation. Finally, there are a priori reasons to believe that certain categories of traits are much more effective than others in driving speciation. The combination of these points suggests a classification of traits that may shed light on the broader role of sexual selection in speciation with gene flow. In particular, we suggest that sexual selection can act as a driver of speciation in some scenarios, but may play a negligible role in potentially common categories of magic traits, and may be likely to inhibit speciation in common categories of non-magic traits [Current Zoology 58 (3: 507–513, 2012].

  1. 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.

  2. LCIA selection methods for assessing toxic releases

    DEFF Research Database (Denmark)

    Larsen, Henrik Fred; Birkved, Morten; Hauschild, Michael Zwicky

    2002-01-01

    the inventory that contribute significantly to the impact categories on ecotoxicity and human toxicity to focus the characterisation work. The reason why the selection methods are more important for the chemical-related impact categories than for other impact categories is the extremely high number......Characterization of toxic emissions in life cycle impact assessment (LCIA) is in many cases severely limited by the lack of characterization factors for the emissions mapped in the inventory. The number of substances assigned characterization factors for (eco)toxicity included in the dominating LCA....... The methods are evaluated against a set of pre-defined criteria (comprising consistency with characterization and data requirement) and applied to case studies and a test set of chemicals. The reported work is part of the EU-project OMNIITOX....

  3. Selection of Highly Expressed Gene Variants in Escherichia coli Using Translationally Coupled Antibiotic Selection Markers

    DEFF Research Database (Denmark)

    Rennig, Maja; Daley, Daniel O.; Nørholm, Morten H. H.

    2018-01-01

    Strategies to select highly expressed variants of a protein coding sequence are usually based on trial-and-error approaches, which are time-consuming and expensive. We address this problem using translationally coupled antibiotic resistance markers. The system requires that the target gene can...

  4. Altering the selection capabilities of common cloning vectors via restriction enzyme mediated gene disruption

    Science.gov (United States)

    2013-01-01

    Background The cloning of gene sequences forms the basis for many molecular biological studies. One important step in the cloning process is the isolation of bacterial transformants carrying vector DNA. This involves a vector-encoded selectable marker gene, which in most cases, confers resistance to an antibiotic. However, there are a number of circumstances in which a different selectable marker is required or may be preferable. Such situations can include restrictions to host strain choice, two phase cloning experiments and mutagenesis experiments, issues that result in additional unnecessary cloning steps, in which the DNA needs to be subcloned into a vector with a suitable selectable marker. Results We have used restriction enzyme mediated gene disruption to modify the selectable marker gene of a given vector by cloning a different selectable marker gene into the original marker present in that vector. Cloning a new selectable marker into a pre-existing marker was found to change the selection phenotype conferred by that vector, which we were able to demonstrate using multiple commonly used vectors and multiple resistance markers. This methodology was also successfully applied not only to cloning vectors, but also to expression vectors while keeping the expression characteristics of the vector unaltered. Conclusions Changing the selectable marker of a given vector has a number of advantages and applications. This rapid and efficient method could be used for co-expression of recombinant proteins, optimisation of two phase cloning procedures, as well as multiple genetic manipulations within the same host strain without the need to remove a pre-existing selectable marker in a previously genetically modified strain. PMID:23497512

  5. The Integrative Method Based on the Module-Network for Identifying Driver Genes in Cancer Subtypes

    Directory of Open Access Journals (Sweden)

    Xinguo Lu

    2018-01-01

    Full Text Available With advances in next-generation sequencing(NGS technologies, a large number of multiple types of high-throughput genomics data are available. A great challenge in exploring cancer progression is to identify the driver genes from the variant genes by analyzing and integrating multi-types genomics data. Breast cancer is known as a heterogeneous disease. The identification of subtype-specific driver genes is critical to guide the diagnosis, assessment of prognosis and treatment of breast cancer. We developed an integrated frame based on gene expression profiles and copy number variation (CNV data to identify breast cancer subtype-specific driver genes. In this frame, we employed statistical machine-learning method to select gene subsets and utilized an module-network analysis method to identify potential candidate driver genes. The final subtype-specific driver genes were acquired by paired-wise comparison in subtypes. To validate specificity of the driver genes, the gene expression data of these genes were applied to classify the patient samples with 10-fold cross validation and the enrichment analysis were also conducted on the identified driver genes. The experimental results show that the proposed integrative method can identify the potential driver genes and the classifier with these genes acquired better performance than with genes identified by other methods.

  6. Positive selection on MHC class II DRB and DQB genes in the bank vole (Myodes glareolus).

    Science.gov (United States)

    Scherman, Kristin; Råberg, Lars; Westerdahl, Helena

    2014-05-01

    The major histocompatibility complex (MHC) class IIB genes show considerable sequence similarity between loci. The MHC class II DQB and DRB genes are known to exhibit a high level of polymorphism, most likely maintained by parasite-mediated selection. Studies of the MHC in wild rodents have focused on DRB, whilst DQB has been given much less attention. Here, we characterised DQB genes in Swedish bank voles Myodes glareolus, using full-length transcripts. We then designed primers that specifically amplify exon 2 from DRB (202 bp) and DQB (205 bp) and investigated molecular signatures of natural selection on DRB and DQB alleles. The presence of two separate gene clusters was confirmed using BLASTN and phylogenetic analysis, where our seven transcripts clustered according to either DQB or DRB homologues. These gene clusters were again confirmed on exon 2 data from 454-amplicon sequencing. Our DRB primers amplify a similar number of alleles per individual as previously published DRB primers, though our reads are longer. Traditional d N/d S analyses of DRB sequences in the bank vole have not found a conclusive signal of positive selection. Using a more advanced substitution model (the Kumar method) we found positive selection in the peptide binding region (PBR) of both DRB and DQB genes. Maximum likelihood models of codon substitutions detected positively selected sites located in the PBR of both DQB and DRB. Interestingly, these analyses detected at least twice as many positively selected sites in DQB than DRB, suggesting that DQB has been under stronger positive selection than DRB over evolutionary time.

  7. A review for detecting gene-gene interactions using machine learning methods in genetic epidemiology.

    Science.gov (United States)

    Koo, Ching Lee; Liew, Mei Jing; Mohamad, Mohd Saberi; Salleh, Abdul Hakim Mohamed

    2013-01-01

    Recently, the greatest statistical computational challenge in genetic epidemiology is to identify and characterize the genes that interact with other genes and environment factors that bring the effect on complex multifactorial disease. These gene-gene interactions are also denoted as epitasis in which this phenomenon cannot be solved by traditional statistical method due to the high dimensionality of the data and the occurrence of multiple polymorphism. Hence, there are several machine learning methods to solve such problems by identifying such susceptibility gene which are neural networks (NNs), support vector machine (SVM), and random forests (RFs) in such common and multifactorial disease. This paper gives an overview on machine learning methods, describing the methodology of each machine learning methods and its application in detecting gene-gene and gene-environment interactions. Lastly, this paper discussed each machine learning method and presents the strengths and weaknesses of each machine learning method in detecting gene-gene interactions in complex human disease.

  8. Cytogenetic analysis and mapping of leaf rust resistance in Aegilops speltoides Tausch derived bread wheat line Selection2427 carrying putative gametocidal gene(s).

    Science.gov (United States)

    Niranjana, M; Vinod; Sharma, J B; Mallick, Niharika; Tomar, S M S; Jha, S K

    2017-12-01

    Leaf rust (Puccinia triticina) is a major biotic stress affecting wheat yields worldwide. Host-plant resistance is the best method for controlling leaf rust. Aegilops speltoides is a good source of resistance against wheat rusts. To date, five Lr genes, Lr28, Lr35, Lr36, Lr47, and Lr51, have been transferred from Ae. speltoides to bread wheat. In Selection2427, a bread wheat introgresed line with Ae. speltoides as the donor parent, a dominant gene for leaf rust resistance was mapped to the long arm of chromosome 3B (LrS2427). None of the Lr genes introgressed from Ae. speltoides have been mapped to chromosome 3B. Since none of the designated seedling leaf rust resistance genes have been located on chromosome 3B, LrS2427 seems to be a novel gene. Selection2427 showed a unique property typical of gametocidal genes, that when crossed to other bread wheat cultivars, the F 1 showed partial pollen sterility and poor seed setting, whilst Selection2427 showed reasonable male and female fertility. Accidental co-transfer of gametocidal genes with LrS2427 may have occurred in Selection2427. Though LrS2427 did not show any segregation distortion and assorted independently of putative gametocidal gene(s), its utilization will be difficult due to the selfish behavior of gametocidal genes.

  9. Gene expression network reconstruction by convex feature selection when incorporating genetic perturbations.

    Directory of Open Access Journals (Sweden)

    Benjamin A Logsdon

    Full Text Available Cellular gene expression measurements contain regulatory information that can be used to discover novel network relationships. Here, we present a new algorithm for network reconstruction powered by the adaptive lasso, a theoretically and empirically well-behaved method for selecting the regulatory features of a network. Any algorithms designed for network discovery that make use of directed probabilistic graphs require perturbations, produced by either experiments or naturally occurring genetic variation, to successfully infer unique regulatory relationships from gene expression data. Our approach makes use of appropriately selected cis-expression Quantitative Trait Loci (cis-eQTL, which provide a sufficient set of independent perturbations for maximum network resolution. We compare the performance of our network reconstruction algorithm to four other approaches: the PC-algorithm, QTLnet, the QDG algorithm, and the NEO algorithm, all of which have been used to reconstruct directed networks among phenotypes leveraging QTL. We show that the adaptive lasso can outperform these algorithms for networks of ten genes and ten cis-eQTL, and is competitive with the QDG algorithm for networks with thirty genes and thirty cis-eQTL, with rich topologies and hundreds of samples. Using this novel approach, we identify unique sets of directed relationships in Saccharomyces cerevisiae when analyzing genome-wide gene expression data for an intercross between a wild strain and a lab strain. We recover novel putative network relationships between a tyrosine biosynthesis gene (TYR1, and genes involved in endocytosis (RCY1, the spindle checkpoint (BUB2, sulfonate catabolism (JLP1, and cell-cell communication (PRM7. Our algorithm provides a synthesis of feature selection methods and graphical model theory that has the potential to reveal new directed regulatory relationships from the analysis of population level genetic and gene expression data.

  10. Location of airports - selected quantitative methods

    Directory of Open Access Journals (Sweden)

    Agnieszka Merkisz-Guranowska

    2016-09-01

    Full Text Available Background: The role of air transport in  the economic development of a country and its regions cannot be overestimated. The decision concerning an airport's location must be in line with the expectations of all the stakeholders involved. This article deals with the issues related to the choice of  sites where airports should be located. Methods: Two main quantitative approaches related to the issue of airport location are presented in this article, i.e. the question of optimizing such a choice and the issue of selecting the location from a predefined set. The former involves mathematical programming and formulating the problem as an optimization task, the latter, however, involves ranking the possible variations. Due to various methodological backgrounds, the authors present the advantages and disadvantages of both approaches and point to the one which currently has its own practical application. Results: Based on real-life examples, the authors present a multi-stage procedure, which renders it possible to solve the problem of airport location. Conclusions: Based on the overview of literature of the subject, the authors point to three types of approach to the issue of airport location which could enable further development of currently applied methods.

  11. Evidence for natural selection at the melanocortin-3 receptor gene in European and African populations.

    Science.gov (United States)

    Yoshiuchi, Issei

    2016-08-01

    Obesity is increasing steadily in worldwide prevalence and is known to cause serious health problems in association with type 2 diabetes mellitus (T2DM), including hypertension, stroke, and cardiovascular diseases. According to the thrifty gene hypothesis, the natural selection of obesity-related genes is important during feast and famine because they control body weight and fat levels. Past human adaptations to environmental changes in food supply, lifestyle, and geography may have influenced the selection of genes associated with the metabolism of glucose, lipids, and energy. The melanocortin-3 receptor gene (MC3R) is associated with obesity, with MC3R-deficient mice showing increased fat mass. MC3R variations are also linked with childhood obesity and insulin resistance. Here, we aimed to uncover evidence of selection at MC3R. We performed a three-step method to detect selection at MC3R using HapMap population data. We used Wright's F statistics as a measure of population differentiation, the long-range haplotype test to identify extended haplotypes, and the integrated haplotype score (iHS) to detect selection at MC3R. We observed high population differentiation between European and African populations at two MC3R childhood obesity- and insulin resistance-associated single-nucleotide polymorphisms (rs3746619 and rs3827103) using Wright's F statistics. The iHS revealed evidence of natural selection at MC3R. These findings provide evidence for natural selection at MC3R. Further investigation is warranted into adaptive evolution at T2DM- and obesity-associated genes.

  12. Selection of Suitable Endogenous Reference Genes for Relative Copy Number Detection in Sugarcane

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    Bantong Xue

    2014-05-01

    Full Text Available Transgene copy number has a great impact on the expression level and stability of exogenous gene in transgenic plants. Proper selection of endogenous reference genes is necessary for detection of genetic components in genetically modification (GM crops by quantitative real-time PCR (qPCR or by qualitative PCR approach, especially in sugarcane with polyploid and aneuploid genomic structure. qPCR technique has been widely accepted as an accurate, time-saving method on determination of copy numbers in transgenic plants and on detection of genetically modified plants to meet the regulatory and legislative requirement. In this study, to find a suitable endogenous reference gene and its real-time PCR assay for sugarcane (Saccharum spp. hybrids DNA content quantification, we evaluated a set of potential “single copy” genes including P4H, APRT, ENOL, CYC, TST and PRR, through qualitative PCR and absolute quantitative PCR. Based on copy number comparisons among different sugarcane genotypes, including five S. officinarum, one S. spontaneum and two S. spp. hybrids, these endogenous genes fell into three groups: ENOL-3—high copy number group, TST-1 and PRR-1—medium copy number group, P4H-1, APRT-2 and CYC-2—low copy number group. Among these tested genes, P4H, APRT and CYC were the most stable, while ENOL and TST were the least stable across different sugarcane genotypes. Therefore, three primer pairs of P4H-3, APRT-2 and CYC-2 were then selected as the suitable reference gene primer pairs for sugarcane. The test of multi-target reference genes revealed that the APRT gene was a specific amplicon, suggesting this gene is the most suitable to be used as an endogenous reference target for sugarcane DNA content quantification. These results should be helpful for establishing accurate and reliable qualitative and quantitative PCR analysis of GM sugarcane.

  13. Transcriptome sequencing and positive selected genes analysis of Bombyx mandarina.

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    Tingcai Cheng

    Full Text Available The wild silkworm Bombyx mandarina is widely believed to be an ancestor of the domesticated silkworm, Bombyx mori. Silkworms are often used as a model for studying the mechanism of species domestication. Here, we performed transcriptome sequencing of the wild silkworm using an Illumina HiSeq2000 platform. We produced 100,004,078 high-quality reads and assembled them into 50,773 contigs with an N50 length of 1764 bp and a mean length of 941.62 bp. A total of 33,759 unigenes were identified, with 12,805 annotated in the Nr database, 8273 in the Pfam database, and 9093 in the Swiss-Prot database. Expression profile analysis found significant differential expression of 1308 unigenes between the middle silk gland (MSG and posterior silk gland (PSG. Three sericin genes (sericin 1, sericin 2, and sericin 3 were expressed specifically in the MSG and three fibroin genes (fibroin-H, fibroin-L, and fibroin/P25 were expressed specifically in the PSG. In addition, 32,297 Single-nucleotide polymorphisms (SNPs and 361 insertion-deletions (INDELs were detected. Comparison with the domesticated silkworm p50/Dazao identified 5,295 orthologous genes, among which 400 might have experienced or to be experiencing positive selection by Ka/Ks analysis. These data and analyses presented here provide insights into silkworm domestication and an invaluable resource for wild silkworm genomics research.

  14. 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.

  15. A hybrid computational method for the discovery of novel reproduction-related genes.

    Science.gov (United States)

    Chen, Lei; Chu, Chen; Kong, Xiangyin; Huang, Guohua; Huang, Tao; Cai, Yu-Dong

    2015-01-01

    Uncovering the molecular mechanisms underlying reproduction is of great importance to infertility treatment and to the generation of healthy offspring. In this study, we discovered novel reproduction-related genes with a hybrid computational method, integrating three different types of method, which offered new clues for further reproduction research. This method was first executed on a weighted graph, constructed based on known protein-protein interactions, to search the shortest paths connecting any two known reproduction-related genes. Genes occurring in these paths were deemed to have a special relationship with reproduction. These newly discovered genes were filtered with a randomization test. Then, the remaining genes were further selected according to their associations with known reproduction-related genes measured by protein-protein interaction score and alignment score obtained by BLAST. The in-depth analysis of the high confidence novel reproduction genes revealed hidden mechanisms of reproduction and provided guidelines for further experimental validations.

  16. Genes under positive selection in a model plant pathogenic fungus, Botrytis.

    Science.gov (United States)

    Aguileta, Gabriela; Lengelle, Juliette; Chiapello, Hélène; Giraud, Tatiana; Viaud, Muriel; Fournier, Elisabeth; Rodolphe, François; Marthey, Sylvain; Ducasse, Aurélie; Gendrault, Annie; Poulain, Julie; Wincker, Patrick; Gout, Lilian

    2012-07-01

    The rapid evolution of particular genes is essential for the adaptation of pathogens to new hosts and new environments. Powerful methods have been developed for detecting targets of selection in the genome. Here we used divergence data to compare genes among four closely related fungal pathogens adapted to different hosts to elucidate the functions putatively involved in adaptive processes. For this goal, ESTs were sequenced in the specialist fungal pathogens Botrytis tulipae and Botrytis ficariarum, and compared with genome sequences of Botrytis cinerea and Sclerotinia sclerotiorum, responsible for diseases on over 200 plant species. A maximum likelihood-based analysis of 642 predicted orthologs detected 21 genes showing footprints of positive selection. These results were validated by resequencing nine of these genes in additional Botrytis species, showing they have also been rapidly evolving in other related species. Twenty of the 21 genes had not previously been identified as pathogenicity factors in B. cinerea, but some had functions related to plant-fungus interactions. The putative functions were involved in respiratory and energy metabolism, protein and RNA metabolism, signal transduction or virulence, similarly to what was detected in previous studies using the same approach in other pathogens. Mutants of B. cinerea were generated for four of these genes as a first attempt to elucidate their functions. Copyright © 2012 Elsevier B.V. All rights reserved.

  17. When is hub gene selection better than standard meta-analysis?

    Science.gov (United States)

    Langfelder, Peter; Mischel, Paul S; Horvath, Steve

    2013-01-01

    Since hub nodes have been found to play important roles in many networks, highly connected hub genes are expected to play an important role in biology as well. However, the empirical evidence remains ambiguous. An open question is whether (or when) hub gene selection leads to more meaningful gene lists than a standard statistical analysis based on significance testing when analyzing genomic data sets (e.g., gene expression or DNA methylation data). Here we address this question for the special case when multiple genomic data sets are available. This is of great practical importance since for many research questions multiple data sets are publicly available. In this case, the data analyst can decide between a standard statistical approach (e.g., based on meta-analysis) and a co-expression network analysis approach that selects intramodular hubs in consensus modules. We assess the performance of these two types of approaches according to two criteria. The first criterion evaluates the biological insights gained and is relevant in basic research. The second criterion evaluates the validation success (reproducibility) in independent data sets and often applies in clinical diagnostic or prognostic applications. We compare meta-analysis with consensus network analysis based on weighted correlation network analysis (WGCNA) in three comprehensive and unbiased empirical studies: (1) Finding genes predictive of lung cancer survival, (2) finding methylation markers related to age, and (3) finding mouse genes related to total cholesterol. The results demonstrate that intramodular hub gene status with respect to consensus modules is more useful than a meta-analysis p-value when identifying biologically meaningful gene lists (reflecting criterion 1). However, standard meta-analysis methods perform as good as (if not better than) a consensus network approach in terms of validation success (criterion 2). The article also reports a comparison of meta-analysis techniques applied to

  18. When Is Hub Gene Selection Better than Standard Meta-Analysis?

    Science.gov (United States)

    Langfelder, Peter; Mischel, Paul S.; Horvath, Steve

    2013-01-01

    Since hub nodes have been found to play important roles in many networks, highly connected hub genes are expected to play an important role in biology as well. However, the empirical evidence remains ambiguous. An open question is whether (or when) hub gene selection leads to more meaningful gene lists than a standard statistical analysis based on significance testing when analyzing genomic data sets (e.g., gene expression or DNA methylation data). Here we address this question for the special case when multiple genomic data sets are available. This is of great practical importance since for many research questions multiple data sets are publicly available. In this case, the data analyst can decide between a standard statistical approach (e.g., based on meta-analysis) and a co-expression network analysis approach that selects intramodular hubs in consensus modules. We assess the performance of these two types of approaches according to two criteria. The first criterion evaluates the biological insights gained and is relevant in basic research. The second criterion evaluates the validation success (reproducibility) in independent data sets and often applies in clinical diagnostic or prognostic applications. We compare meta-analysis with consensus network analysis based on weighted correlation network analysis (WGCNA) in three comprehensive and unbiased empirical studies: (1) Finding genes predictive of lung cancer survival, (2) finding methylation markers related to age, and (3) finding mouse genes related to total cholesterol. The results demonstrate that intramodular hub gene status with respect to consensus modules is more useful than a meta-analysis p-value when identifying biologically meaningful gene lists (reflecting criterion 1). However, standard meta-analysis methods perform as good as (if not better than) a consensus network approach in terms of validation success (criterion 2). The article also reports a comparison of meta-analysis techniques applied to

  19. When is hub gene selection better than standard meta-analysis?

    Directory of Open Access Journals (Sweden)

    Peter Langfelder

    Full Text Available Since hub nodes have been found to play important roles in many networks, highly connected hub genes are expected to play an important role in biology as well. However, the empirical evidence remains ambiguous. An open question is whether (or when hub gene selection leads to more meaningful gene lists than a standard statistical analysis based on significance testing when analyzing genomic data sets (e.g., gene expression or DNA methylation data. Here we address this question for the special case when multiple genomic data sets are available. This is of great practical importance since for many research questions multiple data sets are publicly available. In this case, the data analyst can decide between a standard statistical approach (e.g., based on meta-analysis and a co-expression network analysis approach that selects intramodular hubs in consensus modules. We assess the performance of these two types of approaches according to two criteria. The first criterion evaluates the biological insights gained and is relevant in basic research. The second criterion evaluates the validation success (reproducibility in independent data sets and often applies in clinical diagnostic or prognostic applications. We compare meta-analysis with consensus network analysis based on weighted correlation network analysis (WGCNA in three comprehensive and unbiased empirical studies: (1 Finding genes predictive of lung cancer survival, (2 finding methylation markers related to age, and (3 finding mouse genes related to total cholesterol. The results demonstrate that intramodular hub gene status with respect to consensus modules is more useful than a meta-analysis p-value when identifying biologically meaningful gene lists (reflecting criterion 1. However, standard meta-analysis methods perform as good as (if not better than a consensus network approach in terms of validation success (criterion 2. The article also reports a comparison of meta-analysis techniques

  20. Gene selection using hybrid binary black hole algorithm and modified binary particle swarm optimization.

    Science.gov (United States)

    Pashaei, Elnaz; Pashaei, Elham; Aydin, Nizamettin

    2018-04-14

    In cancer classification, gene selection is an important data preprocessing technique, but it is a difficult task due to the large search space. Accordingly, the objective of this study is to develop a hybrid meta-heuristic Binary Black Hole Algorithm (BBHA) and Binary Particle Swarm Optimization (BPSO) (4-2) model that emphasizes gene selection. In this model, the BBHA is embedded in the BPSO (4-2) algorithm to make the BPSO (4-2) more effective and to facilitate the exploration and exploitation of the BPSO (4-2) algorithm to further improve the performance. This model has been associated with Random Forest Recursive Feature Elimination (RF-RFE) pre-filtering technique. The classifiers which are evaluated in the proposed framework are Sparse Partial Least Squares Discriminant Analysis (SPLSDA); k-nearest neighbor and Naive Bayes. The performance of the proposed method was evaluated on two benchmark and three clinical microarrays. The experimental results and statistical analysis confirm the better performance of the BPSO (4-2)-BBHA compared with the BBHA, the BPSO (4-2) and several state-of-the-art methods in terms of avoiding local minima, convergence rate, accuracy and number of selected genes. The results also show that the BPSO (4-2)-BBHA model can successfully identify known biologically and statistically significant genes from the clinical datasets. Copyright © 2018 Elsevier Inc. All rights reserved.

  1. Methods for the Isolation of Genes Encoding Novel PHA Metabolism Enzymes from Complex Microbial Communities.

    Science.gov (United States)

    Cheng, Jiujun; Nordeste, Ricardo; Trainer, Maria A; Charles, Trevor C

    2017-01-01

    Development of different PHAs as alternatives to petrochemically derived plastics can be facilitated by mining metagenomic libraries for diverse PHA cycle genes that might be useful for synthesis of bio-plastics. The specific phenotypes associated with mutations of the PHA synthesis pathway genes in Sinorhizobium meliloti and Pseudomonas putida, allows the use of powerful selection and screening tools to identify complementing novel PHA synthesis genes. Identification of novel genes through their function rather than sequence facilitates the functional proteins that may otherwise have been excluded through sequence-only screening methodology. We present here methods that we have developed for the isolation of clones expressing novel PHA metabolism genes from metagenomic libraries.

  2. Methods for the isolation of genes encoding novel PHB cycle enzymes from complex microbial communities.

    Science.gov (United States)

    Nordeste, Ricardo F; Trainer, Maria A; Charles, Trevor C

    2010-01-01

    Development of different PHAs as alternatives to petrochemically derived plastics can be facilitated by mining metagenomic libraries for diverse PHA cycle genes that might be useful for synthesis of bioplastics. The specific phenotypes associated with mutations of the PHA synthesis pathway genes in Sinorhizobium meliloti allows for the use of powerful selection and screening tools to identify complementing novel PHA synthesis genes. Identification of novel genes through their function rather than sequence facilitates finding functional proteins that may otherwise have been excluded through sequence-only screening methodology. We present here methods that we have developed for the isolation of clones expressing novel PHA metabolism genes from metagenomic libraries.

  3. A scan for positively selected genes in the genomes of humans and chimpanzees.

    Directory of Open Access Journals (Sweden)

    Rasmus Nielsen

    2005-06-01

    Full Text Available Since the divergence of humans and chimpanzees about 5 million years ago, these species have undergone a remarkable evolution with drastic divergence in anatomy and cognitive abilities. At the molecular level, despite the small overall magnitude of DNA sequence divergence, we might expect such evolutionary changes to leave a noticeable signature throughout the genome. We here compare 13,731 annotated genes from humans to their chimpanzee orthologs to identify genes that show evidence of positive selection. Many of the genes that present a signature of positive selection tend to be involved in sensory perception or immune defenses. However, the group of genes that show the strongest evidence for positive selection also includes a surprising number of genes involved in tumor suppression and apoptosis, and of genes involved in spermatogenesis. We hypothesize that positive selection in some of these genes may be driven by genomic conflict due to apoptosis during spermatogenesis. Genes with maximal expression in the brain show little or no evidence for positive selection, while genes with maximal expression in the testis tend to be enriched with positively selected genes. Genes on the X chromosome also tend to show an elevated tendency for positive selection. We also present polymorphism data from 20 Caucasian Americans and 19 African Americans for the 50 annotated genes showing the strongest evidence for positive selection. The polymorphism analysis further supports the presence of positive selection in these genes by showing an excess of high-frequency derived nonsynonymous mutations.

  4. Double suicide genes selectively kill human umbilical vein endothelial cells

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    Liu Lunxu

    2011-02-01

    Full Text Available Abstract Background To construct a recombinant adenovirus containing CDglyTK double suicide genes and evaluate the killing effect of the double suicide genes driven by kinase domain insert containing receptor (KDR promoter on human umbilical vein endothelial cells. Methods Human KDR promoter, Escherichia coli (E. coli cytosine deaminase (CD gene and the herpes simplex virus-thymidine kinase (TK gene were cloned using polymerase chain reaction (PCR. Plasmid pKDR-CDglyTK was constructed with the KDR promoter and CDglyTK genes. A recombinant adenoviral plasmid AdKDR-CDglyTK was then constructed and transfected into 293 packaging cells to grow and harvest adenoviruses. KDR-expressing human umbilical vein endothelial cells (ECV304 and KDR-negative liver cancer cell line (HepG2 were infected with the recombinant adenoviruses at different multiplicity of infection (MOI. The infection rate was measured by green fluorescent protein (GFP expression. The infected cells were cultured in culture media containing different concentrations of prodrugs ganciclovir (GCV and/or 5-fluorocytosine (5-FC. The killing effects were measured using two different methods, i.e. annexin V-FITC staining and terminal transferase-mediated dUTP nick end-labeling (TUNEL staining. Results Recombinant adenoviruses AdKDR-CDglyTK were successfully constructed and they infected ECV304 and HepG2 cells efficiently. The infection rate was dependent on MOI of recombinant adenoviruses. ECV304 cells infected with AdKDR-CDglyTK were highly sensitive to GCV and 5-FC. The cell survival rate was dependent on both the concentration of the prodrugs and the MOI of recombinant adenoviruses. In contrast, there were no killing effects in the HepG2 cells. The combination of two prodrugs was much more effective in killing ECV304 cells than GCV or 5-FC alone. The growth of transgenic ECV304 cells was suppressed in the presence of prodrugs. Conclusion AdKDR-CDglyTK/double prodrog system may be a useful

  5. Selection of reference genes for quantitative gene expression normalization in flax (Linum usitatissimum L.

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    Neutelings Godfrey

    2010-04-01

    Full Text Available Abstract Background Quantitative real-time PCR (qRT-PCR is currently the most accurate method for detecting differential gene expression. Such an approach depends on the identification of uniformly expressed 'housekeeping genes' (HKGs. Extensive transcriptomic data mining and experimental validation in different model plants have shown that the reliability of these endogenous controls can be influenced by the plant species, growth conditions and organs/tissues examined. It is therefore important to identify the best reference genes to use in each biological system before using qRT-PCR to investigate differential gene expression. In this paper we evaluate different candidate HKGs for developmental transcriptomic studies in the economically-important flax fiber- and oil-crop (Linum usitatissimum L. Results Specific primers were designed in order to quantify the expression levels of 20 different potential housekeeping genes in flax roots, internal- and external-stem tissues, leaves and flowers at different developmental stages. After calculations of PCR efficiencies, 13 HKGs were retained and their expression stabilities evaluated by the computer algorithms geNorm and NormFinder. According to geNorm, 2 Transcriptional Elongation Factors (TEFs and 1 Ubiquitin gene are necessary for normalizing gene expression when all studied samples are considered. However, only 2 TEFs are required for normalizing expression in stem tissues. In contrast, NormFinder identified glyceraldehyde-3-phosphate dehydrogenase (GADPH as the most stably expressed gene when all samples were grouped together, as well as when samples were classed into different sub-groups. qRT-PCR was then used to investigate the relative expression levels of two splice variants of the flax LuMYB1 gene (homologue of AtMYB59. LuMYB1-1 and LuMYB1-2 were highly expressed in the internal stem tissues as compared to outer stem tissues and other samples. This result was confirmed with both ge

  6. Selection of reference genes for quantitative gene expression normalization in flax (Linum usitatissimum L.).

    Science.gov (United States)

    Huis, Rudy; Hawkins, Simon; Neutelings, Godfrey

    2010-04-19

    Quantitative real-time PCR (qRT-PCR) is currently the most accurate method for detecting differential gene expression. Such an approach depends on the identification of uniformly expressed 'housekeeping genes' (HKGs). Extensive transcriptomic data mining and experimental validation in different model plants have shown that the reliability of these endogenous controls can be influenced by the plant species, growth conditions and organs/tissues examined. It is therefore important to identify the best reference genes to use in each biological system before using qRT-PCR to investigate differential gene expression. In this paper we evaluate different candidate HKGs for developmental transcriptomic studies in the economically-important flax fiber- and oil-crop (Linum usitatissimum L). Specific primers were designed in order to quantify the expression levels of 20 different potential housekeeping genes in flax roots, internal- and external-stem tissues, leaves and flowers at different developmental stages. After calculations of PCR efficiencies, 13 HKGs were retained and their expression stabilities evaluated by the computer algorithms geNorm and NormFinder. According to geNorm, 2 Transcriptional Elongation Factors (TEFs) and 1 Ubiquitin gene are necessary for normalizing gene expression when all studied samples are considered. However, only 2 TEFs are required for normalizing expression in stem tissues. In contrast, NormFinder identified glyceraldehyde-3-phosphate dehydrogenase (GADPH) as the most stably expressed gene when all samples were grouped together, as well as when samples were classed into different sub-groups.qRT-PCR was then used to investigate the relative expression levels of two splice variants of the flax LuMYB1 gene (homologue of AtMYB59). LuMYB1-1 and LuMYB1-2 were highly expressed in the internal stem tissues as compared to outer stem tissues and other samples. This result was confirmed with both geNorm-designated- and Norm

  7. The Ability of Different Imputation Methods to Preserve the Significant Genes and Pathways in Cancer

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    Rosa Aghdam

    2017-12-01

    Full Text Available Deciphering important genes and pathways from incomplete gene expression data could facilitate a better understanding of cancer. Different imputation methods can be applied to estimate the missing values. In our study, we evaluated various imputation methods for their performance in preserving significant genes and pathways. In the first step, 5% genes are considered in random for two types of ignorable and non-ignorable missingness mechanisms with various missing rates. Next, 10 well-known imputation methods were applied to the complete datasets. The significance analysis of microarrays (SAM method was applied to detect the significant genes in rectal and lung cancers to showcase the utility of imputation approaches in preserving significant genes. To determine the impact of different imputation methods on the identification of important genes, the chi-squared test was used to compare the proportions of overlaps between significant genes detected from original data and those detected from the imputed datasets. Additionally, the significant genes are tested for their enrichment in important pathways, using the ConsensusPathDB. Our results showed that almost all the significant genes and pathways of the original dataset can be detected in all imputed datasets, indicating that there is no significant difference in the performance of various imputation methods tested. The source code and selected datasets are available on http://profiles.bs.ipm.ir/softwares/imputation_methods/.

  8. The Ability of Different Imputation Methods to Preserve the Significant Genes and Pathways in Cancer.

    Science.gov (United States)

    Aghdam, Rosa; Baghfalaki, Taban; Khosravi, Pegah; Saberi Ansari, Elnaz

    2017-12-01

    Deciphering important genes and pathways from incomplete gene expression data could facilitate a better understanding of cancer. Different imputation methods can be applied to estimate the missing values. In our study, we evaluated various imputation methods for their performance in preserving significant genes and pathways. In the first step, 5% genes are considered in random for two types of ignorable and non-ignorable missingness mechanisms with various missing rates. Next, 10 well-known imputation methods were applied to the complete datasets. The significance analysis of microarrays (SAM) method was applied to detect the significant genes in rectal and lung cancers to showcase the utility of imputation approaches in preserving significant genes. To determine the impact of different imputation methods on the identification of important genes, the chi-squared test was used to compare the proportions of overlaps between significant genes detected from original data and those detected from the imputed datasets. Additionally, the significant genes are tested for their enrichment in important pathways, using the ConsensusPathDB. Our results showed that almost all the significant genes and pathways of the original dataset can be detected in all imputed datasets, indicating that there is no significant difference in the performance of various imputation methods tested. The source code and selected datasets are available on http://profiles.bs.ipm.ir/softwares/imputation_methods/. Copyright © 2017. Production and hosting by Elsevier B.V.

  9. Rapid and targeted introgression of genes into popular wheat cultivars using marker-assisted background selection.

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    Harpinder S Randhawa

    Full Text Available A marker-assisted background selection (MABS-based gene introgression approach in wheat (Triticum aestivum L. was optimized, where 97% or more of a recurrent parent genome (RPG can be recovered in just two backcross (BC generations. A four-step MABS method was developed based on 'Plabsim' computer simulations and wheat genome structure information. During empirical optimization of this method, double recombinants around the target gene were selected in a step-wise fashion during the two BC cycles followed by selection for recurrent parent genotype on non-carrier chromosomes. The average spacing between carrier chromosome markers was <4 cM. For non-carrier chromosome markers that flanked each of the 48 wheat gene-rich regions, this distance was approximately 12 cM. Employed to introgress seedling stripe rust (Puccinia striiformis f. sp. tritici resistance gene Yr15 into the spring wheat cultivar 'Zak', marker analysis of 2,187 backcross-derived progeny resulted in the recovery of a BC(2F(2ratio3 plant with 97% of the recurrent parent genome. In contrast, only 82% of the recurrent parent genome was recovered in phenotypically selected BC(4F(7 plants developed without MABS. Field evaluation results from 17 locations indicated that the MABS-derived line was either equal or superior to the recurrent parent for the tested agronomic characteristics. Based on these results, MABS is recommended as a strategy for rapidly introgressing a targeted gene into a wheat genotype in just two backcross generations while recovering 97% or more of the recurrent parent genotype.

  10. A Screening Method for the ALK Fusion Gene in NSCLC

    International Nuclear Information System (INIS)

    Murakami, Yoshiko; Mitsudomi, Tetsuya; Yatabe, Yasushi

    2012-01-01

    Lung cancer research has recently made significant progress in understanding the molecular pathogenesis of lung cancer and in developing treatments for it. Such achievements are directly utilized in clinical practice. Indeed, the echinoderm microtubule-associated protein-like 4–anaplastic lymphoma kinase (ALK) fusion gene was first described in non-small cell lung cancer in 2007, and a molecularly targeted drug against the fusion was approved in 2011. However, lung cancer with the ALK fusion constitutes only a small fraction of lung cancers; therefore, efficient patient selection is crucial for successful treatment using the ALK inhibitor. Currently, RT-PCR, fluorescent in situ hybridization (FISH), and immunohistochemistry are commonly used to detect the ALK fusion. Although FISH is currently the gold standard technique, there are no perfect methods for detecting these genetic alterations. In this article, we discuss the advantages and disadvantages of each method and the possible criteria for selecting patients who are more likely to have the ALK fusion. If we can successfully screen patients, then ALK inhibitor treatment will be the best example of personalized therapy in terms of selecting patients with an uncommon genotype from a larger group with the same tumor phenotype. In other words, the personalized therapy may offer a new challenge for current clinical oncology.

  11. AMES: Towards an Agile Method for ERP Selection

    OpenAIRE

    Juell-Skielse, Gustaf; Nilsson, Anders G.; Nordqvist, Andreas; Westergren, Mattias

    2012-01-01

    Conventional on-premise installations of ERP are now rapidly being replaced by ERP as service. Although ERP becomes more accessible and no longer requires local infrastructure, current selection methods do not take full advantage of the provided agility. In this paper we present AMES (Agile Method for ERP Selection), a novel method for ERP selection which better utilizes the strengths of service oriented ERP. AMES is designed to shorten lead time for selection, support identification of essen...

  12. Feature selection and classification of MAQC-II breast cancer and multiple myeloma microarray gene expression data.

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    Qingzhong Liu

    Full Text Available Microarray data has a high dimension of variables but available datasets usually have only a small number of samples, thereby making the study of such datasets interesting and challenging. In the task of analyzing microarray data for the purpose of, e.g., predicting gene-disease association, feature selection is very important because it provides a way to handle the high dimensionality by exploiting information redundancy induced by associations among genetic markers. Judicious feature selection in microarray data analysis can result in significant reduction of cost while maintaining or improving the classification or prediction accuracy of learning machines that are employed to sort out the datasets. In this paper, we propose a gene selection method called Recursive Feature Addition (RFA, which combines supervised learning and statistical similarity measures. We compare our method with the following gene selection methods: Support Vector Machine Recursive Feature Elimination (SVMRFE, Leave-One-Out Calculation Sequential Forward Selection (LOOCSFS, Gradient based Leave-one-out Gene Selection (GLGS. To evaluate the performance of these gene selection methods, we employ several popular learning classifiers on the MicroArray Quality Control phase II on predictive modeling (MAQC-II breast cancer dataset and the MAQC-II multiple myeloma dataset. Experimental results show that gene selection is strictly paired with learning classifier. Overall, our approach outperforms other compared methods. The biological functional analysis based on the MAQC-II breast cancer dataset convinced us to apply our method for phenotype prediction. Additionally, learning classifiers also play important roles in the classification of microarray data and our experimental results indicate that the Nearest Mean Scale Classifier (NMSC is a good choice due to its prediction reliability and its stability across the three performance measurements: Testing accuracy, MCC values, and

  13. Gene-Based Multiclass Cancer Diagnosis with Class-Selective Rejections

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    Nisrine Jrad

    2009-01-01

    rejection scheme. The state of art multiclass algorithms can be considered as a particular case of the proposed algorithm where the number of decisions is given by the classes and the loss function is defined by the Bayesian risk. Two experiments are carried out in the Bayesian and the class selective rejection frameworks. Five genes selected datasets are used to assess the performance of the proposed method. Results are discussed and accuracies are compared with those computed by the Naive Bayes, Nearest Neighbor, Linear Perceptron, Multilayer Perceptron, and Support Vector Machines classifiers.

  14. Ageing Drosophila selected for longevity retain a young gene expression profile

    DEFF Research Database (Denmark)

    Sarup, Pernille Merete

    and longevity selected lines. Among the latter genes we found a clear overrepresentation of genes involved in immune functions supporting the hypothesis of the life shortening effect of an overactive immune system (inflammaging). Eighty-four genes were differentially expressed at the same physiological age...... between control and longevity selected lines, and the overlap between the same chronological and physiological age gene lists counted 40 candidate genes for increased longevity. Among these were genes with functions in starvation resistance, a regulator of immune responses and several genes which have......  We have investigated how the gene-expression profile of longevity selected lines of Drosophila melanogaster differed from control lines in young, middle-aged and old male flies. 530 genes were differentially expressed between selected and control flies at the same chronological age. We used...

  15. Comparison of genome-wide selection strategies to identify furfural tolerance genes in Escherichia coli.

    Science.gov (United States)

    Glebes, Tirzah Y; Sandoval, Nicholas R; Gillis, Jacob H; Gill, Ryan T

    2015-01-01

    Engineering both feedstock and product tolerance is important for transitioning towards next-generation biofuels derived from renewable sources. Tolerance to chemical inhibitors typically results in complex phenotypes, for which multiple genetic changes must often be made to confer tolerance. Here, we performed a genome-wide search for furfural-tolerant alleles using the TRackable Multiplex Recombineering (TRMR) method (Warner et al. (2010), Nature Biotechnology), which uses chromosomally integrated mutations directed towards increased or decreased expression of virtually every gene in Escherichia coli. We employed various growth selection strategies to assess the role of selection design towards growth enrichments. We also compared genes with increased fitness from our TRMR selection to those from a previously reported genome-wide identification study of furfural tolerance genes using a plasmid-based genomic library approach (Glebes et al. (2014) PLOS ONE). In several cases, growth improvements were observed for the chromosomally integrated promoter/RBS mutations but not for the plasmid-based overexpression constructs. Through this assessment, four novel tolerance genes, ahpC, yhjH, rna, and dicA, were identified and confirmed for their effect on improving growth in the presence of furfural. © 2014 Wiley Periodicals, Inc.

  16. Outranking methods in support of supplier selection

    NARCIS (Netherlands)

    de Boer, L.; van der Wegen, Leonardus L.M.; Telgen, Jan

    1998-01-01

    Initial purchasing decisions such as make-or-buy decisions and supplier selection are decisions of strategic importance to companies. The nature of these decisions usually is complex and unstructured. Management Science techniques might be helpful tools for this kind of decision making problems. So

  17. Color selective photodetector and methods of making

    Science.gov (United States)

    Walker, Brian J.; Dorn, August; Bulovic, Vladimir; Bawendi, Moungi G.

    2013-03-19

    A photoelectric device, such as a photodetector, can include a semiconductor nanowire electrostatically associated with a J-aggregate. The J-aggregate can facilitate absorption of a desired wavelength of light, and the semiconductor nanowire can facilitate charge transport. The color of light detected by the device can be chosen by selecting a J-aggregate with a corresponding peak absorption wavelength.

  18. Use of Maximum Likelihood-Mixed Models to select stable reference genes: a case of heat stress response in sheep

    Directory of Open Access Journals (Sweden)

    Salces Judit

    2011-08-01

    Full Text Available Abstract Background Reference genes with stable expression are required to normalize expression differences of target genes in qPCR experiments. Several procedures and companion software have been proposed to find the most stable genes. Model based procedures are attractive because they provide a solid statistical framework. NormFinder, a widely used software, uses a model based method. The pairwise comparison procedure implemented in GeNorm is a simpler procedure but one of the most extensively used. In the present work a statistical approach based in Maximum Likelihood estimation under mixed models was tested and compared with NormFinder and geNorm softwares. Sixteen candidate genes were tested in whole blood samples from control and heat stressed sheep. Results A model including gene and treatment as fixed effects, sample (animal, gene by treatment, gene by sample and treatment by sample interactions as random effects with heteroskedastic residual variance in gene by treatment levels was selected using goodness of fit and predictive ability criteria among a variety of models. Mean Square Error obtained under the selected model was used as indicator of gene expression stability. Genes top and bottom ranked by the three approaches were similar; however, notable differences for the best pair of genes selected for each method and the remaining genes of the rankings were shown. Differences among the expression values of normalized targets for each statistical approach were also found. Conclusions Optimal statistical properties of Maximum Likelihood estimation joined to mixed model flexibility allow for more accurate estimation of expression stability of genes under many different situations. Accurate selection of reference genes has a direct impact over the normalized expression values of a given target gene. This may be critical when the aim of the study is to compare expression rate differences among samples under different environmental

  19. Pearl millet transformation system using the positive selectable marker gene phosphomannose isomerase

    CSIR Research Space (South Africa)

    O'Kennedy, MM

    2004-04-01

    Full Text Available of the transgene. Similar to results obtained from previous studies with maize and wheat, the manA gene was shown to be a superior selectable marker gene for improving transformation efficiencies when compared to antibiotic or herbicide selectable marker genes....

  20. A Cancer Gene Selection Algorithm Based on the K-S Test and CFS

    Directory of Open Access Journals (Sweden)

    Qiang Su

    2017-01-01

    Full Text Available Background. To address the challenging problem of selecting distinguished genes from cancer gene expression datasets, this paper presents a gene subset selection algorithm based on the Kolmogorov-Smirnov (K-S test and correlation-based feature selection (CFS principles. The algorithm selects distinguished genes first using the K-S test, and then, it uses CFS to select genes from those selected by the K-S test. Results. We adopted support vector machines (SVM as the classification tool and used the criteria of accuracy to evaluate the performance of the classifiers on the selected gene subsets. This approach compared the proposed gene subset selection algorithm with the K-S test, CFS, minimum-redundancy maximum-relevancy (mRMR, and ReliefF algorithms. The average experimental results of the aforementioned gene selection algorithms for 5 gene expression datasets demonstrate that, based on accuracy, the performance of the new K-S and CFS-based algorithm is better than those of the K-S test, CFS, mRMR, and ReliefF algorithms. Conclusions. The experimental results show that the K-S test-CFS gene selection algorithm is a very effective and promising approach compared to the K-S test, CFS, mRMR, and ReliefF algorithms.

  1. GAP1, a novel selection and counter-selection marker for multiple gene disruptions in Saccharomyces cerevisiae

    DEFF Research Database (Denmark)

    Regenberg, Birgitte; Hansen, J.

    2000-01-01

    the GAP1 gene. This is caused by recombination between two Salmonella typuimurium hisG direct repeats embracing GAP1, and will result in a sub-population of gap1 cells. Such cells are selected on a medium containing D-histidine, and may subsequently be used for a second gene disruption. Hence, multiple...... flanked by short (60 bp) stretches of the gene in question. Through homologous recombination, the cassette will integrate into the target gene, which is thus replaced by GAP1, and mutants are selected for on minimal L-citrulline medium. When propagated under non-selective conditions, some cells will lose...... gene disruptions can be made fast, cheaply and easily in a gap1 strain, with two positive selection steps for each disruption. Copyright (C) 2000 John Wiley & Sons, Ltd....

  2. 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.

  3. Method for Business Process Management System Selection

    OpenAIRE

    Westelaken, van de, Thijs; Terwee, Bas; Ravesteijn, Pascal

    2013-01-01

    In recent years business process management (BPM) and specifically information systems that support the analysis, design and execution of processes (also called business process management systems (BPMS)) are getting more attention. This has lead to an increase in research on BPM and BPMS. However the research on BPMS is mostly focused on the architecture of the system and how to implement such systems. How to select a BPM system that fits the strategy and goals of a specific organization is ...

  4. Bayesian nonparametric variable selection as an exploratory tool for discovering differentially expressed genes.

    Science.gov (United States)

    Shahbaba, Babak; Johnson, Wesley O

    2013-05-30

    High-throughput scientific studies involving no clear a priori hypothesis are common. For example, a large-scale genomic study of a disease may examine thousands of genes without hypothesizing that any specific gene is responsible for the disease. In these studies, the objective is to explore a large number of possible factors (e.g., genes) in order to identify a small number that will be considered in follow-up studies that tend to be more thorough and on smaller scales. A simple, hierarchical, linear regression model with random coefficients is assumed for case-control data that correspond to each gene. The specific model used will be seen to be related to a standard Bayesian variable selection model. Relatively large regression coefficients correspond to potential differences in responses for cases versus controls and thus to genes that might 'matter'. For large-scale studies, and using a Dirichlet process mixture model for the regression coefficients, we are able to find clusters of regression effects of genes with increasing potential effect or 'relevance', in relation to the outcome of interest. One cluster will always correspond to genes whose coefficients are in a neighborhood that is relatively close to zero and will be deemed least relevant. Other clusters will correspond to increasing magnitudes of the random/latent regression coefficients. Using simulated data, we demonstrate that our approach could be quite effective in finding relevant genes compared with several alternative methods. We apply our model to two large-scale studies. The first study involves transcriptome analysis of infection by human cytomegalovirus. The second study's objective is to identify differentially expressed genes between two types of leukemia. Copyright © 2012 John Wiley & Sons, Ltd.

  5. Selection of housekeeping genes and demonstration of RNAi in cotton leafhopper, Amrasca biguttula biguttula (Ishida)

    Science.gov (United States)

    Gupta, Mridula; Pandher, Suneet; Kaur, Gurmeet; Rathore, Pankaj; Palli, Subba Reddy

    2018-01-01

    Amrasca biguttula biguttula (Ishida) commonly known as cotton leafhopper is a severe pest of cotton and okra. Not much is known on this insect at molecular level due to lack of genomic and transcriptomic data. To prepare for functional genomic studies in this insect, we evaluated 15 common housekeeping genes (Tub, B-Tub, EF alpha, GADPH, UbiCF, RP13, Ubiq, G3PD, VATPase, Actin, 18s, 28s, TATA, ETF, SOD and Cytolytic actin) during different developmental stages and under starvation stress. We selected early (1st and 2nd), late (3rd and 4th) stage nymphs and adults for identification of stable housekeeping genes using geNorm, NormFinder, BestKeeper and RefFinder software. Based on the different algorithms, RP13 and VATPase are identified as the most suitable reference genes for quantification of gene expression by reverse transcriptase quantitative PCR (RT-qPCR). Based on RefFinder which comprehended the results of three algorithms, RP13 in adults, Tubulin (Tub) in late nymphs, 28S in early nymph and UbiCF under starvation stress were identified as the most stable genes. We also developed methods for feeding double-stranded RNA (dsRNA) incorporated in the diet. Feeding dsRNA targeting Snf7, IAP, AQP1, and VATPase caused 56.17–77.12% knockdown of targeted genes compared to control and 16 to 48% mortality of treated insects when compared to control. PMID:29329327

  6. Selection of housekeeping genes and demonstration of RNAi in cotton leafhopper, Amrasca biguttula biguttula (Ishida.

    Directory of Open Access Journals (Sweden)

    Satnam Singh

    Full Text Available Amrasca biguttula biguttula (Ishida commonly known as cotton leafhopper is a severe pest of cotton and okra. Not much is known on this insect at molecular level due to lack of genomic and transcriptomic data. To prepare for functional genomic studies in this insect, we evaluated 15 common housekeeping genes (Tub, B-Tub, EF alpha, GADPH, UbiCF, RP13, Ubiq, G3PD, VATPase, Actin, 18s, 28s, TATA, ETF, SOD and Cytolytic actin during different developmental stages and under starvation stress. We selected early (1st and 2nd, late (3rd and 4th stage nymphs and adults for identification of stable housekeeping genes using geNorm, NormFinder, BestKeeper and RefFinder software. Based on the different algorithms, RP13 and VATPase are identified as the most suitable reference genes for quantification of gene expression by reverse transcriptase quantitative PCR (RT-qPCR. Based on RefFinder which comprehended the results of three algorithms, RP13 in adults, Tubulin (Tub in late nymphs, 28S in early nymph and UbiCF under starvation stress were identified as the most stable genes. We also developed methods for feeding double-stranded RNA (dsRNA incorporated in the diet. Feeding dsRNA targeting Snf7, IAP, AQP1, and VATPase caused 56.17-77.12% knockdown of targeted genes compared to control and 16 to 48% mortality of treated insects when compared to control.

  7. A GMM-IG framework for selecting genes as expression panel biomarkers.

    Science.gov (United States)

    Wang, Mingyi; Chen, Jake Y

    2010-01-01

    The limitation of small sample size of functional genomics experiments has made it necessary to integrate DNA microarray experimental data from different sources. However, experimentation noises and biases of different microarray platforms have made integrated data analysis challenging. In this work, we propose an integrative computational framework to identify candidate biomarker genes from publicly available functional genomics studies. We developed a new framework, Gaussian Mixture Modeling-Coupled Information Gain (GMM-IG). In this framework, we first apply a two-component Gaussian mixture model (GMM) to estimate the conditional probability distributions of gene expression data between two different types of samples, for example, normal versus cancer. An expectation-maximization algorithm is then used to estimate the maximum likelihood parameters of a mixture of two Gaussian models in the feature space and determine the underlying expression levels of genes. Gene expression results from different studies are discretized, based on GMM estimations and then unified. Significantly differentially-expressed genes are filtered and assessed with information gain (IG) measures. DNA microarray experimental data for lung cancers from three different prior studies was processed using the new GMM-IG method. Target gene markers from a gene expression panel were selected and compared with several conventional computational biomarker data analysis methods. GMM-IG showed consistently high accuracy for several classification assessments. A high reproducibility of gene selection results was also determined from statistical validations. Our study shows that the GMM-IG framework can overcome poor reliability issues from single-study DNA microarray experiment while maintaining high accuracies by combining true signals from multiple studies. We present a conceptually simple framework that enables reliable integration of true differential gene expression signals from multiple

  8. 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.

  9. Selection of reference genes for tissue/organ samples on day 3 fifth-instar larvae in silkworm, Bombyx mori.

    Science.gov (United States)

    Wang, Genhong; Chen, Yanfei; Zhang, Xiaoying; Bai, Bingchuan; Yan, Hao; Qin, Daoyuan; Xia, Qingyou

    2018-06-01

    The silkworm, Bombyx mori, is one of the world's most economically important insect. Surveying variations in gene expression among multiple tissue/organ samples will provide clues for gene function assignments and will be helpful for identifying genes related to economic traits or specific cellular processes. To ensure their accuracy, commonly used gene expression quantification methods require a set of stable reference genes for data normalization. In this study, 24 candidate reference genes were assessed in 10 tissue/organ samples of day 3 fifth-instar B. mori larvae using geNorm and NormFinder. The results revealed that, using the combination of the expression of BGIBMGA003186 and BGIBMGA008209 was the optimum choice for normalizing the expression data of the B. mori tissue/organ samples. The most stable gene, BGIBMGA003186, is recommended if just one reference gene is used. Moreover, the commonly used reference gene encoding cytoplasmic actin was the least appropriate reference gene of the samples investigated. The reliability of the selected reference genes was further confirmed by evaluating the expression profiles of two cathepsin genes. Our results may be useful for future studies involving the quantification of relative gene expression levels of different tissue/organ samples in B. mori. © 2018 Wiley Periodicals, Inc.

  10. Selection of reliable reference genes for quantitative real-time PCR in human T cells and neutrophils

    Directory of Open Access Journals (Sweden)

    Ledderose Carola

    2011-10-01

    Full Text Available Abstract Background The choice of reliable reference genes is a prerequisite for valid results when analyzing gene expression with real-time quantitative PCR (qPCR. This method is frequently applied to study gene expression patterns in immune cells, yet a thorough validation of potential reference genes is still lacking for most leukocyte subtypes and most models of their in vitro stimulation. In the current study, we evaluated the expression stability of common reference genes in two widely used cell culture models-anti-CD3/CD28 activated T cells and lipopolysaccharide stimulated neutrophils-as well as in unselected untreated leukocytes. Results The mRNA expression of 17 (T cells, 7 (neutrophils or 8 (unselected leukocytes potential reference genes was quantified by reverse transcription qPCR, and a ranking of the preselected candidate genes according to their expression stability was calculated using the programs NormFinder, geNorm and BestKeeper. IPO8, RPL13A, TBP and SDHA were identified as suitable reference genes in T cells. TBP, ACTB and SDHA were stably expressed in neutrophils. TBP and SDHA were also the most stable genes in untreated total blood leukocytes. The critical impact of reference gene selection on the estimated target gene expression is demonstrated for IL-2 and FIH expression in T cells. Conclusions The study provides a shortlist of suitable reference genes for normalization of gene expression data in unstimulated and stimulated T cells, unstimulated and stimulated neutrophils and in unselected leukocytes.

  11. Improvement Method of Gene Transfer in Kappaphycus Alvarezii

    OpenAIRE

    Triana, St. Hidayah; Alimuddin,; Widyastuti, Utut; Suharsono,; Suryati, Emma; Parenrengi, Andi

    2016-01-01

    Method of foreign gene transfer in red seaweed Kappaphycus alvarezii has been reported, however, li-mited number of transgenic F0 (broodstock) was obtained. This study was conducted to improve the method of gene transfer mediated by Agrobacterium tumefaciens in order to obtain high percentage of K. alvarezii transgenic. Superoxide dismutase gene from Melastoma malabatrichum (MmCu/Zn-SOD) was used as model towards increasing adaptability of K. alvarezii to environmental stress. The treat-ment...

  12. Evaluation of gene association methods for coexpression network construction and biological knowledge discovery.

    Directory of Open Access Journals (Sweden)

    Sapna Kumari

    Full Text Available BACKGROUND: Constructing coexpression networks and performing network analysis using large-scale gene expression data sets is an effective way to uncover new biological knowledge; however, the methods used for gene association in constructing these coexpression networks have not been thoroughly evaluated. Since different methods lead to structurally different coexpression networks and provide different information, selecting the optimal gene association method is critical. METHODS AND RESULTS: In this study, we compared eight gene association methods - Spearman rank correlation, Weighted Rank Correlation, Kendall, Hoeffding's D measure, Theil-Sen, Rank Theil-Sen, Distance Covariance, and Pearson - and focused on their true knowledge discovery rates in associating pathway genes and construction coordination networks of regulatory genes. We also examined the behaviors of different methods to microarray data with different properties, and whether the biological processes affect the efficiency of different methods. CONCLUSIONS: We found that the Spearman, Hoeffding and Kendall methods are effective in identifying coexpressed pathway genes, whereas the Theil-sen, Rank Theil-Sen, Spearman, and Weighted Rank methods perform well in identifying coordinated transcription factors that control the same biological processes and traits. Surprisingly, the widely used Pearson method is generally less efficient, and so is the Distance Covariance method that can find gene pairs of multiple relationships. Some analyses we did clearly show Pearson and Distance Covariance methods have distinct behaviors as compared to all other six methods. The efficiencies of different methods vary with the data properties to some degree and are largely contingent upon the biological processes, which necessitates the pre-analysis to identify the best performing method for gene association and coexpression network construction.

  13. Selective visualization of gene structure with ultraviolet light

    International Nuclear Information System (INIS)

    Wang, Z.; Becker, M.M.

    1988-01-01

    The ability of the ultraviolet (UV) footprinting technique to detect chromatin has been investigated in vitro. Two basic types of chromatin, a phased nucleosome and a phased nucleosome containing a phased H1 protein, have been reconstituted onto a cloned 5S ribosomal RNA gene from sea urchin. The histone-DNA interactions in each complex have been probed with exonuclease III, DNase I, dimethyl sulfate, and UV light. Whereas DNase I and exonuclease III readily detect interactions between histones and DNA, UV light and dimethyl sulfate do not. In contrast to histone-DNA interactions, we demonstrate that intimate sequence-specific contacts between the same sea urchin 5S DNA and the Xenopus laevis transcription factor IIIA (TFIIIA) are readily detected with UV light. Since the sensitivity of UV light for TFIIIA contacts is similar to its sensitivity for other regulatory protein-DNA contacts, these studies demonstrate the feasibility of using UV light to selectively visualize regulatory protein-DNA interactions in vivo with little or no interference from histone-DNA interactions

  14. Gene-Based Multiclass Cancer Diagnosis with Class-Selective Rejections

    Science.gov (United States)

    Jrad, Nisrine; Grall-Maës, Edith; Beauseroy, Pierre

    2009-01-01

    Supervised learning of microarray data is receiving much attention in recent years. Multiclass cancer diagnosis, based on selected gene profiles, are used as adjunct of clinical diagnosis. However, supervised diagnosis may hinder patient care, add expense or confound a result. To avoid this misleading, a multiclass cancer diagnosis with class-selective rejection is proposed. It rejects some patients from one, some, or all classes in order to ensure a higher reliability while reducing time and expense costs. Moreover, this classifier takes into account asymmetric penalties dependant on each class and on each wrong or partially correct decision. It is based on ν-1-SVM coupled with its regularization path and minimizes a general loss function defined in the class-selective rejection scheme. The state of art multiclass algorithms can be considered as a particular case of the proposed algorithm where the number of decisions is given by the classes and the loss function is defined by the Bayesian risk. Two experiments are carried out in the Bayesian and the class selective rejection frameworks. Five genes selected datasets are used to assess the performance of the proposed method. Results are discussed and accuracies are compared with those computed by the Naive Bayes, Nearest Neighbor, Linear Perceptron, Multilayer Perceptron, and Support Vector Machines classifiers. PMID:19584932

  15. A Review for Detecting Gene-Gene Interactions Using Machine Learning Methods in Genetic Epidemiology

    Directory of Open Access Journals (Sweden)

    Ching Lee Koo

    2013-01-01

    Full Text Available Recently, the greatest statistical computational challenge in genetic epidemiology is to identify and characterize the genes that interact with other genes and environment factors that bring the effect on complex multifactorial disease. These gene-gene interactions are also denoted as epitasis in which this phenomenon cannot be solved by traditional statistical method due to the high dimensionality of the data and the occurrence of multiple polymorphism. Hence, there are several machine learning methods to solve such problems by identifying such susceptibility gene which are neural networks (NNs, support vector machine (SVM, and random forests (RFs in such common and multifactorial disease. This paper gives an overview on machine learning methods, describing the methodology of each machine learning methods and its application in detecting gene-gene and gene-environment interactions. Lastly, this paper discussed each machine learning method and presents the strengths and weaknesses of each machine learning method in detecting gene-gene interactions in complex human disease.

  16. Effect of cooking methods on the micronutrient profile of selected ...

    African Journals Online (AJOL)

    Effect of cooking methods on the micronutrient profile of selected vegetables: okra fruit ( Abelmoshcus esculentus ), fluted pumpkin ( Telfairia occidentalis ), African spinach ( Amarantus viridis ), and scent leaf ( Ocumum gratissimum.

  17. Genetic diversity of selected genes that are potentially economically important in feral sheep of New Zealand

    Directory of Open Access Journals (Sweden)

    Sedcole J Richard

    2010-12-01

    Full Text Available Abstract Background Feral sheep are considered to be a source of genetic variation that has been lost from their domestic counterparts through selection. Methods This study investigates variation in the genes KRTAP1-1, KRT33, ADRB3 and DQA2 in Merino-like feral sheep populations from New Zealand and its offshore islands. These genes have previously been shown to influence wool, lamb survival and animal health. Results All the genes were polymorphic, but no new allele was identified in the feral populations. In some of these populations, allele frequencies differed from those observed in commercial Merino sheep and other breeds found in New Zealand. Heterozygosity levels were comparable to those observed in other studies on feral sheep. Our results suggest that some of the feral populations may have been either inbred or outbred over the duration of their apparent isolation. Conclusion The variation described here allows us to draw some conclusions about the likely genetic origin of the populations and selective pressures that may have acted upon them, but they do not appear to be a source of new genetic material, at least for these four genes.

  18. SELECTION METHOD FOR AUTOMOTIVE PARTS RECONDITIONING

    Directory of Open Access Journals (Sweden)

    Dan Florin NITOI

    2015-05-01

    Full Text Available Paper presents technological methods for metal deposition, costs calculation and clasification for the main process that helps in automotive technologies to repair or to increase pieces properties. Paper was constructed based on many technological experiments that starts from practicans and returns to them. The main aim is to help young engineers or practicians engineers to choose the proper reconditioning process with the best information in repairing pieces from automotive industry.

  19. Proteomics in pulmonary research: selected methodical aspects

    Directory of Open Access Journals (Sweden)

    Martin Petrek

    2007-10-01

    Full Text Available Recent years witness rapid expansion of applications of proteomics to clinical research including non-malignant lung disorders. These developments bring along the need for standardisation of proteomic experiments. This paper briefly reviews basic methodical aspects of appliedproteomic studies using SELDI-TOF mass spectrometry platform as example but also emphasizes general aspects of quality assurance in proteomics. Key-words: lung proteome, quality assurance, SELDI-TOF MS

  20. 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.

  1. Comparative genomic and transcriptomic analysis of selected fatty acid biosynthesis genes and CNL disease resistance genes in oil palm

    Science.gov (United States)

    Rosli, Rozana; Amiruddin, Nadzirah; Ab Halim, Mohd Amin; Chan, Pek-Lan; Chan, Kuang-Lim; Azizi, Norazah; Morris, Priscilla E.; Leslie Low, Eng-Ti; Ong-Abdullah, Meilina; Sambanthamurthi, Ravigadevi; Singh, Rajinder

    2018-01-01

    Comparative genomics and transcriptomic analyses were performed on two agronomically important groups of genes from oil palm versus other major crop species and the model organism, Arabidopsis thaliana. The first analysis was of two gene families with key roles in regulation of oil quality and in particular the accumulation of oleic acid, namely stearoyl ACP desaturases (SAD) and acyl-acyl carrier protein (ACP) thioesterases (FAT). In both cases, these were found to be large gene families with complex expression profiles across a wide range of tissue types and developmental stages. The detailed classification of the oil palm SAD and FAT genes has enabled the updating of the latest version of the oil palm gene model. The second analysis focused on disease resistance (R) genes in order to elucidate possible candidates for breeding of pathogen tolerance/resistance. Ortholog analysis showed that 141 out of the 210 putative oil palm R genes had homologs in banana and rice. These genes formed 37 clusters with 634 orthologous genes. Classification of the 141 oil palm R genes showed that the genes belong to the Kinase (7), CNL (95), MLO-like (8), RLK (3) and Others (28) categories. The CNL R genes formed eight clusters. Expression data for selected R genes also identified potential candidates for breeding of disease resistance traits. Furthermore, these findings can provide information about the species evolution as well as the identification of agronomically important genes in oil palm and other major crops. PMID:29672525

  2. Comparative genomic and transcriptomic analysis of selected fatty acid biosynthesis genes and CNL disease resistance genes in oil palm.

    Science.gov (United States)

    Rosli, Rozana; Amiruddin, Nadzirah; Ab Halim, Mohd Amin; Chan, Pek-Lan; Chan, Kuang-Lim; Azizi, Norazah; Morris, Priscilla E; Leslie Low, Eng-Ti; Ong-Abdullah, Meilina; Sambanthamurthi, Ravigadevi; Singh, Rajinder; Murphy, Denis J

    2018-01-01

    Comparative genomics and transcriptomic analyses were performed on two agronomically important groups of genes from oil palm versus other major crop species and the model organism, Arabidopsis thaliana. The first analysis was of two gene families with key roles in regulation of oil quality and in particular the accumulation of oleic acid, namely stearoyl ACP desaturases (SAD) and acyl-acyl carrier protein (ACP) thioesterases (FAT). In both cases, these were found to be large gene families with complex expression profiles across a wide range of tissue types and developmental stages. The detailed classification of the oil palm SAD and FAT genes has enabled the updating of the latest version of the oil palm gene model. The second analysis focused on disease resistance (R) genes in order to elucidate possible candidates for breeding of pathogen tolerance/resistance. Ortholog analysis showed that 141 out of the 210 putative oil palm R genes had homologs in banana and rice. These genes formed 37 clusters with 634 orthologous genes. Classification of the 141 oil palm R genes showed that the genes belong to the Kinase (7), CNL (95), MLO-like (8), RLK (3) and Others (28) categories. The CNL R genes formed eight clusters. Expression data for selected R genes also identified potential candidates for breeding of disease resistance traits. Furthermore, these findings can provide information about the species evolution as well as the identification of agronomically important genes in oil palm and other major crops.

  3. Novel method to load multiple genes onto a mammalian artificial chromosome.

    Science.gov (United States)

    Tóth, Anna; Fodor, Katalin; Praznovszky, Tünde; Tubak, Vilmos; Udvardy, Andor; Hadlaczky, Gyula; Katona, Robert L

    2014-01-01

    Mammalian artificial chromosomes are natural chromosome-based vectors that may carry a vast amount of genetic material in terms of both size and number. They are reasonably stable and segregate well in both mitosis and meiosis. A platform artificial chromosome expression system (ACEs) was earlier described with multiple loading sites for a modified lambda-integrase enzyme. It has been shown that this ACEs is suitable for high-level industrial protein production and the treatment of a mouse model for a devastating human disorder, Krabbe's disease. ACEs-treated mutant mice carrying a therapeutic gene lived more than four times longer than untreated counterparts. This novel gene therapy method is called combined mammalian artificial chromosome-stem cell therapy. At present, this method suffers from the limitation that a new selection marker gene should be present for each therapeutic gene loaded onto the ACEs. Complex diseases require the cooperative action of several genes for treatment, but only a limited number of selection marker genes are available and there is also a risk of serious side-effects caused by the unwanted expression of these marker genes in mammalian cells, organs and organisms. We describe here a novel method to load multiple genes onto the ACEs by using only two selectable marker genes. These markers may be removed from the ACEs before therapeutic application. This novel technology could revolutionize gene therapeutic applications targeting the treatment of complex disorders and cancers. It could also speed up cell therapy by allowing researchers to engineer a chromosome with a predetermined set of genetic factors to differentiate adult stem cells, embryonic stem cells and induced pluripotent stem (iPS) cells into cell types of therapeutic value. It is also a suitable tool for the investigation of complex biochemical pathways in basic science by producing an ACEs with several genes from a signal transduction pathway of interest.

  4. Novel method to load multiple genes onto a mammalian artificial chromosome.

    Directory of Open Access Journals (Sweden)

    Anna Tóth

    Full Text Available Mammalian artificial chromosomes are natural chromosome-based vectors that may carry a vast amount of genetic material in terms of both size and number. They are reasonably stable and segregate well in both mitosis and meiosis. A platform artificial chromosome expression system (ACEs was earlier described with multiple loading sites for a modified lambda-integrase enzyme. It has been shown that this ACEs is suitable for high-level industrial protein production and the treatment of a mouse model for a devastating human disorder, Krabbe's disease. ACEs-treated mutant mice carrying a therapeutic gene lived more than four times longer than untreated counterparts. This novel gene therapy method is called combined mammalian artificial chromosome-stem cell therapy. At present, this method suffers from the limitation that a new selection marker gene should be present for each therapeutic gene loaded onto the ACEs. Complex diseases require the cooperative action of several genes for treatment, but only a limited number of selection marker genes are available and there is also a risk of serious side-effects caused by the unwanted expression of these marker genes in mammalian cells, organs and organisms. We describe here a novel method to load multiple genes onto the ACEs by using only two selectable marker genes. These markers may be removed from the ACEs before therapeutic application. This novel technology could revolutionize gene therapeutic applications targeting the treatment of complex disorders and cancers. It could also speed up cell therapy by allowing researchers to engineer a chromosome with a predetermined set of genetic factors to differentiate adult stem cells, embryonic stem cells and induced pluripotent stem (iPS cells into cell types of therapeutic value. It is also a suitable tool for the investigation of complex biochemical pathways in basic science by producing an ACEs with several genes from a signal transduction pathway of interest.

  5. Comparative GO: a web application for comparative gene ontology and gene ontology-based gene selection in bacteria.

    Directory of Open Access Journals (Sweden)

    Mario Fruzangohar

    Full Text Available The primary means of classifying new functions for genes and proteins relies on Gene Ontology (GO, which defines genes/proteins using a controlled vocabulary in terms of their Molecular Function, Biological Process and Cellular Component. The challenge is to present this information to researchers to compare and discover patterns in multiple datasets using visually comprehensible and user-friendly statistical reports. Importantly, while there are many GO resources available for eukaryotes, there are none suitable for simultaneous, graphical and statistical comparison between multiple datasets. In addition, none of them supports comprehensive resources for bacteria. By using Streptococcus pneumoniae as a model, we identified and collected GO resources including genes, proteins, taxonomy and GO relationships from NCBI, UniProt and GO organisations. Then, we designed database tables in PostgreSQL database server and developed a Java application to extract data from source files and loaded into database automatically. We developed a PHP web application based on Model-View-Control architecture, used a specific data structure as well as current and novel algorithms to estimate GO graphs parameters. We designed different navigation and visualization methods on the graphs and integrated these into graphical reports. This tool is particularly significant when comparing GO groups between multiple samples (including those of pathogenic bacteria from different sources simultaneously. Comparing GO protein distribution among up- or down-regulated genes from different samples can improve understanding of biological pathways, and mechanism(s of infection. It can also aid in the discovery of genes associated with specific function(s for investigation as a novel vaccine or therapeutic targets.http://turing.ersa.edu.au/BacteriaGO.

  6. A high efficiency gene disruption strategy using a positive-negative split selection marker and electroporation for Fusarium oxysporum.

    Science.gov (United States)

    Liang, Liqin; Li, Jianqiang; Cheng, Lin; Ling, Jian; Luo, Zhongqin; Bai, Miao; Xie, Bingyan

    2014-11-01

    The Fusarium oxysporum species complex consists of fungal pathogens that cause serial vascular wilt disease on more than 100 cultivated species throughout the world. Gene function analysis is rapidly becoming more and more important as the whole-genome sequences of various F. oxysporum strains are being completed. Gene-disruption techniques are a common molecular tool for studying gene function, yet are often a limiting step in gene function identification. In this study we have developed a F. oxysporum high-efficiency gene-disruption strategy based on split-marker homologous recombination cassettes with dual selection and electroporation transformation. The method was efficiently used to delete three RNA-dependent RNA polymerase (RdRP) genes. The gene-disruption cassettes of three genes can be constructed simultaneously within a short time using this technique. The optimal condition for electroporation is 10μF capacitance, 300Ω resistance, 4kV/cm field strength, with 1μg of DNA (gene-disruption cassettes). Under these optimal conditions, we were able to obtain 95 transformants per μg DNA. And after positive-negative selection, the transformants were efficiently screened by PCR, screening efficiency averaged 85%: 90% (RdRP1), 85% (RdRP2) and 77% (RdRP3). This gene-disruption strategy should pave the way for high throughout genetic analysis in F. oxysporum. Copyright © 2014 Elsevier GmbH. All rights reserved.

  7. Actin gene identification from selected medicinal plants for their use as internal controls for gene expression studies

    International Nuclear Information System (INIS)

    Mufti, F.U.D.; Banaras, S.

    2015-01-01

    Internal control genes are the constitutive genes which maintain the basic cellular functions and regularly express in both normal and stressed conditions in living organisms. They are used in normalization of gene expression studies in comparative analysis of target genes, as their expression remains comparatively unchanged in all varied conditions. Among internal control genes, actin is considered as a candidate gene for expression studies due to its vital role in shaping cytoskeleton and plant physiology. Unfortunately most of such knowledge is limited to only model plants or crops, not much is known about important medicinal plants. Therefore, we selected seven important medicinal wild plants for molecular identification of actin gene. We used gene specific primers designed from the conserved regions of several known orthologues or homologues of actin genes from other plants. The amplified products of 370-380 bp were sequenced and submitted to GeneBank after their confirmation using different bioinformatics tools. All the novel partial sequences of putative actin genes were submitted to GeneBank (Parthenium hysterophorus (KJ774023), Fagonia indica (KJ774024), Rhazya stricta (KJ774025), Whithania coagulans (KJ774026), Capparis decidua (KJ774027), Verbena officinalis (KJ774028) and Aerva javanica (KJ774029)). The comparisons of these partial sequences by Basic Local Alignment Search Tool (BLAST) and phylogenetic trees demonstrated high similarity with known actin genes of other plants. Our findings illustrated highly conserved nature of actin gene among these selected plants. These novel partial fragments of actin genes from these wild medicinal plants can be used as internal controls for future gene expression studies of these important plants after precise validations of their stable expression in such plants. (author)

  8. Flexible metabolic pathway construction using modular and divisible selection gene regulators

    DEFF Research Database (Denmark)

    Rugbjerg, Peter; Myling-Petersen, Nils; Sommer, Morten Otto Alexander

    2015-01-01

    Genetic selections are important to biological engineering. Although selectable traits are limited,currently each trait only permits simultaneous introduction of a single DNA fragment. Complex pathwayand strain construction however depends on rapid, combinatorial introduction of many genes thaten...

  9. Selection of industrial robots using the Polygons area method

    Directory of Open Access Journals (Sweden)

    Mortaza Honarmande Azimi

    2014-08-01

    Full Text Available Selection of robots from the several proposed alternatives is a very important and tedious task. Decision makers are not limited to one method and several methods have been proposed for solving this problem. This study presents Polygons Area Method (PAM as a multi attribute decision making method for robot selection problem. In this method, the maximum polygons area obtained from the attributes of an alternative robot on the radar chart is introduced as a decision-making criterion. The results of this method are compared with other typical multiple attribute decision-making methods (SAW, WPM, TOPSIS, and VIKOR by giving two examples. To find similarity in ranking given by different methods, Spearman’s rank correlation coefficients are obtained for different pairs of MADM methods. It was observed that the introduced method is in good agreement with other well-known MADM methods in the robot selection problem.

  10. Selected methods of rehabilitation in systemic sclerosis

    Directory of Open Access Journals (Sweden)

    Agnieszka Gerkowicz

    2017-09-01

    Full Text Available Systemic sclerosis is a chronic connective tissue disease characterized by microvascular abnormalities, immune disturbances and progressive fibrosis of the skin and internal organs. Skin involvement may result in contractures, leading to marked loss of hand mobility, adversely affecting the performance of daily activities and decreasing the quality of life. Face involvement not only causes functional loss, but also lowers the self-esteem of patients. Increasing attention has recently been focused on the need to rehabilitate patients with systemic sclerosis in order to prevent the development of joint contractures and loss of mobility. The study presents a review of the current literature on rehabilitation possibilities in patients with systemic sclerosis, with a special focus on physiotherapy methods.

  11. A new electrospray method for targeted gene delivery.

    Science.gov (United States)

    Boehringer, Stephan; Ruzgys, Paulius; Tamò, Luca; Šatkauskas, Saulius; Geiser, Thomas; Gazdhar, Amiq; Hradetzky, David

    2018-03-05

    A challenge for gene therapy is absence of safe and efficient local delivery of therapeutic genetic material. An efficient and reproducible physical method of electrospray for localized and targeted gene delivery is presented. Electrospray works on the principle of coulombs repulsion, under influence of electric field the liquid carrying genetic material is dispersed into micro droplets and is accelerated towards the targeted tissue, acting as a counter electrode. The accelerated droplets penetrate the targeted cells thus facilitating the transfer of genetic material into the cell. The work described here presents the principle of electrospray for gene delivery, the basic instrument design, and the various optimized parameters to enhance gene transfer in vitro. We estimate a transfection efficiency of up to 60% was achieved. We describe an efficient gene transfer method and a potential electrospray-mediated gene transfer mechanism.

  12. Network-Based Method for Identifying Co- Regeneration Genes in Bone, Dentin, Nerve and Vessel Tissues.

    Science.gov (United States)

    Chen, Lei; Pan, Hongying; Zhang, Yu-Hang; Feng, Kaiyan; Kong, XiangYin; Huang, Tao; Cai, Yu-Dong

    2017-10-02

    Bone and dental diseases are serious public health problems. Most current clinical treatments for these diseases can produce side effects. Regeneration is a promising therapy for bone and dental diseases, yielding natural tissue recovery with few side effects. Because soft tissues inside the bone and dentin are densely populated with nerves and vessels, the study of bone and dentin regeneration should also consider the co-regeneration of nerves and vessels. In this study, a network-based method to identify co-regeneration genes for bone, dentin, nerve and vessel was constructed based on an extensive network of protein-protein interactions. Three procedures were applied in the network-based method. The first procedure, searching, sought the shortest paths connecting regeneration genes of one tissue type with regeneration genes of other tissues, thereby extracting possible co-regeneration genes. The second procedure, testing, employed a permutation test to evaluate whether possible genes were false discoveries; these genes were excluded by the testing procedure. The last procedure, screening, employed two rules, the betweenness ratio rule and interaction score rule, to select the most essential genes. A total of seventeen genes were inferred by the method, which were deemed to contribute to co-regeneration of at least two tissues. All these seventeen genes were extensively discussed to validate the utility of the method.

  13. Two-Way Gene Interaction From Microarray Data Based on Correlation Methods.

    Science.gov (United States)

    Alavi Majd, Hamid; Talebi, Atefeh; Gilany, Kambiz; Khayyer, Nasibeh

    2016-06-01

    Gene networks have generated a massive explosion in the development of high-throughput techniques for monitoring various aspects of gene activity. Networks offer a natural way to model interactions between genes, and extracting gene network information from high-throughput genomic data is an important and difficult task. The purpose of this study is to construct a two-way gene network based on parametric and nonparametric correlation coefficients. The first step in constructing a Gene Co-expression Network is to score all pairs of gene vectors. The second step is to select a score threshold and connect all gene pairs whose scores exceed this value. In the foundation-application study, we constructed two-way gene networks using nonparametric methods, such as Spearman's rank correlation coefficient and Blomqvist's measure, and compared them with Pearson's correlation coefficient. We surveyed six genes of venous thrombosis disease, made a matrix entry representing the score for the corresponding gene pair, and obtained two-way interactions using Pearson's correlation, Spearman's rank correlation, and Blomqvist's coefficient. Finally, these methods were compared with Cytoscape, based on BIND, and Gene Ontology, based on molecular function visual methods; R software version 3.2 and Bioconductor were used to perform these methods. Based on the Pearson and Spearman correlations, the results were the same and were confirmed by Cytoscape and GO visual methods; however, Blomqvist's coefficient was not confirmed by visual methods. Some results of the correlation coefficients are not the same with visualization. The reason may be due to the small number of data.

  14. EEG feature selection method based on decision tree.

    Science.gov (United States)

    Duan, Lijuan; Ge, Hui; Ma, Wei; Miao, Jun

    2015-01-01

    This paper aims to solve automated feature selection problem in brain computer interface (BCI). In order to automate feature selection process, we proposed a novel EEG feature selection method based on decision tree (DT). During the electroencephalogram (EEG) signal processing, a feature extraction method based on principle component analysis (PCA) was used, and the selection process based on decision tree was performed by searching the feature space and automatically selecting optimal features. Considering that EEG signals are a series of non-linear signals, a generalized linear classifier named support vector machine (SVM) was chosen. In order to test the validity of the proposed method, we applied the EEG feature selection method based on decision tree to BCI Competition II datasets Ia, and the experiment showed encouraging results.

  15. Construction and applications of exon-trapping gene-targeting vectors with a novel strategy for negative selection.

    Science.gov (United States)

    Saito, Shinta; Ura, Kiyoe; Kodama, Miho; Adachi, Noritaka

    2015-06-30

    Targeted gene modification by homologous recombination provides a powerful tool for studying gene function in cells and animals. In higher eukaryotes, non-homologous integration of targeting vectors occurs several orders of magnitude more frequently than does targeted integration, making the gene-targeting technology highly inefficient. For this reason, negative-selection strategies have been employed to reduce the number of drug-resistant clones associated with non-homologous vector integration, particularly when artificial nucleases to introduce a DNA break at the target site are unavailable or undesirable. As such, an exon-trap strategy using a promoterless drug-resistance marker gene provides an effective way to counterselect non-homologous integrants. However, constructing exon-trapping targeting vectors has been a time-consuming and complicated process. By virtue of highly efficient att-mediated recombination, we successfully developed a simple and rapid method to construct plasmid-based vectors that allow for exon-trapping gene targeting. These exon-trap vectors were useful in obtaining correctly targeted clones in mouse embryonic stem cells and human HT1080 cells. Most importantly, with the use of a conditionally cytotoxic gene, we further developed a novel strategy for negative selection, thereby enhancing the efficiency of counterselection for non-homologous integration of exon-trap vectors. Our methods will greatly facilitate exon-trapping gene-targeting technologies in mammalian cells, particularly when combined with the novel negative selection strategy.

  16. A copula method for modeling directional dependence of genes

    Directory of Open Access Journals (Sweden)

    Park Changyi

    2008-05-01

    Full Text Available Abstract Background Genes interact with each other as basic building blocks of life, forming a complicated network. The relationship between groups of genes with different functions can be represented as gene networks. With the deposition of huge microarray data sets in public domains, study on gene networking is now possible. In recent years, there has been an increasing interest in the reconstruction of gene networks from gene expression data. Recent work includes linear models, Boolean network models, and Bayesian networks. Among them, Bayesian networks seem to be the most effective in constructing gene networks. A major problem with the Bayesian network approach is the excessive computational time. This problem is due to the interactive feature of the method that requires large search space. Since fitting a model by using the copulas does not require iterations, elicitation of the priors, and complicated calculations of posterior distributions, the need for reference to extensive search spaces can be eliminated leading to manageable computational affords. Bayesian network approach produces a discretely expression of conditional probabilities. Discreteness of the characteristics is not required in the copula approach which involves use of uniform representation of the continuous random variables. Our method is able to overcome the limitation of Bayesian network method for gene-gene interaction, i.e. information loss due to binary transformation. Results We analyzed the gene interactions for two gene data sets (one group is eight histone genes and the other group is 19 genes which include DNA polymerases, DNA helicase, type B cyclin genes, DNA primases, radiation sensitive genes, repaire related genes, replication protein A encoding gene, DNA replication initiation factor, securin gene, nucleosome assembly factor, and a subunit of the cohesin complex by adopting a measure of directional dependence based on a copula function. We have compared

  17. The utility of optical detection system (qPCR) and bioinformatics methods in reference gene expression analysis

    Science.gov (United States)

    Skarzyńska, Agnieszka; Pawełkowicz, Magdalena; PlÄ der, Wojciech; Przybecki, Zbigniew

    2016-09-01

    Real-time quantitative polymerase chain reaction is consider as the most reliable method for gene expression studies. However, the expression of target gene could be misinterpreted due to improper normalization. Therefore, the crucial step for analysing of qPCR data is selection of suitable reference genes, which should be validated experimentally. In order to choice the gene with stable expression in the designed experiment, we performed reference gene expression analysis. In this study genes described in the literature and novel genes predicted as control genes, based on the in silico analysis of transcriptome data were used. Analysis with geNorm and NormFinder algorithms allow to create the ranking of candidate genes and indicate the best reference for flower morphogenesis study. According to the results, genes CACS and CYCL were characterised the most stable expression, but the least suitable genes were TUA and EF.

  18. Methods for producing thin film charge selective transport layers

    Science.gov (United States)

    Hammond, Scott Ryan; Olson, Dana C.; van Hest, Marinus Franciscus Antonius Maria

    2018-01-02

    Methods for producing thin film charge selective transport layers are provided. In one embodiment, a method for forming a thin film charge selective transport layer comprises: providing a precursor solution comprising a metal containing reactive precursor material dissolved into a complexing solvent; depositing the precursor solution onto a surface of a substrate to form a film; and forming a charge selective transport layer on the substrate by annealing the film.

  19. Selection on the Major Color Gene Melanocortin-1-Receptor Shaped the Evolution of the Melanocortin System Genes

    Directory of Open Access Journals (Sweden)

    Linda Dib

    2017-12-01

    Full Text Available Modular genetic systems and networks have complex evolutionary histories shaped by selection acting on single genes as well as on their integrated function within the network. However, uncovering molecular coevolution requires the detection of coevolving sites in sequences. Detailed knowledge of the functions of each gene in the system is also necessary to identify the selective agents driving coevolution. Using recently developed computational tools, we investigated the effect of positive selection on the coevolution of ten major genes in the melanocortin system, responsible for multiple physiological functions and human diseases. Substitutions driven by positive selection at the melanocortin-1-receptor (MC1R induced more coevolutionary changes on the system than positive selection on other genes in the system. Contrarily, selection on the highly pleiotropic POMC gene, which orchestrates the activation of the different melanocortin receptors, had the lowest coevolutionary influence. MC1R and possibly its main function, melanin pigmentation, seems to have influenced the evolution of the melanocortin system more than functions regulated by MC2-5Rs such as energy homeostasis, glucocorticoid-dependent stress and anti-inflammatory responses. Although replication in other regulatory systems is needed, this suggests that single functional aspects of a genetic network or system can be of higher importance than others in shaping coevolution among the genes that integrate it.

  20. Cartilage-selective genes identified in genome-scale analysis of non-cartilage and cartilage gene expression

    Directory of Open Access Journals (Sweden)

    Cohn Zachary A

    2007-06-01

    Full Text Available Abstract Background Cartilage plays a fundamental role in the development of the human skeleton. Early in embryogenesis, mesenchymal cells condense and differentiate into chondrocytes to shape the early skeleton. Subsequently, the cartilage anlagen differentiate to form the growth plates, which are responsible for linear bone growth, and the articular chondrocytes, which facilitate joint function. However, despite the multiplicity of roles of cartilage during human fetal life, surprisingly little is known about its transcriptome. To address this, a whole genome microarray expression profile was generated using RNA isolated from 18–22 week human distal femur fetal cartilage and compared with a database of control normal human tissues aggregated at UCLA, termed Celsius. Results 161 cartilage-selective genes were identified, defined as genes significantly expressed in cartilage with low expression and little variation across a panel of 34 non-cartilage tissues. Among these 161 genes were cartilage-specific genes such as cartilage collagen genes and 25 genes which have been associated with skeletal phenotypes in humans and/or mice. Many of the other cartilage-selective genes do not have established roles in cartilage or are novel, unannotated genes. Quantitative RT-PCR confirmed the unique pattern of gene expression observed by microarray analysis. Conclusion Defining the gene expression pattern for cartilage has identified new genes that may contribute to human skeletogenesis as well as provided further candidate genes for skeletal dysplasias. The data suggest that fetal cartilage is a complex and transcriptionally active tissue and demonstrate that the set of genes selectively expressed in the tissue has been greatly underestimated.

  1. A general method for identifying major hybrid male sterility genes in Drosophila.

    Science.gov (United States)

    Zeng, L W; Singh, R S

    1995-10-01

    The genes responsible for hybrid male sterility in species crosses are usually identified by introgressing chromosome segments, monitored by visible markers, between closely related species by continuous backcrosses. This commonly used method, however, suffers from two problems. First, it relies on the availability of markers to monitor the introgressed regions and so the portion of the genome examined is limited to the marked regions. Secondly, the introgressed regions are usually large and it is impossible to tell if the effects of the introgressed regions are the result of single (or few) major genes or many minor genes (polygenes). Here we introduce a simple and general method for identifying putative major hybrid male sterility genes which is free of these problems. In this method, the actual hybrid male sterility genes (rather than markers), or tightly linked gene complexes with large effects, are selectively introgressed from one species into the background of another species by repeated backcrosses. This is performed by selectively backcrossing heterozygous (for hybrid male sterility gene or genes) females producing fertile and sterile sons in roughly equal proportions to males of either parental species. As no marker gene is required for this procedure, this method can be used with any species pairs that produce unisexual sterility. With the application of this method, a small X chromosome region of Drosophila mauritiana which produces complete hybrid male sterility (aspermic testes) in the background of D. simulans was identified. Recombination analysis reveals that this region contains a second major hybrid male sterility gene linked to the forked locus located at either 62.7 +/- 0.66 map units or at the centromere region of the X chromosome of D. mauritiana.

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

    Directory of Open Access Journals (Sweden)

    Ali Oghabian

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

  3. Status of clean gene (selection marker-free)technology | Afolabi ...

    African Journals Online (AJOL)

    ... (2) site-specific recombination systems and (3) intra-chromosomal recombination. (B) Gene replacement or Targeted gene replacement; and (C) transformation with multiple T-DNAs, which could result in linked and/or unlinked co-integration of transgenes. Unlinked transgenes are then segregated out during meiosis.

  4. Empirical Bayes ranking and selection methods via semiparametric hierarchical mixture models in microarray studies.

    Science.gov (United States)

    Noma, Hisashi; Matsui, Shigeyuki

    2013-05-20

    The main purpose of microarray studies is screening of differentially expressed genes as candidates for further investigation. Because of limited resources in this stage, prioritizing genes are relevant statistical tasks in microarray studies. For effective gene selections, parametric empirical Bayes methods for ranking and selection of genes with largest effect sizes have been proposed (Noma et al., 2010; Biostatistics 11: 281-289). The hierarchical mixture model incorporates the differential and non-differential components and allows information borrowing across differential genes with separation from nuisance, non-differential genes. In this article, we develop empirical Bayes ranking methods via a semiparametric hierarchical mixture model. A nonparametric prior distribution, rather than parametric prior distributions, for effect sizes is specified and estimated using the "smoothing by roughening" approach of Laird and Louis (1991; Computational statistics and data analysis 12: 27-37). We present applications to childhood and infant leukemia clinical studies with microarrays for exploring genes related to prognosis or disease progression. Copyright © 2012 John Wiley & Sons, Ltd.

  5. A Selective Review of Multimodal Fusion Methods in Schizophrenia

    Directory of Open Access Journals (Sweden)

    Jing eSui

    2012-02-01

    Full Text Available Schizophrenia (SZ is one of the most cryptic and costly mental disorders in terms of human suffering and societal expenditure (van Os and Kapur, 2009. Though strong evidences for functional, structural and genetic abnormalities associated with this disease exist, there is yet no replicable finding which has proven accurate enough to be useful in clinical decision making (Fornito et al., 2009, and its diagnosis relies primarily upon symptom assessment (Williams et al., 2010a. It is likely in part that the lack of consistent neuroimaging findings is because most models favor only one data type or do not combine data from different imaging modalities effectively, thus missing potentially important differences which are only partially detected by each modality (Calhoun et al., 2006a. It is becoming increasingly clear that multi-modal fusion, a technique which takes advantage of the fact that each modality provides a limited view of the brain/gene and may uncover hidden relationships, is an important tool to help unravel the black box of schizophrenia. In this review paper, we survey a number of multimodal fusion applications which enable us to study the schizophrenia macro-connectome, including brain functional, structural and genetic aspects and may help us understand the disorder in a more comprehensive and integrated manner. We also provide a table that characterizes these applications by the methods used and compare these methods in detail, especially for multivariate models, which may serve as a valuable reference that helps readers select an appropriate method based on a given research.

  6. Allopatric integrations selectively change host transcriptomes, leading to varied expression efficiencies of exotic genes in Myxococcus xanthus.

    Science.gov (United States)

    Zhu, Li-Ping; Yue, Xin-Jing; Han, Kui; Li, Zhi-Feng; Zheng, Lian-Shuai; Yi, Xiu-Nan; Wang, Hai-Long; Zhang, You-Ming; Li, Yue-Zhong

    2015-07-22

    Exotic genes, especially clustered multiple-genes for a complex pathway, are normally integrated into chromosome for heterologous expression. The influences of insertion sites on heterologous expression and allotropic expressions of exotic genes on host remain mostly unclear. We compared the integration and expression efficiencies of single and multiple exotic genes that were inserted into Myxococcus xanthus genome by transposition and attB-site-directed recombination. While the site-directed integration had a rather stable chloramphenicol acetyl transferase (CAT) activity, the transposition produced varied CAT enzyme activities. We attempted to integrate the 56-kb gene cluster for the biosynthesis of antitumor polyketides epothilones into M. xanthus genome by site-direction but failed, which was determined to be due to the insertion size limitation at the attB site. The transposition technique produced many recombinants with varied production capabilities of epothilones, which, however, were not paralleled to the transcriptional characteristics of the local sites where the genes were integrated. Comparative transcriptomics analysis demonstrated that the allopatric integrations caused selective changes of host transcriptomes, leading to varied expressions of epothilone genes in different mutants. With the increase of insertion fragment size, transposition is a more practicable integration method for the expression of exotic genes. Allopatric integrations selectively change host transcriptomes, which lead to varied expression efficiencies of exotic genes.

  7. Inventory of LCIA selection methods for assessing toxic releases. Methods and typology report part B

    DEFF Research Database (Denmark)

    Larsen, Henrik Fred; Birkved, Morten; Hauschild, Michael Zwicky

    method(s) in Work package 8 (WP8) of the OMNIITOX project. The selection methods and the other CRS methods are described in detail, a set of evaluation criteria are developed and the methods are evaluated against these criteria. This report (Deliverable 11B (D11B)) gives the results from task 7.1d, 7.1e......This report describes an inventory of Life Cycle Impact Assessment (LCIA) selection methods for assessing toxic releases. It consists of an inventory of current selection methods and other Chemical Ranking and Scoring (CRS) methods assessed to be relevant for the development of (a) new selection...... and 7.1f of WP 7 for selection methods. The other part of D11 (D11A) is reported in another report and deals with characterisation methods. A selection method is a method for prioritising chemical emissions to be included in an LCIA characterisation of toxic releases, i.e. calculating indicator scores...

  8. Positive selection in the SLC11A1 gene in the family Equidae

    DEFF Research Database (Denmark)

    Bayerova, Zuzana; Janova, Eva; Matiasovic, Jan

    2016-01-01

    Immunity-related genes are a suitable model for studying effects of selection at the genomic level. Some of them are highly conserved due to functional constraints and purifying selection, while others are variable and change quickly to cope with the variation of pathogens. The SLC11A1 gene encodes...... a transporter protein mediating antimicrobial activity of macrophages. Little is known about the patterns of selection shaping this gene during evolution. Although it is a typical evolutionarily conserved gene, functionally important polymorphisms associated with various diseases were identified in humans...... and other species. We analyzed the genomic organization, genetic variation, and evolution of the SLC11A1 gene in the family Equidae to identify patterns of selection within this important gene. Nucleotide SLC11A1 sequences were shown to be highly conserved in ten equid species, with more than 97 % sequence...

  9. Selection and validation of endogenous reference genes for qRT-PCR analysis in leafy spurge (Euphorbia esula.

    Directory of Open Access Journals (Sweden)

    Wun S Chao

    Full Text Available Quantitative real-time polymerase chain reaction (qRT-PCR is the most important tool in measuring levels of gene expression due to its accuracy, specificity, and sensitivity. However, the accuracy of qRT-PCR analysis strongly depends on transcript normalization using stably expressed reference genes. The aim of this study was to find internal reference genes for qRT-PCR analysis in various experimental conditions for seed, adventitious underground bud, and other organs of leafy spurge. Eleven candidate reference genes (BAM4, PU1, TRP-like, FRO1, ORE9, BAM1, SEU, ARF2, KAPP, ZTL, and MPK4 were selected from among 171 genes based on expression stabilities during seed germination and bud growth. The other ten candidate reference genes were selected from three different sources: (1 3 stably expressed leafy spurge genes (60S, bZIP21, and MD-100 identified from the analyses of leafy spurge microarray data; (2 3 orthologs of Arabidopsis "general purpose" traditional reference genes (GAPDH_1, GAPDH_2, and UBC; and (3 4 orthologs of Arabidopsis stably expressed genes (UBC9, SAND, PTB, and F-box identified from Affymetrix ATH1 whole-genome GeneChip studies. The expression stabilities of these 21 genes were ranked based on the C(T values of 72 samples using four different computation programs including geNorm, Normfinder, BestKeeper, and the comparative ΔC(T method. Our analyses revealed SAND, PTB, ORE9, and ARF2 to be the most appropriate reference genes for accurate normalization of gene expression data. Since SAND and PTB were obtained from 4 orthologs of Arabidopsis, while ORE9 and ARF2 were selected from 171 leafy spurge genes, it was more efficient to identify good reference genes from the orthologs of other plant species that were known to be stably expressed than that of randomly testing endogenous genes. Nevertheless, the two newly identified leafy spurge genes, ORE9 and ARF2, can serve as orthologous candidates in the search for reference genes

  10. Selecting patients with young-onset colorectal cancer for mismatch repair gene analysis

    DEFF Research Database (Denmark)

    Walker, M; O'Sullivan, B; Perakath, B

    2007-01-01

    BACKGROUND: Young patients with colorectal cancer are at increased risk of carrying a germline mutation in mismatch repair (MMR) genes. This study investigated the role of clinical criteria and immunohistochemistry for MMR proteins in selecting young patients for mutation testing. METHODS: A cohort...... of 56 consecutive patients with colorectal cancer aged less than 45 years were stratified into three groups based on clinical criteria: 'Amsterdam criteria', 'high risk' and 'young onset only'. Immunohistochemistry for four MMR proteins was carried out and the rate of compliance with clinical guidelines...

  11. Selection and validation of reference genes for quantitative gene expression analyses in various tissues and seeds at different developmental stages in Bixa orellana L.

    Science.gov (United States)

    Moreira, Viviane S; Soares, Virgínia L F; Silva, Raner J S; Sousa, Aurizangela O; Otoni, Wagner C; Costa, Marcio G C

    2018-05-01

    Bixa orellana L., popularly known as annatto, produces several secondary metabolites of pharmaceutical and industrial interest, including bixin, whose molecular basis of biosynthesis remain to be determined. Gene expression analysis by quantitative real-time PCR (qPCR) is an important tool to advance such knowledge. However, correct interpretation of qPCR data requires the use of suitable reference genes in order to reduce experimental variations. In the present study, we have selected four different candidates for reference genes in B. orellana , coding for 40S ribosomal protein S9 (RPS9), histone H4 (H4), 60S ribosomal protein L38 (RPL38) and 18S ribosomal RNA (18SrRNA). Their expression stabilities in different tissues (e.g. flower buds, flowers, leaves and seeds at different developmental stages) were analyzed using five statistical tools (NormFinder, geNorm, BestKeeper, ΔCt method and RefFinder). The results indicated that RPL38 is the most stable gene in different tissues and stages of seed development and 18SrRNA is the most unstable among the analyzed genes. In order to validate the candidate reference genes, we have analyzed the relative expression of a target gene coding for carotenoid cleavage dioxygenase 1 (CCD1) using the stable RPL38 and the least stable gene, 18SrRNA , for normalization of the qPCR data. The results demonstrated significant differences in the interpretation of the CCD1 gene expression data, depending on the reference gene used, reinforcing the importance of the correct selection of reference genes for normalization.

  12. Evaluation of Gene-Based Family-Based Methods to Detect Novel Genes Associated With Familial Late Onset Alzheimer Disease

    Directory of Open Access Journals (Sweden)

    Maria V. Fernández

    2018-04-01

    Full Text Available Gene-based tests to study the combined effect of rare variants on a particular phenotype have been widely developed for case-control studies, but their evolution and adaptation for family-based studies, especially studies of complex incomplete families, has been slower. In this study, we have performed a practical examination of all the latest gene-based methods available for family-based study designs using both simulated and real datasets. We examined the performance of several collapsing, variance-component, and transmission disequilibrium tests across eight different software packages and 22 models utilizing a cohort of 285 families (N = 1,235 with late-onset Alzheimer disease (LOAD. After a thorough examination of each of these tests, we propose a methodological approach to identify, with high confidence, genes associated with the tested phenotype and we provide recommendations to select the best software and model for family-based gene-based analyses. Additionally, in our dataset, we identified PTK2B, a GWAS candidate gene for sporadic AD, along with six novel genes (CHRD, CLCN2, HDLBP, CPAMD8, NLRP9, and MAS1L as candidate genes for familial LOAD.

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

    Science.gov (United States)

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

  14. Relationship of Source Selection Methods to Contract Outcomes: an Analysis of Air Force Source Selection

    Science.gov (United States)

    2015-12-01

    some occasions, performance is terminated early; this can occur due to either mutual agreement or a breach of contract by one of the parties (Garrett...Relationship of Source Selection Methods to Contract Outcomes: an Analysis of Air Force Source Selection December 2015 Capt Jacques Lamoureux, USAF...on the contract management process, with special emphasis on the source selection methods of tradeoff and lowest price technically acceptable (LPTA

  15. A Fast Adaptive Receive Antenna Selection Method in MIMO System

    Directory of Open Access Journals (Sweden)

    Chaowei Wang

    2013-01-01

    Full Text Available Antenna selection has been regarded as an effective method to acquire the diversity benefits of multiple antennas while potentially reduce hardware costs. This paper focuses on receive antenna selection. According to the proportion between the numbers of total receive antennas and selected antennas and the influence of each antenna on system capacity, we propose a fast adaptive antenna selection algorithm for wireless multiple-input multiple-output (MIMO systems. Mathematical analysis and numerical results show that our algorithm significantly reduces the computational complexity and memory requirement and achieves considerable system capacity gain compared with the optimal selection technique in the same time.

  16. BRCA1-mediated repression of select X chromosome genes

    Directory of Open Access Journals (Sweden)

    Ropers H Hilger

    2004-09-01

    Full Text Available Abstract Recently BRCA1 has been implicated in the regulation of gene expression from the X chromosome. In this study the influence of BRCA1 on expression of X chromosome genes was investigated. Complementary DNA microarrays were used to compare the expression levels of X chromosome genes in 18 BRCA1-associated ovarian cancers to those of the 13 "BRCA1-like" and 14 "BRCA2-like" sporadic tumors (as defined by previously reported expression profiling. Significance was determined using parametric statistics with P

  17. Compositions and Methods for Inhibiting Gene Expressions

    Science.gov (United States)

    Williams, Loren D. (Inventor); Fang, Po-Yu (Inventor); Hsiao, Chiaolong (Inventor); Williams, Justin (Inventor)

    2018-01-01

    A combined packing and assembly method that efficiently packs ribonucleic acid (RNA) into virus like particles (VLPs) has been developed. The VLPs can spontaneously assemble and load RNA in vivo, efficiently packaging specifically designed RNAs at high densities and with high purity. In some embodiments the RNA is capable of interference activity, or is a precursor of a RNA capable of causing interference activity. Compositions and methods for the efficient expression, production and purification of VLP-RNAs are provided. VLP-RNAs can be used for the storage of RNA for long periods, and provide the ability to deliver RNA in stable form that is readily taken up by cells.

  18. Lack of direct evidence for natural selection at the candidate thrifty gene locus, PPARGC1A.

    Science.gov (United States)

    Cadzow, Murray; Merriman, Tony R; Boocock, James; Dalbeth, Nicola; Stamp, Lisa K; Black, Michael A; Visscher, Peter M; Wilcox, Phillip L

    2016-11-15

    The gene PPARGC1A, in particular the Gly482Ser variant (rs8192678), had been proposed to be subject to natural selection, particularly in recent progenitors of extant Polynesian populations. Reasons include high levels of population differentiation and increased frequencies of the derived type 2 diabetes (T2D) risk 482Ser allele, and association with body mass index (BMI) in a small Tongan population. However, no direct statistical tests for selection have been applied. Using a range of Polynesian populations (Tongan, Māori, Samoan) we re-examined evidence for association between Gly482Ser with T2D and BMI as well as gout. Using also Asian, European, and African 1000 Genome Project samples a range of statistical tests for selection (F ST , integrated haplotype score (iHS), cross population extended haplotype homozygosity (XP-EHH), Tajima's D and Fay and Wu's H) were conducted on the PPARGC1A locus. No statistically significant evidence for association between Gly482Ser and any of BMI, T2D or gout was found. Population differentiation (F ST ) was smallest between Asian and Pacific populations (New Zealand Māori ≤ 0.35, Samoan ≤ 0.20). When compared to European (New Zealand Māori ≤ 0.40, Samoan ≤ 0.25) or African populations (New Zealand Māori ≤ 0.80, Samoan ≤ 0.66) this differentiation was larger. We did not find any strong evidence for departure from neutral evolution at this locus when applying any of the other statistical tests for selection. However, using the same analytical methods, we found evidence for selection in specific populations at previously identified loci, indicating that lack of selection was the most likely explanation for the lack of evidence of selection in PPARGC1A. We conclude that there is no compelling evidence for selection at this locus, and that this gene should not be considered a candidate thrifty gene locus in Pacific populations. High levels of population differentiation at this locus and the

  19. Population Level Purifying Selection and Gene Expression Shape Subgenome Evolution in Maize.

    Science.gov (United States)

    Pophaly, Saurabh D; Tellier, Aurélien

    2015-12-01

    The maize ancestor experienced a recent whole-genome duplication (WGD) followed by gene erosion which generated two subgenomes, the dominant subgenome (maize1) experiencing fewer deletions than maize2. We take advantage of available extensive polymorphism and gene expression data in maize to study purifying selection and gene expression divergence between WGD retained paralog pairs. We first report a strong correlation in nucleotide diversity between duplicate pairs, except for upstream regions. We then show that maize1 genes are under stronger purifying selection than maize2. WGD retained genes have higher gene dosage and biased Gene Ontologies consistent with previous studies. The relative gene expression of paralogs across tissues demonstrates that 98% of duplicate pairs have either subfunctionalized in a tissuewise manner or have diverged consistently in their expression thereby preventing functional complementation. Tissuewise subfunctionalization seems to be a hallmark of transcription factors, whereas consistent repression occurs for macromolecular complexes. We show that dominant gene expression is a strong determinant of the strength of purifying selection, explaining the inferred stronger negative selection on maize1 genes. We propose a novel expression-based classification of duplicates which is more robust to explain observed polymorphism patterns than the subgenome location. Finally, upstream regions of repressed genes exhibit an enrichment in transposable elements which indicates a possible mechanism for expression divergence. © The Author 2015. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

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

    Directory of Open Access Journals (Sweden)

    Chris Cheadle

    2007-01-01

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

  1. Selection of relatively exact reference genes for gene expression studies in goosegrass (Eleusine indica) under herbicide stress.

    Science.gov (United States)

    Chen, Jingchao; Huang, Zhaofeng; Huang, Hongjuan; Wei, Shouhui; Liu, Yan; Jiang, Cuilan; Zhang, Jie; Zhang, Chaoxian

    2017-04-21

    Goosegrass (Eleusine indica) is one of the most serious annual grassy weeds worldwide, and its evolved herbicide-resistant populations are more difficult to control. Quantitative real-time PCR (qPCR) is a common technique for investigating the resistance mechanism; however, there is as yet no report on the systematic selection of stable reference genes for goosegrass. This study proposed to test the expression stability of 9 candidate reference genes in goosegrass in different tissues and developmental stages and under stress from three types of herbicide. The results show that for different developmental stages and organs (control), eukaryotic initiation factor 4 A (eIF-4) is the most stable reference gene. Chloroplast acetolactate synthase (ALS) is the most stable reference gene under glyphosate stress. Under glufosinate stress, eIF-4 is the best reference gene. Ubiquitin-conjugating enzyme (UCE) is the most stable reference gene under quizalofop-p-ethyl stress. The gene eIF-4 is the recommended reference gene for goosegrass under the stress of all three herbicides. Moreover, pairwise analysis showed that seven reference genes were sufficient to normalize the gene expression data under three herbicides treatment. This study provides a list of reliable reference genes for transcript normalization in goosegrass, which will facilitate resistance mechanism studies in this weed species.

  2. Adaptive L1/2 Shooting Regularization Method for Survival Analysis Using Gene Expression Data

    Directory of Open Access Journals (Sweden)

    Xiao-Ying Liu

    2013-01-01

    Full Text Available A new adaptive L1/2 shooting regularization method for variable selection based on the Cox’s proportional hazards mode being proposed. This adaptive L1/2 shooting algorithm can be easily obtained by the optimization of a reweighed iterative series of L1 penalties and a shooting strategy of L1/2 penalty. Simulation results based on high dimensional artificial data show that the adaptive L1/2 shooting regularization method can be more accurate for variable selection than Lasso and adaptive Lasso methods. The results from real gene expression dataset (DLBCL also indicate that the L1/2 regularization method performs competitively.

  3. Targeting of breast metastases using a viral gene vector with tumour-selective transcription.

    LENUS (Irish Health Repository)

    Rajendran, Simon

    2012-01-31

    BACKGROUND: Adeno-associated virus (AAV) vectors have significant potential as gene delivery vectors for cancer gene therapy. However, broad AAV2 tissue tropism results in nonspecific gene expression. MATERIALS AND METHODS: We investigated use of the C-X-C chemokine receptor type 4 (CXCR4) promoter to restrict AAV expression to tumour cells, in subcutaneous MCF-7 xenograft mouse models of breast cancer and in patient samples, using bioluminescent imaging and flow cytometric analysis. RESULTS: Higher transgene expression levels were observed in subcutaneous MCF-7 tumours relative to normal tissue (muscle) using the CXCR4 promoter, unlike a ubiquitously expressing Cytomegalovirus promoter construct, with preferential AAVCXCR4 expression in epithelial tumour and CXCR4-positive cells. Transgene expression following intravenously administered AAVCXCR4 in a model of liver metastasis was detected specifically in livers of tumour bearing mice. Ex vivo analysis using patient samples also demonstrated higher AAVCXCR4 expression in tumour compared with normal liver tissue. CONCLUSION: This study demonstrates for the first time, the potential for systemic administration of AAV2 vector for tumour-selective gene therapy.

  4. Alternative microbial methods: An overview and selection criteria.

    Science.gov (United States)

    Jasson, Vicky; Jacxsens, Liesbeth; Luning, Pieternel; Rajkovic, Andreja; Uyttendaele, Mieke

    2010-09-01

    This study provides an overview and criteria for the selection of a method, other than the reference method, for microbial analysis of foods. In a first part an overview of the general characteristics of rapid methods available, both for enumeration and detection, is given with reference to relevant bibliography. Perspectives on future development and the potential of the rapid method for routine application in food diagnostics are discussed. As various alternative "rapid" methods in different formats are available on the market, it can be very difficult for a food business operator or for a control authority to select the most appropriate method which fits its purpose. Validation of a method by a third party, according to international accepted protocol based upon ISO 16140, may increase the confidence in the performance of a method. A list of at the moment validated methods for enumeration of both utility indicators (aerobic plate count) and hygiene indicators (Enterobacteriaceae, Escherichia coli, coagulase positive Staphylococcus) as well as for detection of the four major pathogens (Salmonella spp., Listeria monocytogenes, E. coli O157 and Campylobacter spp.) is included with reference to relevant websites to check for updates. In a second part of this study, selection criteria are introduced to underpin the choice of the appropriate method(s) for a defined application. The selection criteria link the definition of the context in which the user of the method functions - and thus the prospective use of the microbial test results - with the technical information on the method and its operational requirements and sustainability. The selection criteria can help the end user of the method to obtain a systematic insight into all relevant factors to be taken into account for selection of a method for microbial analysis. Copyright 2010 Elsevier Ltd. All rights reserved.

  5. Adiponectin gene polymorphism is selectively associated with the concomitant presence of metabolic syndrome and essential hypertension.

    Directory of Open Access Journals (Sweden)

    Hsin-Bang Leu

    Full Text Available OBJECTIVE: Cardiovascular risk increases with the presence of both metabolic syndrome (MetS and hypertension (HTN. Although the adiponectin (ADIPOQ gene has been reported to be involved in MetS, its association with HTN remained undetermined. This study aimed to investigate the association of ADIPOQ gene with the phenotypes of HTN and MetS. METHODS: A total of 962 participants from 302 families from the Taiwan young-onset hypertension genetic study were enrolled. Plasma adiponectin were measured, and association analysis was conducted by using GEE regression-based method. Another study, of 1448 unrelated participants, was conducted to replicate the association between ADIPOQ gene and variable phenotypes of MetS with or without HTN. RESULTS: Among 962 subjects from family samples, the lowest plasma adiponectin value was observed in MetS with HTN component (9.3±0.47 µg/ml compared with hypertensives (13.4±0.74 µg /ml or MetS without HTN (11.9±0.60 µg/ml, P<0.05. The SNP rs1501299 (G276T in ADIPOQ gene was found associated with the presence of HTN in MetS (odds ratio for GG+GT vs. TT = 2.46; 95% CI: 1.14-5.3, p = 0.02, but not rs2241766 (T45G. No association of ADIPOQ gene with HTN alone or MetS without HTN was observed. The significant association of the SNP rs1501299 (G276T with the phenotype of presence of HTN in MetS was confirmed (odds ratio for GG+GT vs. TT = 2.15; 95% CI: 1.1-4.3 in the replication study. CONCLUSIONS: ADIPOQ genetic variants were selectively and specifically associated with the concomitant presence of MetS and HTN, suggesting potential genetic linkage between MetS and HTN.

  6. Selective Gene Delivery for Integrating Exogenous DNA into Plastid and Mitochondrial Genomes Using Peptide-DNA Complexes.

    Science.gov (United States)

    Yoshizumi, Takeshi; Oikawa, Kazusato; Chuah, Jo-Ann; Kodama, Yutaka; Numata, Keiji

    2018-05-14

    Selective gene delivery into organellar genomes (mitochondrial and plastid genomes) has been limited because of a lack of appropriate platform technology, even though these organelles are essential for metabolite and energy production. Techniques for selective organellar modification are needed to functionally improve organelles and produce transplastomic/transmitochondrial plants. However, no method for mitochondrial genome modification has yet been established for multicellular organisms including plants. Likewise, modification of plastid genomes has been limited to a few plant species and algae. In the present study, we developed ionic complexes of fusion peptides containing organellar targeting signal and plasmid DNA for selective delivery of exogenous DNA into the plastid and mitochondrial genomes of intact plants. This is the first report of exogenous DNA being integrated into the mitochondrial genomes of not only plants, but also multicellular organisms in general. This fusion peptide-mediated gene delivery system is a breakthrough platform for both plant organellar biotechnology and gene therapy for mitochondrial diseases in animals.

  7. Balancing selection on immunity genes: review of the current literature and new analysis in Drosophila melanogaster.

    Science.gov (United States)

    Croze, Myriam; Živković, Daniel; Stephan, Wolfgang; Hutter, Stephan

    2016-08-01

    Balancing selection has been widely assumed to be an important evolutionary force, yet even today little is known about its abundance and its impact on the patterns of genetic diversity. Several studies have shown examples of balancing selection in humans, plants or parasites, and many genes under balancing selection are involved in immunity. It has been proposed that host-parasite coevolution is one of the main forces driving immune genes to evolve under balancing selection. In this paper, we review the literature on balancing selection on immunity genes in several organisms, including Drosophila. Furthermore, we performed a genome scan for balancing selection in an African population of Drosophila melanogaster using coalescent simulations of a demographic model with and without selection. We find very few genes under balancing selection and only one novel candidate gene related to immunity. Finally, we discuss the possible causes of the low number of genes under balancing selection. Copyright © 2016 The Authors. Published by Elsevier GmbH.. All rights reserved.

  8. Alternative microbial methods: An overview and selection criteria.

    NARCIS (Netherlands)

    Jasson, V.; Jacxsens, L.; Luning, P.A.; Rajkovic, A.; Uyttendaele, M.

    2010-01-01

    This study provides an overview and criteria for the selection of a method, other than the reference method, for microbial analysis of foods. In a first part an overview of the general characteristics of rapid methods available, both for enumeration and detection, is given with reference to relevant

  9. The Hull Method for Selecting the Number of Common Factors

    Science.gov (United States)

    Lorenzo-Seva, Urbano; Timmerman, Marieke E.; Kiers, Henk A. L.

    2011-01-01

    A common problem in exploratory factor analysis is how many factors need to be extracted from a particular data set. We propose a new method for selecting the number of major common factors: the Hull method, which aims to find a model with an optimal balance between model fit and number of parameters. We examine the performance of the method in an…

  10. Orthogonal feature selection method. [For preprocessing of man spectral data

    Energy Technology Data Exchange (ETDEWEB)

    Kowalski, B R [Univ. of Washington, Seattle; Bender, C F

    1976-01-01

    A new method of preprocessing spectral data for extraction of molecular structural information is desired. This SELECT method generates orthogonal features that are important for classification purposes and that also retain their identity to the original measurements. A brief introduction to chemical pattern recognition is presented. A brief description of the method and an application to mass spectral data analysis follow. (BLM)

  11. B lymphocyte selection and age-related changes in VH gene usage in mutant Alicia rabbits.

    Science.gov (United States)

    Zhu, X; Boonthum, A; Zhai, S K; Knight, K L

    1999-09-15

    Young Alicia rabbits use VHa-negative genes, VHx and VHy, in most VDJ genes, and their serum Ig is VHa negative. However, as Alicia rabbits age, VHa2 allotype Ig is produced at high levels. We investigated which VH gene segments are used in the VDJ genes of a2 Ig-secreting hybridomas and of a2 Ig+ B cells from adult Alicia rabbits. We found that 21 of the 25 VDJ genes used the a2-encoding genes, VH4 or VH7; the other four VDJ genes used four unknown VH gene segments. Because VH4 and VH7 are rarely found in VDJ genes of normal or young Alicia rabbits, we investigated the timing of rearrangement of these genes in Alicia rabbits. During fetal development, VH4 was used in 60-80% of nonproductively rearranged VDJ genes, and VHx and VHy together were used in 10-26%. These data indicate that during B lymphopoiesis VH4 is preferentially rearranged. However, the percentage of productive VHx- and VHy-utilizing VDJ genes increased from 38% at day 21 of gestation to 89% at birth (gestation day 31), whereas the percentage of VH4-utilizing VDJ genes remained at 15%. These data suggest that during fetal development, either VH4-utilizing B-lineage cells are selectively eliminated, or B cells with VHx- and VHy-utilizing VDJ genes are selectively expanded, or both. The accumulation of peripheral VH4-utilizing a2 B cells with age indicates that these B cells might be selectively expanded in the periphery. We discuss the possible selection mechanisms that regulate VH gene segment usage in rabbit B cells during lymphopoiesis and in the periphery.

  12. A new screening method for selection of desired recombinant ...

    African Journals Online (AJOL)

    A new screening method for selection of desired recombinant plasmids in molecular cloning. ... African Journal of Biotechnology ... Regarding the facts of this study, after digestion process, the products directly were subjected to ligation. Due to ...

  13. Selection of Reference Genes for qRT-PCR Analysis of Gene Expression in Stipa grandis during Environmental Stresses.

    Directory of Open Access Journals (Sweden)

    Dongli Wan

    Full Text Available Stipa grandis P. Smirn. is a dominant plant species in the typical steppe of the Xilingole Plateau of Inner Mongolia. Selection of suitable reference genes for the quantitative real-time reverse transcription polymerase chain reaction (qRT-PCR is important for gene expression analysis and research into the molecular mechanisms underlying the stress responses of S. grandis. In the present study, 15 candidate reference genes (EF1 beta, ACT, GAPDH, SamDC, CUL4, CAP, SNF2, SKIP1, SKIP5, SKIP11, UBC2, UBC15, UBC17, UCH, and HERC2 were evaluated for their stability as potential reference genes for qRT-PCR under different stresses. Four algorithms were used: GeNorm, NormFinder, BestKeeper, and RefFinder. The results showed that the most stable reference genes were different under different stress conditions: EF1beta and UBC15 during drought and salt stresses; ACT and GAPDH under heat stress; SKIP5 and UBC17 under cold stress; UBC15 and HERC2 under high pH stress; UBC2 and UBC15 under wounding stress; EF1beta and UBC17 under jasmonic acid treatment; UBC15 and CUL4 under abscisic acid treatment; and HERC2 and UBC17 under salicylic acid treatment. EF1beta and HERC2 were the most suitable genes for the global analysis of all samples. Furthermore, six target genes, SgPOD, SgPAL, SgLEA, SgLOX, SgHSP90 and SgPR1, were selected to validate the most and least stable reference genes under different treatments. Our results provide guidelines for reference gene selection for more accurate qRT-PCR quantification and will promote studies of gene expression in S. grandis subjected to environmental stress.

  14. A Comparison of Selective Pressures in Plant X-Linked and Autosomal Genes.

    Science.gov (United States)

    Krasovec, Marc; Nevado, Bruno; Filatov, Dmitry A

    2018-05-03

    Selection is expected to work differently in autosomal and X-linked genes because of their ploidy difference and the exposure of recessive X-linked mutations to haploid selection in males. However, it is not clear whether these expectations apply to recently evolved sex chromosomes, where many genes retain functional X- and Y-linked gametologs. We took advantage of the recently evolved sex chromosomes in the plant Silene latifolia and its closely related species to compare the selective pressures between hemizygous and non-hemizygous X-linked genes as well as between X-linked genes and autosomal genes. Our analysis, based on over 1000 genes, demonstrated that, similar to animals, X-linked genes in Silene evolve significantly faster than autosomal genes—the so-called faster-X effect. Contrary to expectations, faster-X divergence was detectable only for non-hemizygous X-linked genes. Our phylogeny-based analyses of selection revealed no evidence for faster adaptation in X-linked genes compared to autosomal genes. On the other hand, partial relaxation of purifying selection was apparent on the X-chromosome compared to the autosomes, consistent with a smaller genetic diversity in S. latifolia X-linked genes (π x = 0.016; π aut = 0.023). Thus, the faster-X divergence in S. latifolia appears to be a consequence of the smaller effective population size rather than of a faster adaptive evolution on the X-chromosome. We argue that this may be a general feature of “young” sex chromosomes, where the majority of X-linked genes are not hemizygous, preventing haploid selection in heterogametic sex.

  15. Positive selection in the SLC11A1 gene in the family Equidae.

    Science.gov (United States)

    Bayerova, Zuzana; Janova, Eva; Matiasovic, Jan; Orlando, Ludovic; Horin, Petr

    2016-05-01

    Immunity-related genes are a suitable model for studying effects of selection at the genomic level. Some of them are highly conserved due to functional constraints and purifying selection, while others are variable and change quickly to cope with the variation of pathogens. The SLC11A1 gene encodes a transporter protein mediating antimicrobial activity of macrophages. Little is known about the patterns of selection shaping this gene during evolution. Although it is a typical evolutionarily conserved gene, functionally important polymorphisms associated with various diseases were identified in humans and other species. We analyzed the genomic organization, genetic variation, and evolution of the SLC11A1 gene in the family Equidae to identify patterns of selection within this important gene. Nucleotide SLC11A1 sequences were shown to be highly conserved in ten equid species, with more than 97 % sequence identity across the family. Single nucleotide polymorphisms (SNPs) were found in the coding and noncoding regions of the gene. Seven codon sites were identified to be under strong purifying selection. Codons located in three regions, including the glycosylated extracellular loop, were shown to be under diversifying selection. A 3-bp indel resulting in a deletion of the amino acid 321 in the predicted protein was observed in all horses, while it has been maintained in all other equid species. This codon comprised in an N-glycosylation site was found to be under positive selection. Interspecific variation in the presence of predicted N-glycosylation sites was observed.

  16. Methods for selective functionalization and separation of carbon nanotubes

    Science.gov (United States)

    Strano, Michael S. (Inventor); Usrey, Monica (Inventor); Barone, Paul (Inventor); Dyke, Christopher A. (Inventor); Tour, James M. (Inventor); Kittrell, W. Carter (Inventor); Hauge, Robert H (Inventor); Smalley, Richard E. (Inventor); Marek, legal representative, Irene Marie (Inventor)

    2011-01-01

    The present invention is directed toward methods of selectively functionalizing carbon nanotubes of a specific type or range of types, based on their electronic properties, using diazonium chemistry. The present invention is also directed toward methods of separating carbon nanotubes into populations of specific types or range(s) of types via selective functionalization and electrophoresis, and also to the novel compositions generated by such separations.

  17. Supplier selection based on multi-criterial AHP method

    Directory of Open Access Journals (Sweden)

    Jana Pócsová

    2010-03-01

    Full Text Available This paper describes a case-study of supplier selection based on multi-criterial Analytic Hierarchy Process (AHP method.It is demonstrated that using adequate mathematical method can bring us “unprejudiced” conclusion, even if the alternatives (suppliercompanies are very similar in given selection-criteria. The result is the best possible supplier company from the viewpoint of chosen criteriaand the price of the product.

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

    Directory of Open Access Journals (Sweden)

    Teng Shaolei

    2013-01-01

    Full Text Available Abstract Background Understanding how genes are expressed specifically in particular tissues is a fundamental question in developmental biology. Many tissue-specific genes are involved in the pathogenesis of complex human diseases. However, experimental identification of tissue-specific genes is time consuming and difficult. The accurate predictions of tissue-specific gene targets could provide useful information for biomarker development and drug target identification. Results In this study, we have developed a machine learning approach for predicting the human tissue-specific genes using microarray expression data. The lists of known tissue-specific genes for different tissues were collected from UniProt database, and the expression data retrieved from the previously compiled dataset according to the lists were used for input vector encoding. Random Forests (RFs and Support Vector Machines (SVMs were used to construct accurate classifiers. The RF classifiers were found to outperform SVM models for tissue-specific gene prediction. The results suggest that the candidate genes for brain or liver specific expression can provide valuable information for further experimental studies. Our approach was also applied for identifying tissue-selective gene targets for different types of tissues. Conclusions A machine learning approach has been developed for accurately identifying the candidate genes for tissue specific/selective expression. The approach provides an efficient way to select some interesting genes for developing new biomedical markers and improve our knowledge of tissue-specific expression.

  19. An Identification Key for Selecting Methods for Sustainability Assessments

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    Michiel C. Zijp

    2015-03-01

    Full Text Available Sustainability assessments can play an important role in decision making. This role starts with selecting appropriate methods for a given situation. We observed that scientists, consultants, and decision-makers often do not systematically perform a problem analyses that guides the choice of the method, partly related to a lack of systematic, though sufficiently versatile approaches to do so. Therefore, we developed and propose a new step towards method selection on the basis of question articulation: the Sustainability Assessment Identification Key. The identification key was designed to lead its user through all important choices needed for comprehensive question articulation. Subsequently, methods that fit the resulting specific questions are suggested by the key. The key consists of five domains, of which three determine method selection and two the design or use of the method. Each domain consists of four or more criteria that need specification. For example in the domain “system boundaries”, amongst others, the spatial and temporal scales are specified. The key was tested (retrospectively on a set of thirty case studies. Using the key appeared to contribute to improved: (i transparency in the link between the question and method selection; (ii consistency between questions asked and answers provided; and (iii internal consistency in methodological design. There is latitude to develop the current initial key further, not only for selecting methods pertinent to a problem definition, but also as a principle for associated opportunities such as stakeholder identification.

  20. The experiments and analysis of several selective video encryption methods

    Science.gov (United States)

    Zhang, Yue; Yang, Cheng; Wang, Lei

    2013-07-01

    This paper presents four methods for selective video encryption based on the MPEG-2 video compression,including the slices, the I-frames, the motion vectors, and the DCT coefficients. We use the AES encryption method for simulation experiment for the four methods on VS2010 Platform, and compare the video effects and the processing speed of each frame after the video encrypted. The encryption depth can be arbitrarily selected, and design the encryption depth by using the double limit counting method, so the accuracy can be increased.

  1. Polymorphism at selected defence gene analogs (DGAs) of Musa ...

    African Journals Online (AJOL)

    One of the major diseases affecting banana is Sigatoka or leaf spot disease that comprises three species, Mycosphaerella fijiensis, Mycosphaerella musicola and Mycosphaerella eumusae. Plants have a large number of defence related genes which trigger a cascade of defense responses that halt the spread of pathogens.

  2. ReliefSeq: a gene-wise adaptive-K nearest-neighbor feature selection tool for finding gene-gene interactions and main effects in mRNA-Seq gene expression data.

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    Brett A McKinney

    Full Text Available Relief-F is a nonparametric, nearest-neighbor machine learning method that has been successfully used to identify relevant variables that may interact in complex multivariate models to explain phenotypic variation. While several tools have been developed for assessing differential expression in sequence-based transcriptomics, the detection of statistical interactions between transcripts has received less attention in the area of RNA-seq analysis. We describe a new extension and assessment of Relief-F for feature selection in RNA-seq data. The ReliefSeq implementation adapts the number of nearest neighbors (k for each gene to optimize the Relief-F test statistics (importance scores for finding both main effects and interactions. We compare this gene-wise adaptive-k (gwak Relief-F method with standard RNA-seq feature selection tools, such as DESeq and edgeR, and with the popular machine learning method Random Forests. We demonstrate performance on a panel of simulated data that have a range of distributional properties reflected in real mRNA-seq data including multiple transcripts with varying sizes of main effects and interaction effects. For simulated main effects, gwak-Relief-F feature selection performs comparably to standard tools DESeq and edgeR for ranking relevant transcripts. For gene-gene interactions, gwak-Relief-F outperforms all comparison methods at ranking relevant genes in all but the highest fold change/highest signal situations where it performs similarly. The gwak-Relief-F algorithm outperforms Random Forests for detecting relevant genes in all simulation experiments. In addition, Relief-F is comparable to the other methods based on computational time. We also apply ReliefSeq to an RNA-Seq study of smallpox vaccine to identify gene expression changes between vaccinia virus-stimulated and unstimulated samples. ReliefSeq is an attractive tool for inclusion in the suite of tools used for analysis of mRNA-Seq data; it has power to

  3. Investigation of the molecular relationship between breast cancer and obesity by candidate gene prioritization methods

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    Saba Garshasbi

    2015-10-01

    Full Text Available Background: Cancer and obesity are two major public health concerns. More than 12 million cases of cancer are reported annually. Many reports confirmed obesity as a risk factor for cancer. The molecular relationship between obesity and breast cancer has not been clear yet. The purpose of this study was to investigate priorities of effective genes in the molecular relationship between obesity and breast cancer. Methods: In this study, computer simulation method was used for prioritizing the genes that involved in the molecular links between obesity and breast cancer in laboratory of systems biology and bioinformatics (LBB, Tehran University, Tehran, Iran, from March to July 2014. In this study, ENDEAVOUR software was used for prioritizing the genes and integrating multiple data sources was used for data analysis. Training genes were selected from effective genes in obesity and/or breast cancer. Two groups of candidate genes were selected. The first group was included the existential genes in 5 common region chromosomes (between obesity and breast cancer and the second group was included the results of genes microarray data analysis of research Creighton, et al (In 2012 on patients with breast cancer. The microarray data were analyzed with GER2 software (R online software on GEO website. Finally, both training and candidate genes were entered in ENDEAVOUR software package. Results: The candidate genes were prioritized to four style and five genes in ten of the first priorities were repeated twice. In other word, the outcome of prioritizing of 72 genes (Product of microarray data analysis and genes of 5 common chromosome regions (Between obesity and breast cancer showed, 5 genes (TNFRSF10B, F2, IGFALS, NTRK3 and HSP90B1 were the priorities in the molecular connection between obesity and breast cancer. Conclusion: There are some common genes between breast cancer and obesity. So, molecular relationship is confirmed. In this study the possible effect

  4. Expression stability and selection of optimal reference genes for gene expression normalization in early life stage rainbow trout exposed to cadmium and copper.

    Science.gov (United States)

    Shekh, Kamran; Tang, Song; Niyogi, Som; Hecker, Markus

    2017-09-01

    Gene expression analysis represents a powerful approach to characterize the specific mechanisms by which contaminants interact with organisms. One of the key considerations when conducting gene expression analyses using quantitative real-time reverse transcription-polymerase chain reaction (qPCR) is the selection of appropriate reference genes, which is often overlooked. Specifically, to reach meaningful conclusions when using relative quantification approaches, expression levels of reference genes must be highly stable and cannot vary as a function of experimental conditions. However, to date, information on the stability of commonly used reference genes across developmental stages, tissues and after exposure to contaminants such as metals is lacking for many vertebrate species including teleost fish. Therefore, in this study, we assessed the stability of expression of 8 reference gene candidates in the gills and skin of three different early life-stages of rainbow trout after acute exposure (24h) to two metals, cadmium (Cd) and copper (Cu) using qPCR. Candidate housekeeping genes were: beta actin (b-actin), DNA directed RNA polymerase II subunit I (DRP2), elongation factor-1 alpha (EF1a), glyceraldehyde 3-phosphate dehydrogenase (GAPDH), glucose-6-phosphate dehydrogenase (G6PD), hypoxanthine phosphoribosyltransferase (HPRT), ribosomal protein L8 (RPL8), and 18S ribosomal RNA (18S). Four algorithms, geNorm, NormFinder, BestKeeper, and the comparative ΔCt method were employed to systematically evaluate the expression stability of these candidate genes under control and exposed conditions as well as across three different life-stages. Finally, stability of genes was ranked by taking geometric means of the ranks established by the different methods. Stability of reference genes was ranked in the following order (from lower to higher stability): HPRT

  5. Selection and evaluation of potential reference genes for gene expression analysis in the brown planthopper, Nilaparvata lugens (Hemiptera: Delphacidae using reverse-transcription quantitative PCR.

    Directory of Open Access Journals (Sweden)

    Miao Yuan

    Full Text Available The brown planthopper (BPH, Nilaparvata lugens (Hemiptera, Delphacidae, is one of the most important rice pests. Abundant genetic studies on BPH have been conducted using reverse-transcription quantitative real-time PCR (qRT-PCR. Using qRT-PCR, the expression levels of target genes are calculated on the basis of endogenous controls. These genes need to be appropriately selected by experimentally assessing whether they are stably expressed under different conditions. However, such studies on potential reference genes in N. lugens are lacking. In this paper, we presented a systematic exploration of eight candidate reference genes in N. lugens, namely, actin 1 (ACT, muscle actin (MACT, ribosomal protein S11 (RPS11, ribosomal protein S15e (RPS15, alpha 2-tubulin (TUB, elongation factor 1 delta (EF, 18S ribosomal RNA (18S, and arginine kinase (AK and used four alternative methods (BestKeeper, geNorm, NormFinder, and the delta Ct method to evaluate the suitability of these genes as endogenous controls. We examined their expression levels among different experimental factors (developmental stage, body part, geographic population, temperature variation, pesticide exposure, diet change, and starvation following the MIQE (Minimum Information for publication of Quantitative real time PCR Experiments guidelines. Based on the results of RefFinder, which integrates four currently available major software programs to compare and rank the tested candidate reference genes, RPS15, RPS11, and TUB were found to be the most suitable reference genes in different developmental stages, body parts, and geographic populations, respectively. RPS15 was the most suitable gene under different temperature and diet conditions, while RPS11 was the most suitable gene under different pesticide exposure and starvation conditions. This work sheds light on establishing a standardized qRT-PCR procedure in N. lugens, and serves as a starting point for screening for reference genes for

  6. A probabilistic method for testing and estimating selection differences between populations.

    Science.gov (United States)

    He, Yungang; Wang, Minxian; Huang, Xin; Li, Ran; Xu, Hongyang; Xu, Shuhua; Jin, Li

    2015-12-01

    Human populations around the world encounter various environmental challenges and, consequently, develop genetic adaptations to different selection forces. Identifying the differences in natural selection between populations is critical for understanding the roles of specific genetic variants in evolutionary adaptation. Although numerous methods have been developed to detect genetic loci under recent directional selection, a probabilistic solution for testing and quantifying selection differences between populations is lacking. Here we report the development of a probabilistic method for testing and estimating selection differences between populations. By use of a probabilistic model of genetic drift and selection, we showed that logarithm odds ratios of allele frequencies provide estimates of the differences in selection coefficients between populations. The estimates approximate a normal distribution, and variance can be estimated using genome-wide variants. This allows us to quantify differences in selection coefficients and to determine the confidence intervals of the estimate. Our work also revealed the link between genetic association testing and hypothesis testing of selection differences. It therefore supplies a solution for hypothesis testing of selection differences. This method was applied to a genome-wide data analysis of Han and Tibetan populations. The results confirmed that both the EPAS1 and EGLN1 genes are under statistically different selection in Han and Tibetan populations. We further estimated differences in the selection coefficients for genetic variants involved in melanin formation and determined their confidence intervals between continental population groups. Application of the method to empirical data demonstrated the outstanding capability of this novel approach for testing and quantifying differences in natural selection. © 2015 He et al.; Published by Cold Spring Harbor Laboratory Press.

  7. The Impact of Selection, Gene Conversion, and Biased Sampling on the Assessment of Microbial Demography.

    Science.gov (United States)

    Lapierre, Marguerite; Blin, Camille; Lambert, Amaury; Achaz, Guillaume; Rocha, Eduardo P C

    2016-07-01

    Recent studies have linked demographic changes and epidemiological patterns in bacterial populations using coalescent-based approaches. We identified 26 studies using skyline plots and found that 21 inferred overall population expansion. This surprising result led us to analyze the impact of natural selection, recombination (gene conversion), and sampling biases on demographic inference using skyline plots and site frequency spectra (SFS). Forward simulations based on biologically relevant parameters from Escherichia coli populations showed that theoretical arguments on the detrimental impact of recombination and especially natural selection on the reconstructed genealogies cannot be ignored in practice. In fact, both processes systematically lead to spurious interpretations of population expansion in skyline plots (and in SFS for selection). Weak purifying selection, and especially positive selection, had important effects on skyline plots, showing patterns akin to those of population expansions. State-of-the-art techniques to remove recombination further amplified these biases. We simulated three common sampling biases in microbiological research: uniform, clustered, and mixed sampling. Alone, or together with recombination and selection, they further mislead demographic inferences producing almost any possible skyline shape or SFS. Interestingly, sampling sub-populations also affected skyline plots and SFS, because the coalescent rates of populations and their sub-populations had different distributions. This study suggests that extreme caution is needed to infer demographic changes solely based on reconstructed genealogies. We suggest that the development of novel sampling strategies and the joint analyzes of diverse population genetic methods are strictly necessary to estimate demographic changes in populations where selection, recombination, and biased sampling are present. © The Author 2016. Published by Oxford University Press on behalf of the Society for

  8. Using MACBETH method for supplier selection in manufacturing environment

    Directory of Open Access Journals (Sweden)

    Prasad Karande

    2013-04-01

    Full Text Available Supplier selection is always found to be a complex decision-making problem in manufacturing environment. The presence of several independent and conflicting evaluation criteria, either qualitative or quantitative, makes the supplier selection problem a candidate to be solved by multi-criteria decision-making (MCDM methods. Even several MCDM methods have already been proposed for solving the supplier selection problems, the need for an efficient method that can deal with qualitative judgments related to supplier selection still persists. In this paper, the applicability and usefulness of measuring attractiveness by a categorical-based evaluation technique (MACBETH is demonstrated to act as a decision support tool while solving two real time supplier selection problems having qualitative performance measures. The ability of MACBETH method to quantify the qualitative performance measures helps to provide a numerical judgment scale for ranking the alternative suppliers and selecting the best one. The results obtained from MACBETH method exactly corroborate with those derived by the past researchers employing different mathematical approaches.

  9. Selection of reference genes for qPCR in hairy root cultures of peanut

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    Medrano Giuliana

    2011-10-01

    Full Text Available Abstract Background Hairy root cultures produced via Agrobacterium rhizogenes-mediated transformation have emerged as practical biological models to elucidate the biosynthesis of specialized metabolites. To effectively understand the expression patterns of the genes involved in the metabolic pathways of these compounds, reference genes need to be systematically validated under specific experimental conditions as established by the MIQE (Minimum Information for Publication of Quantitative Real-Time PCR Experiments guidelines. In the present report we describe the first validation of reference genes for RT-qPCR in hairy root cultures of peanut which produce stilbenoids upon elicitor treatments. Results A total of 21 candidate reference genes were evaluated. Nineteen genes were selected based on previous qPCR studies in plants and two were from the T-DNAs transferred from A. rhizogenes. Nucleotide sequences of peanut candidate genes were obtained using their homologous sequences in Arabidopsis. To identify the suitable primers, calibration curves were obtained for each candidate reference gene. After data analysis, 12 candidate genes meeting standard efficiency criteria were selected. The expression stability of these genes was analyzed using geNorm and NormFinder algorithms and a ranking was established based on expression stability of the genes. Candidate reference gene expression was shown to have less variation in methyl jasmonate (MeJA treated root cultures than those treated with sodium acetate (NaOAc. Conclusions This work constitutes the first effort to validate reference genes for RT-qPCR in hairy roots. While these genes were selected under conditions of NaOAc and MeJA treatment, we anticipate these genes to provide good targets for reference genes for hairy roots under a variety of stress conditions. The lead reference genes were a gene encoding for a TATA box binding protein (TBP2 and a gene encoding a ribosomal protein (RPL8C. A

  10. Link-based quantitative methods to identify differentially coexpressed genes and gene Pairs

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    Ye Zhi-Qiang

    2011-08-01

    Full Text Available Abstract Background Differential coexpression analysis (DCEA is increasingly used for investigating the global transcriptional mechanisms underlying phenotypic changes. Current DCEA methods mostly adopt a gene connectivity-based strategy to estimate differential coexpression, which is characterized by comparing the numbers of gene neighbors in different coexpression networks. Although it simplifies the calculation, this strategy mixes up the identities of different coexpression neighbors of a gene, and fails to differentiate significant differential coexpression changes from those trivial ones. Especially, the correlation-reversal is easily missed although it probably indicates remarkable biological significance. Results We developed two link-based quantitative methods, DCp and DCe, to identify differentially coexpressed genes and gene pairs (links. Bearing the uniqueness of exploiting the quantitative coexpression change of each gene pair in the coexpression networks, both methods proved to be superior to currently popular methods in simulation studies. Re-mining of a publicly available type 2 diabetes (T2D expression dataset from the perspective of differential coexpression analysis led to additional discoveries than those from differential expression analysis. Conclusions This work pointed out the critical weakness of current popular DCEA methods, and proposed two link-based DCEA algorithms that will make contribution to the development of DCEA and help extend it to a broader spectrum.

  11. "Every Gene Is Everywhere but the Environment Selects": Global Geolocalization of Gene Sharing in Environmental Samples through Network Analysis.

    Science.gov (United States)

    Fondi, Marco; Karkman, Antti; Tamminen, Manu V; Bosi, Emanuele; Virta, Marko; Fani, Renato; Alm, Eric; McInerney, James O

    2016-05-13

    The spatial distribution of microbes on our planet is famously formulated in the Baas Becking hypothesis as "everything is everywhere but the environment selects." While this hypothesis does not strictly rule out patterns caused by geographical effects on ecology and historical founder effects, it does propose that the remarkable dispersal potential of microbes leads to distributions generally shaped by environmental factors rather than geographical distance. By constructing sequence similarity networks from uncultured environmental samples, we show that microbial gene pool distributions are not influenced nearly as much by geography as ecology, thus extending the Bass Becking hypothesis from whole organisms to microbial genes. We find that gene pools are shaped by their broad ecological niche (such as sea water, fresh water, host, and airborne). We find that freshwater habitats act as a gene exchange bridge between otherwise disconnected habitats. Finally, certain antibiotic resistance genes deviate from the general trend of habitat specificity by exhibiting a high degree of cross-habitat mobility. The strong cross-habitat mobility of antibiotic resistance genes is a cause for concern and provides a paradigmatic example of the rate by which genes colonize new habitats when new selective forces emerge. © The Author(s) 2016. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.

  12. Selective AR Modulators that Distinguish Proliferative from Differentiative Gene Promoters

    Science.gov (United States)

    2016-08-01

    levels, and in some cases be useful in early stage disease or watchful waiting, and in other cases castration resistant prostate cancer (CRPC...dependent kinase inhibitor p21 gene through an androgen response element in the proximal promoter. Molecular endocrinology 13, 376 (Mar, 1999). 9...analyses and in mouse xenograft experiments, as planned. We will also continue to probe the molecular mechanism by which dox elicits these differential

  13. Proactive AP Selection Method Considering the Radio Interference Environment

    Science.gov (United States)

    Taenaka, Yuzo; Kashihara, Shigeru; Tsukamoto, Kazuya; Yamaguchi, Suguru; Oie, Yuji

    In the near future, wireless local area networks (WLANs) will overlap to provide continuous coverage over a wide area. In such ubiquitous WLANs, a mobile node (MN) moving freely between multiple access points (APs) requires not only permanent access to the Internet but also continuous communication quality during handover. In order to satisfy these requirements, an MN needs to (1) select an AP with better performance and (2) execute a handover seamlessly. To satisfy requirement (2), we proposed a seamless handover method in a previous study. Moreover, in order to achieve (1), the Received Signal Strength Indicator (RSSI) is usually employed to measure wireless link quality in a WLAN system. However, in a real environment, especially if APs are densely situated, it is difficult to always select an AP with better performance based on only the RSSI. This is because the RSSI alone cannot detect the degradation of communication quality due to radio interference. Moreover, it is important that AP selection is completed only on an MN, because we can assume that, in ubiquitous WLANs, various organizations or operators will manage APs. Hence, we cannot modify the APs for AP selection. To overcome these difficulties, in the present paper, we propose and implement a proactive AP selection method considering wireless link condition based on the number of frame retransmissions in addition to the RSSI. In the evaluation, we show that the proposed AP selection method can appropriately select an AP with good wireless link quality, i.e., high RSSI and low radio interference.

  14. Maintenance of the selected infant feeding methods amongst ...

    African Journals Online (AJOL)

    The focus of this study was to explore and describe influences on decision making related to infant feeding methods in the context of HIV and AIDS. Study objectives were: (1) to explore and describe the influences on decision making related to infant feeding methods selected by the mother during the antenatal period and ...

  15. MICB gene diversity and balancing selection on its promoter region in Yao population in southern China.

    Science.gov (United States)

    Chen, Xiang; Liu, Xuexiang; Wei, Xiaomou; Meng, Yuming; Liu, Limin; Qin, Shini; Liu, Yanyu; Dai, Shengming

    2016-12-01

    To comprehensively examine the MICB gene polymorphism and identify its differences in Chinese Yao population from other ethnic groups, we investigated the polymorphism in the 5'-upstream regulation region (5'-URR), coding region (exons 2-4), and the 3'-untranslated region (3'-UTR) of MICB gene by using PCR-SBT method in 125 healthy unrelated Yao individuals in Guangxi Zhuang Autonomous Region. Higher polymorphism was observed in the 5'-URR, nine single nucleotide polymorphisms (SNPs) and a two base pairs deletion at position -139/-138 were found in our study. Only five different variation sites, however, were detected in exons 2-4 and three were observed in the 3'-UTR. The minor allele frequencies of all variants were greater than 5%, except for rs3828916, rs3131639, rs45627734, rs113620316, rs779737471, and the variation at position +11803 in the 3'-UTR. The first nine SNPs of 5'-URR and rs1065075, rs1051788 of the coding region showed significant linkage disequilibrium with each other. Ten different MICB extended haplotypes (EH) encompassing the 5'-URR, exons 2-4, and 3'-UTR were found in this population, and the most frequent was EH1 (23.2%). We provided several evidences for balancing selection effect on the 5'-URR of MICB gene in Yao population. Copyright © 2016 American Society for Histocompatibility and Immunogenetics. Published by Elsevier Inc. All rights reserved.

  16. Selection of reliable reference genes in Caenorhabditis elegans for analysis of nanotoxicity.

    Directory of Open Access Journals (Sweden)

    Yanqiong Zhang

    Full Text Available Despite rapid development and application of a wide range of manufactured metal oxide nanoparticles (NPs, the understanding of potential risks of using NPs is less completed, especially at the molecular level. The nematode Caenorhabditis elegans (C.elegans has been emerging as an environmental model to study the molecular mechanism of environmental contaminations, using standard genetic tools such as the real-time quantitative PCR (RT-qPCR. The most important factor that may affect the accuracy of RT-qPCR is to choose appropriate genes for normalization. In this study, we selected 13 reference gene candidates (act-1, cdc-42, pmp-3, eif-3.C, actin, act-2, csq-1, Y45F10D.4, tba-1, mdh-1, ama-1, F35G12.2, and rbd-1 to test their expression stability under different doses of nano-copper oxide (CuO 0, 1, 10, and 50 µg/mL using RT-qPCR. Four algorithms, geNorm, NormFinder, BestKeeper, and the comparative ΔCt method, were employed to evaluate these 13 candidates expressions. As a result, tba-1, Y45F10D.4 and pmp-3 were the most reliable, which may be used as reference genes in future study of nanoparticle-induced genetic response using C.elegans.

  17. Selection of reliable reference genes in Caenorhabditis elegans for analysis of nanotoxicity.

    Science.gov (United States)

    Zhang, Yanqiong; Chen, Dongliang; Smith, Michael A; Zhang, Baohong; Pan, Xiaoping

    2012-01-01

    Despite rapid development and application of a wide range of manufactured metal oxide nanoparticles (NPs), the understanding of potential risks of using NPs is less completed, especially at the molecular level. The nematode Caenorhabditis elegans (C.elegans) has been emerging as an environmental model to study the molecular mechanism of environmental contaminations, using standard genetic tools such as the real-time quantitative PCR (RT-qPCR). The most important factor that may affect the accuracy of RT-qPCR is to choose appropriate genes for normalization. In this study, we selected 13 reference gene candidates (act-1, cdc-42, pmp-3, eif-3.C, actin, act-2, csq-1, Y45F10D.4, tba-1, mdh-1, ama-1, F35G12.2, and rbd-1) to test their expression stability under different doses of nano-copper oxide (CuO 0, 1, 10, and 50 µg/mL) using RT-qPCR. Four algorithms, geNorm, NormFinder, BestKeeper, and the comparative ΔCt method, were employed to evaluate these 13 candidates expressions. As a result, tba-1, Y45F10D.4 and pmp-3 were the most reliable, which may be used as reference genes in future study of nanoparticle-induced genetic response using C.elegans.

  18. Tetracycline resistance genes persist in soil amended with cattle feces independently from chlortetracycline selection pressure

    NARCIS (Netherlands)

    Kyselkova, Martina; Kotrbova, Lucie; Bhumibhamon, Gamonsiri; Chronakova, Alica; Jirout, Jiri; Vrchotova, Nadezda; Schmitt, Heike; Elhottova, Dana

    Antibiotic residues and antibiotic resistance genes originating from animal waste represent environmental pollutants with possible human health consequences. In this study, we addressed the question whether chlortetracycline (CTC) residues in soils can act as selective pressure enhancing the

  19. Selection of reference genes for transcriptional analysis of edible tubers of potato (Solanum tuberosum L..

    Directory of Open Access Journals (Sweden)

    Roberta Fogliatto Mariot

    Full Text Available Potato (Solanum tuberosum yield has increased dramatically over the last 50 years and this has been achieved by a combination of improved agronomy and biotechnology efforts. Gene studies are taking place to improve new qualities and develop new cultivars. Reverse transcriptase quantitative polymerase chain reaction (RT-qPCR is a bench-marking analytical tool for gene expression analysis, but its accuracy is highly dependent on a reliable normalization strategy of an invariant reference genes. For this reason, the goal of this work was to select and validate reference genes for transcriptional analysis of edible tubers of potato. To do so, RT-qPCR primers were designed for ten genes with relatively stable expression in potato tubers as observed in RNA-Seq experiments. Primers were designed across exon boundaries to avoid genomic DNA contamination. Differences were observed in the ranking of candidate genes identified by geNorm, NormFinder and BestKeeper algorithms. The ranks determined by geNorm and NormFinder were very similar and for all samples the most stable candidates were C2, exocyst complex component sec3 (SEC3 and ATCUL3/ATCUL3A/CUL3/CUL3A (CUL3A. According to BestKeeper, the importin alpha and ubiquitin-associated/ts-n genes were the most stable. Three genes were selected as reference genes for potato edible tubers in RT-qPCR studies. The first one, called C2, was selected in common by NormFinder and geNorm, the second one is SEC3, selected by NormFinder, and the third one is CUL3A, selected by geNorm. Appropriate reference genes identified in this work will help to improve the accuracy of gene expression quantification analyses by taking into account differences that may be observed in RNA quality or reverse transcription efficiency across the samples.

  20. Selection of reference genes for transcriptional analysis of edible tubers of potato (Solanum tuberosum L.).

    Science.gov (United States)

    Mariot, Roberta Fogliatto; de Oliveira, Luisa Abruzzi; Voorhuijzen, Marleen M; Staats, Martijn; Hutten, Ronald C B; Van Dijk, Jeroen P; Kok, Esther; Frazzon, Jeverson

    2015-01-01

    Potato (Solanum tuberosum) yield has increased dramatically over the last 50 years and this has been achieved by a combination of improved agronomy and biotechnology efforts. Gene studies are taking place to improve new qualities and develop new cultivars. Reverse transcriptase quantitative polymerase chain reaction (RT-qPCR) is a bench-marking analytical tool for gene expression analysis, but its accuracy is highly dependent on a reliable normalization strategy of an invariant reference genes. For this reason, the goal of this work was to select and validate reference genes for transcriptional analysis of edible tubers of potato. To do so, RT-qPCR primers were designed for ten genes with relatively stable expression in potato tubers as observed in RNA-Seq experiments. Primers were designed across exon boundaries to avoid genomic DNA contamination. Differences were observed in the ranking of candidate genes identified by geNorm, NormFinder and BestKeeper algorithms. The ranks determined by geNorm and NormFinder were very similar and for all samples the most stable candidates were C2, exocyst complex component sec3 (SEC3) and ATCUL3/ATCUL3A/CUL3/CUL3A (CUL3A). According to BestKeeper, the importin alpha and ubiquitin-associated/ts-n genes were the most stable. Three genes were selected as reference genes for potato edible tubers in RT-qPCR studies. The first one, called C2, was selected in common by NormFinder and geNorm, the second one is SEC3, selected by NormFinder, and the third one is CUL3A, selected by geNorm. Appropriate reference genes identified in this work will help to improve the accuracy of gene expression quantification analyses by taking into account differences that may be observed in RNA quality or reverse transcription efficiency across the samples.

  1. The roles of gene duplication, gene conversion and positive selection in rodent Esp and Mup pheromone gene families with comparison to the Abp family.

    Science.gov (United States)

    Karn, Robert C; Laukaitis, Christina M

    2012-01-01

    Three proteinaceous pheromone families, the androgen-binding proteins (ABPs), the exocrine-gland secreting peptides (ESPs) and the major urinary proteins (MUPs) are encoded by large gene families in the genomes of Mus musculus and Rattus norvegicus. We studied the evolutionary histories of the Mup and Esp genes and compared them with what is known about the Abp genes. Apparently gene conversion has played little if any role in the expansion of the mouse Class A and Class B Mup genes and pseudogenes, and the rat Mups. By contrast, we found evidence of extensive gene conversion in many Esp genes although not in all of them. Our studies of selection identified at least two amino acid sites in β-sheets as having evolved under positive selection in the mouse Class A and Class B MUPs and in rat MUPs. We show that selection may have acted on the ESPs by determining K(a)/K(s) for Exon 3 sequences with and without the converted sequence segment. While it appears that purifying selection acted on the ESP signal peptides, the secreted portions of the ESPs probably have undergone much more rapid evolution. When the inner gene converted fragment sequences were removed, eleven Esp paralogs were present in two or more pairs with K(a)/K(s) >1.0 and thus we propose that positive selection is detectable by this means in at least some mouse Esp paralogs. We compare and contrast the evolutionary histories of all three mouse pheromone gene families in light of their proposed functions in mouse communication.

  2. Use of the alr gene as a food-grade selection marker in lactic acid bacteria

    NARCIS (Netherlands)

    Bron, P.A.; Benchimol, M.G.; Lambert, J.; Palumbo, E.; Deghorain, M.; Delcour, J.; Vos, de W.M.; Kleerebezem, M.; Hols, P.

    2002-01-01

    Both Lactococcus lactis and Lactobacillus plantarum contain a single alr gene, encoding an alanine racemase (EC 5.1.1.1), which catalyzes the interconversion of D-alanine and L-alanine. The alr genes of these lactic acid bacteria were investigated for their application as food-grade selection

  3. Sustainable Supplier Performance Evaluation and Selection with Neofuzzy TOPSIS Method.

    Science.gov (United States)

    Chaharsooghi, S K; Ashrafi, Mehdi

    2014-01-01

    Supplier selection plays an important role in the supply chain management and traditional criteria such as price, quality, and flexibility are considered for supplier performance evaluation in researches. In recent years sustainability has received more attention in the supply chain management literature with triple bottom line (TBL) describing the sustainability in supply chain management with social, environmental, and economic initiatives. This paper explores sustainability in supply chain management and examines the problem of identifying a new model for supplier selection based on extended model of TBL approach in supply chain by presenting fuzzy multicriteria method. Linguistic values of experts' subjective preferences are expressed with fuzzy numbers and Neofuzzy TOPSIS is proposed for finding the best solution of supplier selection problem. Numerical results show that the proposed model is efficient for integrating sustainability in supplier selection problem. The importance of using complimentary aspects of sustainability and Neofuzzy TOPSIS concept in sustainable supplier selection process is shown with sensitivity analysis.

  4. Cross-organism learning method to discover new gene functionalities.

    Science.gov (United States)

    Domeniconi, Giacomo; Masseroli, Marco; Moro, Gianluca; Pinoli, Pietro

    2016-04-01

    Knowledge of gene and protein functions is paramount for the understanding of physiological and pathological biological processes, as well as in the development of new drugs and therapies. Analyses for biomedical knowledge discovery greatly benefit from the availability of gene and protein functional feature descriptions expressed through controlled terminologies and ontologies, i.e., of gene and protein biomedical controlled annotations. In the last years, several databases of such annotations have become available; yet, these valuable annotations are incomplete, include errors and only some of them represent highly reliable human curated information. Computational techniques able to reliably predict new gene or protein annotations with an associated likelihood value are thus paramount. Here, we propose a novel cross-organisms learning approach to reliably predict new functionalities for the genes of an organism based on the known controlled annotations of the genes of another, evolutionarily related and better studied, organism. We leverage a new representation of the annotation discovery problem and a random perturbation of the available controlled annotations to allow the application of supervised algorithms to predict with good accuracy unknown gene annotations. Taking advantage of the numerous gene annotations available for a well-studied organism, our cross-organisms learning method creates and trains better prediction models, which can then be applied to predict new gene annotations of a target organism. We tested and compared our method with the equivalent single organism approach on different gene annotation datasets of five evolutionarily related organisms (Homo sapiens, Mus musculus, Bos taurus, Gallus gallus and Dictyostelium discoideum). Results show both the usefulness of the perturbation method of available annotations for better prediction model training and a great improvement of the cross-organism models with respect to the single-organism ones

  5. Genome-wide analysis of positively selected genes in seasonal and non-seasonal breeding species.

    Directory of Open Access Journals (Sweden)

    Yuhuan Meng

    Full Text Available Some mammals breed throughout the year, while others breed only at certain times of year. These differences in reproductive behavior can be explained by evolution. We identified positively-selected genes in two sets of species with different degrees of relatedness including seasonal and non-seasonal breeding species, using branch-site models. After stringent filtering by sum of pairs scoring, we revealed that more genes underwent positive selection in seasonal compared with non-seasonal breeding species. Positively-selected genes were verified by cDNA mapping of the positive sites with the corresponding cDNA sequences. The design of the evolutionary analysis can effectively lower the false-positive rate and thus identify valid positive genes. Validated, positively-selected genes, including CGA, DNAH1, INVS, and CD151, were related to reproductive behaviors such as spermatogenesis and cell proliferation in non-seasonal breeding species. Genes in seasonal breeding species, including THRAP3, TH1L, and CMTM6, may be related to the evolution of sperm and the circadian rhythm system. Identification of these positively-selected genes might help to identify the molecular mechanisms underlying seasonal and non-seasonal reproductive behaviors.

  6. Natural selection against a circadian clock gene mutation in mice.

    Science.gov (United States)

    Spoelstra, Kamiel; Wikelski, Martin; Daan, Serge; Loudon, Andrew S I; Hau, Michaela

    2016-01-19

    Circadian rhythms with an endogenous period close to or equal to the natural light-dark cycle are considered evolutionarily adaptive ("circadian resonance hypothesis"). Despite remarkable insight into the molecular mechanisms driving circadian cycles, this hypothesis has not been tested under natural conditions for any eukaryotic organism. We tested this hypothesis in mice bearing a short-period mutation in the enzyme casein kinase 1ε (tau mutation), which accelerates free-running circadian cycles. We compared daily activity (feeding) rhythms, survivorship, and reproduction in six replicate populations in outdoor experimental enclosures, established with wild-type, heterozygous, and homozygous mice in a Mendelian ratio. In the release cohort, survival was reduced in the homozygote mutant mice, revealing strong selection against short-period genotypes. Over the course of 14 mo, the relative frequency of the tau allele dropped from initial parity to 20%. Adult survival and recruitment of juveniles into the population contributed approximately equally to the selection for wild-type alleles. The expression of activity during daytime varied throughout the experiment and was significantly increased by the tau mutation. The strong selection against the short-period tau allele observed here contrasts with earlier studies showing absence of selection against a Period 2 (Per2) mutation, which disrupts internal clock function, but does not change period length. These findings are consistent with, and predicted by the theory that resonance of the circadian system plays an important role in individual fitness.

  7. Personnel Selection Method Based on Personnel-Job Matching

    OpenAIRE

    Li Wang; Xilin Hou; Lili Zhang

    2013-01-01

    The existing personnel selection decisions in practice are based on the evaluation of job seeker's human capital, and it may be difficult to make personnel-job matching and make each party satisfy. Therefore, this paper puts forward a new personnel selection method by consideration of bilateral matching. Starting from the employment thoughts of ¡°satisfy¡±, the satisfaction evaluation indicator system of each party are constructed. The multi-objective optimization model is given according to ...

  8. Selection of Reliable Reference Genes for Gene Expression Studies of a Promising Oilseed Crop, Plukenetia volubilis, by Real-Time Quantitative PCR

    Directory of Open Access Journals (Sweden)

    Longjian Niu

    2015-06-01

    Full Text Available Real-time quantitative PCR (RT-qPCR is a reliable and widely used method for gene expression analysis. The accuracy of the determination of a target gene expression level by RT-qPCR demands the use of appropriate reference genes to normalize the mRNA levels among different samples. However, suitable reference genes for RT-qPCR have not been identified in Sacha inchi (Plukenetia volubilis, a promising oilseed crop known for its polyunsaturated fatty acid (PUFA-rich seeds. In this study, using RT-qPCR, twelve candidate reference genes were examined in seedlings and adult plants, during flower and seed development and for the entire growth cycle of Sacha inchi. Four statistical algorithms (delta cycle threshold (ΔCt, BestKeeper, geNorm, and NormFinder were used to assess the expression stabilities of the candidate genes. The results showed that ubiquitin-conjugating enzyme (UCE, actin (ACT and phospholipase A22 (PLA were the most stable genes in Sacha inchi seedlings. For roots, stems, leaves, flowers, and seeds from adult plants, 30S ribosomal protein S13 (RPS13, cyclophilin (CYC and elongation factor-1alpha (EF1α were recommended as reference genes for RT-qPCR. During the development of reproductive organs, PLA, ACT and UCE were the optimal reference genes for flower development, whereas UCE, RPS13 and RNA polymerase II subunit (RPII were optimal for seed development. Considering the entire growth cycle of Sacha inchi, UCE, ACT and EF1α were sufficient for the purpose of normalization. Our results provide useful guidelines for the selection of reliable reference genes for the normalization of RT-qPCR data for seedlings and adult plants, for reproductive organs, and for the entire growth cycle of Sacha inchi.

  9. Selection of Reliable Reference Genes for Gene Expression Studies of a Promising Oilseed Crop, Plukenetia volubilis, by Real-Time Quantitative PCR

    Science.gov (United States)

    Niu, Longjian; Tao, Yan-Bin; Chen, Mao-Sheng; Fu, Qiantang; Li, Chaoqiong; Dong, Yuling; Wang, Xiulan; He, Huiying; Xu, Zeng-Fu

    2015-01-01

    Real-time quantitative PCR (RT-qPCR) is a reliable and widely used method for gene expression analysis. The accuracy of the determination of a target gene expression level by RT-qPCR demands the use of appropriate reference genes to normalize the mRNA levels among different samples. However, suitable reference genes for RT-qPCR have not been identified in Sacha inchi (Plukenetia volubilis), a promising oilseed crop known for its polyunsaturated fatty acid (PUFA)-rich seeds. In this study, using RT-qPCR, twelve candidate reference genes were examined in seedlings and adult plants, during flower and seed development and for the entire growth cycle of Sacha inchi. Four statistical algorithms (delta cycle threshold (ΔCt), BestKeeper, geNorm, and NormFinder) were used to assess the expression stabilities of the candidate genes. The results showed that ubiquitin-conjugating enzyme (UCE), actin (ACT) and phospholipase A22 (PLA) were the most stable genes in Sacha inchi seedlings. For roots, stems, leaves, flowers, and seeds from adult plants, 30S ribosomal protein S13 (RPS13), cyclophilin (CYC) and elongation factor-1alpha (EF1α) were recommended as reference genes for RT-qPCR. During the development of reproductive organs, PLA, ACT and UCE were the optimal reference genes for flower development, whereas UCE, RPS13 and RNA polymerase II subunit (RPII) were optimal for seed development. Considering the entire growth cycle of Sacha inchi, UCE, ACT and EF1α were sufficient for the purpose of normalization. Our results provide useful guidelines for the selection of reliable reference genes for the normalization of RT-qPCR data for seedlings and adult plants, for reproductive organs, and for the entire growth cycle of Sacha inchi. PMID:26047338

  10. Methods for model selection in applied science and engineering.

    Energy Technology Data Exchange (ETDEWEB)

    Field, Richard V., Jr.

    2004-10-01

    Mathematical models are developed and used to study the properties of complex systems and/or modify these systems to satisfy some performance requirements in just about every area of applied science and engineering. A particular reason for developing a model, e.g., performance assessment or design, is referred to as the model use. Our objective is the development of a methodology for selecting a model that is sufficiently accurate for an intended use. Information on the system being modeled is, in general, incomplete, so that there may be two or more models consistent with the available information. The collection of these models is called the class of candidate models. Methods are developed for selecting the optimal member from a class of candidate models for the system. The optimal model depends on the available information, the selected class of candidate models, and the model use. Classical methods for model selection, including the method of maximum likelihood and Bayesian methods, as well as a method employing a decision-theoretic approach, are formulated to select the optimal model for numerous applications. There is no requirement that the candidate models be random. Classical methods for model selection ignore model use and require data to be available. Examples are used to show that these methods can be unreliable when data is limited. The decision-theoretic approach to model selection does not have these limitations, and model use is included through an appropriate utility function. This is especially important when modeling high risk systems, where the consequences of using an inappropriate model for the system can be disastrous. The decision-theoretic method for model selection is developed and applied for a series of complex and diverse applications. These include the selection of the: (1) optimal order of the polynomial chaos approximation for non-Gaussian random variables and stationary stochastic processes, (2) optimal pressure load model to be

  11. 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.

  12. Nucleofection: A New Method for Cutaneous Gene Transfer?

    Directory of Open Access Journals (Sweden)

    Frank Jacobsen

    2006-01-01

    Full Text Available Background. Transfection efficacy after nonviral gene transfer in primary epithelial cells is limited. The aim of this study was to compare transfection efficacy of the recently available method of nucleofection with the established transfection reagent FuGENE6. Methods. Primary human keratinocytes (HKC, primary human fibroblasts (HFB, and a human keratinocyte cell line (HaCaT were transfected with reporter gene construct by FuGENE6 or Amaxa Nucleofector device. At corresponding time points, β-galactosidase expression, cell proliferation (MTT-Test, transduction efficiency (X-gal staining, cell morphology, and cytotoxicity (CASY were determined. Results. Transgene expression after nucleofection was significantly higher in HKC and HFB and detected earlier (3 h vs. 24 h than in FuGENE6. After lipofection 80%–90% of the cells remained proliferative without any influence on cell morphology. In contrast, nucleofection led to a decrease in keratinocyte cell size, with only 20%–42% proliferative cells. Conclusion. Related to the method-dependent increase of cytotoxicity, transgene expression after nucleofection was earlier and higher than after lipofection.

  13. Nucleofection: A New Method for Cutaneous Gene Transfer?

    Science.gov (United States)

    Jacobsen, Frank; Mertens-Rill, Janine; Beller, Juergen; Hirsch, Tobias; Daigeler, Adrien; Langer, Stefan; Lehnhardt, Marcus; Steinau, Hans-Ulrich; Steinstraesser, Lars

    2006-01-01

    Background. Transfection efficacy after nonviral gene transfer in primary epithelial cells is limited. The aim of this study was to compare transfection efficacy of the recently available method of nucleofection with the established transfection reagent FuGENE6. Methods. Primary human keratinocytes (HKC), primary human fibroblasts (HFB), and a human keratinocyte cell line (HaCaT) were transfected with reporter gene construct by FuGENE6 or Amaxa Nucleofector device. At corresponding time points, β-galactosidase expression, cell proliferation (MTT-Test), transduction efficiency (X-gal staining), cell morphology, and cytotoxicity (CASY) were determined. Results. Transgene expression after nucleofection was significantly higher in HKC and HFB and detected earlier (3 h vs. 24 h) than in FuGENE6. After lipofection 80%–90% of the cells remained proliferative without any influence on cell morphology. In contrast, nucleofection led to a decrease in keratinocyte cell size, with only 20%–42% proliferative cells. Conclusion. Related to the method-dependent increase of cytotoxicity, transgene expression after nucleofection was earlier and higher than after lipofection. PMID:17489014

  14. Combining AHP and DEA Methods for Selecting a Project Manager

    Directory of Open Access Journals (Sweden)

    Baruch Keren

    2014-07-01

    Full Text Available A project manager has a major influence on the success or failure of the project. A good project manager can match between the strategy and objectives of the organization and the goals of the project. Therefore, the selection of the appropriate project manager is a key factor for the success of the project. A potential project manager is judged by his or her proven performance and personal qualifications. This paper proposes a method to calculate the weighted scores and the full rank of candidates for managing a project, and to select the best of those candidates. The proposed method combines specific methodologies: the Data Envelopment Analysis (DEA and the Analytical Hierarchical Process (AHP and uses DEA Ranking Methods to enhance selection.

  15. Selection method of terrain matching area for TERCOM algorithm

    Science.gov (United States)

    Zhang, Qieqie; Zhao, Long

    2017-10-01

    The performance of terrain aided navigation is closely related to the selection of terrain matching area. The different matching algorithms have different adaptability to terrain. This paper mainly studies the adaptability to terrain of TERCOM algorithm, analyze the relation between terrain feature and terrain characteristic parameters by qualitative and quantitative methods, and then research the relation between matching probability and terrain characteristic parameters by the Monte Carlo method. After that, we propose a selection method of terrain matching area for TERCOM algorithm, and verify the method correctness with real terrain data by simulation experiment. Experimental results show that the matching area obtained by the method in this paper has the good navigation performance and the matching probability of TERCOM algorithm is great than 90%

  16. Selection of appropriate reference genes for the detection of rhythmic gene expression via quantitative real-time PCR in Tibetan hulless barley.

    Directory of Open Access Journals (Sweden)

    Jing Cai

    Full Text Available Hulless barley (Hordeum vulgare L. var. nudum. hook. f. has been cultivated as a major crop in the Qinghai-Tibet plateau of China for thousands of years. Compared to other cereal crops, the Tibetan hulless barley has developed stronger endogenous resistances to survive in the severe environment of its habitat. To understand the unique resistant mechanisms of this plant, detailed genetic studies need to be performed. The quantitative real-time reverse transcription-polymerase chain reaction (qRT-PCR is the most commonly used method in detecting gene expression. However, the selection of stable reference genes under limited experimental conditions was considered to be an essential step for obtaining accurate results in qRT-PCR. In this study, 10 candidate reference genes-ACT (Actin, E2 (Ubiquitin conjugating enzyme 2, TUBα (Alpha-tubulin, TUBβ6 (Beta-tubulin 6, GAPDH (Glyceraldehyde 3-phosphate dehydrogenase, EF-1α (Elongation factor 1-alpha, SAMDC (S-adenosylmethionine decarboxylase, PKABA1 (Gene for protein kinase HvPKABA1, PGK (Phosphoglycerate kinase, and HSP90 (Heat shock protein 90-were selected from the NCBI gene database of barley. Following qRT-PCR amplifications of all candidate reference genes in Tibetan hulless barley seedlings under various stressed conditions, the stabilities of these candidates were analyzed by three individual software packages including geNorm, NormFinder, and BestKeeper. The results demonstrated that TUBβ6, E2, TUBα, and HSP90 were generally the most suitable sets under all tested conditions; similarly, TUBα and HSP90 showed peak stability under salt stress, TUBα and EF-1α were the most suitable reference genes under cold stress, and ACT and E2 were the most stable under drought stress. Finally, a known circadian gene CCA1 was used to verify the service ability of chosen reference genes. The results confirmed that all recommended reference genes by the three software were suitable for gene expression

  17. Selection of appropriate reference genes for the detection of rhythmic gene expression via quantitative real-time PCR in Tibetan hulless barley.

    Science.gov (United States)

    Cai, Jing; Li, Pengfei; Luo, Xiao; Chang, Tianliang; Li, Jiaxing; Zhao, Yuwei; Xu, Yao

    2018-01-01

    Hulless barley (Hordeum vulgare L. var. nudum. hook. f.) has been cultivated as a major crop in the Qinghai-Tibet plateau of China for thousands of years. Compared to other cereal crops, the Tibetan hulless barley has developed stronger endogenous resistances to survive in the severe environment of its habitat. To understand the unique resistant mechanisms of this plant, detailed genetic studies need to be performed. The quantitative real-time reverse transcription-polymerase chain reaction (qRT-PCR) is the most commonly used method in detecting gene expression. However, the selection of stable reference genes under limited experimental conditions was considered to be an essential step for obtaining accurate results in qRT-PCR. In this study, 10 candidate reference genes-ACT (Actin), E2 (Ubiquitin conjugating enzyme 2), TUBα (Alpha-tubulin), TUBβ6 (Beta-tubulin 6), GAPDH (Glyceraldehyde 3-phosphate dehydrogenase), EF-1α (Elongation factor 1-alpha), SAMDC (S-adenosylmethionine decarboxylase), PKABA1 (Gene for protein kinase HvPKABA1), PGK (Phosphoglycerate kinase), and HSP90 (Heat shock protein 90)-were selected from the NCBI gene database of barley. Following qRT-PCR amplifications of all candidate reference genes in Tibetan hulless barley seedlings under various stressed conditions, the stabilities of these candidates were analyzed by three individual software packages including geNorm, NormFinder, and BestKeeper. The results demonstrated that TUBβ6, E2, TUBα, and HSP90 were generally the most suitable sets under all tested conditions; similarly, TUBα and HSP90 showed peak stability under salt stress, TUBα and EF-1α were the most suitable reference genes under cold stress, and ACT and E2 were the most stable under drought stress. Finally, a known circadian gene CCA1 was used to verify the service ability of chosen reference genes. The results confirmed that all recommended reference genes by the three software were suitable for gene expression analysis

  18. A Scan for Positively Selected Genes in the Genomes of Humans and Chimpanzees

    DEFF Research Database (Denmark)

    Nielsen, Rasmus; Bustamente, Carlos; Clark, Andrew G.

    2005-01-01

    Since the divergence of humans and chimpanzees about 5 million years ago, these species have undergone a remarkable evolution with drastic divergence in anatomy and cognitive abilities. At the molecular level, despite the small overall magnitude of DNA sequence divergence, we might expect...... such evolutionary changes to leave a noticeable signature throughout the genome. We here compare 13,731 annotated genes from humans to their chimpanzee orthologs to identify genes that show evidence of positive selection. Many of the genes that present a signature of positive selection tend to be involved...

  19. Selection and validation of reference genes for qRT-PCR expression analysis of candidate genes involved in olfactory communication in the butterfly Bicyclus anynana.

    Directory of Open Access Journals (Sweden)

    Alok Arun

    Full Text Available Real-time quantitative reverse transcription PCR (qRT-PCR is a technique widely used to quantify the transcriptional expression level of candidate genes. qRT-PCR requires the selection of one or several suitable reference genes, whose expression profiles remain stable across conditions, to normalize the qRT-PCR expression profiles of candidate genes. Although several butterfly species (Lepidoptera have become important models in molecular evolutionary ecology, so far no study aimed at identifying reference genes for accurate data normalization for any butterfly is available. The African bush brown butterfly Bicyclus anynana has drawn considerable attention owing to its suitability as a model for evolutionary ecology, and we here provide a maiden extensive study to identify suitable reference gene in this species. We monitored the expression profile of twelve reference genes: eEF-1α, FK506, UBQL40, RpS8, RpS18, HSP, GAPDH, VATPase, ACT3, TBP, eIF2 and G6PD. We tested the stability of their expression profiles in three different tissues (wings, brains, antennae, two developmental stages (pupal and adult and two sexes (male and female, all of which were subjected to two food treatments (food stress and control feeding ad libitum. The expression stability and ranking of twelve reference genes was assessed using two algorithm-based methods, NormFinder and geNorm. Both methods identified RpS8 as the best suitable reference gene for expression data normalization. We also showed that the use of two reference genes is sufficient to effectively normalize the qRT-PCR data under varying tissues and experimental conditions that we used in B. anynana. Finally, we tested the effect of choosing reference genes with different stability on the normalization of the transcript abundance of a candidate gene involved in olfactory communication in B. anynana, the Fatty Acyl Reductase 2, and we confirmed that using an unstable reference gene can drastically alter the

  20. Selection and validation of reference genes for qRT-PCR expression analysis of candidate genes involved in olfactory communication in the butterfly Bicyclus anynana.

    Science.gov (United States)

    Arun, Alok; Baumlé, Véronique; Amelot, Gaël; Nieberding, Caroline M

    2015-01-01

    Real-time quantitative reverse transcription PCR (qRT-PCR) is a technique widely used to quantify the transcriptional expression level of candidate genes. qRT-PCR requires the selection of one or several suitable reference genes, whose expression profiles remain stable across conditions, to normalize the qRT-PCR expression profiles of candidate genes. Although several butterfly species (Lepidoptera) have become important models in molecular evolutionary ecology, so far no study aimed at identifying reference genes for accurate data normalization for any butterfly is available. The African bush brown butterfly Bicyclus anynana has drawn considerable attention owing to its suitability as a model for evolutionary ecology, and we here provide a maiden extensive study to identify suitable reference gene in this species. We monitored the expression profile of twelve reference genes: eEF-1α, FK506, UBQL40, RpS8, RpS18, HSP, GAPDH, VATPase, ACT3, TBP, eIF2 and G6PD. We tested the stability of their expression profiles in three different tissues (wings, brains, antennae), two developmental stages (pupal and adult) and two sexes (male and female), all of which were subjected to two food treatments (food stress and control feeding ad libitum). The expression stability and ranking of twelve reference genes was assessed using two algorithm-based methods, NormFinder and geNorm. Both methods identified RpS8 as the best suitable reference gene for expression data normalization. We also showed that the use of two reference genes is sufficient to effectively normalize the qRT-PCR data under varying tissues and experimental conditions that we used in B. anynana. Finally, we tested the effect of choosing reference genes with different stability on the normalization of the transcript abundance of a candidate gene involved in olfactory communication in B. anynana, the Fatty Acyl Reductase 2, and we confirmed that using an unstable reference gene can drastically alter the expression

  1. "Contrasting patterns of selection at Pinus pinaster Ait. Drought stress candidate genes as revealed by genetic differentiation analyses".

    Science.gov (United States)

    Eveno, Emmanuelle; Collada, Carmen; Guevara, M Angeles; Léger, Valérie; Soto, Alvaro; Díaz, Luis; Léger, Patrick; González-Martínez, Santiago C; Cervera, M Teresa; Plomion, Christophe; Garnier-Géré, Pauline H

    2008-02-01

    The importance of natural selection for shaping adaptive trait differentiation among natural populations of allogamous tree species has long been recognized. Determining the molecular basis of local adaptation remains largely unresolved, and the respective roles of selection and demography in shaping population structure are actively debated. Using a multilocus scan that aims to detect outliers from simulated neutral expectations, we analyzed patterns of nucleotide diversity and genetic differentiation at 11 polymorphic candidate genes for drought stress tolerance in phenotypically contrasted Pinus pinaster Ait. populations across its geographical range. We compared 3 coalescent-based methods: 2 frequentist-like, including 1 approach specifically developed for biallelic single nucleotide polymorphisms (SNPs) here and 1 Bayesian. Five genes showed outlier patterns that were robust across methods at the haplotype level for 2 of them. Two genes presented higher F(ST) values than expected (PR-AGP4 and erd3), suggesting that they could have been affected by the action of diversifying selection among populations. In contrast, 3 genes presented lower F(ST) values than expected (dhn-1, dhn2, and lp3-1), which could represent signatures of homogenizing selection among populations. A smaller proportion of outliers were detected at the SNP level suggesting the potential functional significance of particular combinations of sites in drought-response candidate genes. The Bayesian method appeared robust to low sample sizes, flexible to assumptions regarding migration rates, and powerful for detecting selection at the haplotype level, but the frequentist-like method adapted to SNPs was more efficient for the identification of outlier SNPs showing low differentiation. Population-specific effects estimated in the Bayesian method also revealed populations with lower immigration rates, which could have led to favorable situations for local adaptation. Outlier patterns are discussed

  2. Selection of reliable reference genes for gene expression studies in Trichoderma afroharzianum LTR-2 under oxalic acid stress.

    Science.gov (United States)

    Lyu, Yuping; Wu, Xiaoqing; Ren, He; Zhou, Fangyuan; Zhou, Hongzi; Zhang, Xinjian; Yang, Hetong

    2017-10-01

    An appropriate reference gene is required to get reliable results from gene expression analysis by quantitative real-time reverse transcription PCR (qRT-PCR). In order to identify stable and reliable reference genes in Trichoderma afroharzianum under oxalic acid (OA) stress, six commonly used housekeeping genes, i.e., elongation factor 1, ubiquitin, ubiquitin-conjugating enzyme, glyceraldehyde-3-phosphate dehydrogenase, α-tubulin, actin, from the effective biocontrol isolate T. afroharzianum strain LTR-2 were tested for their expression during growth in liquid culture amended with OA. Four in silico programs (comparative ΔCt, NormFinder, geNorm and BestKeeper) were used to evaluate the expression stabilities of six candidate reference genes. The elongation factor 1 gene EF-1 was identified as the most stably expressed reference gene, and was used as the normalizer to quantify the expression level of the oxalate decarboxylase coding gene OXDC in T. afroharzianum strain LTR-2 under OA stress. The result showed that the expression of OXDC was significantly up-regulated as expected. This study provides an effective method to quantify expression changes of target genes in T. afroharzianum under OA stress. Copyright © 2017 Elsevier B.V. All rights reserved.

  3. A fuzzy logic based PROMETHEE method for material selection problems

    Directory of Open Access Journals (Sweden)

    Muhammet Gul

    2018-03-01

    Full Text Available Material selection is a complex problem in the design and development of products for diverse engineering applications. This paper presents a fuzzy PROMETHEE (Preference Ranking Organization Method for Enrichment Evaluation method based on trapezoidal fuzzy interval numbers that can be applied to the selection of materials for an automotive instrument panel. Also, it presents uniqueness in making a significant contribution to the literature in terms of the application of fuzzy decision-making approach to material selection problems. The method is illustrated, validated, and compared against three different fuzzy MCDM methods (fuzzy VIKOR, fuzzy TOPSIS, and fuzzy ELECTRE in terms of its ranking performance. Also, the relationships between the compared methods and the proposed scenarios for fuzzy PROMETHEE are evaluated via the Spearman’s correlation coefficient. Styrene Maleic Anhydride and Polypropylene are determined optionally as suitable materials for the automotive instrument panel case. We propose a generic fuzzy MCDM methodology that can be practically implemented to material selection problem. The main advantages of the methodology are consideration of the vagueness, uncertainty, and fuzziness to decision making environment.

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

    Science.gov (United States)

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

    2016-10-10

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

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

    Directory of Open Access Journals (Sweden)

    Liming Wang

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

  6. IMPROVEMENT METHOD OF GENE TRANSFER IN Kappaphycus alvarezii

    Directory of Open Access Journals (Sweden)

    St. Hidayah Triana

    2016-11-01

    Full Text Available Method of foreign gene transfer in red seaweed Kappaphycus alvarezii has been reported, however, li-mited number of transgenic F0 (broodstock was obtained. This study was conducted to improve the method of gene transfer mediated by Agrobacterium tumefaciens in order to obtain high percentage of K. alvarezii transgenic. Superoxide dismutase gene from Melastoma malabatrichum (MmCu/Zn-SOD was used as model towards increasing adaptability of K. alvarezii to environmental stress. The treat-ments were the culture media and recovery duration, and each treatment consisted of three replica-tions. The best method was co-cultivation using liquid media, then recovery was conducted in liquid media for 10 days. That treatment allowed higher transformation percentage (90%, regeneration effi-ciency (90%, putative bud efficiency (100%, number of buds and explants sprouted (100% and transgenic explants (100%. The transgenic explants showed an amplification PCR product of Mm-Cu/Zn-SOD gene fragment, whereas the non-transgenic explants showed no amplification product.  All results revealed that suitable method of transgenesis for K. alvarezii has been developed. Keywords:       Agrobacterium tumefaciens, culture media, Kappaphycus alvarezii, recovery duration, transformation

  7. Comparison of multiple gene assembly methods for metabolic engineering

    Science.gov (United States)

    Chenfeng Lu; Karen Mansoorabadi; Thomas Jeffries

    2007-01-01

    A universal, rapid DNA assembly method for efficient multigene plasmid construction is important for biological research and for optimizing gene expression in industrial microbes. Three different approaches to achieve this goal were evaluated. These included creating long complementary extensions using a uracil-DNA glycosylase technique, overlap extension polymerase...

  8. Selective modes determine evolutionary rates, gene compactness and expression patterns in Brassica.

    Science.gov (United States)

    Guo, Yue; Liu, Jing; Zhang, Jiefu; Liu, Shengyi; Du, Jianchang

    2017-07-01

    It has been well documented that most nuclear protein-coding genes in organisms can be classified into two categories: positively selected genes (PSGs) and negatively selected genes (NSGs). The characteristics and evolutionary fates of different types of genes, however, have been poorly understood. In this study, the rates of nonsynonymous substitution (K a ) and the rates of synonymous substitution (K s ) were investigated by comparing the orthologs between the two sequenced Brassica species, Brassica rapa and Brassica oleracea, and the evolutionary rates, gene structures, expression patterns, and codon bias were compared between PSGs and NSGs. The resulting data show that PSGs have higher protein evolutionary rates, lower synonymous substitution rates, shorter gene length, fewer exons, higher functional specificity, lower expression level, higher tissue-specific expression and stronger codon bias than NSGs. Although the quantities and values are different, the relative features of PSGs and NSGs have been largely verified in the model species Arabidopsis. These data suggest that PSGs and NSGs differ not only under selective pressure (K a /K s ), but also in their evolutionary, structural and functional properties, indicating that selective modes may serve as a determinant factor for measuring evolutionary rates, gene compactness and expression patterns in Brassica. © 2017 The Authors The Plant Journal © 2017 John Wiley & Sons Ltd.

  9. Identification of learning and memory genes in canine; promoter investigation and determining the selective pressure.

    Science.gov (United States)

    Seifi Moroudi, Reihane; Masoudi, Ali Akbar; Vaez Torshizi, Rasoul; Zandi, Mohammad

    2014-12-01

    One of the important behaviors of dogs is trainability which is affected by learning and memory genes. These kinds of the genes have not yet been identified in dogs. In the current research, these genes were found in animal models by mining the biological data and scientific literatures. The proteins of these genes were obtained from the UniProt database in dogs and humans. Not all homologous proteins perform similar functions, thus comparison of these proteins was studied in terms of protein families, domains, biological processes, molecular functions, and cellular location of metabolic pathways in Interpro, KEGG, Quick Go and Psort databases. The results showed that some of these proteins have the same performance in the rat or mouse, dog, and human. It is anticipated that the protein of these genes may be effective in learning and memory in dogs. Then, the expression pattern of the recognized genes was investigated in the dog hippocampus using the existing information in the GEO profile. The results showed that BDNF, TAC1 and CCK genes are expressed in the dog hippocampus, therefore, these genes could be strong candidates associated with learning and memory in dogs. Subsequently, due to the importance of the promoter regions in gene function, this region was investigated in the above genes. Analysis of the promoter indicated that the HNF-4 site of BDNF gene and the transcription start site of CCK gene is exposed to methylation. Phylogenetic analysis of protein sequences of these genes showed high similarity in each of these three genes among the studied species. The dN/dS ratio for BDNF, TAC1 and CCK genes indicates a purifying selection during the evolution of the genes.

  10. Selection for the compactness of highly expressed genes in Gallus gallus

    Directory of Open Access Journals (Sweden)

    Zhou Ming

    2010-05-01

    Full Text Available Abstract Background Coding sequence (CDS length, gene size, and intron length vary within a genome and among genomes. Previous studies in diverse organisms, including human, D. Melanogaster, C. elegans, S. cerevisiae, and Arabidopsis thaliana, indicated that there are negative relationships between expression level and gene size, CDS length as well as intron length. Different models such as selection for economy model, genomic design model, and mutational bias hypotheses have been proposed to explain such observation. The debate of which model is a superior one to explain the observation has not been settled down. The chicken (Gallus gallus is an important model organism that bridges the evolutionary gap between mammals and other vertebrates. As D. Melanogaster, chicken has a larger effective population size, selection for chicken genome is expected to be more effective in increasing protein synthesis efficiency. Therefore, in this study the chicken was used as a model organism to elucidate the interaction between gene features and expression pattern upon selection pressure. Results Based on different technologies, we gathered expression data for nuclear protein coding, single-splicing genes from Gallus gallus genome and compared them with gene parameters. We found that gene size, CDS length, first intron length, average intron length, and total intron length are negatively correlated with expression level and expression breadth significantly. The tissue specificity is positively correlated with the first intron length but negatively correlated with the average intron length, and not correlated with the CDS length and protein domain numbers. Comparison analyses showed that ubiquitously expressed genes and narrowly expressed genes with the similar expression levels do not differ in compactness. Our data provided evidence that the genomic design model can not, at least in part, explain our observations. We grouped all somatic-tissue-specific genes

  11. Identification of landscape features influencing gene flow: How useful are habitat selection models?

    Science.gov (United States)

    Gretchen H. Roffler; Michael K. Schwartz; Kristine Pilgrim; Sandra L. Talbot; George K. Sage; Layne G. Adams; Gordon Luikart

    2016-01-01

    Understanding how dispersal patterns are influenced by landscape heterogeneity is critical for modeling species connectivity. Resource selection function (RSF) models are increasingly used in landscape genetics approaches. However, because the ecological factors that drive habitat selection may be different from those influencing dispersal and gene flow, it is...

  12. PSP: rapid identification of orthologous coding genes under positive selection across multiple closely related prokaryotic genomes.

    Science.gov (United States)

    Su, Fei; Ou, Hong-Yu; Tao, Fei; Tang, Hongzhi; Xu, Ping

    2013-12-27

    With genomic sequences of many closely related bacterial strains made available by deep sequencing, it is now possible to investigate trends in prokaryotic microevolution. Positive selection is a sub-process of microevolution, in which a particular mutation is favored, causing the allele frequency to continuously shift in one direction. Wide scanning of prokaryotic genomes has shown that positive selection at the molecular level is much more frequent than expected. Genes with significant positive selection may play key roles in bacterial adaption to different environmental pressures. However, selection pressure analyses are computationally intensive and awkward to configure. Here we describe an open access web server, which is designated as PSP (Positive Selection analysis for Prokaryotic genomes) for performing evolutionary analysis on orthologous coding genes, specially designed for rapid comparison of dozens of closely related prokaryotic genomes. Remarkably, PSP facilitates functional exploration at the multiple levels by assignments and enrichments of KO, GO or COG terms. To illustrate this user-friendly tool, we analyzed Escherichia coli and Bacillus cereus genomes and found that several genes, which play key roles in human infection and antibiotic resistance, show significant evidence of positive selection. PSP is freely available to all users without any login requirement at: http://db-mml.sjtu.edu.cn/PSP/. PSP ultimately allows researchers to do genome-scale analysis for evolutionary selection across multiple prokaryotic genomes rapidly and easily, and identify the genes undergoing positive selection, which may play key roles in the interactions of host-pathogen and/or environmental adaptation.

  13. Signatures of positive selection in LY96 gene in vertebrates

    Indian Academy of Sciences (India)

    2013-11-06

    Nov 6, 2013 ... 2002), which is implicated in lipid recognition, particularly in the recognition of .... comparing the corresponding part of two secondary structures. (Kabsch and ... protein sequence classification and comparison. Methods Mol.

  14. Personnel selection using group fuzzy AHP and SAW methods

    Directory of Open Access Journals (Sweden)

    Ali Reza Afshari

    2017-01-01

    Full Text Available Personnel evaluation and selection is a very important activity for the enterprises. Different job needs different ability and the requirement of criteria which can measure ability is different. It needs a suitable and flexible method to evaluate the performance of each candidate according to different requirements of different jobs in relation to each criterion. Analytic Hierarchy Process (AHP is one of Multi Criteria decision making methods derived from paired comparisons. Simple Additive Weighting (SAW is most frequently used multi attribute decision technique. The method is based on the weighted average. It successfully models the ambiguity and imprecision associated with the pair wise comparison process and reduces the personal biasness. This study tries to analyze the Analytic Hierarchy Process in order to make the recruitment process more reasonable, based on the fuzzy multiple criteria decision making model to achieve the goal of personnel selection. Finally, an example is implemented to demonstrate the practicability of the proposed method.

  15. Toward optimal feature selection using ranking methods and classification algorithms

    Directory of Open Access Journals (Sweden)

    Novaković Jasmina

    2011-01-01

    Full Text Available We presented a comparison between several feature ranking methods used on two real datasets. We considered six ranking methods that can be divided into two broad categories: statistical and entropy-based. Four supervised learning algorithms are adopted to build models, namely, IB1, Naive Bayes, C4.5 decision tree and the RBF network. We showed that the selection of ranking methods could be important for classification accuracy. In our experiments, ranking methods with different supervised learning algorithms give quite different results for balanced accuracy. Our cases confirm that, in order to be sure that a subset of features giving the highest accuracy has been selected, the use of many different indices is recommended.

  16. Evidence for positive selection on the leptin gene in Cetacea and Pinnipedia.

    Directory of Open Access Journals (Sweden)

    Li Yu

    Full Text Available The leptin gene has received intensive attention and scientific investigation for its importance in energy homeostasis and reproductive regulation in mammals. Furthermore, study of the leptin gene is of crucial importance for public health, particularly for its role in obesity, as well as for other numerous physiological roles that it plays in mammals. In the present work, we report the identification of novel leptin genes in 4 species of Cetacea, and a comparison with 55 publicly available leptin sequences from mammalian genome assemblies and previous studies. Our study provides evidence for positive selection in the suborder Odontoceti (toothed whales of the Cetacea and the family Phocidae (earless seals of the Pinnipedia. We also detected positive selection in several leptin gene residues in these two lineages. To test whether leptin and its receptor evolved in a coordinated manner, we analyzed 24 leptin receptor gene (LPR sequences from available mammalian genome assemblies and other published data. Unlike the case of leptin, our analyses did not find evidence of positive selection for LPR across the Cetacea and Pinnipedia lineages. In line with this, positively selected sites identified in the leptin genes of these two lineages were located outside of leptin receptor binding sites, which at least partially explains why co-evolution of leptin and its receptor was not observed in the present study. Our study provides interesting insights into current understanding of the evolution of mammalian leptin genes in response to selective pressures from life in an aquatic environment, and leads to a hypothesis that new tissue specificity or novel physiologic functions of leptin genes may have arisen in both odontocetes and phocids. Additional data from other species encompassing varying life histories and functional tests of the adaptive role of the amino acid changes identified in this study will help determine the factors that promote the adaptive

  17. Method for Selection of Solvents for Promotion of Organic Reactions

    DEFF Research Database (Denmark)

    Gani, Rafiqul; Jiménez-González, Concepción; Constable, David J.C.

    2005-01-01

    is to produce, for a given reaction, a short list of chemicals that could be considered as potential solvents, to evaluate their performance in the reacting system, and, based on this, to rank them according to a scoring system. Several examples of application are given to illustrate the main features and steps......A method to select appropriate green solvents for the promotion of a class of organic reactions has been developed. The method combines knowledge from industrial practice and physical insights with computer-aided property estimation tools for selection/design of solvents. In particular, it employs...... estimates of thermodynamic properties to generate a knowledge base of reaction, solvent and environment related properties that directly or indirectly influence the rate and/or conversion of a given reaction. Solvents are selected using a rules-based procedure where the estimated reaction-solvent properties...

  18. An iterative method for selecting degenerate multiplex PCR primers.

    Science.gov (United States)

    Souvenir, Richard; Buhler, Jeremy; Stormo, Gary; Zhang, Weixiong

    2007-01-01

    Single-nucleotide polymorphism (SNP) genotyping is an important molecular genetics process, which can produce results that will be useful in the medical field. Because of inherent complexities in DNA manipulation and analysis, many different methods have been proposed for a standard assay. One of the proposed techniques for performing SNP genotyping requires amplifying regions of DNA surrounding a large number of SNP loci. To automate a portion of this particular method, it is necessary to select a set of primers for the experiment. Selecting these primers can be formulated as the Multiple Degenerate Primer Design (MDPD) problem. The Multiple, Iterative Primer Selector (MIPS) is an iterative beam-search algorithm for MDPD. Theoretical and experimental analyses show that this algorithm performs well compared with the limits of degenerate primer design. Furthermore, MIPS outperforms an existing algorithm that was designed for a related degenerate primer selection problem.

  19. Investigation of the paired-gear method in selectivity studies

    DEFF Research Database (Denmark)

    Sistiaga, Manu; Herrmann, Bent; Larsen, R.B.

    2009-01-01

    was repeated throughout the eight cases in this investigation. When using the paired-gear method, the distribution of the estimated L50 and SR is wider; the distribution of the estimated split parameter has a higher variability than the true split; the estimated mean L50 and SR can be biased; the estimated...... recommend that the methodology used to obtain selectivity estimates using the paired-gear method be reviewed....

  20. Selective Integration in the Material-Point Method

    DEFF Research Database (Denmark)

    Andersen, Lars; Andersen, Søren; Damkilde, Lars

    2009-01-01

    The paper deals with stress integration in the material-point method. In order to avoid parasitic shear in bending, a formulation is proposed, based on selective integration in the background grid that is used to solve the governing equations. The suggested integration scheme is compared...... to a traditional material-point-method computation in which the stresses are evaluated at the material points. The deformation of a cantilever beam is analysed, assuming elastic or elastoplastic material behaviour....

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

    Directory of Open Access Journals (Sweden)

    Shohag Barman

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

  2. Selection of Suitable Reference Genes for Quantitative Real-time PCR in Sapium sebiferum

    Directory of Open Access Journals (Sweden)

    Xue Chen

    2017-05-01

    Full Text Available Chinese tallow (Sapium sebiferum L. is a promising landscape and bioenergy plant. Measuring gene expression by quantitative real-time polymerase chain reaction (qRT-PCR can provide valuable information on gene function. Stably expressed reference genes for normalization are a prerequisite for ensuring the accuracy of the target gene expression level among different samples. However, the reference genes in Chinese tallow have not been systematically validated. In this study, 12 candidate reference genes (18S, GAPDH, UBQ, RPS15, SAND, TIP41, 60S, ACT7, PDF2, APT, TBP, and TUB were investigated with qRT-PCR in 18 samples, including those from different tissues, from plants treated with sucrose and cold stresses. The data were calculated with four common algorithms, geNorm, BestKeeper, NormFinder, and the delta cycle threshold (ΔCt. TIP41 and GAPDH were the most stable for the tissue-specific experiment, GAPDH and 60S for cold treatment, and GAPDH and UBQ for sucrose stresses, while the least stable genes were 60S, TIP41, and 18S respectively. The comprehensive results showed APT, GAPDH, and UBQ to be the top-ranked stable genes across all the samples. The stability of 60S was the lowest during all experiments. These selected reference genes were further validated by comparing the expression profiles of the chalcone synthase gene in Chinese tallow in different samples. The results will help to improve the accuracy of gene expression studies in Chinese tallow.

  3. Standard methods for rearing and selection of Apis mellifera queens

    DEFF Research Database (Denmark)

    Büchler, Ralph; Andonov, Sreten; Bienefeld, Kaspar

    2013-01-01

    Here we cover a wide range of methods currently in use and recommended in modern queen rearing, selection and breeding. The recommendations are meant to equally serve as standards for both scientific and practical beekeeping purposes. The basic conditions and different management techniques for q...

  4. Preparation of Iron Nanoparticles by Selective Leaching Method

    Czech Academy of Sciences Publication Activity Database

    Michalcová, A.; Vojtěch, D.; Kubatík, Tomáš František; Stehlíková, K.; Brabec, F.; Marek, I.

    2015-01-01

    Roč. 128, č. 4 (2015), s. 640-642 ISSN 0587-4246. [International Symposium on Physics of Materials (ISPMA) /13./. Prague, 31.08.2014-04.09.2014] Institutional support: RVO:61389021 Keywords : Iron nanoparticles * selective leaching method Subject RIV: JK - Corrosion ; Surface Treatment of Materials Impact factor: 0.525, year: 2015

  5. Sampling point selection for energy estimation in the quasicontinuum method

    NARCIS (Netherlands)

    Beex, L.A.A.; Peerlings, R.H.J.; Geers, M.G.D.

    2010-01-01

    The quasicontinuum (QC) method reduces computational costs of atomistic calculations by using interpolation between a small number of so-called repatoms to represent the displacements of the complete lattice and by selecting a small number of sampling atoms to estimate the total potential energy of

  6. Selecting and Using Mathematics Methods Texts: Nontrivial Tasks

    Science.gov (United States)

    Harkness, Shelly Sheats; Brass, Amy

    2017-01-01

    Mathematics methods textbooks/texts are important components of many courses for preservice teachers. Researchers should explore how these texts are selected and used. Within this paper we report the findings of a survey administered electronically to 132 members of the Association of Mathematics Teacher Educators (AMTE) in order to answer the…

  7. Underground Mining Method Selection Using WPM and PROMETHEE

    Science.gov (United States)

    Balusa, Bhanu Chander; Singam, Jayanthu

    2018-04-01

    The aim of this paper is to represent the solution to the problem of selecting suitable underground mining method for the mining industry. It is achieved by using two multi-attribute decision making techniques. These two techniques are weighted product method (WPM) and preference ranking organization method for enrichment evaluation (PROMETHEE). In this paper, analytic hierarchy process is used for weight's calculation of the attributes (i.e. parameters which are used in this paper). Mining method selection depends on physical parameters, mechanical parameters, economical parameters and technical parameters. WPM and PROMETHEE techniques have the ability to consider the relationship between the parameters and mining methods. The proposed techniques give higher accuracy and faster computation capability when compared with other decision making techniques. The proposed techniques are presented to determine the effective mining method for bauxite mine. The results of these techniques are compared with methods used in the earlier research works. The results show, conventional cut and fill method is the most suitable mining method.

  8. Determination of Selection Method in Genetic Algorithm for Land Suitability

    Directory of Open Access Journals (Sweden)

    Irfianti Asti Dwi

    2016-01-01

    Full Text Available Genetic Algoirthm is one alternative solution in the field of modeling optimization, automatic programming and machine learning. The purpose of the study was to compare some type of selection methods in Genetic Algorithm for land suitability. Contribution of this research applies the best method to develop region based horticultural commodities. This testing is done by comparing the three methods on the method of selection, the Roulette Wheel, Tournament Selection and Stochastic Universal Sampling. Parameters of the locations used in the test scenarios include Temperature = 27°C, Rainfall = 1200 mm, hummidity = 30%, Cluster fruit = 4, Crossover Probabiitiy (Pc = 0.6, Mutation Probabilty (Pm = 0.2 and Epoch = 10. The second test epoch incluides location parameters consist of Temperature = 30°C, Rainfall = 2000 mm, Humidity = 35%, Cluster fruit = 5, Crossover Probability (Pc = 0.7, Mutation Probability (Pm = 0.3 and Epoch 10. The conclusion of this study shows that the Roulette Wheel is the best method because it produces more stable and fitness value than the other two methods.

  9. [Methylation of selected tumor-supressor genes in benign and malignant ovarian tumors].

    Science.gov (United States)

    Cul'bová, M; Lasabová, Z; Stanclová, A; Tilandyová, P; Zúbor, P; Fiolka, R; Danko, J; Visnovský, J

    2011-09-01

    To evaluate the usefullness of examination of methylation status of selected tumor-supressor genes in early diagnosis of ovarian cancer. Prospective clinical study. Department of Gynecology and Obstetrics, Department of Molecular Biology, Jessenius Medical Faculty, Commenius University, Martin, Slovak Republic. In this study we analyzed hypermethylation of 5 genes RASSF1A, GSTP, E-cadherin, p16 and APC in ovarian tumor samples from 34 patients - 13 patients with epithelial ovarian cancer, 2 patients with border-line ovarian tumors, 12 patients with benign lesions of ovaries and 7 patients with healthy ovarian tissue. The methylation status of promoter region of tumor-supressor genes was determined by Methylation Specific Polymerase Chain Reaction (MSP) using a nested two-step approach with bisulfite modified DNA template and specific primers. Gene methylation analysis revealed hypermethylation of gene RASSF1A (46%) and GSTP (8%) only in malignant ovarian tissue samples. Ecad, p16 and APC genes were methylated both in maignant and benign tissue samples. Methylation positivity in observed genes was present independently to all clinical stages of ovarian cancer and to tumor grades. However, there was observed a trend of increased number and selective involvement of methylated genes with increasing disease stages. Furthermore, there was no association between positive methylation status and histological subtypes of ovarian carcinomas. RASSF1A and GSTP promoter methylation positivity is associated with ovarian cancer. The revealed gene-selective methylation positivity and the increased number of methylated genes with advancing disease stages could be considered as a useful molecular marker for early detection of ovarian cancer. However, there is need to find diagnostic approach of specifically and frequently methylated genes to determining a methylation phenotype for early detection of ovarian malignancies.

  10. Selection of internal control genes for real-time quantitative PCR in ovary and uterus of sows across pregnancy.

    Directory of Open Access Journals (Sweden)

    María Martínez-Giner

    Full Text Available BACKGROUND: Reproductive traits play a key role in pig production in order to reduce costs and increase economic returns. Among others, gene expression analyses represent a useful approach to study genetic mechanisms underlying reproductive traits in pigs. The application of reverse-transcription quantitative PCR requires the selection of appropriate reference genes, whose expression levels should not be affected by the experimental conditions, especially when comparing gene expression across different physiological stages. RESULTS: The gene expression stability of ten potential reference genes was studied by three different methods (geNorm, NormFinder and BestKeeper in ovary and uterus collected at five different physiological time points (heat, and 15, 30, 45 and 60 days of pregnancy. Although final ranking differed, the three algorithms gave very similar results. Thus, the most stable genes across time were TBP and UBC in uterus and TBP and HPRT1 in ovary, while HMBS and ACTB showed the less stable expression in uterus and ovary, respectively. When studied as a systematic effect, the reproductive stage did not significantly affect the expression of the candidate reference genes except at 30d and 60d of pregnancy, when a general drop in expression was observed in ovary. CONCLUSIONS: Based in our results, we propose the use of TBP, UBC and SDHA in uterus and TBP, GNB2L1 and HPRT1 in ovary for normalization of longitudinal expression studies using quantitative PCR in sows.

  11. Examination of Signatures of Recent Positive Selection on Genes Involved in Human Sialic Acid Biology.

    Science.gov (United States)

    Moon, Jiyun M; Aronoff, David M; Capra, John A; Abbot, Patrick; Rokas, Antonis

    2018-03-28

    Sialic acids are nine carbon sugars ubiquitously found on the surfaces of vertebrate cells and are involved in various immune response-related processes. In humans, at least 58 genes spanning diverse functions, from biosynthesis and activation to recycling and degradation, are involved in sialic acid biology. Because of their role in immunity, sialic acid biology genes have been hypothesized to exhibit elevated rates of evolutionary change. Consistent with this hypothesis, several genes involved in sialic acid biology have experienced higher rates of non-synonymous substitutions in the human lineage than their counterparts in other great apes, perhaps in response to ancient pathogens that infected hominins millions of years ago (paleopathogens). To test whether sialic acid biology genes have also experienced more recent positive selection during the evolution of the modern human lineage, reflecting adaptation to contemporary cosmopolitan or geographically-restricted pathogens, we examined whether their protein-coding regions showed evidence of recent hard and soft selective sweeps. This examination involved the calculation of four measures that quantify changes in allele frequency spectra, extent of population differentiation, and haplotype homozygosity caused by recent hard and soft selective sweeps for 55 sialic acid biology genes using publicly available whole genome sequencing data from 1,668 humans from three ethnic groups. To disentangle evidence for selection from confounding demographic effects, we compared the observed patterns in sialic acid biology genes to simulated sequences of the same length under a model of neutral evolution that takes into account human demographic history. We found that the patterns of genetic variation of most sialic acid biology genes did not significantly deviate from neutral expectations and were not significantly different among genes belonging to different functional categories. Those few sialic acid biology genes that

  12. Physical non-viral gene delivery methods for tissue engineering

    Science.gov (United States)

    Mellott, Adam J.; Forrest, M. Laird; Detamore, Michael S.

    2016-01-01

    The integration of gene therapy into tissue engineering to control differentiation and direct tissue formation is not a new concept; however, successful delivery of nucleic acids into primary cells, progenitor cells, and stem cells has proven exceptionally challenging. Viral vectors are generally highly effective at delivering nucleic acids to a variety of cell populations, both dividing and non-dividing, yet these viral vectors are marred by significant safety concerns. Non-viral vectors are preferred for gene therapy, despite lower transfection efficiencies, and possess many customizable attributes that are desirable for tissue engineering applications. However, there is no single non-viral gene delivery strategy that “fits-all” cell types and tissues. Thus, there is a compelling opportunity to examine different non-viral vectors, especially physical vectors, and compare their relative degrees of success. This review examines the advantages and disadvantages of physical non-viral methods (i.e., microinjection, ballistic gene delivery, electroporation, sonoporation, laser irradiation, magnetofection, and electric field-induced molecular vibration), with particular attention given to electroporation because of its versatility, with further special emphasis on Nucleofection™. In addition, attributes of cellular character that can be used to improve differentiation strategies are examined for tissue engineering applications. Ultimately, electroporation exhibits a high transfection efficiency in many cell types, which is highly desirable for tissue engineering applications, but electroporation and other physical non-viral gene delivery methods are still limited by poor cell viability. Overcoming the challenge of poor cell viability in highly efficient physical non-viral techniques is the key to using gene delivery to enhance tissue engineering applications. PMID:23099792

  13. Physical non-viral gene delivery methods for tissue engineering.

    Science.gov (United States)

    Mellott, Adam J; Forrest, M Laird; Detamore, Michael S

    2013-03-01

    The integration of gene therapy into tissue engineering to control differentiation and direct tissue formation is not a new concept; however, successful delivery of nucleic acids into primary cells, progenitor cells, and stem cells has proven exceptionally challenging. Viral vectors are generally highly effective at delivering nucleic acids to a variety of cell populations, both dividing and non-dividing, yet these viral vectors are marred by significant safety concerns. Non-viral vectors are preferred for gene therapy, despite lower transfection efficiencies, and possess many customizable attributes that are desirable for tissue engineering applications. However, there is no single non-viral gene delivery strategy that "fits-all" cell types and tissues. Thus, there is a compelling opportunity to examine different non-viral vectors, especially physical vectors, and compare their relative degrees of success. This review examines the advantages and disadvantages of physical non-viral methods (i.e., microinjection, ballistic gene delivery, electroporation, sonoporation, laser irradiation, magnetofection, and electric field-induced molecular vibration), with particular attention given to electroporation because of its versatility, with further special emphasis on Nucleofection™. In addition, attributes of cellular character that can be used to improve differentiation strategies are examined for tissue engineering applications. Ultimately, electroporation exhibits a high transfection efficiency in many cell types, which is highly desirable for tissue engineering applications, but electroporation and other physical non-viral gene delivery methods are still limited by poor cell viability. Overcoming the challenge of poor cell viability in highly efficient physical non-viral techniques is the key to using gene delivery to enhance tissue engineering applications.

  14. Selective saturation method for EPR dosimetry with tooth enamel

    International Nuclear Information System (INIS)

    Ignatiev, E.A.; Romanyukha, A.A.; Koshta, A.A.; Wieser, A.

    1996-01-01

    The method of selective saturation is based on the difference in the microwave (mw) power dependence of the background and radiation induced EPR components of the tooth enamel spectrum. The subtraction of the EPR spectrum recorded at low mw power from that recorded at higher mw power provides a considerable reduction of the background component in the spectrum. The resolution of the EPR spectrum could be improved 10-fold, however simultaneously the signal-to-noise ratio was found to be reduced twice. A detailed comparative study of reference samples with known absorbed doses was performed to demonstrate the advantage of the method. The application of the selective saturation method for EPR dosimetry with tooth enamel reduced the lower limit of EPR dosimetry to about 100 mGy. (author)

  15. Some selected quantitative methods of thermal image analysis in Matlab.

    Science.gov (United States)

    Koprowski, Robert

    2016-05-01

    The paper presents a new algorithm based on some selected automatic quantitative methods for analysing thermal images. It shows the practical implementation of these image analysis methods in Matlab. It enables to perform fully automated and reproducible measurements of selected parameters in thermal images. The paper also shows two examples of the use of the proposed image analysis methods for the area of ​​the skin of a human foot and face. The full source code of the developed application is also provided as an attachment. The main window of the program during dynamic analysis of the foot thermal image. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  16. A new DEA-GAHP method for supplier selection problem

    Directory of Open Access Journals (Sweden)

    Behrooz Ahadian

    2012-10-01

    Full Text Available Supplier selection is one of the most important decisions made in supply chain management. Supplier evaluation problem has been in the center of supply chain researcher’s attention in these years. Managers regard some of these studies and methods inappropriate due to simple, weight scoring methods that generally are based on subjective opinions and judgments of decision maker units involved in the supplier evaluation process yielding imprecise and even unreliable results. This paper seeks to propose a methodology to integrate data envelopment analysis (DEA and group analytical hierarchy process (GAHP for evaluating and selecting the most efficient supplier. We develop a methodology, which consists of 6 steps, one by one has been introduced in lecture and finally applicability of proposed method is indicated by assessing 12 suppliers in a numerical example.

  17. Selection of Reference Genes for Expression Studies in Diaphorina citri (Hemiptera: Liviidae).

    Science.gov (United States)

    Bassan, Meire Menezes; Angelotti-Mendonc A, Je Ssika; Alves, Gustavo Rodrigues; Yamamoto, Pedro Takao; Moura O Filho, Francisco de Assis Alves

    2017-12-05

    The Asian citrus psyllid, Diaphorina citri Kuwayama (Hemiptera: Liviidae), is considered the main vector of the bacteria associated with huanglongbing, a very serious disease that has threatened the world citrus industry. The absence of efficient control management protocols, including a lack of resistant cultivars, has led to the development of different approaches to study this pathosystem. The production of resistant genotypes relies on D. citri gene expression analyses by RT-qPCR to assess control of the vector population. High-quality, reliable RT-qPCR analyses depend upon proper reference gene selection and validation. However, adequate D. citri reference genes have not yet been identified. In the present study, we evaluated the genes EF 1-α, ACT, GAPDH, RPL7, RPL17, and TUB as candidate reference genes for this insect. Gene expression stability was evaluated using the mathematical algorithms deltaCt, NormFinder, BestKeeper, and geNorm, at five insect developmental stages, grown on two different plant hosts [Citrus sinensis (L.) Osbeck (Sapindales: Rutaceae) and Murraya paniculata (L.) Jack (Sapindales: Rutaceae)]. The final gene ranking was calculated using RefFinder software, and the V-ATPase-A gene was selected for validation. According to our results, two reference genes are recommended when different plant hosts and developmental stages are considered. Considering gene expression studies in D. citri grown on M. paniculata, regardless of the insect developmental stage, GAPDH and RPL7 have the best fit as reference genes in RT-qPCR analyses, whereas GAPDH and EF 1-α are recommended as reference genes in insect studies using C. sinensis. © The Author(s) 2017. Published by Oxford University Press on behalf of Entomological Society of America. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

  18. Self-assembled pentablock copolymers for selective and sustained gene delivery

    Energy Technology Data Exchange (ETDEWEB)

    Zhang, Bingqi [Iowa State Univ., Ames, IA (United States)

    2011-05-15

    The poly(diethylaminoethyl methacrylate) (PDEAEM) - Pluronic F127 - PDEAEM pentablock copolymer (PB) gene delivery vector system has been found to possess an inherent selectivity in transfecting cancer cells over non-cancer cells in vitro, without attaching any targeting ligands. In order to understand the mechanism of this selective transfection, three possible intracellular barriers to transfection were investigated in both cancer and non-cancer cells. We concluded that escape from the endocytic pathway served as the primary intracellular barrier for PB-mediated transfection. Most likely, PB vectors were entrapped and rendered non-functional in acidic lysosomes of non-cancer cells, but survived in less acidic lysosomes of cancer cells. The work highlights the importance of identifying intracellular barriers for different gene delivery systems and provides a new paradigm for designing targeting vectors based on intracellular differences between cell types, rather than through the use of targeting ligands. The PB vector was further developed to simultaneously deliver anticancer drugs and genes, which showed a synergistic effect demonstrated by significantly enhanced gene expression in vitro. Due to the thermosensitive gelation behavior, the PB vector packaging both drug and gene was also investigated for its in vitro sustained release properties by using polyethylene glycol diacrylate as a barrier gel to mimic the tumor matrix in vivo. Overall, this work resulted in the development of a gene delivery vector for sustained and selective gene delivery to tumor cells for cancer therapy.

  19. Pyrochemical and Dry Processing Methods Program. A selected bibliography

    International Nuclear Information System (INIS)

    McDuffie, H.F.; Smith, D.H.; Owen, P.T.

    1979-03-01

    This selected bibliography with abstracts was compiled to provide information support to the Pyrochemical and Dry Processing Methods (PDPM) Program sponsored by DOE and administered by the Argonne National Laboratory. Objectives of the PDPM Program are to evaluate nonaqueous methods of reprocessing spent fuel as a route to the development of proliferation-resistant and diversion-resistant methods for widespread use in the nuclear industry. Emphasis was placed on the literature indexed in the ERDA--DOE Energy Data Base (EDB). The bibliography includes indexes to authors, subject descriptors, EDB subject categories, and titles

  20. Pyrochemical and Dry Processing Methods Program. A selected bibliography

    Energy Technology Data Exchange (ETDEWEB)

    McDuffie, H.F.; Smith, D.H.; Owen, P.T.

    1979-03-01

    This selected bibliography with abstracts was compiled to provide information support to the Pyrochemical and Dry Processing Methods (PDPM) Program sponsored by DOE and administered by the Argonne National Laboratory. Objectives of the PDPM Program are to evaluate nonaqueous methods of reprocessing spent fuel as a route to the development of proliferation-resistant and diversion-resistant methods for widespread use in the nuclear industry. Emphasis was placed on the literature indexed in the ERDA--DOE Energy Data Base (EDB). The bibliography includes indexes to authors, subject descriptors, EDB subject categories, and titles.

  1. Selection method and characterization of neutron monochromator natural crystals

    International Nuclear Information System (INIS)

    Stasiulevicius, R.; Kastner, G.F.

    2000-01-01

    Thermal neutrons are important analytical tools for microscopic material probe. These neutrons can be selected by diffraction technique using monocrystal, usually artificial. A crystal selection process was implemented and the characteristics of natural specimens were studied by activation analysis-k 0 method. The representative 120 samples, of which 21 best types, were irradiated in IPR-R1 and measured with a neutron diffractometer at IEA-R1m Brazilian reactors. These results are useful for database build up and ease the choice of appropriate natural crystal, with some advantage options: highest intensity diffracted, enlarging the energy operational interval and optimal performance in special applications. (author)

  2. Systematic differences in the response of genetic variation to pedigree and genome-based selection methods.

    Science.gov (United States)

    Heidaritabar, M; Vereijken, A; Muir, W M; Meuwissen, T; Cheng, H; Megens, H-J; Groenen, M A M; Bastiaansen, J W M

    2014-12-01

    Genomic selection (GS) is a DNA-based method of selecting for quantitative traits in animal and plant breeding, and offers a potentially superior alternative to traditional breeding methods that rely on pedigree and phenotype information. Using a 60 K SNP chip with markers spaced throughout the entire chicken genome, we compared the impact of GS and traditional BLUP (best linear unbiased prediction) selection methods applied side-by-side in three different lines of egg-laying chickens. Differences were demonstrated between methods, both at the level and genomic distribution of allele frequency changes. In all three lines, the average allele frequency changes were larger with GS, 0.056 0.064 and 0.066, compared with BLUP, 0.044, 0.045 and 0.036 for lines B1, B2 and W1, respectively. With BLUP, 35 selected regions (empirical P selected regions were identified. Empirical thresholds for local allele frequency changes were determined from gene dropping, and differed considerably between GS (0.167-0.198) and BLUP (0.105-0.126). Between lines, the genomic regions with large changes in allele frequencies showed limited overlap. Our results show that GS applies selection pressure much more locally than BLUP, resulting in larger allele frequency changes. With these results, novel insights into the nature of selection on quantitative traits have been gained and important questions regarding the long-term impact of GS are raised. The rapid changes to a part of the genetic architecture, while another part may not be selected, at least in the short term, require careful consideration, especially when selection occurs before phenotypes are observed.

  3. Expression of Root Genes in Arabidopsis Seedlings Grown by Standard and Improved Growing Methods.

    Science.gov (United States)

    Qu, Yanli; Liu, Shuai; Bao, Wenlong; Xue, Xian; Ma, Zhengwen; Yokawa, Ken; Baluška, František; Wan, Yinglang

    2017-05-03

    Roots of Arabidopsis thaliana seedlings grown in the laboratory using the traditional plant-growing culture system (TPG) were covered to maintain them in darkness. This new method is based on a dark chamber and is named the improved plant-growing method (IPG). We measured the light conditions in dark chambers, and found that the highest light intensity was dramatically reduced deeper in the dark chamber. In the bottom and side parts of dark chambers, roots were almost completely shaded. Using the high-throughput RNA sequencing method on the whole RNA extraction from roots, we compared the global gene expression levels in roots of seedlings from these two conditions and identified 141 differently expressed genes (DEGs) between them. According to the KEGG (Kyoto Encyclopedia of Genes and Genomes) enrichment, the flavone and flavonol biosynthesis and flavonoid biosynthesis pathways were most affected among all annotated pathways. Surprisingly, no genes of known plant photoreceptors were identified as DEGs by this method. Considering that the light intensity was decreased in the IPG system, we collected four sections (1.5 cm for each) of Arabidopsis roots grown in TPG and IPG conditions, and the spatial-related differential gene expression levels of plant photoreceptors and polar auxin transporters, including CRY1 , CRY2 , PHYA , PHYB , PHOT1 , PHOT2 , and UVR8 were analyzed by qRT-PCR. Using these results, we generated a map of the spatial-related expression patterns of these genes under IPG and TPG conditions. The expression levels of light-related genes in roots is highly sensitive to illumination and it provides a background reference for selecting an improved culture method for laboratory-maintained Arabidopsis seedlings.

  4. Purifying selection acts on coding and non-coding sequences of paralogous genes in Arabidopsis thaliana.

    Science.gov (United States)

    Hoffmann, Robert D; Palmgren, Michael

    2016-06-13

    Whole-genome duplications in the ancestors of many diverse species provided the genetic material for evolutionary novelty. Several models explain the retention of paralogous genes. However, how these models are reflected in the evolution of coding and non-coding sequences of paralogous genes is unknown. Here, we analyzed the coding and non-coding sequences of paralogous genes in Arabidopsis thaliana and compared these sequences with those of orthologous genes in Arabidopsis lyrata. Paralogs with lower expression than their duplicate had more nonsynonymous substitutions, were more likely to fractionate, and exhibited less similar expression patterns with their orthologs in the other species. Also, lower-expressed genes had greater tissue specificity. Orthologous conserved non-coding sequences in the promoters, introns, and 3' untranslated regions were less abundant at lower-expressed genes compared to their higher-expressed paralogs. A gene ontology (GO) term enrichment analysis showed that paralogs with similar expression levels were enriched in GO terms related to ribosomes, whereas paralogs with different expression levels were enriched in terms associated with stress responses. Loss of conserved non-coding sequences in one gene of a paralogous gene pair correlates with reduced expression levels that are more tissue specific. Together with increased mutation rates in the coding sequences, this suggests that similar forces of purifying selection act on coding and non-coding sequences. We propose that coding and non-coding sequences evolve concurrently following gene duplication.

  5. Purifying Selection Maintains Dosage-Sensitive Genes during Degeneration of the Threespine Stickleback Y Chromosome

    Science.gov (United States)

    White, Michael A.; Kitano, Jun; Peichel, Catherine L.

    2015-01-01

    Sex chromosomes are subject to unique evolutionary forces that cause suppression of recombination, leading to sequence degeneration and the formation of heteromorphic chromosome pairs (i.e., XY or ZW). Although progress has been made in characterizing the outcomes of these evolutionary processes on vertebrate sex chromosomes, it is still unclear how recombination suppression and sequence divergence typically occur and how gene dosage imbalances are resolved in the heterogametic sex. The threespine stickleback fish (Gasterosteus aculeatus) is a powerful model system to explore vertebrate sex chromosome evolution, as it possesses an XY sex chromosome pair at relatively early stages of differentiation. Using a combination of whole-genome and transcriptome sequencing, we characterized sequence evolution and gene expression across the sex chromosomes. We uncovered two distinct evolutionary strata that correspond with known structural rearrangements on the Y chromosome. In the oldest stratum, only a handful of genes remain, and these genes are under strong purifying selection. By comparing sex-linked gene expression with expression of autosomal orthologs in an outgroup, we show that dosage compensation has not evolved in threespine sticklebacks through upregulation of the X chromosome in males. Instead, in the oldest stratum, the genes that still possess a Y chromosome allele are enriched for genes predicted to be dosage sensitive in mammals and yeast. Our results suggest that dosage imbalances may have been avoided at haploinsufficient genes by retaining function of the Y chromosome allele through strong purifying selection. PMID:25818858

  6. Factors of Selection of the Stock Allocation Method

    Directory of Open Access Journals (Sweden)

    Rohov Heorhii K.

    2014-03-01

    Full Text Available The article describes results of the author’s study of factors of making strategic decisions on selection of methods of stock allocation by public joint stock companies in Ukraine. The author used the Random forest mathematical apparatus of classification trees building and also informal methods. The article analyses the reasons that restrain public allocation of stock. It shows significant influence upon selection of a method of stock allocation of such factors as capital concentration, balance rate of corporate rights, sector of economy and significant participation of the institutes of common investment or the state in the authorised capital. The built hierarchical model of classification of factors of the issuing policy of joint stock companies finds logical justification in specific features of the institutional environment, however, it does not fit into the framework of the classical concept of the market economy. The model could be used both for formation of goals of corporate financial strategies and in the process of improvement of state regulation of activity of securities issuers. The prospect of further studies in this direction is identification of transformation of factors of selection of the stock allocation method under conditions of revival of the stock market.

  7. Tracing evolutionary relicts of positive selection on eight malaria-related immune genes in mammals.

    Science.gov (United States)

    Huang, Bing-Hong; Liao, Pei-Chun

    2015-07-01

    Plasmodium-induced malaria widely infects primates and other mammals. Multiple past studies have revealed that positive selection could be the main evolutionary force triggering the genetic diversity of anti-malaria resistance-associated genes in human or primates. However, researchers focused most of their attention on the infra-generic and intra-specific genome evolution rather than analyzing the complete evolutionary history of mammals. Here we extend previous research by testing the evolutionary link of natural selection on eight candidate genes associated with malaria resistance in mammals. Three of the eight genes were detected to be affected by recombination, including TNF-α, iNOS and DARC. Positive selection was detected in the rest five immunogenes multiple times in different ancestral lineages of extant species throughout the mammalian evolution. Signals of positive selection were exposed in four malaria-related immunogenes in primates: CCL2, IL-10, HO1 and CD36. However, selection signals of G6PD have only been detected in non-primate eutherians. Significantly higher evolutionary rates and more radical amino acid replacement were also detected in primate CD36, suggesting its functional divergence from other eutherians. Prevalent positive selection throughout the evolutionary trajectory of mammalian malaria-related genes supports the arms race evolutionary hypothesis of host genetic response of mammalian immunogenes to infectious pathogens. © The Author(s) 2014 Reprints and permissions: sagepub.co.uk/journalsPermissions.nav.

  8. 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...

  9. Comparison of normalization methods for the analysis of metagenomic gene abundance data.

    Science.gov (United States)

    Pereira, Mariana Buongermino; Wallroth, Mikael; Jonsson, Viktor; Kristiansson, Erik

    2018-04-20

    In shotgun metagenomics, microbial communities are studied through direct sequencing of DNA without any prior cultivation. By comparing gene abundances estimated from the generated sequencing reads, functional differences between the communities can be identified. However, gene abundance data is affected by high levels of systematic variability, which can greatly reduce the statistical power and introduce false positives. Normalization, which is the process where systematic variability is identified and removed, is therefore a vital part of the data analysis. A wide range of normalization methods for high-dimensional count data has been proposed but their performance on the analysis of shotgun metagenomic data has not been evaluated. Here, we present a systematic evaluation of nine normalization methods for gene abundance data. The methods were evaluated through resampling of three comprehensive datasets, creating a realistic setting that preserved the unique characteristics of metagenomic data. Performance was measured in terms of the methods ability to identify differentially abundant genes (DAGs), correctly calculate unbiased p-values and control the false discovery rate (FDR). Our results showed that the choice of normalization method has a large impact on the end results. When the DAGs were asymmetrically present between the experimental conditions, many normalization methods had a reduced true positive rate (TPR) and a high false positive rate (FPR). The methods trimmed mean of M-values (TMM) and relative log expression (RLE) had the overall highest performance and are therefore recommended for the analysis of gene abundance data. For larger sample sizes, CSS also showed satisfactory performance. This study emphasizes the importance of selecting a suitable normalization methods in the analysis of data from shotgun metagenomics. Our results also demonstrate that improper methods may result in unacceptably high levels of false positives, which in turn may lead

  10. Multicriteria Personnel Selection by the Modified Fuzzy VIKOR Method

    Directory of Open Access Journals (Sweden)

    Rasim M. Alguliyev

    2015-01-01

    Full Text Available Personnel evaluation is an important process in human resource management. The multicriteria nature and the presence of both qualitative and quantitative factors make it considerably more complex. In this study, a fuzzy hybrid multicriteria decision-making (MCDM model is proposed to personnel evaluation. This model solves personnel evaluation problem in a fuzzy environment where both criteria and weights could be fuzzy sets. The triangular fuzzy numbers are used to evaluate the suitability of personnel and the approximate reasoning of linguistic values. For evaluation, we have selected five information culture criteria. The weights of the criteria were calculated using worst-case method. After that, modified fuzzy VIKOR is proposed to rank the alternatives. The outcome of this research is ranking and selecting best alternative with the help of fuzzy VIKOR and modified fuzzy VIKOR techniques. A comparative analysis of results by fuzzy VIKOR and modified fuzzy VIKOR methods is presented. Experiments showed that the proposed modified fuzzy VIKOR method has some advantages over fuzzy VIKOR method. Firstly, from a computational complexity point of view, the presented model is effective. Secondly, compared to fuzzy VIKOR method, it has high acceptable advantage compared to fuzzy VIKOR method.

  11. Analysis of Criteria Influencing Contractor Selection Using TOPSIS Method

    Science.gov (United States)

    Alptekin, Orkun; Alptekin, Nesrin

    2017-10-01

    Selection of the most suitable contractor is an important process in public construction projects. This process is a major decision which may influence the progress and success of a construction project. Improper selection of contractors may lead to problems such as bad quality of work and delay in project duration. Especially in the construction projects of public buildings, the proper choice of contractor is beneficial to the public institution. Public procurement processes have different characteristics in respect to dissimilarities in political, social and economic features of every country. In Turkey, Turkish Public Procurement Law PPL 4734 is the main regulatory law for the procurement of the public buildings. According to the PPL 4734, public construction administrators have to contract with the lowest bidder who has the minimum requirements according to the criteria in prequalification process. Public administrators are not sufficient for selection of the proper contractor because of the restrictive provisions of the PPL 4734. The lowest bid method does not enable public construction administrators to select the most qualified contractor and they have realised the fact that the selection of a contractor based on lowest bid alone is inadequate and may lead to the failure of the project in terms of time delay Eand poor quality standards. In order to evaluate the overall efficiency of a project, it is necessary to identify selection criteria. This study aims to focus on identify importance of other criteria besides lowest bid criterion in contractor selection process of PPL 4734. In this study, a survey was conducted to staff of Department of Construction Works of Eskisehir Osmangazi University. According to TOPSIS (Technique for Order Preference by Similarity to the Ideal Solution) for analysis results, termination of construction work in previous tenders is the most important criterion of 12 determined criteria. The lowest bid criterion is ranked in rank 5.

  12. On a selection method of imaging condition in scintigraphy

    International Nuclear Information System (INIS)

    Ikeda, Hozumi; Kishimoto, Kenji; Shimonishi, Yoshihiro; Ohmura, Masahiro; Kosakai, Kazuhisa; Ochi, Hironobu

    1992-01-01

    Selection of imaging condition in scintigraphy was evaluated using analytic hierarchy process. First, a method of the selection was led by determining at the points of image quantity and imaging time. Influence of image quality was thought to depend on changes of system resolution, count density, image size, and image density. Also influence of imaging time was thought to depend on changes of system sensitivity and data acquisition time. Phantom study was done for paired comparison of these selection factors, and relations of sample data and the factors, that is Rollo phantom images were taken by changing count density, image size, and image density. Image quality was shown by calculating the score of visual evaluation that done by comparing of a pair of images in clearer cold lesion on the scintigrams. Imaging time was shown by relative values for changes of count density. However, system resolution and system sensitivity were constant in this study. Next, using these values analytic hierarchy process was adapted for this selection of imaging conditions. We conclude that this selection of imaging conditions can be analyzed quantitatively using analytic hierarchy process and this analysis develops theoretical consideration of imaging technique. (author)

  13. Evaluating the sustainable mining contractor selection problems: An imprecise last aggregation preference selection index method

    Directory of Open Access Journals (Sweden)

    Mohammad Panahi Borujeni

    2017-01-01

    Full Text Available The increasing complexity surrounding decision-making situations has made it inevitable for practitioners to apply ideas from a group of experts or decision makers (DMs instead of individuals. In a large proportion of recent studies, not enough attention has been paid to considering uncertainty in practical ways. In this paper, a hesitant fuzzy preference selection index (HFPSI method is proposed based on a new soft computing approach with risk preferences of DMs to deal with imprecise multi-criteria decision-making problems. Meanwhile, qualitative assessing criteria are considered in the process of the proposed method to help the DMs by providing suitable expressions of membership degrees for an element under a set. Moreover, the best alternative is selected based on considering the concepts of preference relation and hesitant fuzzy sets, simultaneously. Therefore, DMs' weights are determined according to the proposed hesitant fuzzy compromise solution technique to prevent judgment errors. Moreover, the proposed method has been extended based on the last aggregation method by aggregating the DMs' opinions during the last stage to avoid data loss. In this respect, a real case study about the mining contractor selection problem is provided to represent the effectiveness and efficiency of the proposed HFPSI method in practice. Then, a comparative analysis is performed to show the feasibility of the presented approach. Finally, sensitivity analysis is carried out to show the effect of considering the DMs' weights and last aggregation approach in a dispersion of the alternatives’ ranking values.

  14. Selection-independent generation of gene knockout mouse embryonic stem cells using zinc-finger nucleases.

    Directory of Open Access Journals (Sweden)

    Anna Osiak

    Full Text Available Gene knockout in murine embryonic stem cells (ESCs has been an invaluable tool to study gene function in vitro or to generate animal models with altered phenotypes. Gene targeting using standard techniques, however, is rather inefficient and typically does not exceed frequencies of 10(-6. In consequence, the usage of complex positive/negative selection strategies to isolate targeted clones has been necessary. Here, we present a rapid single-step approach to generate a gene knockout in mouse ESCs using engineered zinc-finger nucleases (ZFNs. Upon transient expression of ZFNs, the target gene is cleaved by the designer nucleases and then repaired by non-homologous end-joining, an error-prone DNA repair process that introduces insertions/deletions at the break site and therefore leads to functional null mutations. To explore and quantify the potential of ZFNs to generate a gene knockout in pluripotent stem cells, we generated a mouse ESC line containing an X-chromosomally integrated EGFP marker gene. Applying optimized conditions, the EGFP locus was disrupted in up to 8% of ESCs after transfection of the ZFN expression vectors, thus obviating the need of selection markers to identify targeted cells, which may impede or complicate downstream applications. Both activity and ZFN-associated cytotoxicity was dependent on vector dose and the architecture of the nuclease domain. Importantly, teratoma formation assays of selected ESC clones confirmed that ZFN-treated ESCs maintained pluripotency. In conclusion, the described ZFN-based approach represents a fast strategy for generating gene knockouts in ESCs in a selection-independent fashion that should be easily transferrable to other pluripotent stem cells.

  15. Neuroplasticity of selective attention: Research foundations and preliminary evidence for a gene by intervention interaction

    Science.gov (United States)

    Stevens, Courtney; Pakulak, Eric; Hampton Wray, Amanda; Bell, Theodore A.; Neville, Helen J.

    2017-01-01

    This article reviews the trajectory of our research program on selective attention, which has moved from basic research on the neural processes underlying selective attention to translational studies using selective attention as a neurobiological target for evidence-based interventions. We use this background to present a promising preliminary investigation of how genetic and experiential factors interact during development (i.e., gene × intervention interactions). Our findings provide evidence on how exposure to a family-based training can modify the associations between genotype (5-HTTLPR) and the neural mechanisms of selective attention in preschool children from lower socioeconomic status backgrounds. PMID:28819066

  16. Neuroplasticity of selective attention: Research foundations and preliminary evidence for a gene by intervention interaction.

    Science.gov (United States)

    Isbell, Elif; Stevens, Courtney; Pakulak, Eric; Hampton Wray, Amanda; Bell, Theodore A; Neville, Helen J

    2017-08-29

    This article reviews the trajectory of our research program on selective attention, which has moved from basic research on the neural processes underlying selective attention to translational studies using selective attention as a neurobiological target for evidence-based interventions. We use this background to present a promising preliminary investigation of how genetic and experiential factors interact during development (i.e., gene × intervention interactions). Our findings provide evidence on how exposure to a family-based training can modify the associations between genotype (5-HTTLPR) and the neural mechanisms of selective attention in preschool children from lower socioeconomic status backgrounds.

  17. Essay on Methods in Futures Studies and a Selective Bibliography

    DEFF Research Database (Denmark)

    Poulsen, Claus

    2005-01-01

    Futures studies is often conflated with science fiction or pop-futurism. Consequently there is a need for demarcation of what is futures studies and what is not. From the same reason the essay stresses the need for quality control to focus on futures research and its methods: Publications in futu...... programme are (only) partly reduced by applying Causal Layered Analysis as an internal quality control. The following selective bibliography is focussed on these methodological issues...

  18. Selection of reference genes for expression analysis in the entomophthoralean fungus Pandora neoaphidis.

    Science.gov (United States)

    Chen, Chun; Xie, Tingna; Ye, Sudan; Jensen, Annette Bruun; Eilenberg, Jørgen

    2016-01-01

    The selection of suitable reference genes is crucial for accurate quantification of gene expression and can add to our understanding of host-pathogen interactions. To identify suitable reference genes in Pandora neoaphidis, an obligate aphid pathogenic fungus, the expression of three traditional candidate genes including 18S rRNA(18S), 28S rRNA(28S) and elongation factor 1 alpha-like protein (EF1), were measured by quantitative polymerase chain reaction at different developmental stages (conidia, conidia with germ tubes, short hyphae and elongated hyphae), and under different nutritional conditions. We calculated the expression stability of candidate reference genes using four algorithms including geNorm, NormFinder, BestKeeper and Delta Ct. The analysis results revealed that the comprehensive ranking of candidate reference genes from the most stable to the least stable was 18S (1.189), 28S (1.414) and EF1 (3). The 18S was, therefore, the most suitable reference gene for real-time RT-PCR analysis of gene expression under all conditions. These results will support further studies on gene expression in P. neoaphidis. Copyright © 2015 Sociedade Brasileira de Microbiologia. Published by Elsevier Editora Ltda. All rights reserved.

  19. Selection of reference genes for expression analysis in the entomophthoralean fungus Pandora neoaphidis

    Directory of Open Access Journals (Sweden)

    Chun Chen

    2016-03-01

    Full Text Available Abstract The selection of suitable reference genes is crucial for accurate quantification of gene expression and can add to our understanding of host–pathogen interactions. To identify suitable reference genes in Pandora neoaphidis, an obligate aphid pathogenic fungus, the expression of three traditional candidate genes including 18S rRNA(18S, 28S rRNA(28S and elongation factor 1 alpha-like protein (EF1, were measured by quantitative polymerase chain reaction at different developmental stages (conidia, conidia with germ tubes, short hyphae and elongated hyphae, and under different nutritional conditions. We calculated the expression stability of candidate reference genes using four algorithms including geNorm, NormFinder, BestKeeper and Delta Ct. The analysis results revealed that the comprehensive ranking of candidate reference genes from the most stable to the least stable was 18S (1.189, 28S (1.414 and EF1 (3. The 18S was, therefore, the most suitable reference gene for real-time RT-PCR analysis of gene expression under all conditions. These results will support further studies on gene expression in P. neoaphidis.

  20. Ferritin gene organization: differences between plants and animals suggest possible kingdom-specific selective constraints.

    Science.gov (United States)

    Proudhon, D; Wei, J; Briat, J; Theil, E C

    1996-03-01

    exist to maintain a particular intron/exon pattern within ferritin genes. In the case of plants, where ferritin gene intron placement is unrelated to triplet codons or protein structure, and where ferritin is targeted to the plastid, the selection pressure on gene organization may relate to RNA function and plastid/nuclear signaling.

  1. Evaluation of Stress Loaded Steel Samples Using Selected Electromagnetic Methods

    International Nuclear Information System (INIS)

    Chady, T.

    2004-01-01

    In this paper the magnetic leakage flux and eddy current method were used to evaluate changes of materials' properties caused by stress. Seven samples made of ferromagnetic material with different level of applied stress were prepared. First, the leakage magnetic fields were measured by scanning the surface of the specimens with GMR gradiometer. Next, the same samples were evaluated using an eddy current sensor. A comparison between results obtained from both methods was carried out. Finally, selected parameters of the measured signal were calculated and utilized to evaluate level of the applied stress. A strong coincidence between amount of the applied stress and the maximum amplitude of the derivative was confirmed

  2. Sibling genes as environment: Sibling dopamine genotypes and adolescent health support frequency dependent selection.

    Science.gov (United States)

    Rauscher, Emily; Conley, Dalton; Siegal, Mark L

    2015-11-01

    While research consistently suggests siblings matter for individual outcomes, it remains unclear why. At the same time, studies of genetic effects on health typically correlate variants of a gene with the average level of behavioral or health measures, ignoring more complicated genetic dynamics. Using National Longitudinal Study of Adolescent Health data, we investigate whether sibling genes moderate individual genetic expression. We compare twin variation in health-related absences and self-rated health by genetic differences at three locations related to dopamine regulation and transport to test sibship-level cross-person gene-gene interactions. Results suggest effects of variation at these genetic locations are moderated by sibling genes. Although the mechanism remains unclear, this evidence is consistent with frequency dependent selection and suggests much genetic research may violate the stable unit treatment value assumption. Copyright © 2015 Elsevier Inc. All rights reserved.

  3. LEGO: a novel method for gene set over-representation analysis by incorporating network-based gene weights.

    Science.gov (United States)

    Dong, Xinran; Hao, Yun; Wang, Xiao; Tian, Weidong

    2016-01-11

    Pathway or gene set over-representation analysis (ORA) has become a routine task in functional genomics studies. However, currently widely used ORA tools employ statistical methods such as Fisher's exact test that reduce a pathway into a list of genes, ignoring the constitutive functional non-equivalent roles of genes and the complex gene-gene interactions. Here, we develop a novel method named LEGO (functional Link Enrichment of Gene Ontology or gene sets) that takes into consideration these two types of information by incorporating network-based gene weights in ORA analysis. In three benchmarks, LEGO achieves better performance than Fisher and three other network-based methods. To further evaluate LEGO's usefulness, we compare LEGO with five gene expression-based and three pathway topology-based methods using a benchmark of 34 disease gene expression datasets compiled by a recent publication, and show that LEGO is among the top-ranked methods in terms of both sensitivity and prioritization for detecting target KEGG pathways. In addition, we develop a cluster-and-filter approach to reduce the redundancy among the enriched gene sets, making the results more interpretable to biologists. Finally, we apply LEGO to two lists of autism genes, and identify relevant gene sets to autism that could not be found by Fisher.

  4. A fractured rock geophysical toolbox method selection tool

    Science.gov (United States)

    Day-Lewis, F. D.; Johnson, C.D.; Slater, L.D.; Robinson, J.L.; Williams, J.H.; Boyden, C.L.; Werkema, D.D.; Lane, J.W.

    2016-01-01

    Geophysical technologies have the potential to improve site characterization and monitoring in fractured rock, but the appropriate and effective application of geophysics at a particular site strongly depends on project goals (e.g., identifying discrete fractures) and site characteristics (e.g., lithology). No method works at every site or for every goal. New approaches are needed to identify a set of geophysical methods appropriate to specific project goals and site conditions while considering budget constraints. To this end, we present the Excel-based Fractured-Rock Geophysical Toolbox Method Selection Tool (FRGT-MST). We envision the FRGT-MST (1) equipping remediation professionals with a tool to understand what is likely to be realistic and cost-effective when contracting geophysical services, and (2) reducing applications of geophysics with unrealistic objectives or where methods are likely to fail.

  5. The selective dynamical downscaling method for extreme-wind atlases

    DEFF Research Database (Denmark)

    Larsén, Xiaoli Guo; Badger, Jake; Hahmann, Andrea N.

    2012-01-01

    A selective dynamical downscaling method is developed to obtain extreme-wind atlases for large areas. The method is general, efficient and flexible. The method consists of three steps: (i) identifying storm episodes for a particular area, (ii) downscaling of the storms using mesoscale modelling...... and (iii) post-processing. The post-processing generalizes the winds from the mesoscale modelling to standard conditions, i.e. 10-m height over a homogeneous surface with roughness length of 5 cm. The generalized winds are then used to calculate the 50-year wind using the annual maximum method for each...... mesoscale grid point. The generalization of the mesoscale winds through the post-processing provides a framework for data validation and for applying further the mesoscale extreme winds at specific places using microscale modelling. The results are compared with measurements from two areas with different...

  6. Tagging of blast resistance gene(s) to DNA markers and marker-assisted selection (MAS) in rice improvement

    International Nuclear Information System (INIS)

    Zhuang, J.Y.; Lu, J.; Qian, H.R.; Lin, H.X.; Zheng, K.L.

    1998-01-01

    This paper reports progress made on the tagging of blast resistance gene(s) to DNA markers and on the initiation of marker-assisted selection (MAS) for blast resistance in rice improvement. A pair of near isogenic lines, K8OR and K79S, were developed using a Chinese landrace Hong-jiao-zhan as the resistance donor. Ten putatively positive markers were identified by screening 177 mapped DNA markers. Using the F 2 population of 143 plants and the derived F 3 lines, three Restriction Fragment Length Polymorphism (RFLP) markers (RG81, RG869 and RZ397) on chromosome 12 of rice were identified to be closely linked to the blast resistance gene Pi-12(t). The genetic distance between Pi-12(t) and the closest marker RG869 was 5.1 cM. By employing the bulk segregant analysis (BSA) procedure, six of 199 arbitrary primers were found to produce positive Randomly Amplified Polymorphic DNA (RAPD) bands. Tight linkage between Pi-12(t) and three RAPD bands, each from a different primer, was confirmed after amplification of DNA of all F 2 individuals. Two fragments were cloned and sequenced, and two sequence characterised amplified re-ion (SCAR) markers were established. In two other F 3 populations, Xian-feng I/Tetep and Xian-feng, 1/Hong-jiao-zhan, the blast resistance was found to be controlled by interactions of two or more genes. One resistance gene was located in the vicinity of RG81 in both populations. Work to identify other gene(s) is currently under way. Marker assisted selection for blast resistance was initiated. Crosses were made between elite varieties and blast resistance donors to develop populations for DNA marker-assisted selection of blast resistance. In addition, 48 varieties widely used in current rice breeding programs were provided by rice breeders. DNA marker-based polymorphism among, these varieties and resistance donors were analysed to produce a database for future MAS program. (author)

  7. An efficient parallel stochastic simulation method for analysis of nonviral gene delivery systems

    KAUST Repository

    Kuwahara, Hiroyuki

    2011-01-01

    Gene therapy has a great potential to become an effective treatment for a wide variety of diseases. One of the main challenges to make gene therapy practical in clinical settings is the development of efficient and safe mechanisms to deliver foreign DNA molecules into the nucleus of target cells. Several computational and experimental studies have shown that the design process of synthetic gene transfer vectors can be greatly enhanced by computational modeling and simulation. This paper proposes a novel, effective parallelization of the stochastic simulation algorithm (SSA) for pharmacokinetic models that characterize the rate-limiting, multi-step processes of intracellular gene delivery. While efficient parallelizations of the SSA are still an open problem in a general setting, the proposed parallel simulation method is able to substantially accelerate the next reaction selection scheme and the reaction update scheme in the SSA by exploiting and decomposing the structures of stochastic gene delivery models. This, thus, makes computationally intensive analysis such as parameter optimizations and gene dosage control for specific cell types, gene vectors, and transgene expression stability substantially more practical than that could otherwise be with the standard SSA. Here, we translated the nonviral gene delivery model based on mass-action kinetics by Varga et al. [Molecular Therapy, 4(5), 2001] into a more realistic model that captures intracellular fluctuations based on stochastic chemical kinetics, and as a case study we applied our parallel simulation to this stochastic model. Our results show that our simulation method is able to increase the efficiency of statistical analysis by at least 50% in various settings. © 2011 ACM.

  8. [Gene method for inconsistent hydrological frequency calculation. 2: Diagnosis system of hydrological genes and method of hydrological moment genes with inconsistent characters].

    Science.gov (United States)

    Xie, Ping; Zhao, Jiang Yan; Wu, Zi Yi; Sang, Yan Fang; Chen, Jie; Li, Bin Bin; Gu, Hai Ting

    2018-04-01

    The analysis of inconsistent hydrological series is one of the major problems that should be solved for engineering hydrological calculation in changing environment. In this study, the diffe-rences of non-consistency and non-stationarity were analyzed from the perspective of composition of hydrological series. The inconsistent hydrological phenomena were generalized into hydrological processes with inheritance, variability and evolution characteristics or regulations. Furthermore, the hydrological genes were identified following the theory of biological genes, while their inheritance bases and variability bases were determined based on composition of hydrological series under diffe-rent time scales. To identify and test the components of hydrological genes, we constructed a diagnosis system of hydrological genes. With the P-3 distribution as an example, we described the process of construction and expression of the moment genes to illustrate the inheritance, variability and evolution principles of hydrological genes. With the annual minimum 1-month runoff series of Yunjinghong station in Lancangjiang River basin as an example, we verified the feasibility and practicability of hydrological gene theory for the calculation of inconsistent hydrological frequency. The results showed that the method could be used to reveal the evolution of inconsistent hydrological series. Therefore, it provided a new research pathway for engineering hydrological calculation in changing environment and an essential reference for the assessment of water security.

  9. Natural selection on protein-coding genes in the human genome

    DEFF Research Database (Denmark)

    Bustamente, Carlos D.; Fledel-Alon, Adi; Williamson, Scott

    2005-01-01

    , showing an excess of deleterious variation within local populations 9, 10 . Here we contrast patterns of coding sequence polymorphism identified by direct sequencing of 39 humans for over 11,000 genes to divergence between humans and chimpanzees, and find strong evidence that natural selection has shaped......Comparisons of DNA polymorphism within species to divergence between species enables the discovery of molecular adaptation in evolutionarily constrained genes as well as the differentiation of weak from strong purifying selection 1, 2, 3, 4 . The extent to which weak negative and positive darwinian...... selection have driven the molecular evolution of different species varies greatly 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16 , with some species, such as Drosophila melanogaster, showing strong evidence of pervasive positive selection 6, 7, 8, 9 , and others, such as the selfing weed Arabidopsis thaliana...

  10. Development of a rapid method for direct detection of tet(M) genes in soil from Danish farmland

    DEFF Research Database (Denmark)

    Agersø, Yvonne; Sengeløv, Gitte; Jensen, Lars Bogø

    2004-01-01

    . The tet(M) gene was directly detected in 10-80% of the samples from the various farmland soils and could be detected in all samples tested after selective enrichment. To validate the obtained results, the method was applied to garden soil samples where lower prevalence of resistance was found. Result......A method for direct detection of antibiotic resistance genes in soil samples has been developed. The tetracycline resistance gene, tet(M), was used as a model. The method was validated on Danish farmland soil that had repeatedly been treated with pig manure slurry containing resistant bacteria......: A detection limit of 10(2)-10(3) copies of the tet(M) gene per gram of soil (in a Bacillus cereus group bacterium) was achieved. tet(M) gene was detected in soil samples with the highest prevalence on farmland treated with pig manure slurry....

  11. Variable selection in near-infrared spectroscopy: Benchmarking of feature selection methods on biodiesel data

    International Nuclear Information System (INIS)

    Balabin, Roman M.; Smirnov, Sergey V.

    2011-01-01

    During the past several years, near-infrared (near-IR/NIR) spectroscopy has increasingly been adopted as an analytical tool in various fields from petroleum to biomedical sectors. The NIR spectrum (above 4000 cm -1 ) of a sample is typically measured by modern instruments at a few hundred of wavelengths. Recently, considerable effort has been directed towards developing procedures to identify variables (wavelengths) that contribute useful information. Variable selection (VS) or feature selection, also called frequency selection or wavelength selection, is a critical step in data analysis for vibrational spectroscopy (infrared, Raman, or NIRS). In this paper, we compare the performance of 16 different feature selection methods for the prediction of properties of biodiesel fuel, including density, viscosity, methanol content, and water concentration. The feature selection algorithms tested include stepwise multiple linear regression (MLR-step), interval partial least squares regression (iPLS), backward iPLS (BiPLS), forward iPLS (FiPLS), moving window partial least squares regression (MWPLS), (modified) changeable size moving window partial least squares (CSMWPLS/MCSMWPLSR), searching combination moving window partial least squares (SCMWPLS), successive projections algorithm (SPA), uninformative variable elimination (UVE, including UVE-SPA), simulated annealing (SA), back-propagation artificial neural networks (BP-ANN), Kohonen artificial neural network (K-ANN), and genetic algorithms (GAs, including GA-iPLS). Two linear techniques for calibration model building, namely multiple linear regression (MLR) and partial least squares regression/projection to latent structures (PLS/PLSR), are used for the evaluation of biofuel properties. A comparison with a non-linear calibration model, artificial neural networks (ANN-MLP), is also provided. Discussion of gasoline, ethanol-gasoline (bioethanol), and diesel fuel data is presented. The results of other spectroscopic

  12. Use of the alr gene as a food-grade selection marker in lactic acid bacteria.

    Science.gov (United States)

    Bron, Peter A; Benchimol, Marcos G; Lambert, Jolanda; Palumbo, Emmanuelle; Deghorain, Marie; Delcour, Jean; De Vos, Willem M; Kleerebezem, Michiel; Hols, Pascal

    2002-11-01

    Both Lactococcus lactis and Lactobacillus plantarum contain a single alr gene, encoding an alanine racemase (EC 5.1.1.1), which catalyzes the interconversion of D-alanine and L-alanine. The alr genes of these lactic acid bacteria were investigated for their application as food-grade selection markers in a heterologous complementation approach. Since isogenic mutants of both species carrying an alr deletion (Deltaalr) showed auxotrophy for D-alanine, plasmids carrying a heterologous alr were constructed and could be selected, since they complemented D-alanine auxotrophy in the L. plantarum Deltaalr and L. lactis Deltaalr strains. Selection was found to be highly stringent, and plasmids were stably maintained over 200 generations of culturing. Moreover, the plasmids carrying the heterologous alr genes could be stably maintained in wild-type strains of L. plantarum and L. lactis by selection for resistance to D-cycloserine, a competitive inhibitor of Alr (600 and 200 micro g/ml, respectively). In addition, a plasmid carrying the L. plantarum alr gene under control of the regulated nisA promoter was constructed to demonstrate that D-cycloserine resistance of L. lactis is linearly correlated to the alr expression level. Finally, the L. lactis alr gene controlled by the nisA promoter, together with the nisin-regulatory genes nisRK, were integrated into the chromosome of L. plantarum Deltaalr. The resulting strain could grow in the absence of D-alanine only when expression of the alr gene was induced with nisin.

  13. Will genomic selection be a practical method for plant breeding?

    Science.gov (United States)

    Nakaya, Akihiro; Isobe, Sachiko N

    2012-11-01

    Genomic selection or genome-wide selection (GS) has been highlighted as a new approach for marker-assisted selection (MAS) in recent years. GS is a form of MAS that selects favourable individuals based on genomic estimated breeding values. Previous studies have suggested the utility of GS, especially for capturing small-effect quantitative trait loci, but GS has not become a popular methodology in the field of plant breeding, possibly because there is insufficient information available on GS for practical use. In this review, GS is discussed from a practical breeding viewpoint. Statistical approaches employed in GS are briefly described, before the recent progress in GS studies is surveyed. GS practices in plant breeding are then reviewed before future prospects are discussed. Statistical concepts used in GS are discussed with genetic models and variance decomposition, heritability, breeding value and linear model. Recent progress in GS studies is reviewed with a focus on empirical studies. For the practice of GS in plant breeding, several specific points are discussed including linkage disequilibrium, feature of populations and genotyped markers and breeding scheme. Currently, GS is not perfect, but it is a potent, attractive and valuable approach for plant breeding. This method will be integrated into many practical breeding programmes in the near future with further advances and the maturing of its theory.

  14. Selective adsorption-desorption method for the enrichment of krypton

    International Nuclear Information System (INIS)

    Yuasa, Y.; Ohta, M.; Watanabe, A.; Tani, A.; Takashima, N.

    1975-01-01

    Selective adsorption-desorption method has been developed as an effective means of enriching krypton and xenon gases. A seriesof laboratory-scale tests were performed to provide some basic data of the method when applied to off-gas streams of nuclear power plants. For the first step of the enrichment process of the experiments, krypton was adsorbed on solid adsorbents from dilute mixtures with air at temperatures ranging from -50 0 C to -170 0 C. After the complete breakthrough was obtained, the adsorption bed was evacuated at low temperature by a vacuum pump. By combining these two steps krypton was highly enriched on the adsorbents, and the enrichment factor for krypton was calculated as the product of individual enrichment factors of each step. Two types of adsorbents, coconut charcoal and molecular sieves 5A, were used. Experimental results showed that the present method gave the greater enrichment factor than the conventional method which used selective adsorption step only. (U.S.)

  15. Selection criteria for oxidation method in total organic carbon measurement.

    Science.gov (United States)

    Yoon, GeunSeok; Park, Sang-Min; Yang, Heuiwon; Tsang, Daniel C W; Alessi, Daniel S; Baek, Kitae

    2018-05-01

    During the measurement of total organic carbon (TOC), dissolved organic carbon is converted into CO 2 by using high temperature combustion (HTC) or wet chemical oxidation (WCO). However, the criteria for selecting the oxidation methods are not clear. In this study, the chemical structures of organic material were considered as a key factor to select the oxidation method used. Most non-degradable organic compounds showed a similar oxidation efficiency in both methods, including natural organic compounds, dyes, and pharmaceuticals, and thus both methods are appropriate to measure TOC in waters containing these compounds. However, only a fraction of the carbon in the halogenated compounds (perfluorooctanoic acid and trifluoroacetic acid) were oxidized using WCO, resulting in measured TOC values that are considerably lower than those determined by HTC. This result is likely due to the electronegativity of halogen elements which inhibits the approach of electron-rich sulfate radicals in the WCO, and the higher bond strength of carbon-halogen pairs as compared to carbon-hydrogen bonds, which results in a lower degree of oxidation of the compounds. Our results indicate that WCO could be used to oxidize most organic compounds, but may not be appropriate to quantify TOC in organic carbon pools that contain certain halogenated compounds. Copyright © 2018 Elsevier Ltd. All rights reserved.

  16. Selected Tools and Methods from Quality Management Field

    Directory of Open Access Journals (Sweden)

    Kateřina BRODECKÁ

    2009-06-01

    Full Text Available Following paper describes selected tools and methods from Quality management field and their practical applications on defined examples. Solved examples were elaborated in the form of electronic support. This in detail elaborated electronic support provides students opportunity to thoroughly practice specific issues, help them to prepare for exams and consequently will lead to education improvement. Especially students of combined study form will appreciate this support. The paper specifies project objectives, subjects that will be covered by mentioned support, target groups, structure and the way of elaboration of electronic exercise book in view. The emphasis is not only on manual solution of selected examples that may help students to understand the principles and relationships, but also on solving and results interpreting of selected examples using software support. Statistic software Statgraphics Plus v 5.0 is used while working support, because it is free to use for all students of the faculty. Exemplary example from the subject Basic Statistical Methods of Quality Management is also part of this paper.

  17. Selecting device for processing method of radioactive gaseous wastes

    International Nuclear Information System (INIS)

    Sasaki, Ryoichi; Komoda, Norihisa.

    1976-01-01

    Object: To extend the period of replacement of a filter for adsorbing radioactive material by discharging waste gas containing radioactive material produced from an atomic power equipment after treating it by a method selected on the basis of the results of measurement of wind direction. Structure: Exhaust gas containing radioactive material produced from atomic power equipment is discharged after it is treated by a method selected on the basis of the results of wind direction measurement. For Instance, in case of sea wind the waste gas passes through a route selected for this case and is discharged through the waste gas outlet. When the sea wind disappears (that is, when a land wind or calm sets in), the exhaust gas is switched to a route for the case other than that of the sea wind, so that it passes through a filter consisting of active carbon where the radioactive material is removed through adsorption. The waste gas now free from the radioactive material is discharged through the waste gas outlet. (Moriyama, K.)

  18. Evidence of Positive Selection of Aquaporins Genes from Pontoporia blainvillei during the Evolutionary Process of Cetaceans.

    Directory of Open Access Journals (Sweden)

    Simone Lima São Pedro

    Full Text Available Marine mammals are well adapted to their hyperosmotic environment. Several morphological and physiological adaptations for water conservation and salt excretion are known to be present in cetaceans, being responsible for regulating salt balance. However, most previous studies have focused on the unique renal physiology of marine mammals, but the molecular bases of these mechanisms remain poorly explored. Many genes have been identified to be involved in osmotic regulation, including the aquaporins. Considering that aquaporin genes were potentially subject to strong selective pressure, the aim of this study was to analyze the molecular evolution of seven aquaporin genes (AQP1, AQP2, AQP3, AQP4, AQP6, AQP7, and AQP9 comparing the lineages of cetaceans and terrestrial mammals.Our results demonstrated strong positive selection in cetacean-specific lineages acting only in the gene for AQP2 (amino acids 23, 83, 107,179, 180, 181, 182, whereas no selection was observed in terrestrial mammalian lineages. We also analyzed the changes in the 3D structure of the aquaporin 2 protein. Signs of strong positive selection in AQP2 sites 179, 180, 181, and 182 were unexpectedly identified only in the baiji lineage, which was the only river dolphin examined in this study. Positive selection in aquaporins AQP1 (45, AQP4 (74, AQP7 (342, 343, 356 was detected in cetaceans and artiodactyls, suggesting that these events are not related to maintaining water and electrolyte homeostasis in seawater.Our results suggest that the AQP2 gene might reflect different selective pressures in maintaining water balance in cetaceans, contributing to the passage from the terrestrial environment to the aquatic. Further studies are necessary, especially those including other freshwater dolphins, who exhibit osmoregulatory mechanisms different from those of marine cetaceans for the same essential task of maintaining serum electrolyte balance.

  19. Primitive polynomials selection method for pseudo-random number generator

    Science.gov (United States)

    Anikin, I. V.; Alnajjar, Kh

    2018-01-01

    In this paper we suggested the method for primitive polynomials selection of special type. This kind of polynomials can be efficiently used as a characteristic polynomials for linear feedback shift registers in pseudo-random number generators. The proposed method consists of two basic steps: finding minimum-cost irreducible polynomials of the desired degree and applying primitivity tests to get the primitive ones. Finally two primitive polynomials, which was found by the proposed method, used in pseudorandom number generator based on fuzzy logic (FRNG) which had been suggested before by the authors. The sequences generated by new version of FRNG have low correlation magnitude, high linear complexity, less power consumption, is more balanced and have better statistical properties.

  20. Manual of selected physico-chemical analytical methods. IV

    International Nuclear Information System (INIS)

    Beran, M.; Klosova, E.; Krtil, J.; Sus, F.; Kuvik, V.; Vrbova, L.; Hamplova, M.; Lengyel, J.; Kelnar, L.; Zakouril, K.

    1990-11-01

    The Central Testing Laboratory of the Nuclear Research Institute at Rez has for a decade been participating in the development of analytical procedures and has been providing analyses of samples of different types and origin. The analytical procedures developed have been published in special journals and a number of them in the Manuals of analytical methods, in three parts. The 4th part of the Manual contains selected physico-chemical methods developed or modified by the Laboratory in the years 1986-1990 within the project ''Development of physico-chemical analytical methods''. In most cases, techniques are involved for non-nuclear applications. Some can find wider applications, especially in analyses of environmental samples. Others have been developed for specific cases of sample analyses or require special instrumentation (mass spectrometer), which partly restricts their applicability by other institutions. (author)

  1. METHODS OF SELECTING THE EFFECTIVE MODELS OF BUILDINGS REPROFILING PROJECTS

    Directory of Open Access Journals (Sweden)

    Александр Иванович МЕНЕЙЛЮК

    2016-02-01

    Full Text Available The article highlights the important task of project management in reprofiling of buildings. It is expedient to pay attention to selecting effective engineering solutions to reduce the duration and cost reduction at the project management in the construction industry. This article presents a methodology for the selection of efficient organizational and technical solutions for the reconstruction of buildings reprofiling. The method is based on a compilation of project variants in the program Microsoft Project and experimental statistical analysis using the program COMPEX. The introduction of this technique in the realigning of buildings allows choosing efficient models of projects, depending on the given constraints. Also, this technique can be used for various construction projects.

  2. A systematic and practical method for selecting systems engineering tools

    DEFF Research Database (Denmark)

    Munck, Allan; Madsen, Jan

    2017-01-01

    analyses of the actual needs and the available tools. Grouping needs into categories, allow us to obtain a comprehensive set of requirements for the tools. The entire model-based systems engineering discipline was categorized for a modeling tool case to enable development of a tool specification...... in successful operation since 2013 at GN Hearing. We further utilized the method to select a set of tools that we used on pilot cases at GN Hearing for modeling, simulating and formally verifying embedded systems.......The complexity of many types of systems has grown considerably over the last decades. Using appropriate systems engineering tools therefore becomes increasingly important. Starting the tool selection process can be intimidating because organizations often only have a vague idea about what they need...

  3. Reference Gene Selection in the Desert Plant Eremosparton songoricum

    Directory of Open Access Journals (Sweden)

    Dao-Yuan Zhang

    2012-06-01

    Full Text Available Eremosparton songoricum (Litv. Vass. (E. songoricum is a rare and extremely drought-tolerant desert plant that holds promise as a model organism for the identification of genes associated with water deficit stress. Here, we cloned and evaluated the expression of eight candidate reference genes using quantitative real-time reverse transcriptase polymerase chain reactions. The expression of these candidate reference genes was analyzed in a diverse set of 20 samples including various E. songoricum plant tissues exposed to multiple environmental stresses. GeNorm analysis indicated that expression stability varied between the reference genes in the different experimental conditions, but the two most stable reference genes were sufficient for normalization in most conditions. EsEF and Esα-TUB were sufficient for various stress conditions, EsEF and EsACT were suitable for samples of differing germination stages, and EsGAPDHand EsUBQ were most stable across multiple adult tissue samples. The Es18S gene was unsuitable as a reference gene in our analysis. In addition, the expression level of the drought-stress related transcription factor EsDREB2 verified the utility of E. songoricum reference genes and indicated that no single gene was adequate for normalization on its own. This is the first systematic report on the selection of reference genes in E. songoricum, and these data will facilitate future work on gene expression in this species.

  4. The joint effects of background selection and genetic recombination on local gene genealogies.

    Science.gov (United States)

    Zeng, Kai; Charlesworth, Brian

    2011-09-01

    Background selection, the effects of the continual removal of deleterious mutations by natural selection on variability at linked sites, is potentially a major determinant of DNA sequence variability. However, the joint effects of background selection and genetic recombination on the shape of the neutral gene genealogy have proved hard to study analytically. The only existing formula concerns the mean coalescent time for a pair of alleles, making it difficult to assess the importance of background selection from genome-wide data on sequence polymorphism. Here we develop a structured coalescent model of background selection with recombination and implement it in a computer program that efficiently generates neutral gene genealogies for an arbitrary sample size. We check the validity of the structured coalescent model against forward-in-time simulations and show that it accurately captures the effects of background selection. The model produces more accurate predictions of the mean coalescent time than the existing formula and supports the conclusion that the effect of background selection is greater in the interior of a deleterious region than at its boundaries. The level of linkage disequilibrium between sites is elevated by background selection, to an extent that is well summarized by a change in effective population size. The structured coalescent model is readily extendable to more realistic situations and should prove useful for analyzing genome-wide polymorphism data.

  5. Selecting Question-Specific Genes to Reduce Incongruence in Phylogenomics: A Case Study of Jawed Vertebrate Backbone Phylogeny.

    Science.gov (United States)

    Chen, Meng-Yun; Liang, Dan; Zhang, Peng

    2015-11-01

    Incongruence between different phylogenomic analyses is the main challenge faced by phylogeneticists in the genomic era. To reduce incongruence, phylogenomic studies normally adopt some data filtering approaches, such as reducing missing data or using slowly evolving genes, to improve the signal quality of data. Here, we assembled a phylogenomic data set of 58 jawed vertebrate taxa and 4682 genes to investigate the backbone phylogeny of jawed vertebrates under both concatenation and coalescent-based frameworks. To evaluate the efficiency of extracting phylogenetic signals among different data filtering methods, we chose six highly intractable internodes within the backbone phylogeny of jawed vertebrates as our test questions. We found that our phylogenomic data set exhibits substantial conflicting signal among genes for these questions. Our analyses showed that non-specific data sets that are generated without bias toward specific questions are not sufficient to produce consistent results when there are several difficult nodes within a phylogeny. Moreover, phylogenetic accuracy based on non-specific data is considerably influenced by the size of data and the choice of tree inference methods. To address such incongruences, we selected genes that resolve a given internode but not the entire phylogeny. Notably, not only can this strategy yield correct relationships for the question, but it also reduces inconsistency associated with data sizes and inference methods. Our study highlights the importance of gene selection in phylogenomic analyses, suggesting that simply using a large amount of data cannot guarantee correct results. Constructing question-specific data sets may be more powerful for resolving problematic nodes. © The Author(s) 2015. Published by Oxford University Press, on behalf of the Society of Systematic Biologists. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

  6. Evolutionary dynamics on graphs: Efficient method for weak selection

    Science.gov (United States)

    Fu, Feng; Wang, Long; Nowak, Martin A.; Hauert, Christoph

    2009-04-01

    Investigating the evolutionary dynamics of game theoretical interactions in populations where individuals are arranged on a graph can be challenging in terms of computation time. Here, we propose an efficient method to study any type of game on arbitrary graph structures for weak selection. In this limit, evolutionary game dynamics represents a first-order correction to neutral evolution. Spatial correlations can be empirically determined under neutral evolution and provide the basis for formulating the game dynamics as a discrete Markov process by incorporating a detailed description of the microscopic dynamics based on the neutral correlations. This framework is then applied to one of the most intriguing questions in evolutionary biology: the evolution of cooperation. We demonstrate that the degree heterogeneity of a graph impedes cooperation and that the success of tit for tat depends not only on the number of rounds but also on the degree of the graph. Moreover, considering the mutation-selection equilibrium shows that the symmetry of the stationary distribution of states under weak selection is skewed in favor of defectors for larger selection strengths. In particular, degree heterogeneity—a prominent feature of scale-free networks—generally results in a more pronounced increase in the critical benefit-to-cost ratio required for evolution to favor cooperation as compared to regular graphs. This conclusion is corroborated by an analysis of the effects of population structures on the fixation probabilities of strategies in general 2×2 games for different types of graphs. Computer simulations confirm the predictive power of our method and illustrate the improved accuracy as compared to previous studies.

  7. Disentangling the effects of selection and loss bias on gene dynamics

    NARCIS (Netherlands)

    Iranzo, J.; Cuesta, J.A.; Manrubia, S.; Katsnelson, M.I.; Koonin, E.V.

    2017-01-01

    We combine mathematical modeling of genome evolution with comparative analysis of prokaryotic genomes to estimate the relative contributions of selection and intrinsic loss bias to the evolution of different functional classes of genes and mobile genetic elements (MGE). An exact solution for the

  8. Selecting between-sample RNA-Seq normalization methods from the perspective of their assumptions.

    Science.gov (United States)

    Evans, Ciaran; Hardin, Johanna; Stoebel, Daniel M

    2017-02-27

    RNA-Seq is a widely used method for studying the behavior of genes under different biological conditions. An essential step in an RNA-Seq study is normalization, in which raw data are adjusted to account for factors that prevent direct comparison of expression measures. Errors in normalization can have a significant impact on downstream analysis, such as inflated false positives in differential expression analysis. An underemphasized feature of normalization is the assumptions on which the methods rely and how the validity of these assumptions can have a substantial impact on the performance of the methods. In this article, we explain how assumptions provide the link between raw RNA-Seq read counts and meaningful measures of gene expression. We examine normalization methods from the perspective of their assumptions, as an understanding of methodological assumptions is necessary for choosing methods appropriate for the data at hand. Furthermore, we discuss why normalization methods perform poorly when their assumptions are violated and how this causes problems in subsequent analysis. To analyze a biological experiment, researchers must select a normalization method with assumptions that are met and that produces a meaningful measure of expression for the given experiment. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

  9. An objective method for High Dynamic Range source content selection

    DEFF Research Database (Denmark)

    Narwaria, Manish; Mantel, Claire; Da Silva, Matthieu Perreira

    2014-01-01

    With the aim of improving the immersive experience of the end user, High Dynamic Range (HDR) imaging has been gaining popularity. Therefore, proper validation and performance benchmarking of HDR processing algorithms is a key step towards standardization and commercial deployment. A crucial...... component of such validation studies is the selection of a challenging and balanced set of source (reference) HDR content. In order to facilitate this, we present an objective method based on the premise that a more challenging HDR scene encapsulates higher contrast, and as a result will show up more...

  10. Analysis of Various Frequency Selective Shielding Glass by FDTD method

    OpenAIRE

    笠嶋, 善憲; Kasashima, Yoshinori

    2012-01-01

    A frequency Selective shielding (FSS) glass is a print of many same size antennas on a sheet of glass, and it has high shielding properties for one specific frequency. This time, the author analyzed characteristics of various FSSs whose antenna types are different by FDTD method. The antenna types are cross dipole, circular loop, square loop, circular patch, and square patch. As the result, the FSSs can be composed of the various types of the antennas, and the FSSs have broad-band shielding c...

  11. Linear feature selection in texture analysis - A PLS based method

    DEFF Research Database (Denmark)

    Marques, Joselene; Igel, Christian; Lillholm, Martin

    2013-01-01

    We present a texture analysis methodology that combined uncommitted machine-learning techniques and partial least square (PLS) in a fully automatic framework. Our approach introduces a robust PLS-based dimensionality reduction (DR) step to specifically address outliers and high-dimensional feature...... and considering all CV groups, the methods selected 36 % of the original features available. The diagnosis evaluation reached a generalization area-under-the-ROC curve of 0.92, which was higher than established cartilage-based markers known to relate to OA diagnosis....

  12. Selection on plant male function genes identifies candidates for reproductive isolation of yellow monkeyflowers.

    Directory of Open Access Journals (Sweden)

    Jan E Aagaard

    Full Text Available Understanding the genetic basis of reproductive isolation promises insight into speciation and the origins of biological diversity. While progress has been made in identifying genes underlying barriers to reproduction that function after fertilization (post-zygotic isolation, we know much less about earlier acting pre-zygotic barriers. Of particular interest are barriers involved in mating and fertilization that can evolve extremely rapidly under sexual selection, suggesting they may play a prominent role in the initial stages of reproductive isolation. A significant challenge to the field of speciation genetics is developing new approaches for identification of candidate genes underlying these barriers, particularly among non-traditional model systems. We employ powerful proteomic and genomic strategies to study the genetic basis of conspecific pollen precedence, an important component of pre-zygotic reproductive isolation among yellow monkeyflowers (Mimulus spp. resulting from male pollen competition. We use isotopic labeling in combination with shotgun proteomics to identify more than 2,000 male function (pollen tube proteins within maternal reproductive structures (styles of M. guttatus flowers where pollen competition occurs. We then sequence array-captured pollen tube exomes from a large outcrossing population of M. guttatus, and identify those genes with evidence of selective sweeps or balancing selection consistent with their role in pollen competition. We also test for evidence of positive selection on these genes more broadly across yellow monkeyflowers, because a signal of adaptive divergence is a common feature of genes causing reproductive isolation. Together the molecular evolution studies identify 159 pollen tube proteins that are candidate genes for conspecific pollen precedence. Our work demonstrates how powerful proteomic and genomic tools can be readily adapted to non-traditional model systems, allowing for genome-wide screens

  13. Recurrent selection on the Winters sex-ratio genes in Drosophila simulans.

    Science.gov (United States)

    Kingan, Sarah B; Garrigan, Daniel; Hartl, Daniel L

    2010-01-01

    Selfish genes, such as meiotic drive elements, propagate themselves through a population without increasing the fitness of host organisms. X-linked (or Y-linked) meiotic drive elements reduce the transmission of the Y (X) chromosome and skew progeny and population sex ratios, leading to intense conflict among genomic compartments. Drosophila simulans is unusual in having a least three distinct systems of X chromosome meiotic drive. Here, we characterize naturally occurring genetic variation at the Winters sex-ratio driver (Distorter on the X or Dox), its progenitor gene (Mother of Dox or MDox), and its suppressor gene (Not Much Yang or Nmy), which have been previously mapped and characterized. We survey three North American populations as well as 13 globally distributed strains and present molecular polymorphism data at the three loci. We find that all three genes show signatures of selection in North America, judging from levels of polymorphism and skews in the site-frequency spectrum. These signatures likely result from the biased transmission of the driver and selection on the suppressor for the maintenance of equal sex ratios. Coalescent modeling indicates that the timing of selection is more recent than the age of the alleles, suggesting that the driver and suppressor are coevolving under an evolutionary "arms race." None of the Winters sex-ratio genes are fixed in D. simulans, and at all loci we find ancestral alleles, which lack the gene insertions and exhibit high levels of nucleotide polymorphism compared to the derived alleles. In addition, we find several "null" alleles that have mutations on the derived Dox background, which result in loss of drive function. We discuss the possible causes of the maintenance of presence-absence polymorphism in the Winters sex-ratio genes.

  14. A complex selection signature at the human AVPR1B gene

    Directory of Open Access Journals (Sweden)

    Cagliani Rachele

    2009-06-01

    Full Text Available Abstract Background The vasopressin receptor type 1b (AVPR1B is mainly expressed by pituitary corticotropes and it mediates the stimulatory effects of AVP on ACTH release; common AVPR1B haplotypes have been involved in mood and anxiety disorders in humans, while rodents lacking a functional receptor gene display behavioral defects and altered stress responses. Results Here we have analyzed the two exons of the gene and the data we present suggest that AVPR1B has been subjected to natural selection in humans. In particular, analysis of exon 2 strongly suggests the action of balancing selection in African populations and Europeans: the region displays high nucleotide diversity, an excess of intermediate-frequency alleles, a higher level of within-species diversity compared to interspecific divergence and a genealogy with common haplotypes separated by deep branches. This relatively unambiguous situation coexists with unusual features across exon 1, raising the possibility that a nonsynonymous variant (Gly191Arg in this region has been subjected to directional selection. Conclusion Although the underlying selective pressure(s remains to be identified, we consider this to be among the first documented examples of a gene involved in mood disorders and subjected to natural selection in humans; this observation might add support to the long-debated idea that depression/low mood might have played an adaptive role during human evolution.

  15. A complex selection signature at the human AVPR1B gene.

    Science.gov (United States)

    Cagliani, Rachele; Fumagalli, Matteo; Pozzoli, Uberto; Riva, Stefania; Cereda, Matteo; Comi, Giacomo P; Pattini, Linda; Bresolin, Nereo; Sironi, Manuela

    2009-06-01

    The vasopressin receptor type 1b (AVPR1B) is mainly expressed by pituitary corticotropes and it mediates the stimulatory effects of AVP on ACTH release; common AVPR1B haplotypes have been involved in mood and anxiety disorders in humans, while rodents lacking a functional receptor gene display behavioral defects and altered stress responses. Here we have analyzed the two exons of the gene and the data we present suggest that AVPR1B has been subjected to natural selection in humans. In particular, analysis of exon 2 strongly suggests the action of balancing selection in African populations and Europeans: the region displays high nucleotide diversity, an excess of intermediate-frequency alleles, a higher level of within-species diversity compared to interspecific divergence and a genealogy with common haplotypes separated by deep branches. This relatively unambiguous situation coexists with unusual features across exon 1, raising the possibility that a nonsynonymous variant (Gly191Arg) in this region has been subjected to directional selection. Although the underlying selective pressure(s) remains to be identified, we consider this to be among the first documented examples of a gene involved in mood disorders and subjected to natural selection in humans; this observation might add support to the long-debated idea that depression/low mood might have played an adaptive role during human evolution.

  16. Duration and speed of speech events: A selection of methods

    Directory of Open Access Journals (Sweden)

    Gibbon Dafydd

    2015-07-01

    Full Text Available The study of speech timing, i.e. the duration and speed or tempo of speech events, has increased in importance over the past twenty years, in particular in connection with increased demands for accuracy, intelligibility and naturalness in speech technology, with applications in language teaching and testing, and with the study of speech timing patterns in language typology. H owever, the methods used in such studies are very diverse, and so far there is no accessible overview of these methods. Since the field is too broad for us to provide an exhaustive account, we have made two choices: first, to provide a framework of paradigmatic (classificatory, syntagmatic (compositional and functional (discourse-oriented dimensions for duration analysis; and second, to provide worked examples of a selection of methods associated primarily with these three dimensions. Some of the methods which are covered are established state-of-the-art approaches (e.g. the paradigmatic Classification and Regression Trees, CART , analysis, others are discussed in a critical light (e.g. so-called ‘rhythm metrics’. A set of syntagmatic approaches applies to the tokenisation and tree parsing of duration hierarchies, based on speech annotations, and a functional approach describes duration distributions with sociolinguistic variables. Several of the methods are supported by a new web-based software tool for analysing annotated speech data, the Time Group Analyser.

  17. Gene features selection for three-class disease classification via multiple orthogonal partial least square discriminant analysis and S-plot using microarray data.

    Science.gov (United States)

    Yang, Mingxing; Li, Xiumin; Li, Zhibin; Ou, Zhimin; Liu, Ming; Liu, Suhuan; Li, Xuejun; Yang, Shuyu

    2013-01-01

    DNA microarray analysis is characterized by obtaining a large number of gene variables from a small number of observations. Cluster analysis is widely used to analyze DNA microarray data to make classification and diagnosis of disease. Because there are so many irrelevant and insignificant genes in a dataset, a feature selection approach must be employed in data analysis. The performance of cluster analysis of this high-throughput data depends on whether the feature selection approach chooses the most relevant genes associated with disease classes. Here we proposed a new method using multiple Orthogonal Partial Least Squares-Discriminant Analysis (mOPLS-DA) models and S-plots to select the most relevant genes to conduct three-class disease classification and prediction. We tested our method using Golub's leukemia microarray data. For three classes with subtypes, we proposed hierarchical orthogonal partial least squares-discriminant analysis (OPLS-DA) models and S-plots to select features for two main classes and their subtypes. For three classes in parallel, we employed three OPLS-DA models and S-plots to choose marker genes for each class. The power of feature selection to classify and predict three-class disease was evaluated using cluster analysis. Further, the general performance of our method was tested using four public datasets and compared with those of four other feature selection methods. The results revealed that our method effectively selected the most relevant features for disease classification and prediction, and its performance was better than that of the other methods.

  18. Selection of reference genes for quantitative real-time PCR in bovine preimplantation embryos

    Directory of Open Access Journals (Sweden)

    Van Zeveren Alex

    2005-12-01

    Full Text Available Abstract Background Real-time quantitative PCR is a sensitive and very efficient technique to examine gene transcription patterns in preimplantation embryos, in order to gain information about embryo development and to optimize assisted reproductive technologies. Critical to the succesful application of real-time PCR is careful assay design, reaction optimization and validation to maximize sensitivity and accuracy. In most of the studies published GAPD, ACTB or 18S rRNA have been used as a single reference gene without prior verification of their expression stability. Normalization of the data using unstable controls can result in erroneous conclusions, especially when only one reference gene is used. Results In this study the transcription levels of 8 commonly used reference genes (ACTB, GAPD, Histone H2A, TBP, HPRT1, SDHA, YWHAZ and 18S rRNA were determined at different preimplantation stages (2-cell, 8-cell, blastocyst and hatched blastocyst in order to select the most stable genes to normalize quantitative data within different preimplantation embryo stages. Conclusion Using the geNorm application YWHAZ, GAPD and SDHA were found to be the most stable genes across the examined embryonic stages, while the commonly used ACTB was shown to be highly regulated. We recommend the use of the geometric mean of those 3 reference genes as an accurate normalization factor, which allows small expression differences to be reliably measured.

  19. Natural selection in avian protein-coding genes expressed in brain.

    Science.gov (United States)

    Axelsson, Erik; Hultin-Rosenberg, Lina; Brandström, Mikael; Zwahlén, Martin; Clayton, David F; Ellegren, Hans

    2008-06-01

    The evolution of birds from theropod dinosaurs took place approximately 150 million years ago, and was associated with a number of specific adaptations that are still evident among extant birds, including feathers, song and extravagant secondary sexual characteristics. Knowledge about the molecular evolutionary background to such adaptations is lacking. Here, we analyse the evolution of > 5000 protein-coding gene sequences expressed in zebra finch brain by comparison to orthologous sequences in chicken. Mean d(N)/d(S) is 0.085 and genes with their maximal expression in the eye and central nervous system have the lowest mean d(N)/d(S) value, while those expressed in digestive and reproductive tissues exhibit the highest. We find that fast-evolving genes (those which have higher than expected rate of nonsynonymous substitution, indicative of adaptive evolution) are enriched for biological functions such as fertilization, muscle contraction, defence response, response to stress, wounding and endogenous stimulus, and cell death. After alignment to mammalian orthologues, we identify a catalogue of 228 genes that show a significantly higher rate of protein evolution in the two bird lineages than in mammals. These accelerated bird genes, representing candidates for avian-specific adaptations, include genes implicated in vocal learning and other cognitive processes. Moreover, colouration genes evolve faster in birds than in mammals, which may have been driven by sexual selection for extravagant plumage characteristics.

  20. Selection of suitable reference genes for RT-qPCR analyses in cyanobacteria.

    Directory of Open Access Journals (Sweden)

    Filipe Pinto

    Full Text Available Cyanobacteria are a group of photosynthetic prokaryotes that have a diverse morphology, minimal nutritional requirements and metabolic plasticity that has made them attractive organisms to use in biotechnological applications. The use of these organisms as cell factories requires the knowledge of their physiology and metabolism at a systems level. For the quantification of gene transcripts real-time quantitative polymerase chain reaction (RT-qPCR is the standard technique. However, to obtain reliable RT-qPCR results the use and validation of reference genes is mandatory. Towards this goal we have selected and analyzed twelve candidate reference genes from three morphologically distinct cyanobacteria grown under routinely used laboratory conditions. The six genes exhibiting less variation in each organism were evaluated in terms of their expression stability using geNorm, NormFinder and BestKeeper. In addition, the minimum number of reference genes required for normalization was determined. Based on the three algorithms, we provide a list of genes for cyanobacterial RT-qPCR data normalization. To our knowledge, this is the first work on the validation of reference genes for cyanobacteria constituting a valuable starting point for future works.

  1. A method for selecting cis-acting regulatory sequences that respond to small molecule effectors

    Directory of Open Access Journals (Sweden)

    Allas Ülar

    2010-08-01

    Full Text Available Abstract Background Several cis-acting regulatory sequences functioning at the level of mRNA or nascent peptide and specifically influencing transcription or translation have been described. These regulatory elements often respond to specific chemicals. Results We have developed a method that allows us to select cis-acting regulatory sequences that respond to diverse chemicals. The method is based on the β-lactamase gene containing a random sequence inserted into the beginning of the ORF. Several rounds of selection are used to isolate sequences that suppress β-lactamase expression in response to the compound under study. We have isolated sequences that respond to erythromycin, troleandomycin, chloramphenicol, meta-toluate and homoserine lactone. By introducing synonymous and non-synonymous mutations we have shown that at least in the case of erythromycin the sequences act at the peptide level. We have also tested the cross-activities of the constructs and found that in most cases the sequences respond most strongly to the compound on which they were isolated. Conclusions Several selected peptides showed ligand-specific changes in amino acid frequencies, but no consensus motif could be identified. This is consistent with previous observations on natural cis-acting peptides, showing that it is often impossible to demonstrate a consensus. Applying the currently developed method on a larger scale, by selecting and comparing an extended set of sequences, might allow the sequence rules underlying the activity of cis-acting regulatory peptides to be identified.

  2. FCERI AND HISTAMINE METABOLISM GENE VARIABILITY IN SELECTIVE RESPONDERS TO NSAIDS

    Directory of Open Access Journals (Sweden)

    Gemma Amo

    2016-09-01

    Full Text Available The high-affinity IgE receptor (Fcε RI is a heterotetramer of three subunits: Fcε RIα, Fcε RIβ and Fcε RIγ (αβγ2 encoded by three genes designated as FCER1A, FCER1B (MS4A2 and FCER1G, respectively. Recent evidence points to FCERI gene variability as a relevant factor in the risk of developing allergic diseases. Because Fcε RI plays a key role in the events downstream of the triggering factors in immunological response, we hypothesized that FCERI gene variants might be related with the risk of, or with the clinical response to, selective (IgE mediated non-steroidal anti-inflammatory (NSAID hypersensitivity.From a cohort of 314 patients suffering from selective hypersensitivity to metamizole, ibuprofen, diclofenac, paracetamol, acetylsalicylic acid (ASA, propifenazone, naproxen, ketoprofen, dexketoprofen, etofenamate, aceclofenac, etoricoxib, dexibuprofen, indomethacin, oxyphenylbutazone or piroxicam, and 585 unrelated healthy controls that tolerated these NSAIDs, we analyzed the putative effects of the FCERI SNPs FCER1A rs2494262, rs2427837 and rs2251746; FCER1B rs1441586, rs569108 and rs512555; FCER1G rs11587213, rs2070901 and rs11421. Furthermore, in order to identify additional genetic markers which might be associated with the risk of developing selective NSAID hypersensitivity, or which may modify the putative association of FCERI gene variations with risk, we analyzed polymorphisms known to affect histamine synthesis or metabolism, such as rs17740607, rs2073440, rs1801105, rs2052129, rs10156191, rs1049742 and rs1049793 in the HDC, HNMT and DAO genes.No major genetic associations with risk or with clinical presentation, and no gene-gene interactions, or gene-phenotype interactions (including age, gender, IgE concentration, antecedents of atopy, culprit drug or clinical presentation were identified in patients. However, logistic regression analyses indicated that the presence of antecedents of atopy and the DAO SNP rs2052129 (GG

  3. Differential selection on carotenoid biosynthesis genes as a function of gene position in the metabolic pathway: a study on the carrot and dicots.

    Directory of Open Access Journals (Sweden)

    Jérémy Clotault

    Full Text Available Selection of genes involved in metabolic pathways could target them differently depending on the position of genes in the pathway and on their role in controlling metabolic fluxes. This hypothesis was tested in the carotenoid biosynthesis pathway using population genetics and phylogenetics.Evolutionary rates of seven genes distributed along the carotenoid biosynthesis pathway, IPI, PDS, CRTISO, LCYB, LCYE, CHXE and ZEP, were compared in seven dicot taxa. A survey of deviations from neutrality expectations at these genes was also undertaken in cultivated carrot (Daucus carota subsp. sativus, a species that has been intensely bred for carotenoid pattern diversification in its root during its cultivation history. Parts of sequences of these genes were obtained from 46 individuals representing a wide diversity of cultivated carrots. Downstream genes exhibited higher deviations from neutral expectations than upstream genes. Comparisons of synonymous and nonsynonymous substitution rates between genes among dicots revealed greater constraints on upstream genes than on downstream genes. An excess of intermediate frequency polymorphisms, high nucleotide diversity and/or high differentiation of CRTISO, LCYB1 and LCYE in cultivated carrot suggest that balancing selection may have targeted genes acting centrally in the pathway.Our results are consistent with relaxed constraints on downstream genes and selection targeting the central enzymes of the carotenoid biosynthesis pathway during carrot breeding history.

  4. Bacterial evolution through the selective loss of beneficial Genes. Trade-offs in expression involving two loci.

    Science.gov (United States)

    Zinser, Erik R; Schneider, Dominique; Blot, Michel; Kolter, Roberto

    2003-01-01

    The loss of preexisting genes or gene activities during evolution is a major mechanism of ecological specialization. Evolutionary processes that can account for gene loss or inactivation have so far been restricted to one of two mechanisms: direct selection for the loss of gene activities that are disadvantageous under the conditions of selection (i.e., antagonistic pleiotropy) and selection-independent genetic drift of neutral (or nearly neutral) mutations (i.e., mutation accumulation). In this study we demonstrate with an evolved strain of Escherichia coli that a third, distinct mechanism exists by which gene activities can be lost. This selection-dependent mechanism involves the expropriation of one gene's upstream regulatory element by a second gene via a homologous recombination event. Resulting from this genetic exchange is the activation of the second gene and a concomitant inactivation of the first gene. This gene-for-gene expression tradeoff provides a net fitness gain, even if the forfeited activity of the first gene can play a positive role in fitness under the conditions of selection. PMID:12930738

  5. Bacterial evolution through the selective loss of beneficial Genes. Trade-offs in expression involving two loci.

    Science.gov (United States)

    Zinser, Erik R; Schneider, Dominique; Blot, Michel; Kolter, Roberto

    2003-08-01

    The loss of preexisting genes or gene activities during evolution is a major mechanism of ecological specialization. Evolutionary processes that can account for gene loss or inactivation have so far been restricted to one of two mechanisms: direct selection for the loss of gene activities that are disadvantageous under the conditions of selection (i.e., antagonistic pleiotropy) and selection-independent genetic drift of neutral (or nearly neutral) mutations (i.e., mutation accumulation). In this study we demonstrate with an evolved strain of Escherichia coli that a third, distinct mechanism exists by which gene activities can be lost. This selection-dependent mechanism involves the expropriation of one gene's upstream regulatory element by a second gene via a homologous recombination event. Resulting from this genetic exchange is the activation of the second gene and a concomitant inactivation of the first gene. This gene-for-gene expression tradeoff provides a net fitness gain, even if the forfeited activity of the first gene can play a positive role in fitness under the conditions of selection.

  6. Reference gene selection for real-time quantitative PCR analysis of the mouse uterus in the peri-implantation period.

    Directory of Open Access Journals (Sweden)

    Pengfei Lin

    Full Text Available The study of uterine gene expression patterns is valuable for understanding the biological and molecular mechanisms that occur during embryo implantation. Real-time quantitative RT-PCR (qRT-PCR is an extremely sensitive technique that allows for the precise quantification of mRNA abundance; however, selecting stable reference genes suitable for the normalization of qRT-PCR data is required to avoid the misinterpretation of experimental results and erroneous analyses. This study employs several mouse models, including an early pregnancy, a pseudopregnancy, a delayed implantation and activation, an artificial decidualization and a hormonal treatment model; ten candidate reference genes (PPIA, RPLP0, HPRT1, GAPDH, ACTB, TBP, B2M, 18S, UBC and TUBA that are found in uterine tissues were assessed for their suitability as internal controls for relative qRT-PCR quantification. GeNorm(PLUS, NormFinder, and BestKeeper were used to evaluate these candidate reference genes, and all of these methods identified RPLP0 and GAPDH as the most stable candidates and B2M and 18S as the least stable candidates. However, when the different models were analyzed separately, the reference genes exhibited some variation in their expression levels.

  7. An algebra-based method for inferring gene regulatory networks.

    Science.gov (United States)

    Vera-Licona, Paola; Jarrah, Abdul; Garcia-Puente, Luis David; McGee, John; Laubenbacher, Reinhard

    2014-03-26

    The inference of gene regulatory networks (GRNs) from experimental observations is at the heart of systems biology. This includes the inference of both the network topology and its dynamics. While there are many algorithms available to infer the network topology from experimental data, less emphasis has been placed on methods that infer network dynamics. Furthermore, since the network inference problem is typically underdetermined, it is essential to have the option of incorporating into the inference process, prior knowledge about the network, along with an effective description of the search space of dynamic models. Finally, it is also important to have an understanding of how a given inference method is affected by experimental and other noise in the data used. This paper contains a novel inference algorithm using the algebraic framework of Boolean polynomial dynamical systems (BPDS), meeting all these requirements. The algorithm takes as input time series data, including those from network perturbations, such as knock-out mutant strains and RNAi experiments. It allows for the incorporation of prior biological knowledge while being robust to significant levels of noise in the data used for inference. It uses an evolutionary algorithm for local optimization with an encoding of the mathematical models as BPDS. The BPDS framework allows an effective representation of the search space for algebraic dynamic models that improves computational performance. The algorithm is validated with both simulated and experimental microarray expression profile data. Robustness to noise is tested using a published mathematical model of the segment polarity gene network in Drosophila melanogaster. Benchmarking of the algorithm is done by comparison with a spectrum of state-of-the-art network inference methods on data from the synthetic IRMA network to demonstrate that our method has good precision and recall for the network reconstruction task, while also predicting several of the

  8. SELECTING A MANAGEMENT SYSTEM HOSPITAL BY A METHOD MULTICRITERIA

    Directory of Open Access Journals (Sweden)

    Vitorino, Sidney L.

    2016-12-01

    Full Text Available The objective of this report is to assess how the multi-criteria method Analytic Hierarchy Process [HP] can help a hospital complex to choose a more suitable management system, known as Enterprise Resource Planning (ERP. The choice coated is very complex due to the novelty of the process of choosing and conflicts generated between areas that did not have a single view of organizational needs, generating a lot of pressure in the department responsible for implementing systems. To assist in this process, he was hired an expert consultant in decision-making and AHP, which in its role of facilitator, contributed to the criteria for system selection were defined, and the choice to occur within a consensual process. We used the study of a single case, based on two indepth interviews with the consultant and the project manager, and documents generated by the advisory and the tool that supported the method. The results of this analysis showed that the method could effectively collaborate in the system acquisition process, but knowledge of the problems of employees and senior management support, it was not used in new decisions of the organization. We conclude that this method contributed to the consensus in the procurement process, team commitment and engagement of those involved.

  9. Development of an optimal velocity selection method with velocity obstacle

    Energy Technology Data Exchange (ETDEWEB)

    Kim, Min Geuk; Oh, Jun Ho [KAIST, Daejeon (Korea, Republic of)

    2015-08-15

    The Velocity obstacle (VO) method is one of the most well-known methods for local path planning, allowing consideration of dynamic obstacles and unexpected obstacles. Typical VO methods separate a velocity map into a collision area and a collision-free area. A robot can avoid collisions by selecting its velocity from within the collision-free area. However, if there are numerous obstacles near a robot, the robot will have very few velocity candidates. In this paper, a method for choosing optimal velocity components using the concept of pass-time and vertical clearance is proposed for the efficient movement of a robot. The pass-time is the time required for a robot to pass by an obstacle. By generating a latticized available velocity map for a robot, each velocity component can be evaluated using a cost function that considers the pass-time and other aspects. From the output of the cost function, even a velocity component that will cause a collision in the future can be chosen as a final velocity if the pass-time is sufficiently long enough.

  10. Genetic diversity and natural selection footprints of the glycine amidinotransferase gene in various human populations.

    Science.gov (United States)

    Khan, Asifullah; Tian, Lei; Zhang, Chao; Yuan, Kai; Xu, Shuhua

    2016-01-05

    The glycine amidinotransferase gene (GATM) plays a vital role in energy metabolism in muscle tissues and is associated with multiple clinically important phenotypes. However, the genetic diversity of the GATM gene remains poorly understood within and between human populations. Here we analyzed the 1,000 Genomes Project data through population genetics approaches and observed significant genetic diversity across the GATM gene among various continental human populations. We observed considerable variations in GATM allele frequencies and haplotype composition among different populations. Substantial genetic differences were observed between East Asian and European populations (FST = 0.56). In addition, the frequency of a distinct major GATM haplotype in these groups was congruent with population-wide diversity at this locus. Furthermore, we identified GATM as the top differentiated gene compared to the other statin drug response-associated genes. Composite multiple analyses identified signatures of positive selection at the GATM locus, which was estimated to have occurred around 850 generations ago in European populations. As GATM catalyzes the key step of creatine biosynthesis involved in energy metabolism, we speculate that the European prehistorical demographic transition from hunter-gatherer to farming cultures was the driving force of selection that fulfilled creatine-based metabolic requirement of the populations.

  11. 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.

  12. Preclinical evaluation of gene delivery methods for the treatment of loco-regional disease in breast cancer.

    LENUS (Irish Health Repository)

    Rajendran, Simon

    2011-04-01

    Preclinical results with various gene therapy strategies indicate significant potential for new cancer treatments. However, many therapeutics fail at clinical trial, often due to differences in tissue physiology between animal models and humans, and tumor phenotype variation. Clinical data relevant to treatment strategies may be generated prior to clinical trial through experimentation using intact patient tissue ex vivo. We developed a novel tumor slice model culture system that is universally applicable to gene delivery methods, using a realtime luminescence detection method to assess gene delivery. Methods investigated include viruses (adenovirus [Ad] and adeno-associated virus), lipofection, ultrasound (US), electroporation and naked DNA. Viability and tumor populations within the slices were well maintained for seven days, and gene delivery was qualitatively and quantitatively examinable for all vectors. Ad was the most efficient gene delivery vector with transduction efficiency >50%. US proved the optimal non-viral gene delivery method in human tumor slices. The nature of the ex vivo culture system permitted examination of specific elements. Parameters shown to diminish Ad gene delivery included blood, regions of low viability and secondary disease. US gene delivery was significantly reduced by blood and skin, while tissue hyperthermia improved gene delivery. US achieved improved efficacy for secondary disease. The ex vivo model was also suitable for examination of tissue-specific effects on vector expression, with Ad expression mediated by the CXCR4 promoter shown to provide a tumor selective advantage over the ubiquitously active cytomegalovirus promoter. In conclusion, this is the first study incorporating patient tissue models in comparing gene delivery from various vectors, providing knowledge on cell-type specificity and examining the crucial biological factors determining successful gene delivery. The results highlight the importance of in

  13. Preclinical evaluation of gene delivery methods for the treatment of loco-regional disease in breast cancer.

    LENUS (Irish Health Repository)

    Rajendran, Simon

    2012-01-31

    Preclinical results with various gene therapy strategies indicate significant potential for new cancer treatments. However, many therapeutics fail at clinical trial, often due to differences in tissue physiology between animal models and humans, and tumor phenotype variation. Clinical data relevant to treatment strategies may be generated prior to clinical trial through experimentation using intact patient tissue ex vivo. We developed a novel tumor slice model culture system that is universally applicable to gene delivery methods, using a realtime luminescence detection method to assess gene delivery. Methods investigated include viruses (adenovirus [Ad] and adeno-associated virus), lipofection, ultrasound (US), electroporation and naked DNA. Viability and tumor populations within the slices were well maintained for seven days, and gene delivery was qualitatively and quantitatively examinable for all vectors. Ad was the most efficient gene delivery vector with transduction efficiency >50%. US proved the optimal non-viral gene delivery method in human tumor slices. The nature of the ex vivo culture system permitted examination of specific elements. Parameters shown to diminish Ad gene delivery included blood, regions of low viability and secondary disease. US gene delivery was significantly reduced by blood and skin, while tissue hyperthermia improved gene delivery. US achieved improved efficacy for secondary disease. The ex vivo model was also suitable for examination of tissue-specific effects on vector expression, with Ad expression mediated by the CXCR4 promoter shown to provide a tumor selective advantage over the ubiquitously active cytomegalovirus promoter. In conclusion, this is the first study incorporating patient tissue models in comparing gene delivery from various vectors, providing knowledge on cell-type specificity and examining the crucial biological factors determining successful gene delivery. The results highlight the importance of in

  14. Selection of internal control genes for quantitative real-time RT-PCR studies during tomato development process

    Directory of Open Access Journals (Sweden)

    Borges-Pérez Andrés

    2008-12-01

    Full Text Available Abstract Background The elucidation of gene expression patterns leads to a better understanding of biological processes. Real-time quantitative RT-PCR has become the standard method for in-depth studies of gene expression. A biologically meaningful reporting of target mRNA quantities requires accurate and reliable normalization in order to identify real gene-specific variation. The purpose of normalization is to control several variables such as different amounts and quality of starting material, variable enzymatic efficiencies of retrotranscription from RNA to cDNA, or differences between tissues or cells in overall transcriptional activity. The validity of a housekeeping gene as endogenous control relies on the stability of its expression level across the sample panel being analysed. In the present report we describe the first systematic evaluation of potential internal controls during tomato development process to identify which are the most reliable for transcript quantification by real-time RT-PCR. Results In this study, we assess the expression stability of 7 traditional and 4 novel housekeeping genes in a set of 27 samples representing different tissues and organs of tomato plants at different developmental stages. First, we designed, tested and optimized amplification primers for real-time RT-PCR. Then, expression data from each candidate gene were evaluated with three complementary approaches based on different statistical procedures. Our analysis suggests that SGN-U314153 (CAC, SGN-U321250 (TIP41, SGN-U346908 ("Expressed" and SGN-U316474 (SAND genes provide superior transcript normalization in tomato development studies. We recommend different combinations of these exceptionally stable housekeeping genes for suited normalization of different developmental series, including the complete tomato development process. Conclusion This work constitutes the first effort for the selection of optimal endogenous controls for quantitative real

  15. Mitogen activated protein kinases selectively regulate palytoxin-stimulated gene expression in mouse keratinocytes

    International Nuclear Information System (INIS)

    Zeliadt, Nicholette A.; Warmka, Janel K.; Wattenberg, Elizabeth V.

    2003-01-01

    We have been investigating how the novel skin tumor promoter palytoxin transmits signals through mitogen activated protein kinases (MAPKs). Palytoxin activates three major MAPKs, extracellular signal-regulated kinase (ERK), c-Jun N-terminal kinase (JNK), and p38, in a keratinocyte cell line derived from initiated mouse skin (308). We previously showed that palytoxin requires ERK to increase matrix metalloproteinase-13 (MMP-13) gene expression, an enzyme implicated in carcinogenesis. Diverse stimuli require JNK and p38 to increase MMP-13 gene expression, however. We therefore used the JNK and p38 inhibitors SP 600125 and SB 202190, respectively, to investigate the role of these MAPKs in palytoxin-induced MMP-13 gene expression. Surprisingly, palytoxin does not require JNK and p38 to increase MMP-13 gene expression. Accordingly, ERK activation, independent of palytoxin and in the absence of JNK and p38 activation, is sufficient to induce MMP-13 gene expression in 308 keratinocytes. Dexamethasone, a synthetic glucocorticoid that inhibits activator protein-1 (AP-1), blocked palytoxin-stimulated MMP-13 gene expression. Therefore, the AP-1 site present in the promoter of the MMP-13 gene appears to be functional and to play a key role in palytoxin-stimulated gene expression. Previous studies showed that palytoxin simulates an ERK-dependent selective increase in the c-Fos content of AP-1 complexes that bind to the promoter of the MMP-13 gene. JNK and p38 can also modulate c-Fos. Palytoxin does not require JNK or p38 to increase c-Fos binding, however. Altogether, these studies indicate that ERK plays a distinctly essential role in transmitting palytoxin-stimulated signals to specific nuclear targets in keratinocytes derived from initiated mouse skin

  16. CASCADE, a platform for controlled gene amplification for high, tunable and selection-free gene expression in yeast

    DEFF Research Database (Denmark)

    Strucko, Tomas; Buron, Line Due; Jarczynska, Zofia Dorota

    2017-01-01

    Over-expression of a gene by increasing its copy number is often desirable in the model yeast Saccharomyces cerevisiae. It may facilitate elucidation of enzyme functions, and in cell factory design it is used to increase production of proteins and metabolites. Current methods are typically exploi...... production of two fluorescent proteins, the enzyme β-galactosidase the fungal polyketide 6-methyl salicylic acid and the plant metabolite vanillin glucoside....

  17. An Ensemble Method with Integration of Feature Selection and Classifier Selection to Detect the Landslides

    Science.gov (United States)

    Zhongqin, G.; Chen, Y.

    2017-12-01

    Abstract Quickly identify the spatial distribution of landslides automatically is essential for the prevention, mitigation and assessment of the landslide hazard. It's still a challenging job owing to the complicated characteristics and vague boundary of the landslide areas on the image. The high resolution remote sensing image has multi-scales, complex spatial distribution and abundant features, the object-oriented image classification methods can make full use of the above information and thus effectively detect the landslides after the hazard happened. In this research we present a new semi-supervised workflow, taking advantages of recent object-oriented image analysis and machine learning algorithms to quick locate the different origins of landslides of some areas on the southwest part of China. Besides a sequence of image segmentation, feature selection, object classification and error test, this workflow ensemble the feature selection and classifier selection. The feature this study utilized were normalized difference vegetation index (NDVI) change, textural feature derived from the gray level co-occurrence matrices (GLCM), spectral feature and etc. The improvement of this study shows this algorithm significantly removes some redundant feature and the classifiers get fully used. All these improvements lead to a higher accuracy on the determination of the shape of landslides on the high resolution remote sensing image, in particular the flexibility aimed at different kinds of landslides.

  18. Vancomycin gene selection in the microbiome of urban Rattus norvegicus from hospital environment

    DEFF Research Database (Denmark)

    Arn Hansen, Thomas; Joshi, Tejal; Larsen, Anders Rhod

    2016-01-01

    Widespread use of antibiotics has resulted in selection pressure on genes that make bacteria non-responsive to antibiotics. These antibiotic-resistant bacteria are currently a major threat to global health. There are various possibilities for the transfer of antibiotic resistance genes. It has be....... norvegicus microbiome, potentially driven by the outflow of antibiotics and antibiotic-resistant bacteria into the wastewater systems. Carriage of vancomycin resistance may suggest that R. norvegicus is acting as a reservoir for possible transmission to the human population....

  19. The cld mutation: narrowing the critical chromosomal region and selecting candidate genes.

    Science.gov (United States)

    Péterfy, Miklós; Mao, Hui Z; Doolittle, Mark H

    2006-10-01

    Combined lipase deficiency (cld) is a recessive, lethal mutation specific to the tw73 haplotype on mouse Chromosome 17. While the cld mutation results in lipase proteins that are inactive, aggregated, and retained in the endoplasmic reticulum (ER), it maps separately from the lipase structural genes. We have narrowed the gene critical region by about 50% using the tw18 haplotype for deletion mapping and a recombinant chromosome used originally to map cld with respect to the phenotypic marker tf. The region now extends from 22 to 25.6 Mbp on the wild-type chromosome, currently containing 149 genes and 50 expressed sequence tags (ESTs). To identify the affected gene, we have selected candidates based on their known role in associated biological processes, cellular components, and molecular functions that best fit with the predicted function of the cld gene. A secondary approach was based on differences in mRNA levels between mutant (cld/cld) and unaffected (+/cld) cells. Using both approaches, we have identified seven functional candidates with an ER localization and/or an involvement in protein maturation and folding that could explain the lipase deficiency, and six expression candidates that exhibit large differences in mRNA levels between mutant and unaffected cells. Significantly, two genes were found to be candidates with regard to both function and expression, thus emerging as the strongest candidates for cld. We discuss the implications of our mapping results and our selection of candidates with respect to other genes, deletions, and mutations occurring in the cld critical region.

  20. Gene transfer preferentially selects MHC class I positive tumour cells and enhances tumour immunogenicity.

    Science.gov (United States)

    Hacker, Ulrich T; Schildhauer, Ines; Barroso, Margarita Céspedes; Kofler, David M; Gerner, Franz M; Mysliwietz, Josef; Buening, Hildegard; Hallek, Michael; King, Susan B S

    2006-05-01

    The modulated expression of MHC class I on tumour tissue is well documented. Although the effect of MHC class I expression on the tumorigenicity and immunogenicity of MHC class I negative tumour cell lines has been rigorously studied, less is known about the validity of gene transfer and selection in cell lines with a mixed MHC class I phenotype. To address this issue we identified a C26 cell subline that consists of distinct populations of MHC class I (H-2D/K) positive and negative cells. Transient transfection experiments using liposome-based transfer showed a lower transgene expression in MHC class I negative cells. In addition, MHC class I negative cells were more sensitive to antibiotic selection. This led to the generation of fully MHC class I positive cell lines. In contrast to C26 cells, all transfectants were rejected in vivo and induced protection against the parental tumour cells in rechallenge experiments. Tumour cell specificity of the immune response was demonstrated in in vitro cytokine secretion and cytotoxicity assays. Transfectants expressing CD40 ligand and hygromycin phosphotransferase were not more immunogenic than cells expressing hygromycin resistance alone. We suggest that the MHC class I positive phenotype of the C26 transfectants had a bearing on their immunogenicity, because selected MHC class I positive cells were more immunogenic than parental C26 cells and could induce specific anti-tumour immune responses. These data demonstrate that the generation of tumour cell transfectants can lead to the selection of subpopulations that show an altered phenotype compared to the parental cell line and display altered immunogenicity independent of selection marker genes or other immune modulatory genes. Our results show the importance of monitoring gene transfer in the whole tumour cell population, especially for the evaluation of in vivo therapies targeted to heterogeneous tumour cell populations.

  1. High amino acid diversity and positive selection at a putative coral immunity gene (tachylectin-2

    Directory of Open Access Journals (Sweden)

    Hellberg Michael E

    2010-05-01

    Full Text Available Abstract Background Genes involved in immune functions, including pathogen recognition and the activation of innate defense pathways, are among the most genetically variable known, and the proteins that they encode are often characterized by high rates of amino acid substitutions, a hallmark of positive selection. The high levels of variation characteristic of immunity genes make them useful tools for conservation genetics. To date, highly variable immunity genes have yet to be found in corals, keystone organisms of the world's most diverse marine ecosystem, the coral reef. Here, we examine variation in and selection on a putative innate immunity gene from Oculina, a coral genus previously used as a model for studies of coral disease and bleaching. Results In a survey of 244 Oculina alleles, we find high nonsynonymous variation and a signature of positive selection, consistent with a putative role in immunity. Using computational protein structure prediction, we generate a structural model of the Oculina protein that closely matches the known structure of tachylectin-2 from the Japanese horseshoe crab (Tachypleus tridentatus, a protein with demonstrated function in microbial recognition and agglutination. We also demonstrate that at least three other genera of anthozoan cnidarians (Acropora, Montastrea and Nematostella possess proteins structurally similar to tachylectin-2. Conclusions Taken together, the evidence of high amino acid diversity, positive selection and structural correspondence to the horseshoe crab tachylectin-2 suggests that this protein is 1 part of Oculina's innate immunity repertoire, and 2 evolving adaptively, possibly under selective pressure from coral-associated microorganisms. Tachylectin-2 may serve as a candidate locus to screen coral populations for their capacity to respond adaptively to future environmental change.

  2. On theoretical models of gene expression evolution with random genetic drift and natural selection.

    Directory of Open Access Journals (Sweden)

    Osamu Ogasawara

    2009-11-01

    Full Text Available The relative contributions of natural selection and random genetic drift are a major source of debate in the study of gene expression evolution, which is hypothesized to serve as a bridge from molecular to phenotypic evolution. It has been suggested that the conflict between views is caused by the lack of a definite model of the neutral hypothesis, which can describe the long-run behavior of evolutionary change in mRNA abundance. Therefore previous studies have used inadequate analogies with the neutral prediction of other phenomena, such as amino acid or nucleotide sequence evolution, as the null hypothesis of their statistical inference.In this study, we introduced two novel theoretical models, one based on neutral drift and the other assuming natural selection, by focusing on a common property of the distribution of mRNA abundance among a variety of eukaryotic cells, which reflects the result of long-term evolution. Our results demonstrated that (1 our models can reproduce two independently found phenomena simultaneously: the time development of gene expression divergence and Zipf's law of the transcriptome; (2 cytological constraints can be explicitly formulated to describe long-term evolution; (3 the model assuming that natural selection optimized relative mRNA abundance was more consistent with previously published observations than the model of optimized absolute mRNA abundances.The models introduced in this study give a formulation of evolutionary change in the mRNA abundance of each gene as a stochastic process, on the basis of previously published observations. This model provides a foundation for interpreting observed data in studies of gene expression evolution, including identifying an adequate time scale for discriminating the effect of natural selection from that of random genetic drift of selectively neutral variations.

  3. Development of modelling method selection tool for health services management: from problem structuring methods to modelling and simulation methods.

    Science.gov (United States)

    Jun, Gyuchan T; Morris, Zoe; Eldabi, Tillal; Harper, Paul; Naseer, Aisha; Patel, Brijesh; Clarkson, John P

    2011-05-19

    There is an increasing recognition that modelling and simulation can assist in the process of designing health care policies, strategies and operations. However, the current use is limited and answers to questions such as what methods to use and when remain somewhat underdeveloped. The aim of this study is to provide a mechanism for decision makers in health services planning and management to compare a broad range of modelling and simulation methods so that they can better select and use them or better commission relevant modelling and simulation work. This paper proposes a modelling and simulation method comparison and selection tool developed from a comprehensive literature review, the research team's extensive expertise and inputs from potential users. Twenty-eight different methods were identified, characterised by their relevance to different application areas, project life cycle stages, types of output and levels of insight, and four input resources required (time, money, knowledge and data). The characterisation is presented in matrix forms to allow quick comparison and selection. This paper also highlights significant knowledge gaps in the existing literature when assessing the applicability of particular approaches to health services management, where modelling and simulation skills are scarce let alone money and time. A modelling and simulation method comparison and selection tool is developed to assist with the selection of methods appropriate to supporting specific decision making processes. In particular it addresses the issue of which method is most appropriate to which specific health services management problem, what the user might expect to be obtained from the method, and what is required to use the method. In summary, we believe the tool adds value to the scarce existing literature on methods comparison and selection.

  4. Evolution of High Cellulolytic Activity in Symbiotic Streptomyces through Selection of Expanded Gene Content and Coordinated Gene Expression

    Science.gov (United States)

    McDonald, Bradon R.; Takasuka, Taichi E.; Wendt-Pienkowski, Evelyn; Doering, Drew T.; Raffa, Kenneth F.; Fox, Brian G.; Currie, Cameron R.

    2016-01-01

    The evolution of cellulose degradation was a defining event in the history of life. Without efficient decomposition and recycling, dead plant biomass would quickly accumulate and become inaccessible to terrestrial food webs and the global carbon cycle. On land, the primary drivers of plant biomass deconstruction are fungi and bacteria in the soil or associated with herbivorous eukaryotes. While the ecological importance of plant-decomposing microbes is well established, little is known about the distribution or evolution of cellulolytic activity in any bacterial genus. Here we show that in Streptomyces, a genus of Actinobacteria abundant in soil and symbiotic niches, the ability to rapidly degrade cellulose is largely restricted to two clades of host-associated strains and is not a conserved characteristic of the Streptomyces genus or host-associated strains. Our comparative genomics identify that while plant biomass degrading genes (CAZy) are widespread in Streptomyces, key enzyme families are enriched in highly cellulolytic strains. Transcriptomic analyses demonstrate that cellulolytic strains express a suite of multi-domain CAZy enzymes that are coregulated by the CebR transcriptional regulator. Using targeted gene deletions, we verify the importance of a highly expressed cellulase (GH6 family cellobiohydrolase) and the CebR transcriptional repressor to the cellulolytic phenotype. Evolutionary analyses identify complex genomic modifications that drive plant biomass deconstruction in Streptomyces, including acquisition and selective retention of CAZy genes and transcriptional regulators. Our results suggest that host-associated niches have selected some symbiotic Streptomyces for increased cellulose degrading activity and that symbiotic bacteria are a rich biochemical and enzymatic resource for biotechnology. PMID:27276034

  5. Method selection for mercury removal from hard coal

    Directory of Open Access Journals (Sweden)

    Dziok Tadeusz

    2017-01-01

    Full Text Available Mercury is commonly found in coal and the coal utilization processes constitute one of the main sources of mercury emission to the environment. This issue is particularly important for Poland, because the Polish energy production sector is based on brown and hard coal. The forecasts show that this trend in energy production will continue in the coming years. At the time of the emission limits introduction, methods of reducing the mercury emission will have to be implemented in Poland. Mercury emission can be reduced as a result of using coal with a relatively low mercury content. In the case of the absence of such coals, the methods of mercury removal from coal can be implemented. The currently used and developing methods include the coal cleaning process (both the coal washing and the dry deshaling as well as the thermal pretreatment of coal (mild pyrolysis. The effectiveness of these methods various for different coals, which is caused by the diversity of coal origin, various characteristics of coal and, especially, by the various modes of mercury occurrence in coal. It should be mentioned that the coal cleaning process allows for the removal of mercury occurring in mineral matter, mainly in pyrite. The thermal pretreatment of coal allows for the removal of mercury occurring in organic matter as well as in the inorganic constituents characterized by a low temperature of mercury release. In this paper, the guidelines for the selection of mercury removal method from hard coal were presented. The guidelines were developed taking into consideration: the effectiveness of mercury removal from coal in the process of coal cleaning and thermal pretreatment, the synergy effect resulting from the combination of these processes, the direction of coal utilization as well as the influence of these processes on coal properties.

  6. GxGrare: gene-gene interaction analysis method for rare variants from high-throughput sequencing data.

    Science.gov (United States)

    Kwon, Minseok; Leem, Sangseob; Yoon, Joon; Park, Taesung

    2018-03-19

    With the rapid advancement of array-based genotyping techniques, genome-wide association studies (GWAS) have successfully identified common genetic variants associated with common complex diseases. However, it has been shown that only a small proportion of the genetic etiology of complex diseases could be explained by the genetic factors identified from GWAS. This missing heritability could possibly be explained by gene-gene interaction (epistasis) and rare variants. There has been an exponential growth of gene-gene interaction analysis for common variants in terms of methodological developments and practical applications. Also, the recent advancement of high-throughput sequencing technologies makes it possible to conduct rare variant analysis. However, little progress has been made in gene-gene interaction analysis for rare variants. Here, we propose GxGrare which is a new gene-gene interaction method for the rare variants in the framework of the multifactor dimensionality reduction (MDR) analysis. The proposed method consists of three steps; 1) collapsing the rare variants, 2) MDR analysis for the collapsed rare variants, and 3) detect top candidate interaction pairs. GxGrare can be used for the detection of not only gene-gene interactions, but also interactions within a single gene. The proposed method is illustrated with 1080 whole exome sequencing data of the Korean population in order to identify causal gene-gene interaction for rare variants for type 2 diabetes. The proposed GxGrare performs well for gene-gene interaction detection with collapsing of rare variants. GxGrare is available at http://bibs.snu.ac.kr/software/gxgrare which contains simulation data and documentation. Supported operating systems include Linux and OS X.

  7. A Lightweight Structure Redesign Method Based on Selective Laser Melting

    Directory of Open Access Journals (Sweden)

    Li Tang

    2016-11-01

    Full Text Available The purpose of this paper is to present a new design method of lightweight parts fabricated by selective laser melting (SLM based on the “Skin-Frame” and to explore the influence of fabrication defects on SLM parts with different sizes. Some standard lattice parts were designed according to the Chinese GB/T 1452-2005 standard and manufactured by SLM. Then these samples were tested in an MTS Insight 30 compression testing machine to study the trends of the yield process with different structure sizes. A set of standard cylinder samples were also designed according to the Chinese GB/T 228-2010 standard. These samples, which were made of iron-nickel alloy (IN718, were also processed by SLM, and then tested in the universal material testing machine INSTRON 1346 to obtain their tensile strength. Furthermore, a lightweight redesigned method was researched. Then some common parts such as a stopper and connecting plate were redesigned using this method. These redesigned parts were fabricated and some application tests have already been performed. The compression testing results show that when the minimum structure size is larger than 1.5 mm, the mechanical characteristics will hardly be affected by process defects. The cylinder parts were fractured by the universal material testing machine at about 1069.6 MPa. These redesigned parts worked well in application tests, with both the weight and fabrication time of these parts reduced more than 20%.

  8. Breast cancer tumor classification using LASSO method selection approach

    International Nuclear Information System (INIS)

    Celaya P, J. M.; Ortiz M, J. A.; Martinez B, M. R.; Solis S, L. O.; Castaneda M, R.; Garza V, I.; Martinez F, M.; Ortiz R, J. M.

    2016-10-01

    Breast cancer is one of the leading causes of deaths worldwide among women. Early tumor detection is key in reducing breast cancer deaths and screening mammography is the widest available method for early detection. Mammography is the most common and effective breast cancer screening test. However, the rate of positive findings is very low, making the radiologic interpretation monotonous and biased toward errors. In an attempt to alleviate radiological workload, this work presents a computer-aided diagnosis (CAD x) method aimed to automatically classify tumor lesions into malign or benign as a means to a second opinion. The CAD x methos, extracts image features, and classifies the screening mammogram abnormality into one of two categories: subject at risk of having malignant tumor (malign), and healthy subject (benign). In this study, 143 abnormal segmentation s (57 malign and 86 benign) from the Breast Cancer Digital Repository (BCD R) public database were used to train and evaluate the CAD x system. Percentile-rank (p-rank) was used to standardize the data. Using the LASSO feature selection methodology, the model achieved a Leave-one-out-cross-validation area under the receiver operating characteristic curve (Auc) of 0.950. The proposed method has the potential to rank abnormal lesions with high probability of malignant findings aiding in the detection of potential malign cases as a second opinion to the radiologist. (Author)

  9. Selective methods for polyphenols and sulphur dioxide determination in wines.

    Science.gov (United States)

    García-Guzmán, Juan J; Hernández-Artiga, María P; Palacios-Ponce de León, Lourdes; Bellido-Milla, Dolores

    2015-09-01

    A critical review to the methods recommended by international bodies and widely used in the winery industry and research studies was performed. A Laccase biosensor was applied to the selective determination of polyphenols in wines. The biosensor response was characterised and it responds mainly to o-diphenols which are the principal polyphenols responsible for the stability and sensory qualities of wines. The spectrophotometric method to determine free and total sulphur dioxide recommended for beers was applied directly to wines. A sampling of 14 red and white wines was performed and they were analysed for biosensor polyphenol index (IBP) and sulphur dioxide concentration (SO2). The antioxidant capacity by the ABTS(+) spectrophotometric method was also determined. A correlation study was performed to elucidate the influence of the polyphenols and SO2 on the wines stability. High correlations were found between IBP and antioxidant capacity and low correlation between SO2 and antioxidant capacity. To evaluate the benefits of wine drinking a new parameter (IBP/SO2) is proposed. Copyright © 2015 Elsevier Ltd. All rights reserved.

  10. Breast cancer tumor classification using LASSO method selection approach

    Energy Technology Data Exchange (ETDEWEB)

    Celaya P, J. M.; Ortiz M, J. A.; Martinez B, M. R.; Solis S, L. O.; Castaneda M, R.; Garza V, I.; Martinez F, M.; Ortiz R, J. M., E-mail: morvymm@yahoo.com.mx [Universidad Autonoma de Zacatecas, Av. Ramon Lopez Velarde 801, Col. Centro, 98000 Zacatecas, Zac. (Mexico)

    2016-10-15

    Breast cancer is one of the leading causes of deaths worldwide among women. Early tumor detection is key in reducing breast cancer deaths and screening mammography is the widest available method for early detection. Mammography is the most common and effective breast cancer screening test. However, the rate of positive findings is very low, making the radiologic interpretation monotonous and biased toward errors. In an attempt to alleviate radiological workload, this work presents a computer-aided diagnosis (CAD x) method aimed to automatically classify tumor lesions into malign or benign as a means to a second opinion. The CAD x methos, extracts image features, and classifies the screening mammogram abnormality into one of two categories: subject at risk of having malignant tumor (malign), and healthy subject (benign). In this study, 143 abnormal segmentation s (57 malign and 86 benign) from the Breast Cancer Digital Repository (BCD R) public database were used to train and evaluate the CAD x system. Percentile-rank (p-rank) was used to standardize the data. Using the LASSO feature selection methodology, the model achieved a Leave-one-out-cross-validation area under the receiver operating characteristic curve (Auc) of 0.950. The proposed method has the potential to rank abnormal lesions with high probability of malignant findings aiding in the detection of potential malign cases as a second opinion to the radiologist. (Author)

  11. AST: an automated sequence-sampling method for improving the taxonomic diversity of gene phylogenetic trees.

    Science.gov (United States)

    Zhou, Chan; Mao, Fenglou; Yin, Yanbin; Huang, Jinling; Gogarten, Johann Peter; Xu, Ying

    2014-01-01

    A challenge in phylogenetic inference of gene trees is how to properly sample a large pool of homologous sequences to derive a good representative subset of sequences. Such a need arises in various applications, e.g. when (1) accuracy-oriented phylogenetic reconstruction methods may not be able to deal with a large pool of sequences due to their high demand in computing resources; (2) applications analyzing a collection of gene trees may prefer to use trees with fewer operational taxonomic units (OTUs), for instance for the detection of horizontal gene transfer events by identifying phylogenetic conflicts; and (3) the pool of available sequences is biased towards extensively studied species. In the past, the creation of subsamples often relied on manual selection. Here we present an Automated sequence-Sampling method for improving the Taxonomic diversity of gene phylogenetic trees, AST, to obtain representative sequences that maximize the taxonomic diversity of the sampled sequences. To demonstrate the effectiveness of AST, we have tested it to solve four problems, namely, inference of the evolutionary histories of the small ribosomal subunit protein S5 of E. coli, 16 S ribosomal RNAs and glycosyl-transferase gene family 8, and a study of ancient horizontal gene transfers from bacteria to plants. Our results show that the resolution of our computational results is almost as good as that of manual inference by domain experts, hence making the tool generally useful to phylogenetic studies by non-phylogeny specialists. The program is available at http://csbl.bmb.uga.edu/~zhouchan/AST.php.

  12. Vancomycin gene selection in the microbiome of urban Rattus norvegicus from hospital environment

    DEFF Research Database (Denmark)

    Arn Hansen, Thomas; Joshi, Tejal; Larsen, Anders Rhod

    2016-01-01

    for the presence of antibiotic resistance genes. We show that despite the shared resistome within samples from the same geographic locations, samples from hospital area carry significantly abundant vancomycin resistance genes. The observed pattern is consistent with a selection for vancomycin genes in the R...

  13. Wavelength selection method with standard deviation: application to pulse oximetry.

    Science.gov (United States)

    Vazquez-Jaccaud, Camille; Paez, Gonzalo; Strojnik, Marija

    2011-07-01

    Near-infrared spectroscopy provides useful biological information after the radiation has penetrated through the tissue, within the therapeutic window. One of the significant shortcomings of the current applications of spectroscopic techniques to a live subject is that the subject may be uncooperative and the sample undergoes significant temporal variations, due to his health status that, from radiometric point of view, introduce measurement noise. We describe a novel wavelength selection method for monitoring, based on a standard deviation map, that allows low-noise sensitivity. It may be used with spectral transillumination, transmission, or reflection signals, including those corrupted by noise and unavoidable temporal effects. We apply it to the selection of two wavelengths for the case of pulse oximetry. Using spectroscopic data, we generate a map of standard deviation that we propose as a figure-of-merit in the presence of the noise introduced by the living subject. Even in the presence of diverse sources of noise, we identify four wavelength domains with standard deviation, minimally sensitive to temporal noise, and two wavelengths domains with low sensitivity to temporal noise.

  14. Selection of disposal contractor by multi criteria decision making methods

    Directory of Open Access Journals (Sweden)

    Cenker Korkmazer

    2016-08-01

    Full Text Available Hazardous waste is substance that threaten people and environment in case of improper storage, disposal and transport due to its concentration, physical and chemical properties. Companies producing hazardous waste as a result of several activities mostly do not have any own disposal facilities. In addition, they do not pay attention enough to determine the right contractor as a disposal facility. On the other hand, there are various qualitative and quantitative criteria affecting the selection of the contractor and conflicting with each other. The aim of the performed study is to assist one of these companies producing hazardous waste in the selection of the best contractor that eliminates hazardous waste economic and harmless way. In the study, contractor weights in percentage is calculated by using Analytic Network Process (ANP as one of the multi-criteria decision making (MCDM methods and widely used in the literature which considers both qualitative and quantitative criteria. In the next step, by the help of the mathematical model, contractors that will be given which type of hazardous waste are identified. This integrated approach can be used as a guide for similar firms.

  15. Selection of reference genes for expression analysis of Kumamoto and Portuguese oysters and their hybrid

    Science.gov (United States)

    Yan, Lulu; Su, Jiaqi; Wang, Zhaoping; Yan, Xiwu; Yu, Ruihai

    2017-12-01

    Quantitative real-time polymerase chain reaction (qRT-PCR) is a rapid and reliable technique which has been widely used to quantifying gene transcripts (expression analysis). It is also employed for studying heterosis, hybridization breeding and hybrid tolerability of oysters, an ecologically and economically important taxonomic group. For these studies, selection of a suitable set of housekeeping genes as references is crucial for correct interpretation of qRT-PCR data. To identify suitable reference genes for oysters during low temperature and low salinity stresses, we analyzed twelve genes from the gill tissue of Crassostrea sikamea (SS), Crassostrea angulata (AA) and their hybrid (SA), which included three ribosomal genes, 28S ribosomal protein S5 ( RPS5), ribosomal protein L35 ( RPL35), and 60S ribosomal protein L29 ( RPL29); three structural genes, tubulin gamma ( TUBγ), annexin A6 and A7 ( AA6 and AA7); three metabolic pathway genes, ornithine decarboxylase ( OD), glyceraldehyde-3-phosphate dehydrogenase ( GAPDH) and glutathione S-transferase P1 ( GSP); two transcription factors, elongation factor 1 alpha and beta ( EF1α and EF1β); and one protein synthesis gene (ubiquitin ( UBQ). Primers specific for these genes were successfully developed for the three groups of oysters. Three different algorithms, geNorm, NormFinder and BestKeeper, were used to evaluate the expression stability of these candidate genes. BestKeeper program was found to be the most reliable. Based on our analysis, we found that the expression of RPL35 and EF1α was stable under low salinity stress, and the expression of OD, GAPDH and EF1α was stable under low temperature stress in hybrid (SA) oyster; the expression of RPS5 and GAPDH was stable under low salinity stress, and the expression of RPS5, UBQ, GAPDH was stable under low temperature stress in SS oyster; the expression of RPS5, GAPDH, EF1β and AA7 was stable under low salinity stress, and the expression of RPL35, EF1α, GAPDH

  16. Selection in the dopamine receptor 2 gene: a candidate SNP study

    Directory of Open Access Journals (Sweden)

    Tobias Göllner

    2015-08-01

    Full Text Available Dopamine is a major neurotransmitter in the human brain and is associated with various diseases. Schizophrenia, for example, is treated by blocking the dopamine receptors type 2. Shaner, Miller & Mintz (2004 stated that schizophrenia was the low fitness variant of a highly variable mental trait. We therefore explore whether the dopamine receptor 2 gene (DRD2 underwent any selection processes. We acquired genotype data of the 1,000 Genomes project (phase I, which contains 1,093 individuals from 14 populations. We included single nucleotide polymorphisms (SNPs with two minor allele frequencies (MAFs in the analysis: MAF over 0.05 and over 0.01. This is equivalent to 151 SNPs (MAF > 0.05 and 246 SNPs (MAF > 0.01 for DRD2. We used two different approaches (an outlier approach and a Bayesian approach to detect loci under selection. The combined results of both approaches yielded nine (MAF > 0.05 and two candidate SNPs (MAF > 0.01, under balancing selection. We also found weak signs for directional selection on DRD2, but in our opinion these were too weak to draw any final conclusions on directional selection in DRD2. All candidates for balancing selection are in the intronic region of the gene and only one (rs12574471 has been mentioned in the literature. Two of our candidate SNPs are located in specific regions of the gene: rs80215768 lies within a promoter flanking region and rs74751335 lies within a transcription factor binding site. We strongly encourage research on our candidate SNPs and their possible effects.

  17. Assessing the joint effect of population stratification and sample selection in studies of gene-gene (environment interactions

    Directory of Open Access Journals (Sweden)

    Cheng KF

    2012-01-01

    Full Text Available Abstract Background It is well known that the presence of population stratification (PS may cause the usual test in case-control studies to produce spurious gene-disease associations. However, the impact of the PS and sample selection (SS is less known. In this paper, we provide a systematic study of the joint effect of PS and SS under a more general risk model containing genetic and environmental factors. We provide simulation results to show the magnitude of the bias and its impact on type I error rate of the usual chi-square test under a wide range of PS level and selection bias. Results The biases to the estimation of main and interaction effect are quantified and then their bounds derived. The estimated bounds can be used to compute conservative p-values for the association test. If the conservative p-value is smaller than the significance level, we can safely claim that the association test is significant regardless of the presence of PS or not, or if there is any selection bias. We also identify conditions for the null bias. The bias depends on the allele frequencies, exposure rates, gene-environment odds ratios and disease risks across subpopulations and the sampling of the cases and controls. Conclusion Our results show that the bias cannot be ignored even the case and control data were matched in ethnicity. A real example is given to illustrate application of the conservative p-value. These results are useful to the genetic association studies of main and interaction effects.

  18. An extensive analysis of disease-gene associations using network integration and fast kernel-based gene prioritization methods

    Science.gov (United States)

    Valentini, Giorgio; Paccanaro, Alberto; Caniza, Horacio; Romero, Alfonso E.; Re, Matteo

    2014-01-01

    Objective In the context of “network medicine”, gene prioritization methods represent one of the main tools to discover candidate disease genes by exploiting the large amount of data covering different types of functional relationships between genes. Several works proposed to integrate multiple sources of data to improve disease gene prioritization, but to our knowledge no systematic studies focused on the quantitative evaluation of the impact of network integration on gene prioritization. In this paper, we aim at providing an extensive analysis of gene-disease associations not limited to genetic disorders, and a systematic comparison of different network integration methods for gene prioritization. Materials and methods We collected nine different functional networks representing different functional relationships between genes, and we combined them through both unweighted and weighted network integration methods. We then prioritized genes with respect to each of the considered 708 medical subject headings (MeSH) diseases by applying classical guilt-by-association, random walk and random walk with restart algorithms, and the recently proposed kernelized score functions. Results The results obtained with classical random walk algorithms and the best single network achieved an average area under the curve (AUC) across the 708 MeSH diseases of about 0.82, while kernelized score functions and network integration boosted the average AUC to about 0.89. Weighted integration, by exploiting the different “informativeness” embedded in different functional networks, outperforms unweighted integration at 0.01 significance level, according to the Wilcoxon signed rank sum test. For each MeSH disease we provide the top-ranked unannotated candidate genes, available for further bio-medical investigation. Conclusions Network integration is necessary to boost the performances of gene prioritization methods. Moreover the methods based on kernelized score functions can further

  19. Increasing cocoa butter-like lipid production of Saccharomyces cerevisiae by expression of selected cocoa genes

    DEFF Research Database (Denmark)

    Wei, Yongjun; Gossing, Michael; Bergenholm, David

    2017-01-01

    for CB biosynthesis from the cocoa genome using a phylogenetic analysis approach. By expressing the selected cocoa genes in S. cerevisiae, we successfully increased total fatty acid production, TAG production and CBL production in some S. cerevisiae strains. The relative CBL content in three yeast...... higher level of CBL compared with the control strain. In summary, CBL production by S. cerevisiae were increased through expressing selected cocoa genes potentially involved in CB biosynthesis.......Cocoa butter (CB) extracted from cocoa beans mainly consists of three different kinds of triacylglycerols (TAGs), 1,3-dipalmitoyl-2-oleoyl-glycerol (POP, C16:0-C18:1-C16:0), 1-palmitoyl-3-stearoyl-2-oleoyl-glycerol(POS,C16:0C18:1-C18:0) and 1,3-distearoyl-2-oleoyl-glycerol (SOS, C18:0-C18:1-C18...

  20. An Expression of Periodic Phenomena of Fashion on Sexual Selection Model with Conformity Genes and Memes

    Science.gov (United States)

    Mutoh, Atsuko; Tokuhara, Shinya; Kanoh, Masayoshi; Oboshi, Tamon; Kato, Shohei; Itoh, Hidenori

    It is generally thought that living things have trends in their preferences. The mechanism of occurrence of another trends in successive periods is concerned in their conformity. According to social impact theory, the minority is always exists in the group. There is a possibility that the minority make the transition to the majority by conforming agents. Because of agent's promotion of their conform actions, the majority can make the transition. We proposed an evolutionary model with both genes and memes, and elucidated the interaction between genes and memes on sexual selection. In this paper, we propose an agent model for sexual selection imported the concept of conformity. Using this model we try an environment where male agents and female agents are existed, we find that periodic phenomena of fashion are expressed. And we report the influence of conformity and differentiation on the transition of their preferences.

  1. Tagging of four Rf genes with selective genotyping analysis in rice (Oryza sativa L.

    Directory of Open Access Journals (Sweden)

    Yarahmadi Saeid

    2017-01-01

    Full Text Available Wild abortive type of cytoplasmic male sterility (WA-CMS is commercially used for hybrid rice seed production. The linked markers can be used for selection of plants with desirable traits. Tagging of Rf genes was carried out using recessive and dominant class analysis in a large F2 population from the cross IR58025A×IR42686R. Pollen fertility and seed setting were evaluated at the flowering and maturity stages, respectively. Forty-seven highly sterile and 23 fertile homozygous plants were selected from F2 population for molecular marker assay. Four Rf genes identified in a good restorer line with high-quality derived from a random mating composite population at the International Rice Research Institute (IRRI. The genetic distance from Rf3 locus with flanking markers RM443 and RM315 on chromosome 1 was 3.7 and 21.2 cM, respectively. RM258, RM591, RM271 and RM6737 on the long arm of chromosome 10 were linked with the Rf6 gene with distance of 7.4, 22.6, 6 and 2.9 cM, respectively. Rf6 was flanked by RM6737 and RM591. The Rf4 gene located on chromosome 7 was linked with RM6344 at a genetic distance of 10.6 cM. RM519 and RM7003 were linked with other Rf gene on chromosome 12 at a genetic distance of 8.5 and 20.8 cM, respectively. Closely linked markers identified in this study could be used for marker assisted selection in a hybrid rice breeding program. A new Rf locus on chromosome 12 that designated Rf7 was linked with RM7003 and RM519.

  2. Selection of Housekeeping Genes for Transgene Expression Analysis in Eucommia ulmoides Oliver Using Real-Time RT-PCR

    Directory of Open Access Journals (Sweden)

    Ren Chen

    2010-01-01

    Full Text Available In order to select appropriate housekeeping genes for accurate calibration of experimental variations in real-time (RT- PCR results in transgene expression analysis, particularly with respect to the influence of transgene on stability of endogenous housekeeping gene expression in transgenic plants, we outline a reliable strategy to identify the optimal housekeeping genes from a set of candidates by combining statistical analyses of their (RT- PCR amplification efficiency, gene expression stability, and transgene influences. We used the strategy to select two genes, ACTα and EF1α, from 10 candidate housekeeping genes, as the optimal housekeeping genes to evaluate transgenic Eucommia ulmoides Oliver root lines overexpressing IPPI or FPPS1 genes, which are involved in isoprenoid biosynthesis.

  3. Characterization of the bovine pregnancy-associated glycoprotein gene family – analysis of gene sequences, regulatory regions within the promoter and expression of selected genes

    Directory of Open Access Journals (Sweden)

    Walker Angela M

    2009-04-01

    Full Text Available Abstract Background The Pregnancy-associated glycoproteins (PAGs belong to a large family of aspartic peptidases expressed exclusively in the placenta of species in the Artiodactyla order. In cattle, the PAG gene family is comprised of at least 22 transcribed genes, as well as some variants. Phylogenetic analyses have shown that the PAG family segregates into 'ancient' and 'modern' groupings. Along with sequence differences between family members, there are clear distinctions in their spatio-temporal distribution and in their relative level of expression. In this report, 1 we performed an in silico analysis of the bovine genome to further characterize the PAG gene family, 2 we scrutinized proximal promoter sequences of the PAG genes to evaluate the evolution pressures operating on them and to identify putative regulatory regions, 3 we determined relative transcript abundance of selected PAGs during pregnancy and, 4 we performed preliminary characterization of the putative regulatory elements for one of the candidate PAGs, bovine (bo PAG-2. Results From our analysis of the bovine genome, we identified 18 distinct PAG genes and 14 pseudogenes. We observed that the first 500 base pairs upstream of the translational start site contained multiple regions that are conserved among all boPAGs. However, a preponderance of conserved regions, that harbor recognition sites for putative transcriptional factors (TFs, were found to be unique to the modern boPAG grouping, but not the ancient boPAGs. We gathered evidence by means of Q-PCR and screening of EST databases to show that boPAG-2 is the most abundant of all boPAG transcripts. Finally, we provided preliminary evidence for the role of ETS- and DDVL-related TFs in the regulation of the boPAG-2 gene. Conclusion PAGs represent a relatively large gene family in the bovine genome. The proximal promoter regions of these genes display differences in putative TF binding sites, likely contributing to observed

  4. 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.

  5. Whole-gene positive selection, elevated synonymous substitution rates, duplication, and indel evolution of the chloroplast clpP1 gene.

    Directory of Open Access Journals (Sweden)

    Per Erixon

    Full Text Available BACKGROUND: Synonymous DNA substitution rates in the plant chloroplast genome are generally relatively slow and lineage dependent. Non-synonymous rates are usually even slower due to purifying selection acting on the genes. Positive selection is expected to speed up non-synonymous substitution rates, whereas synonymous rates are expected to be unaffected. Until recently, positive selection has seldom been observed in chloroplast genes, and large-scale structural rearrangements leading to gene duplications are hitherto supposed to be rare. METHODOLOGY/PRINCIPLE FINDINGS: We found high substitution rates in the exons of the plastid clpP1 gene in Oenothera (the Evening Primrose family and three separate lineages in the tribe Sileneae (Caryophyllaceae, the Carnation family. Introns have been lost in some of the lineages, but where present, the intron sequences have substitution rates similar to those found in other introns of their genomes. The elevated substitution rates of clpP1 are associated with statistically significant whole-gene positive selection in three branches of the phylogeny. In two of the lineages we found multiple copies of the gene. Neighboring genes present in the duplicated fragments do not show signs of elevated substitution rates or positive selection. Although non-synonymous substitutions account for most of the increase in substitution rates, synonymous rates are also markedly elevated in some lineages. Whereas plant clpP1 genes experiencing negative (purifying selection are characterized by having very conserved lengths, genes under positive selection often have large insertions of more or less repetitive amino acid sequence motifs. CONCLUSIONS/SIGNIFICANCE: We found positive selection of the clpP1 gene in various plant lineages to correlated with repeated duplication of the clpP1 gene and surrounding regions, repetitive amino acid sequences, and increase in synonymous substitution rates. The present study sheds light on the

  6. Selective sweep on human amylase genes postdates the split with Neanderthals

    OpenAIRE

    Inchley, Charlotte E.; Larbey, Cynthia D. A.; Shwan, Nzar A. A.; Pagani, Luca; Saag, Lauri; Antão, Tiago; Jacobs, Guy; Hudjashov, Georgi; Metspalu, Ene; Mitt, Mario; Eichstaedt, Christina A.; Malyarchuk, Boris; Derenko, Miroslava; Wee, Joseph; Abdullah, Syafiq

    2016-01-01

    Humans have more copies of amylase genes than other primates. It is still poorly understood, however, when the copy number expansion occurred and whether its spread was enhanced by selection. Here we assess amylase copy numbers in a global sample of 480 high coverage genomes and find that regions flanking the amylase locus show notable depression of genetic diversity both in African and non-African populations. Analysis of genetic variation in these regions supports the model of an early sele...

  7. Transcriptome profile and unique genetic evolution of positively selected genes in yak lungs.

    Science.gov (United States)

    Lan, DaoLiang; Xiong, XianRong; Ji, WenHui; Li, Jian; Mipam, Tserang-Donko; Ai, Yi; Chai, ZhiXin

    2018-04-01

    The yak (Bos grunniens), which is a unique bovine breed that is distributed mainly in the Qinghai-Tibetan Plateau, is considered a good model for studying plateau adaptability in mammals. The lungs are important functional organs that enable animals to adapt to their external environment. However, the genetic mechanism underlying the adaptability of yak lungs to harsh plateau environments remains unknown. To explore the unique evolutionary process and genetic mechanism of yak adaptation to plateau environments, we performed transcriptome sequencing of yak and cattle (Bos taurus) lungs using RNA-Seq technology and a subsequent comparison analysis to identify the positively selected genes in the yak. After deep sequencing, a normal transcriptome profile of yak lung that containing a total of 16,815 expressed genes was obtained, and the characteristics of yak lungs transcriptome was described by functional analysis. Furthermore, Ka/Ks comparison statistics result showed that 39 strong positively selected genes are identified from yak lungs. Further GO and KEGG analysis was conducted for the functional annotation of these genes. The results of this study provide valuable data for further explorations of the unique evolutionary process of high-altitude hypoxia adaptation in yaks in the Tibetan Plateau and the genetic mechanism at the molecular level.

  8. Features of mechanical snubbers and the method of selection

    International Nuclear Information System (INIS)

    Sunakoda, Katsuaki

    1978-01-01

    In the oil snubbers used in the high radiation environment of nuclear power stations, gas generation from oil and the deterioration of rubber material for sealing occur due to radiation damage, therefore periodical inspection and replacement are required during operation. The mechanical snubbers developed as aseismatic supporters in place of oil snubbers have entered the stage of practical use, and are made by two companies in USA and a company in Japan. Their features as compared with oil snubbers are as follows. The cost and time required for the maintenance were made as small as possible because the increase of the service life of mechanical components can be expected. The temperature dependence of mechanical snubbers is small. The matters demanding attention in the maintenance are the secular change of lubricating oil and the effect of radiation, and the rust prevention of ball screw bearings. These problems are being studied by Power Reactor and Nuclear Fuel Development Corp. for the fast prototype reactor Monju. The structural feature is to convert the thrust movement of equipments and pipings due to thermal expansion and contraction or earthquakes into rotating motion, using ball screws. The features and the construction of SMS type mechanical snubbers, the test and inspection prior to their shipping, the method of selection, and the method of handling them in actual places are explained. (Kako, I.)

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

    Directory of Open Access Journals (Sweden)

    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

  10. Polymorphisms of Selected DNA Repair Genes and Lung Cancer in Chromium Exposure.

    Science.gov (United States)

    Halasova, E; Matakova, T; Skerenova, M; Krutakova, M; Slovakova, P; Dzian, A; Javorkova, S; Pec, M; Kypusova, K; Hamzik, J

    2016-01-01

    Chromium is a well-known mutagen and carcinogen involved in lung cancer development. DNA repair genes play an important role in the elimination of genetic changes caused by chromium exposure. In the present study, we investigated the polymorphisms of the following DNA repair genes: XRCC3, participating in the homologous recombination repair, and hMLH1 and hMSH2, functioning in the mismatch repair. We focused on the risk the polymorphisms present in the development of lung cancer regarding the exposure to chromium. We analyzed 106 individuals; 45 patients exposed to chromium with diagnosed lung cancer and 61 healthy controls. Genotypes were determined by a PCR-RFLP method. We unravelled a potential for increased risk of lung cancer development in the hMLH1 (rs1800734) AA genotype in the recessive model. In conclusion, gene polymorphisms in the DNA repair genes underscores the risk of lung cancer development in chromium exposed individuals.

  11. Differential gene expression and clonal selection during cellular transformation induced by adhesion deprivation

    Directory of Open Access Journals (Sweden)

    Kumar Mahesh J

    2010-12-01

    Full Text Available Abstract Background Anchorage independent growth is an important hallmark of oncogenic transformation. Previous studies have shown that when adhesion dependent fibroblasts were prevented from adhering to a substrate they underwent anoikis. In the present study we have demonstrated how anoikis resistant cells gain the transformation related properties with sequential selection of genes. We have proposed this process as a model system for selection of transformed cells from normal cells. Results This report demonstrates that some fibroblasts can survive during late stages of anoikis, at which time they exhibit transformation-associated properties such as in vitro colony formation in soft agar and in vivo subcutaneous tumour formation in nude mice. Cytogenetic characterisation of these cells revealed that they contained a t (2; 2 derivative chromosome and they have a selective survival advantage in non adherent conditions. Gene expression profile indicated that these cells over expressed genes related to hypoxia, glycolysis and tumor suppression/metastasis which could be helpful in their retaining a transformed phenotype. Conclusion Our results reveal some new links between anoikis and cell transformation and they provide a reproducible model system which can potentially be useful to study multistage cancer and to identify new targets for drug development.

  12. Selection shaped the evolution of mouse androgen-binding protein (ABP) function and promoted the duplication of Abp genes.

    Science.gov (United States)

    Karn, Robert C; Laukaitis, Christina M

    2014-08-01

    In the present article, we summarize two aspects of our work on mouse ABP (androgen-binding protein): (i) the sexual selection function producing incipient reinforcement on the European house mouse hybrid zone, and (ii) the mechanism behind the dramatic expansion of the Abp gene region in the mouse genome. Selection unifies these two components, although the ways in which selection has acted differ. At the functional level, strong positive selection has acted on key sites on the surface of one face of the ABP dimer, possibly to influence binding to a receptor. A different kind of selection has apparently driven the recent and rapid expansion of the gene region, probably by increasing the amount of Abp transcript, in one or both of two ways. We have shown previously that groups of Abp genes behave as LCRs (low-copy repeats), duplicating as relatively large blocks of genes by NAHR (non-allelic homologous recombination). The second type of selection involves the close link between the accumulation of L1 elements and the expansion of the Abp gene family by NAHR. It is probably predicated on an initial selection for increased transcription of existing Abp genes and/or an increase in Abp gene number providing more transcriptional sites. Either or both could increase initial transcript production, a quantitative change similar to increasing the volume of a radio transmission. In closing, we also provide a note on Abp gene nomenclature.

  13. Genealogy-based methods for inference of historical recombination and gene flow and their application in Saccharomyces cerevisiae.

    Science.gov (United States)

    Jenkins, Paul A; Song, Yun S; Brem, Rachel B

    2012-01-01

    Genetic exchange between isolated populations, or introgression between species, serves as a key source of novel genetic material on which natural selection can act. While detecting historical gene flow from DNA sequence data is of much interest, many existing methods can be limited by requirements for deep population genomic sampling. In this paper, we develop a scalable genealogy-based method to detect candidate signatures of gene flow into a given population when the source of the alleles is unknown. Our method does not require sequenced samples from the source population, provided that the alleles have not reached fixation in the sampled recipient population. The method utilizes recent advances in algorithms for the efficient reconstruction of ancestral recombination graphs, which encode genealogical histories of DNA sequence data at each site, and is capable of detecting the signatures of gene flow whose footprints are of length up to single genes. Further, we employ a theoretical framework based on coalescent theory to test for statistical significance of certain recombination patterns consistent with gene flow from divergent sources. Implementing these methods for application to whole-genome sequences of environmental yeast isolates, we illustrate the power of our approach to highlight loci with unusual recombination histories. By developing innovative theory and methods to analyze signatures of gene flow from population sequence data, our work establishes a foundation for the continued study of introgression and its evolutionary relevance.

  14. An extensive analysis of disease-gene associations using network integration and fast kernel-based gene prioritization methods.

    Science.gov (United States)

    Valentini, Giorgio; Paccanaro, Alberto; Caniza, Horacio; Romero, Alfonso E; Re, Matteo

    2014-06-01

    In the context of "network medicine", gene prioritization methods represent one of the main tools to discover candidate disease genes by exploiting the large amount of data covering different types of functional relationships between genes. Several works proposed to integrate multiple sources of data to improve disease gene prioritization, but to our knowledge no systematic studies focused on the quantitative evaluation of the impact of network integration on gene prioritization. In this paper, we aim at providing an extensive analysis of gene-disease associations not limited to genetic disorders, and a systematic comparison of different network integration methods for gene prioritization. We collected nine different functional networks representing different functional relationships between genes, and we combined them through both unweighted and weighted network integration methods. We then prioritized genes with respect to each of the considered 708 medical subject headings (MeSH) diseases by applying classical guilt-by-association, random walk and random walk with restart algorithms, and the recently proposed kernelized score functions. The results obtained with classical random walk algorithms and the best single network achieved an average area under the curve (AUC) across the 708 MeSH diseases of about 0.82, while kernelized score functions and network integration boosted the average AUC to about 0.89. Weighted integration, by exploiting the different "informativeness" embedded in different functional networks, outperforms unweighted integration at 0.01 significance level, according to the Wilcoxon signed rank sum test. For each MeSH disease we provide the top-ranked unannotated candidate genes, available for further bio-medical investigation. Network integration is necessary to boost the performances of gene prioritization methods. Moreover the methods based on kernelized score functions can further enhance disease gene ranking results, by adopting both

  15. Positive Selection on Hemagglutinin and Neuraminidase Genes of H1N1 Influenza Viruses

    LENUS (Irish Health Repository)

    Li, Wenfu

    2011-04-21

    Abstract Background Since its emergence in March 2009, the pandemic 2009 H1N1 influenza A virus has posed a serious threat to public health. To trace the evolutionary path of these new pathogens, we performed a selection-pressure analysis of a large number of hemagglutinin (HA) and neuraminidase (NA) gene sequences of H1N1 influenza viruses from different hosts. Results Phylogenetic analysis revealed that both HA and NA genes have evolved into five distinct clusters, with further analyses indicating that the pandemic 2009 strains have experienced the strongest positive selection. We also found evidence of strong selection acting on the seasonal human H1N1 isolates. However, swine viruses from North America and Eurasia were under weak positive selection, while there was no significant evidence of positive selection acting on the avian isolates. A site-by-site analysis revealed that the positively selected sites were located in both of the cleaved products of HA (HA1 and HA2), as well as NA. In addition, the pandemic 2009 strains were subject to differential selection pressures compared to seasonal human, North American swine and Eurasian swine H1N1 viruses. Conclusions Most of these positively and\\/or differentially selected sites were situated in the B-cell and\\/or T-cell antigenic regions, suggesting that selection at these sites might be responsible for the antigenic variation of the viruses. Moreover, some sites were also associated with glycosylation and receptor-binding ability. Thus, selection at these positions might have helped the pandemic 2009 H1N1 viruses to adapt to the new hosts after they were introduced from pigs to humans. Positive selection on position 274 of NA protein, associated with drug resistance, might account for the prevalence of drug-resistant variants of seasonal human H1N1 influenza viruses, but there was no evidence that positive selection was responsible for the spread of the drug resistance of the pandemic H1N1 strains.

  16. Using Variable Precision Rough Set for Selection and Classification of Biological Knowledge Integrated in DNA Gene Expression

    Directory of Open Access Journals (Sweden)

    Calvo-Dmgz D.

    2012-12-01

    Full Text Available DNA microarrays have contributed to the exponential growth of genomic and experimental data in the last decade. This large amount of gene expression data has been used by researchers seeking diagnosis of diseases like cancer using machine learning methods. In turn, explicit biological knowledge about gene functions has also grown tremendously over the last decade. This work integrates explicit biological knowledge, provided as gene sets, into the classication process by means of Variable Precision Rough Set Theory (VPRS. The proposed model is able to highlight which part of the provided biological knowledge has been important for classification. This paper presents a novel model for microarray data classification which is able to incorporate prior biological knowledge in the form of gene sets. Based on this knowledge, we transform the input microarray data into supergenes, and then we apply rough set theory to select the most promising supergenes and to derive a set of easy interpretable classification rules. The proposed model is evaluated over three breast cancer microarrays datasets obtaining successful results compared to classical classification techniques. The experimental results shows that there are not significat differences between our model and classical techniques but it is able to provide a biological-interpretable explanation of how it classifies new samples.

  17. Will genomic selection be a practical method for plant breeding?

    OpenAIRE

    Nakaya, Akihiro; Isobe, Sachiko N.

    2012-01-01

    Background Genomic selection or genome-wide selection (GS) has been highlighted as a new approach for marker-assisted selection (MAS) in recent years. GS is a form of MAS that selects favourable individuals based on genomic estimated breeding values. Previous studies have suggested the utility of GS, especially for capturing small-effect quantitative trait loci, but GS has not become a popular methodology in the field of plant breeding, possibly because there is insufficient information avail...

  18. Positive selection within the Schizophrenia-associated GABA(A receptor beta(2 gene.

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    Wing-Sze Lo

    Full Text Available The gamma-aminobutyric acid type-A (GABA(A receptor plays a major role in inhibitory neurotransmissions. Intronic SNPs and haplotypes in GABRB2, the gene for GABA(A receptor beta(2 subunit, are associated with schizophrenia and correlated with the expression of two alternatively spliced beta(2 isoforms. In the present study, using chimpanzee as an ancestral reference, high frequencies were observed for the derived (D alleles of the four SNPs rs6556547, rs187269, rs1816071 and rs1816072 in GABRB2, suggesting the occurrence of positive selection for these derived alleles. Coalescence-based simulation showed that the population frequency spectra and the frequencies of H56, the haplotype having all four D alleles, significantly deviated from neutral-evolution expectation in various demographic models. Haplotypes containing the derived allele of rs1816072 displayed significantly less diversity compared to haplotypes containing its ancestral allele, further supporting positive selection. The variations in DD-genotype frequencies in five human populations provided a snapshot of the evolutionary history, which suggested that the positive selections of the D alleles are recent and likely ongoing. The divergence between the DD-genotype profiles of schizophrenic and control samples pointed to the schizophrenia-relevance of positive selections, with the schizophrenic samples showing weakened selections compared to the controls. These DD-genotypes were previously found to increase the expression of beta(2, especially its long isoform. Electrophysiological analysis showed that this long beta(2 isoform favored by the positive selections is more sensitive than the short isoform to the inhibition of GABA(A receptor function by energy depletion. These findings represent the first demonstration of positive selection in a schizophrenia-associated gene.

  19. Estimation of genetic variability and selection response for clutch length in dwarf brown-egg layers carrying or not the naked neck gene

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    Tixier-Boichard Michèle

    2003-03-01

    Full Text Available Abstract In order to investigate the possibility of using the dwarf gene for egg production, two dwarf brown-egg laying lines were selected for 16 generations on average clutch length; one line (L1 was normally feathered and the other (L2 was homozygous for the naked neck gene NA. A control line from the same base population, dwarf and segregating for the NA gene, was maintained during the selection experiment under random mating. The average clutch length was normalized using a Box-Cox transformation. Genetic variability and selection response were estimated either with the mixed model methodology, or with the classical methods for calculating genetic gain, as the deviation from the control line, and the realized heritability, as the ratio of the selection response on cumulative selection differentials. Heritability of average clutch length was estimated to be 0.42 ± 0.02, with a multiple trait animal model, whereas the estimates of the realized heritability were lower, being 0.28 and 0.22 in lines L1 and L2, respectively. REML estimates of heritability were found to decline with generations of selection, suggesting a departure from the infinitesimal model, either because a limited number of genes was involved, or their frequencies were changed. The yearly genetic gains in average clutch length, after normalization, were estimated to be 0.37 ± 0.02 and 0.33 ± 0.04 with the classical methods, 0.46 ± 0.02 and 0.43 ± 0.01 with animal model methodology, for lines L1 and L2 respectively, which represented about 30% of the genetic standard deviation on the transformed scale. Selection response appeared to be faster in line L2, homozygous for the NA gene, but the final cumulated selection response for clutch length was not different between the L1 and L2 lines at generation 16.

  20. In vitro selection of mutants: Inducible gene regulation for salt tolerance

    International Nuclear Information System (INIS)

    Winicov, I.; Bastola, D.R.; Deutch, C.E.; Pethe, V.V.; Petrusa, L.

    2001-01-01

    Regulation of differentially expressed genes in plants may be involved in inducing tolerance to stress. Isogenic salt-sensitive and salt-tolerant alfalfa lines were investigated for molecular differences in their response to salt. The genes, which are differentially induced by salt in the salt-tolerant alfalfa cells and are also regulated by salt at the whole plant level, were cloned. Both transcriptional and post- transcriptional mechanisms influenced salt-induced product accumulation in the salt-tolerant alfalfa. The salt-tolerant plants doubled proline concentration rapidly in roots, while salt-sensitive plants showed a delayed response. To understand the regulatory system in the salt-tolerant alfalfa, two genes that are expressed in roots were studied. Alfin1 encodes a zinc-finger type putative DNA transcription factor conserved in alfalfa, rice and Arabidopsis, and MsPRP2 encodes a protein that serves as a cell wall- membrane linker in roots. Recombinant Alfin1 protein was selected, amplified, cloned and its consensus sequence was identified. The recombinant Alfin1 also bound specifically to fragments of the MsPRP2 promoter in vitro, containing the Alfin1 binding consensus sequence. The results show unambiguously binding specificity of Alfin1 DNA, supporting its role in gene regulation. Alfin1 function was tested in transformed alfalfa in vivo by over-expressing Alfin1 from 35S CaMV promoter. The transgenic plants appeared normal. However, plants harboring the anti-sense construct did not grow well in soil, indicating that Alfin1 expression was essential. Alfin1 over-expression in transgenic alfalfa led to enhanced levels of MsPRP2 transcript accumulation, demonstrating that Alfin1 functioned in vivo in gene regulation. Since MsPRP2 gene is also induced by salt, it is likely that Alfin1 is an important transcription factor for gene regulation in salt-tolerant alfalfa, and an excellent target for manipulation to improve salt tolerance. (author)

  1. Selection and Validation of Reference Genes for qRT-PCR Expression Analysis of Candidate Genes Involved in Olfactory Communication in the Butterfly Bicyclus anynana

    OpenAIRE

    Arun, Alok; Bauml?, V?ronique; Amelot, Ga?l; Nieberding, Caroline M.

    2015-01-01

    Real-time quantitative reverse transcription PCR (qRT-PCR) is a technique widely used to quantify the transcriptional expression level of candidate genes. qRT-PCR requires the selection of one or several suitable reference genes, whose expression profiles remain stable across conditions, to normalize the qRT-PCR expression profiles of candidate genes. Although several butterfly species (Lepidoptera) have become important models in molecular evolutionary ecology, so far no study aimed at ident...

  2. The importance of the selection of appropriate reference genes for gene expression profiling in adrenal medulla or sympathetic ganglia of spontaneously hypertensive rat

    Czech Academy of Sciences Publication Activity Database

    Vavřínová, Anna; Behuliak, Michal; Zicha, Josef

    2016-01-01

    Roč. 65, č. 3 (2016), s. 401-411 ISSN 0862-8408 R&D Projects: GA ČR(CZ) GP14-16225P Institutional support: RVO:67985823 Keywords : adrenal medulla * gene expression profiling * reference gene selection * sympathetic nervous system Subject RIV: FA - Cardiovascular Diseases incl. Cardiotharic Surgery Impact factor: 1.461, year: 2016

  3. Red Queen Processes Drive Positive Selection on Major Histocompatibility Complex (MHC Genes.

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    Maciej Jan Ejsmond

    2015-11-01

    Full Text Available Major Histocompatibility Complex (MHC genes code for proteins involved in the incitation of the adaptive immune response in vertebrates, which is achieved through binding oligopeptides (antigens of pathogenic origin. Across vertebrate species, substitutions of amino acids at sites responsible for the specificity of antigen binding (ABS are positively selected. This is attributed to pathogen-driven balancing selection, which is also thought to maintain the high polymorphism of MHC genes, and to cause the sharing of allelic lineages between species. However, the nature of this selection remains controversial. We used individual-based computer simulations to investigate the roles of two phenomena capable of maintaining MHC polymorphism: heterozygote advantage and host-pathogen arms race (Red Queen process. Our simulations revealed that levels of MHC polymorphism were high and driven mostly by the Red Queen process at a high pathogen mutation rate, but were low and driven mostly by heterozygote advantage when the pathogen mutation rate was low. We found that novel mutations at ABSs are strongly favored by the Red Queen process, but not by heterozygote advantage, regardless of the pathogen mutation rate. However, while the strong advantage of novel alleles increased the allele turnover rate, under a high pathogen mutation rate, allelic lineages persisted for a comparable length of time under Red Queen and under heterozygote advantage. Thus, when pathogens evolve quickly, the Red Queen is capable of explaining both positive selection and long coalescence times, but the tension between the novel allele advantage and persistence of alleles deserves further investigation.

  4. Selection and validation of reference genes for gene expression analysis in switchgrass (Panicum virgatum using quantitative real-time RT-PCR.

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    Jacinta Gimeno

    Full Text Available Switchgrass (Panicum virgatum has received a lot of attention as a forage and bioenergy crop during the past few years. Gene expression studies are in progress to improve new traits and develop new cultivars. Quantitative real time PCR (qRT-PCR has emerged as an important technique to study gene expression analysis. For accurate and reliable results, normalization of data with reference genes is essential. In this work, we evaluate the stability of expression of genes to use as reference for qRT-PCR in the grass P. virgatum. Eleven candidate reference genes, including eEF-1α, UBQ6, ACT12, TUB6, eIF-4a, GAPDH, SAMDC, TUA6, CYP5, U2AF, and FTSH4, were validated for qRT-PCR normalization in different plant tissues and under different stress conditions. The expression stability of these genes was verified by the use of two distinct algorithms, geNorm and NormFinder. Differences were observed after comparison of the ranking of the candidate reference genes identified by both programs but eEF-1α, eIF-4a, CYP5 and U2AF are ranked as the most stable genes in the samples sets under study. Both programs discard the use of SAMDC and TUA6 for normalization. Validation of the reference genes proposed by geNorm and NormFinder were performed by normalization of transcript abundance of a group of target genes in different samples. Results show similar expression patterns when the best reference genes selected by both programs were used but differences were detected in the transcript abundance of the target genes. Based on the above research, we recommend the use of different statistical algorithms to identify the best reference genes for expression data normalization. The best genes selected in this study will help to improve the quality of gene expression data in a wide variety of samples in switchgrass.

  5. Methods for transient assay of gene function in floral tissues

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    Pathirana Nilangani N

    2007-01-01

    Full Text Available Abstract Background There is considerable interest in rapid assays or screening systems for assigning gene function. However, analysis of gene function in the flowers of some species is restricted due to the difficulty of producing stably transformed transgenic plants. As a result, experimental approaches based on transient gene expression assays are frequently used. Biolistics has long been used for transient over-expression of genes of interest, but has not been exploited for gene silencing studies. Agrobacterium-infiltration has also been used, but the focus primarily has been on the transient transformation of leaf tissue. Results Two constructs, one expressing an inverted repeat of the Antirrhinum majus (Antirrhinum chalcone synthase gene (CHS and the other an inverted repeat of the Antirrhinum transcription factor gene Rosea1, were shown to effectively induce CHS and Rosea1 gene silencing, respectively, when introduced biolistically into petal tissue of Antirrhinum flowers developing in vitro. A high-throughput vector expressing the Antirrhinum CHS gene attached to an inverted repeat of the nos terminator was also shown to be effective. Silencing spread systemically to create large zones of petal tissue lacking pigmentation, with transmission of the silenced state spreading both laterally within the affected epidermal cell layer and into lower cell layers, including the epidermis of the other petal surface. Transient Agrobacterium-mediated transformation of petal tissue of tobacco and petunia flowers in situ or detached was also achieved, using expression of the reporter genes GUS and GFP to visualise transgene expression. Conclusion We demonstrate the feasibility of using biolistics-based transient RNAi, and transient transformation of petal tissue via Agrobacterium infiltration to study gene function in petals. We have also produced a vector for high throughput gene silencing studies, incorporating the option of using T-A cloning to

  6. Selective Inhibition of Histone Deacetylation in Melanoma Increases Targeted Gene Delivery by a Bacteriophage Viral Vector

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    Samuel Campbell

    2018-04-01

    Full Text Available The previously developed adeno-associated virus/phage (AAVP vector, a hybrid between M13 bacteriophage (phage viruses that infect bacteria only and human Adeno-Associated Virus (AAV, is a promising tool in targeted gene therapy against cancer. AAVP can be administered systemically and made tissue specific through the use of ligand-directed targeting. Cancer cells and tumor-associated blood vessels overexpress the αν integrin receptors, which are involved in tumor angiogenesis and tumor invasion. AAVP is targeted to these integrins via a double cyclic RGD4C ligand displayed on the phage capsid. Nevertheless, there remain significant host-defense hurdles to the use of AAVP in targeted gene delivery and subsequently in gene therapy. We previously reported that histone deacetylation in cancer constitutes a barrier to AAVP. Herein, to improve AAVP-mediated gene delivery to cancer cells, we combined the vector with selective adjuvant chemicals that inhibit specific histone deacetylases (HDAC. We examined the effects of the HDAC inhibitor C1A that mainly targets HDAC6 and compared this to sodium butyrate, a pan-HDAC inhibitor with broad spectrum HDAC inhibition. We tested the effects on melanoma, known for HDAC6 up-regulation, and compared this side by side with a normal human kidney HEK293 cell line. Varying concentrations were tested to determine cytotoxic levels as well as effects on AAVP gene delivery. We report that the HDAC inhibitor C1A increased AAVP-mediated transgene expression by up to ~9-fold. These findings indicate that selective HDAC inhibition is a promising adjuvant treatment for increasing the therapeutic value of AAVP.

  7. Gateway binary vectors with the bialaphos resistance gene, bar, as a selection marker for plant transformation.

    Science.gov (United States)

    Nakamura, Shinya; Mano, Shoji; Tanaka, Yuji; Ohnishi, Masato; Nakamori, Chihiro; Araki, Masami; Niwa, Tomoko; Nishimura, Mikio; Kaminaka, Hironori; Nakagawa, Tsuyoshi; Sato, Yutaka; Ishiguro, Sumie

    2010-01-01

    We constructed two series of Gateway binary vectors, pGWBs and R4pGWBs, possessing the bialaphos resistance gene (bar) as a selection marker for plant transformation. The reporters and tags employed in this system are sGFP, GUS, LUC, EYFP, ECFP, G3GFP, mRFP, TagRFP, 6xHis, FLAG, 3xHA, 4xMyc, 10xMyc, GST, T7 and TAP. Selection of Arabidopsis transformants with BASTA was successfully carried out using both plate-grown and soil-grown seedlings. Transformed rice calli and suspension-cultured tobacco cells were selected on plates containing BASTA or glufosinate-ammonium. These vectors are compatible with existing pGWB and R4pGWB vectors carrying kanamycin and hygromycin B resistance.

  8. GAIN RATIO BASED FEATURE SELECTION METHOD FOR PRIVACY PRESERVATION

    Directory of Open Access Journals (Sweden)

    R. Praveena Priyadarsini

    2011-04-01

    Full Text Available Privacy-preservation is a step in data mining that tries to safeguard sensitive information from unsanctioned disclosure and hence protecting individual data records and their privacy. There are various privacy preservation techniques like k-anonymity, l-diversity and t-closeness and data perturbation. In this paper k-anonymity privacy protection technique is applied to high dimensional datasets like adult and census. since, both the data sets are high dimensional, feature subset selection method like Gain Ratio is applied and the attributes of the datasets are ranked and low ranking attributes are filtered to form new reduced data subsets. K-anonymization privacy preservation technique is then applied on reduced datasets. The accuracy of the privacy preserved reduced datasets and the original datasets are compared for their accuracy on the two functionalities of data mining namely classification and clustering using naïve Bayesian and k-means algorithm respectively. Experimental results show that classification and clustering accuracy are comparatively the same for reduced k-anonym zed datasets and the original data sets.

  9. Utilization of Selected Data Mining Methods for Communication Network Analysis

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    V. Ondryhal

    2011-06-01

    Full Text Available The aim of the project was to analyze the behavior of military communication networks based on work with real data collected continuously since 2005. With regard to the nature and amount of the data, data mining methods were selected for the purpose of analyses and experiments. The quality of real data is often insufficient for an immediate analysis. The article presents the data cleaning operations which have been carried out with the aim to improve the input data sample to obtain reliable models. Gradually, by means of properly chosen SW, network models were developed to verify generally valid patterns of network behavior as a bulk service. Furthermore, unlike the commercially available communication networks simulators, the models designed allowed us to capture nonstandard models of network behavior under an increased load, verify the correct sizing of the network to the increased load, and thus test its reliability. Finally, based on previous experience, the models enabled us to predict emergency situations with a reasonable accuracy.

  10. The Choice Method of Selected Material has influence single evaporation flash method

    International Nuclear Information System (INIS)

    Sunaryo, Geni Rina; Sumijanto; Nurul L, Siti

    2000-01-01

    The final objective of this research is to design the mini scale of desalination installation. It has been started from 1997/1998 and has been doing for this 3 years. Where the study on the assessment of various desalination system has been done in the first year and thermodynamic in the second year. In this third year, literatully study on material resistance from outside pressure has been done. The number of pressure for single evaporator flashing method is mainly depend on the temperature that applied in that system. In this paper, the configuration stage, the choice method of selecting material for main evaporator vessel, tube, tube plates, water boxes, pipework, and valves for multistage flash distillation will be described. The choice of selecting material for MSF is base on economical consideration, cheap, high resistance and easy to be maintained

  11. Gene duplication, loss and selection in the evolution of saxitoxin biosynthesis in alveolates.

    Science.gov (United States)

    Murray, Shauna A; Diwan, Rutuja; Orr, Russell J S; Kohli, Gurjeet S; John, Uwe

    2015-11-01

    A group of marine dinoflagellates (Alveolata, Eukaryota), consisting of ∼10 species of the genus Alexandrium, Gymnodinium catenatum and Pyrodinium bahamense, produce the toxin saxitoxin and its analogues (STX), which can accumulate in shellfish, leading to ecosystem and human health impacts. The genes, sxt, putatively involved in STX biosynthesis, have recently been identified, however, the evolution of these genes within dinoflagellates is not clear. There are two reasons for this: uncertainty over the phylogeny of dinoflagellates; and that the sxt genes of many species of Alexandrium and other dinoflagellate genera are not known. Here, we determined the phylogeny of STX-producing and other dinoflagellates based on a concatenated eight-gene alignment. We determined the presence, diversity and phylogeny of sxtA, domains A1 and A4 and sxtG in 52 strains of Alexandrium, and a further 43 species of dinoflagellates and thirteen other alveolates. We confirmed the presence and high sequence conservation of sxtA, domain A4, in 40 strains (35 Alexandrium, 1 Pyrodinium, 4 Gymnodinium) of 8 species of STX-producing dinoflagellates, and absence from non-producing species. We found three paralogs of sxtA, domain A1, and a widespread distribution of sxtA1 in non-STX producing dinoflagellates, indicating duplication events in the evolution of this gene. One paralog, clade 2, of sxtA1 may be particularly related to STX biosynthesis. Similarly, sxtG appears to be generally restricted to STX-producing species, while three amidinotransferase gene paralogs were found in dinoflagellates. We investigated the role of positive (diversifying) selection following duplication in sxtA1 and sxtG, and found negative selection in clades of sxtG and sxtA1, clade 2, suggesting they were functionally constrained. Significant episodic diversifying selection was found in some strains in clade 3 of sxtA1, a clade that may not be involved in STX biosynthesis, indicating pressure for diversification

  12. A Robust and Versatile Method of Combinatorial Chemical Synthesis of Gene Libraries via Hierarchical Assembly of Partially Randomized Modules

    Science.gov (United States)

    Popova, Blagovesta; Schubert, Steffen; Bulla, Ingo; Buchwald, Daniela; Kramer, Wilfried

    2015-01-01

    A major challenge in gene library generation is to guarantee a large functional size and diversity that significantly increases the chances of selecting different functional protein variants. The use of trinucleotides mixtures for controlled randomization results in superior library diversity and offers the ability to specify the type and distribution of the amino acids at each position. Here we describe the generation of a high diversity gene library using tHisF of the hyperthermophile Thermotoga maritima as a scaffold. Combining various rational criteria with contingency, we targeted 26 selected codons of the thisF gene sequence for randomization at a controlled level. We have developed a novel method of creating full-length gene libraries by combinatorial assembly of smaller sub-libraries. Full-length libraries of high diversity can easily be assembled on demand from smaller and much less diverse sub-libraries, which circumvent the notoriously troublesome long-term archivation and repeated proliferation of high diversity ensembles of phages or plasmids. We developed a generally applicable software tool for sequence analysis of mutated gene sequences that provides efficient assistance for analysis of library diversity. Finally, practical utility of the library was demonstrated in principle by assessment of the conformational stability of library members and isolating protein variants with HisF activity from it. Our approach integrates a number of features of nucleic acids synthetic chemistry, biochemistry and molecular genetics to a coherent, flexible and robust method of combinatorial gene synthesis. PMID:26355961

  13. Positive selection and ancient duplications in the evolution of class B floral homeotic genes of orchids and grasses

    Directory of Open Access Journals (Sweden)

    Koch Marcus A

    2009-04-01

    Full Text Available Abstract Background Positive selection is recognized as the prevalence of nonsynonymous over synonymous substitutions in a gene. Models of the functional evolution of duplicated genes consider neofunctionalization as key to the retention of paralogues. For instance, duplicate transcription factors are specifically retained in plant and animal genomes and both positive selection and transcriptional divergence appear to have played a role in their diversification. However, the relative impact of these two factors has not been systematically evaluated. Class B MADS-box genes, comprising DEF-like and GLO-like genes, encode developmental transcription factors essential for establishment of perianth and male organ identity in the flowers of angiosperms. Here, we contrast the role of positive selection and the known divergence in expression patterns of genes encoding class B-like MADS-box transcription factors from monocots, with emphasis on the family Orchidaceae and the order Poales. Although in the monocots these two groups are highly diverse and have a strongly canalized floral morphology, there is no information on the role of positive selection in the evolution of their distinctive flower morphologies. Published research shows that in Poales, class B-like genes are expressed in stamens and in lodicules, the perianth organs whose identity might also be specified by class B-like genes, like the identity of the inner tepals of their lily-like relatives. In orchids, however, the number and pattern of expression of class B-like genes have greatly diverged. Results The DEF-like genes from Orchidaceae form four well-supported, ancient clades of orthologues. In contrast, orchid GLO-like genes form a single clade of ancient orthologues and recent paralogues. DEF-like genes from orchid clade 2 (OMADS3-like genes are under less stringent purifying selection than the other orchid DEF-like and GLO-like genes. In comparison with orchids, purifying selection

  14. Selectable genes for transformation of the fungal plant pathogen Glomerella cingulata f. sp. phaseoli (Colletotrichum lindemuthianum).

    Science.gov (United States)

    Rodriguez, R J; Yoder, O C

    1987-01-01

    Glomerella cingulata f. sp. phaseoli (Gcp) was transformed using either of two selectable markers: the amdS + gene of Aspergillus nidulans, which encodes acetamidase and permits growth on acetamide as the sole nitrogen source and the hygBR gene of Escherichia coli which encodes hygromycin B (Hy) phosphotransferase and permits growth in the presence of the antibiotic Hy. The amdS+ gene functioned in Gcp under control of A. nidulans regulatory signals and hygBR was expressed after fusion to a promoter from Cochliobolus heterostrophus, another filamentous ascomycete. Protoplasts to be transformed were generated with the digestive enzyme complex Novozym 234 and then were exposed to plasmid DNA in the presence of 10 mM CaCl2 and polyethylene glycol. Transformation occurred by integration of single or multiple copies of either the amdS+ or hygBR plasmid into the fungal genome. There was no evidence of autonomous plasmid replication. Transformants were mitotically stable on selective and nonselective media. However, transforming DNA in hygBR transformants was observed to occasionally rearrange during nonselective growth, resulting in fewer copies of the plasmid per genome. These transformants were capable of infecting bean (Phaseolus vulgaris), the Gcp host plant, and after recovery from infected tissue were found to have retained both the transforming DNA unrearranged in their genomes and the Hy resistance phenotype. All single-conidial cultures derived from both amdS+ and hygBR transformants had the transplanted phenotype, suggesting that transformants were homokaryons.

  15. Signature of balancing selection at the MC1R gene in Kunming dog populations.

    Directory of Open Access Journals (Sweden)

    Guo-dong Wang

    Full Text Available Coat color in dog breeds is an excellent character for revealing the power of artificial selection, as it is extremely diverse and likely the result of recent domestication. Coat color is generated by melanocytes, which synthesize pheomelanin (a red or yellow pigment or eumelanin (a black or brown pigment through the pigment type-switching pathway, and is regulated by three genes in dogs: MC1R (melanocortin receptor 1, CBD103 (β-defensin 103, and ASIP (agouti-signaling protein precursor. The genotypes of these three gene loci in dog breeds are associated with coat color pattern. Here, we resequenced these three gene loci in two Kunming dog populations and analyzed these sequences using population genetic approaches to identify evolutionary patterns that have occurred at these loci during the recent domestication and breeding of the Kunming dog. The analysis showed that MC1R undergoes balancing selection in both Kunming dog populations, and that the Fst value for MC1R indicates significant genetic differentiation across the two populations. In contrast, similar results were not observed for CBD103 or ASIP. These results suggest that high heterozygosity and allelic differences at the MC1R locus may explain both the mixed color coat, of yellow and black, and the difference in coat colors in both Kunming dog populations.

  16. LGscore: A method to identify disease-related genes using biological literature and Google data.

    Science.gov (United States)

    Kim, Jeongwoo; Kim, Hyunjin; Yoon, Youngmi; Park, Sanghyun

    2015-04-01

    Since the genome project in 1990s, a number of studies associated with genes have been conducted and researchers have confirmed that genes are involved in disease. For this reason, the identification of the relationships between diseases and genes is important in biology. We propose a method called LGscore, which identifies disease-related genes using Google data and literature data. To implement this method, first, we construct a disease-related gene network using text-mining results. We then extract gene-gene interactions based on co-occurrences in abstract data obtained from PubMed, and calculate the weights of edges in the gene network by means of Z-scoring. The weights contain two values: the frequency and the Google search results. The frequency value is extracted from literature data, and the Google search result is obtained using Google. We assign a score to each gene through a network analysis. We assume that genes with a large number of links and numerous Google search results and frequency values are more likely to be involved in disease. For validation, we investigated the top 20 inferred genes for five different diseases using answer sets. The answer sets comprised six databases that contain information on disease-gene relationships. We identified a significant number of disease-related genes as well as candidate genes for Alzheimer's disease, diabetes, colon cancer, lung cancer, and prostate cancer. Our method was up to 40% more accurate than existing methods. Copyright © 2015 Elsevier Inc. All rights reserved.

  17. A Novel ‘Gene Insertion/Marker Out’ (GIMO) Method for Transgene Expression and Gene Complementation in Rodent Malaria Parasites

    Science.gov (United States)

    Sajid, Mohammed; Chevalley-Maurel, Séverine; Ramesar, Jai; Klop, Onny; Franke-Fayard, Blandine M. D.; Janse, Chris J.; Khan, Shahid M.

    2011-01-01

    Research on the biology of malaria parasites has greatly benefited from the application of reverse genetic technologies, in particular through the analysis of gene deletion mutants and studies on transgenic parasites that express heterologous or mutated proteins. However, transfection in Plasmodium is limited by the paucity of drug-selectable markers that hampers subsequent genetic modification of the same mutant. We report the development of a novel ‘gene insertion/marker out’ (GIMO) method for two rodent malaria parasites, which uses negative selection to rapidly generate transgenic mutants ready for subsequent modifications. We have created reference mother lines for both P. berghei ANKA and P. yoelii 17XNL that serve as recipient parasites for GIMO-transfection. Compared to existing protocols GIMO-transfection greatly simplifies and speeds up the generation of mutants expressing heterologous proteins, free of drug-resistance genes, and requires far fewer laboratory animals. In addition we demonstrate that GIMO-transfection is also a simple and fast method for genetic complementation of mutants with a gene deletion or mutation. The implementation of GIMO-transfection procedures should greatly enhance Plasmodium reverse-genetic research. PMID:22216235

  18. [Gene Expression Profile of Apoptosis in Leukemia Cells Induced by Hsp90 Selective inhibitor 17-AAG].

    Science.gov (United States)

    Wang, Na-Na; Li, Zhi-Heng; Tao, Yan-Fang; Xu, Li-Xiao; Pan, Jian; Hu, Shao-Yan

    2016-06-01

    To investigate the apoptotic effects of Hsp90 selective inhibitor 17-AAG on human leukemia HL-60 and NB4 cells and analyse its possible mechanism. CCK-8 assay was used to quantify the growth inhibition of cells after exposure to 17-AAG for 24 hours. Flow cytometrve with annexin V/propidium iodide staining was used to detect apoptosis of leukemia cells. Then Western blot was used to detect the activation of apoptosis related protein caspase-3 and PARP level. Gene expression profile of NB4 cells treated with 17-AAG was analyzed with real-time PCR arrays. The inhibition of leukemia cell proliferation displayed a dose-dependent manner. Annexin V assay, cell cycle analysis and activation of PARP demonstrate that 17-AAG induced apoptosis leukemia cells. Real-time PCR array analysis showed that expression of 56 genes significantly up-regulated and expression of 23 genes were significantly down-regulated after 17-AAG treatment. The 17-AAG can inhibit the proliferation and induce the apoptosis of leukemia cells. After leukemia cells are treated with 17-AAG, the significant changes of apoptosis-related genes occured, and the cell apoptosis occurs via activating apoptosis related signaling pathway.

  19. Selection of the signal synchronization method in software GPS receivers

    Directory of Open Access Journals (Sweden)

    Vlada S. Sokolović

    2011-04-01

    Full Text Available Introduction This paper presents a critical analysis of the signal processing flow carried out in a software GPS receiver and a critical comparison of different architectures for signal processing within the GPS receiver. A model of software receivers is shown. Based on the displayed model, a receiver has been realized in the MATLAB software package, in which the simulations of signal processing were carried out. The aim of this paper is to demonstrate the advantages and disadvantages of different methods of the synchronization of signals in the receiver, and to propose a solution acceptable for possible implementation. The signal processing flow was observed from the input circuit to the extraction of the bits of the navigation message. The entire signal processing was performed on the L1 signal and the data collected by the input circuit SE4110. A radio signal from the satellite was accepted with the input circuit, filtered and translated into a digital form. The input circuit ends with the hardware of the receiver. A digital signal from the input circuit is brought into the PC Pentium 4 (AMD 3000 + where the receiver is realized in Matlab. Model of software GPS receiver The first level of processing is signal acquisition. Signal acquisition was realized using the cyclic convolution. The acquisition process was carried out by measuring signals from satellites, and these parameters are passed to the next level of processing. The next level was done by monitoring the synchronization signal and extracting the navigation message bits. On the basis of the detection of the navigation message the receiver calculates the position of a satellite and then, based on the position of the satellite, its own position. Tracking of GPS signal synchronization In order to select the most acceptable method of signal synchronization in the receiver, different methods of signal synchronization are compared. The early-late-DLL (Delay Lock Loop, TDL (Tau Dither Loop

  20. Accuracy of multi-trait genomic selection using different methods

    NARCIS (Netherlands)

    Calus, M.P.L.; Veerkamp, R.F.

    2011-01-01

    Background Genomic selection has become a very important tool in animal genetics and is rapidly emerging in plant genetics. It holds the promise to be particularly beneficial to select for traits that are difficult or expensive to measure, such as traits that are measured in one environment and

  1. Antibody-directed lentiviral gene transduction for live-cell monitoring and selection of human iPS and hES cells.

    Directory of Open Access Journals (Sweden)

    Dai-tze Wu

    Full Text Available The identification of stem cells within a mixed population of cells is a major hurdle for stem cell biology--in particular, in the identification of induced pluripotent stem (iPS cells during the reprogramming process. Based on the selective expression of stem cell surface markers, a method to specifically infect stem cells through antibody-conjugated lentiviral particles has been developed that can deliver both visual markers for live-cell imaging as well as selectable markers to enrich for iPS cells. Antibodies recognizing SSEA4 and CD24 mediated the selective infection of the iPS cells over the parental human fibroblasts, allowing for rapid expansion of these cells by puromycin selection. Adaptation of the vector allows for the selective marking of human embryonic stem (hES cells for their removal from a population of differentiated cells. This method has the benefit that it not only identifies stem cells, but that specific genes, including positive and negative selection markers, regulatory genes or miRNA can be delivered to the targeted stem cells. The ability to specifically target gene delivery to human pluripotent stem cells has broad applications in tissue engineering and stem cell therapies.

  2. Relation Between Motility, Accelerated Aging and Gene Expression in Selected Drosophila Strains under Hypergravity Conditions

    Science.gov (United States)

    Serrano, Paloma; van Loon, Jack J. W. A.; Medina, F. Javier; Herranz, Raúl

    2013-02-01

    Motility and aging in Drosophila have proven to be highly modified under altered gravity conditions (both in space and ground simulation facilities). In order to find out how closely connected they are, five strains with altered geotactic response or survival rates were selected and exposed to an altered gravity environment of 2 g. By analysing the different motile and behavioural patterns and the median survival rates, we show that altered gravity leads to changes in motility, which will have a negative impact on the flies' survival. Previous results show a differential gene expression between sessile samples and adults and confirm that environmentally-conditioned behavioural patterns constrain flies' gene expression and life span. Therefore, hypergravity is considered an environmental stress factor and strains that do not respond to this new environment experience an increment in motility, which is the major cause for the observed increased mortality also under microgravity conditions. The neutral-geotaxis selected strain (strain M) showed the most severe phenotype, unable to respond to variations in the gravitational field. Alternatively, the opposite phenotype was observed in positive-geotaxis and long-life selected flies (strains B and L, respectively), suggesting that these populations are less sensitive to alterations in the gravitational load. We conclude that the behavioural response has a greater contribution to aging than the modified energy consumption in altered gravity environments.

  3. An evolutionarily conserved gene family encodes proton-selective ion channels.

    Science.gov (United States)

    Tu, Yu-Hsiang; Cooper, Alexander J; Teng, Bochuan; Chang, Rui B; Artiga, Daniel J; Turner, Heather N; Mulhall, Eric M; Ye, Wenlei; Smith, Andrew D; Liman, Emily R

    2018-03-02

    Ion channels form the basis for cellular electrical signaling. Despite the scores of genetically identified ion channels selective for other monatomic ions, only one type of proton-selective ion channel has been found in eukaryotic cells. By comparative transcriptome analysis of mouse taste receptor cells, we identified Otopetrin1 (OTOP1), a protein required for development of gravity-sensing otoconia in the vestibular system, as forming a proton-selective ion channel. We found that murine OTOP1 is enriched in acid-detecting taste receptor cells and is required for their zinc-sensitive proton conductance. Two related murine genes, Otop2 and Otop3 , and a Drosophila ortholog also encode proton channels. Evolutionary conservation of the gene family and its widespread tissue distribution suggest a broad role for proton channels in physiology and pathophysiology. Copyright © 2018 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works.

  4. Selection and validation of reference genes for miRNA expression studies during porcine pregnancy.

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    Jocelyn M Wessels

    Full Text Available MicroRNAs comprise a family of small non-coding RNAs that modulate several developmental and physiological processes including pregnancy. Their ubiquitous presence is confirmed in mammals, worms, flies and plants. Although rapid advances have been made in microRNA research, information on stable reference genes for validation of microRNA expression is still lacking. Real time PCR is a widely used tool to quantify gene transcripts. An appropriate reference gene must be chosen to minimize experimental error in this system. A small difference in miRNA levels between experimental samples can be biologically meaningful as these entities can affect multiple targets in a pathway. This study examined the suitability of six commercially available reference genes (RNU1A, RNU5A, RNU6B, SNORD25, SCARNA17, and SNORA73A in maternal-fetal tissues from healthy and spontaneously arresting/dying conceptuses from sows were separately analyzed at gestation day 20. Comparisons were also made with non-pregnant endometrial tissues from sows. Spontaneous fetal loss is a prime concern to the commercial pork industry. Our laboratory has previously identified deficits in vasculature development at maternal-fetal interface as one of the major participating causes of fetal loss. Using this well-established model, we have extended our studies to identify suitable microRNA reference genes. A methodical approach to assessing suitability was adopted using standard curve and melting curve analysis, PCR product sequencing, real time PCR expression in a panel of gestational tissues, and geNorm and NormFinder analysis. Our quantitative real time PCR analysis confirmed expression of all 6 reference genes in maternal and fetal tissues. All genes were uniformly expressed in tissues from healthy and spontaneously arresting conceptus attachment sites. Comparisons between tissue types (maternal/fetal/non-pregnant revealed significant differences for RNU5A, RNU6B, SCARNA17, and SNORA73A

  5. Models of Aire-dependent gene regulation for thymic negative selection

    Directory of Open Access Journals (Sweden)

    Dina eDanso-Abeam

    2011-05-01

    Full Text Available Mutations in the Autoimmune Regulator (AIRE gene lead to Autoimmune Polyendocrinopathy Syndrome type 1 (APS1, characterized by the development of multi-organ autoimmune damage. The mechanism by which defects in AIRE result in autoimmunity has been the subject of intense scrutiny. At the cellular level, the working model explains most of the clinical and immunological characteristics of APS1, with AIRE driving the expression of tissue restricted antigens (TRAs in the epithelial cells of the thymic medulla. This TRA expression results in effective negative selection of TRA-reactive thymocytes, preventing autoimmune disease. At the molecular level, the mechanism by which AIRE initiates TRA expression in the thymic medulla remains unclear. Multiple different models for the molecular mechanism have been proposed, ranging from classical transcriptional activity, to random induction of gene expression, to epigenetic tag recognition effect, to altered cell biology. In this review, we evaluate each of these models and discuss their relative strengths and weaknesses.

  6. Evaluation of two main RNA-seq approaches for gene quantification in clinical RNA sequencing: polyA+ selection versus rRNA depletion.

    Science.gov (United States)

    Zhao, Shanrong; Zhang, Ying; Gamini, Ramya; Zhang, Baohong; von Schack, David

    2018-03-19

    To allow efficient transcript/gene detection, highly abundant ribosomal RNAs (rRNA) are generally removed from total RNA either by positive polyA+ selection or by rRNA depletion (negative selection) before sequencing. Comparisons between the two methods have been carried out by various groups, but the assessments have relied largely on non-clinical samples. In this study, we evaluated these two RNA sequencing approaches using human blood and colon tissue samples. Our analyses showed that rRNA depletion captured more unique transcriptome features, whereas polyA+ selection outperformed rRNA depletion with higher exonic coverage and better accuracy of gene quantification. For blood- and colon-derived RNAs, we found that 220% and 50% more reads, respectively, would have to be sequenced to achieve the same level of exonic coverage in the rRNA depletion method compared with the polyA+ selection method. Therefore, in most cases we strongly recommend polyA+ selection over rRNA depletion for gene quantification in clinical RNA sequencing. Our evaluation revealed that a small number of lncRNAs and small RNAs made up a large fraction of the reads in the rRNA depletion RNA sequencing data. Thus, we recommend that these RNAs are specifically depleted to improve the sequencing depth of the remaining RNAs.

  7. Applying the partitioned multiobjective risk method (PMRM) to portfolio selection.

    Science.gov (United States)

    Reyes Santos, Joost; Haimes, Yacov Y

    2004-06-01

    The analysis of risk-return tradeoffs and their practical applications to portfolio analysis paved the way for Modern Portfolio Theory (MPT), which won Harry Markowitz a 1992 Nobel Prize in Economics. A typical approach in measuring a portfolio's expected return is based on the historical returns of the assets included in a portfolio. On the other hand, portfolio risk is usually measured using volatility, which is derived from the historical variance-covariance relationships among the portfolio assets. This article focuses on assessing portfolio risk, with emphasis on extreme risks. To date, volatility is a major measure of risk owing to its simplicity and validity for relatively small asset price fluctuations. Volatility is a justified measure for stable market performance, but it is weak in addressing portfolio risk under aberrant market fluctuations. Extreme market crashes such as that on October 19, 1987 ("Black Monday") and catastrophic events such as the terrorist attack of September 11, 2001 that led to a four-day suspension of trading on the New York Stock Exchange (NYSE) are a few examples where measuring risk via volatility can lead to inaccurate predictions. Thus, there is a need for a more robust metric of risk. By invoking the principles of the extreme-risk-analysis method through the partitioned multiobjective risk method (PMRM), this article contributes to the modeling of extreme risks in portfolio performance. A measure of an extreme portfolio risk, denoted by f(4), is defined as the conditional expectation for a lower-tail region of the distribution of the possible portfolio returns. This article presents a multiobjective problem formulation consisting of optimizing expected return and f(4), whose solution is determined using Evolver-a software that implements a genetic algorithm. Under business-as-usual market scenarios, the results of the proposed PMRM portfolio selection model are found to be compatible with those of the volatility-based model

  8. Method for selection of optimal road safety composite index with examples from DEA and TOPSIS method.

    Science.gov (United States)

    Rosić, Miroslav; Pešić, Dalibor; Kukić, Dragoslav; Antić, Boris; Božović, Milan

    2017-01-01

    Concept of composite road safety index is a popular and relatively new concept among road safety experts around the world. As there is a constant need for comparison among different units (countries, municipalities, roads, etc.) there is need to choose an adequate method which will make comparison fair to all compared units. Usually comparisons using one specific indicator (parameter which describes safety or unsafety) can end up with totally different ranking of compared units which is quite complicated for decision maker to determine "real best performers". Need for comp