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  1. Fast gene ontology based clustering for microarray experiments.

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    Ovaska, Kristian; Laakso, Marko; Hautaniemi, Sampsa

    2008-11-21

    Analysis of a microarray experiment often results in a list of hundreds of disease-associated genes. In order to suggest common biological processes and functions for these genes, Gene Ontology annotations with statistical testing are widely used. However, these analyses can produce a very large number of significantly altered biological processes. Thus, it is often challenging to interpret GO results and identify novel testable biological hypotheses. We present fast software for advanced gene annotation using semantic similarity for Gene Ontology terms combined with clustering and heat map visualisation. The methodology allows rapid identification of genes sharing the same Gene Ontology cluster. Our R based semantic similarity open-source package has a speed advantage of over 2000-fold compared to existing implementations. From the resulting hierarchical clustering dendrogram genes sharing a GO term can be identified, and their differences in the gene expression patterns can be seen from the heat map. These methods facilitate advanced annotation of genes resulting from data analysis.

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

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    Olszewski Kellen L

    2007-07-01

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

  3. Fast Gene Ontology based clustering for microarray experiments

    Directory of Open Access Journals (Sweden)

    Ovaska Kristian

    2008-11-01

    Full Text Available Abstract Background Analysis of a microarray experiment often results in a list of hundreds of disease-associated genes. In order to suggest common biological processes and functions for these genes, Gene Ontology annotations with statistical testing are widely used. However, these analyses can produce a very large number of significantly altered biological processes. Thus, it is often challenging to interpret GO results and identify novel testable biological hypotheses. Results We present fast software for advanced gene annotation using semantic similarity for Gene Ontology terms combined with clustering and heat map visualisation. The methodology allows rapid identification of genes sharing the same Gene Ontology cluster. Conclusion Our R based semantic similarity open-source package has a speed advantage of over 2000-fold compared to existing implementations. From the resulting hierarchical clustering dendrogram genes sharing a GO term can be identified, and their differences in the gene expression patterns can be seen from the heat map. These methods facilitate advanced annotation of genes resulting from data analysis.

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

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    Gong Binsheng

    2011-05-01

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

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

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

    2005-02-01

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

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

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    Liu, Xiao; Shi, Jun; Wang, Congzhi

    2015-01-01

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

  7. A genomics based discovery of secondary metabolite biosynthetic gene clusters in Aspergillus ustus.

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    Borui Pi

    Full Text Available Secondary metabolites (SMs produced by Aspergillus have been extensively studied for their crucial roles in human health, medicine and industrial production. However, the resulting information is almost exclusively derived from a few model organisms, including A. nidulans and A. fumigatus, but little is known about rare pathogens. In this study, we performed a genomics based discovery of SM biosynthetic gene clusters in Aspergillus ustus, a rare human pathogen. A total of 52 gene clusters were identified in the draft genome of A. ustus 3.3904, such as the sterigmatocystin biosynthesis pathway that was commonly found in Aspergillus species. In addition, several SM biosynthetic gene clusters were firstly identified in Aspergillus that were possibly acquired by horizontal gene transfer, including the vrt cluster that is responsible for viridicatumtoxin production. Comparative genomics revealed that A. ustus shared the largest number of SM biosynthetic gene clusters with A. nidulans, but much fewer with other Aspergilli like A. niger and A. oryzae. These findings would help to understand the diversity and evolution of SM biosynthesis pathways in genus Aspergillus, and we hope they will also promote the development of fungal identification methodology in clinic.

  8. A Genomics Based Discovery of Secondary Metabolite Biosynthetic Gene Clusters in Aspergillus ustus

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    Pi, Borui; Yu, Dongliang; Dai, Fangwei; Song, Xiaoming; Zhu, Congyi; Li, Hongye; Yu, Yunsong

    2015-01-01

    Secondary metabolites (SMs) produced by Aspergillus have been extensively studied for their crucial roles in human health, medicine and industrial production. However, the resulting information is almost exclusively derived from a few model organisms, including A. nidulans and A. fumigatus, but little is known about rare pathogens. In this study, we performed a genomics based discovery of SM biosynthetic gene clusters in Aspergillus ustus, a rare human pathogen. A total of 52 gene clusters were identified in the draft genome of A. ustus 3.3904, such as the sterigmatocystin biosynthesis pathway that was commonly found in Aspergillus species. In addition, several SM biosynthetic gene clusters were firstly identified in Aspergillus that were possibly acquired by horizontal gene transfer, including the vrt cluster that is responsible for viridicatumtoxin production. Comparative genomics revealed that A. ustus shared the largest number of SM biosynthetic gene clusters with A. nidulans, but much fewer with other Aspergilli like A. niger and A. oryzae. These findings would help to understand the diversity and evolution of SM biosynthesis pathways in genus Aspergillus, and we hope they will also promote the development of fungal identification methodology in clinic. PMID:25706180

  9. Form gene clustering method about pan-ethnic-group products based on emotional semantic

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    Chen, Dengkai; Ding, Jingjing; Gao, Minzhuo; Ma, Danping; Liu, Donghui

    2016-09-01

    The use of pan-ethnic-group products form knowledge primarily depends on a designer's subjective experience without user participation. The majority of studies primarily focus on the detection of the perceptual demands of consumers from the target product category. A pan-ethnic-group products form gene clustering method based on emotional semantic is constructed. Consumers' perceptual images of the pan-ethnic-group products are obtained by means of product form gene extraction and coding and computer aided product form clustering technology. A case of form gene clustering about the typical pan-ethnic-group products is investigated which indicates that the method is feasible. This paper opens up a new direction for the future development of product form design which improves the agility of product design process in the era of Industry 4.0.

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

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

    2012-07-15

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

  11. Gene cluster statistics with gene families.

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    Raghupathy, Narayanan; Durand, Dannie

    2009-05-01

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

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

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

    2017-11-23

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

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

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    P.Balaji

    2015-01-01

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

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

    DEFF Research Database (Denmark)

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

    2013-01-01

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

  15. Diametrical clustering for identifying anti-correlated gene clusters.

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    Dhillon, Inderjit S; Marcotte, Edward M; Roshan, Usman

    2003-09-01

    Clustering genes based upon their expression patterns allows us to predict gene function. Most existing clustering algorithms cluster genes together when their expression patterns show high positive correlation. However, it has been observed that genes whose expression patterns are strongly anti-correlated can also be functionally similar. Biologically, this is not unintuitive-genes responding to the same stimuli, regardless of the nature of the response, are more likely to operate in the same pathways. We present a new diametrical clustering algorithm that explicitly identifies anti-correlated clusters of genes. Our algorithm proceeds by iteratively (i). re-partitioning the genes and (ii). computing the dominant singular vector of each gene cluster; each singular vector serving as the prototype of a 'diametric' cluster. We empirically show the effectiveness of the algorithm in identifying diametrical or anti-correlated clusters. Testing the algorithm on yeast cell cycle data, fibroblast gene expression data, and DNA microarray data from yeast mutants reveals that opposed cellular pathways can be discovered with this method. We present systems whose mRNA expression patterns, and likely their functions, oppose the yeast ribosome and proteosome, along with evidence for the inverse transcriptional regulation of a number of cellular systems.

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

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

    2016-12-01

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

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

    KAUST Repository

    Abusamra, Heba

    2016-07-20

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

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

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    Morten Thrane Nielsen

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

  19. An improved Pearson's correlation proximity-based hierarchical clustering for mining biological association between genes.

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    Booma, P M; Prabhakaran, S; Dhanalakshmi, R

    2014-01-01

    Microarray gene expression datasets has concerned great awareness among molecular biologist, statisticians, and computer scientists. Data mining that extracts the hidden and usual information from datasets fails to identify the most significant biological associations between genes. A search made with heuristic for standard biological process measures only the gene expression level, threshold, and response time. Heuristic search identifies and mines the best biological solution, but the association process was not efficiently addressed. To monitor higher rate of expression levels between genes, a hierarchical clustering model was proposed, where the biological association between genes is measured simultaneously using proximity measure of improved Pearson's correlation (PCPHC). Additionally, the Seed Augment algorithm adopts average linkage methods on rows and columns in order to expand a seed PCPHC model into a maximal global PCPHC (GL-PCPHC) model and to identify association between the clusters. Moreover, a GL-PCPHC applies pattern growing method to mine the PCPHC patterns. Compared to existing gene expression analysis, the PCPHC model achieves better performance. Experimental evaluations are conducted for GL-PCPHC model with standard benchmark gene expression datasets extracted from UCI repository and GenBank database in terms of execution time, size of pattern, significance level, biological association efficiency, and pattern quality.

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

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    Saurav Mallik

    2017-12-01

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

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

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    Mallik, Saurav; Zhao, Zhongming

    2017-12-28

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

  2. VRprofile: gene-cluster-detection-based profiling of virulence and antibiotic resistance traits encoded within genome sequences of pathogenic bacteria.

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    Li, Jun; Tai, Cui; Deng, Zixin; Zhong, Weihong; He, Yongqun; Ou, Hong-Yu

    2017-01-10

    VRprofile is a Web server that facilitates rapid investigation of virulence and antibiotic resistance genes, as well as extends these trait transfer-related genetic contexts, in newly sequenced pathogenic bacterial genomes. The used backend database MobilomeDB was firstly built on sets of known gene cluster loci of bacterial type III/IV/VI/VII secretion systems and mobile genetic elements, including integrative and conjugative elements, prophages, class I integrons, IS elements and pathogenicity/antibiotic resistance islands. VRprofile is thus able to co-localize the homologs of these conserved gene clusters using HMMer or BLASTp searches. With the integration of the homologous gene cluster search module with a sequence composition module, VRprofile has exhibited better performance for island-like region predictions than the other widely used methods. In addition, VRprofile also provides an integrated Web interface for aligning and visualizing identified gene clusters with MobilomeDB-archived gene clusters, or a variety set of bacterial genomes. VRprofile might contribute to meet the increasing demands of re-annotations of bacterial variable regions, and aid in the real-time definitions of disease-relevant gene clusters in pathogenic bacteria of interest. VRprofile is freely available at http://bioinfo-mml.sjtu.edu.cn/VRprofile. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

  3. Persistence drives gene clustering in bacterial genomes

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    Rocha Eduardo PC

    2008-01-01

    Full Text Available Abstract Background Gene clustering plays an important role in the organization of the bacterial chromosome and several mechanisms have been proposed to explain its extent. However, the controversies raised about the validity of each of these mechanisms remind us that the cause of this gene organization remains an open question. Models proposed to explain clustering did not take into account the function of the gene products nor the likely presence or absence of a given gene in a genome. However, genomes harbor two very different categories of genes: those genes present in a majority of organisms – persistent genes – and those present in very few organisms – rare genes. Results We show that two classes of genes are significantly clustered in bacterial genomes: the highly persistent and the rare genes. The clustering of rare genes is readily explained by the selfish operon theory. Yet, genes persistently present in bacterial genomes are also clustered and we try to understand why. We propose a model accounting specifically for such clustering, and show that indispensability in a genome with frequent gene deletion and insertion leads to the transient clustering of these genes. The model describes how clusters are created via the gene flux that continuously introduces new genes while deleting others. We then test if known selective processes, such as co-transcription, physical interaction or functional neighborhood, account for the stabilization of these clusters. Conclusion We show that the strong selective pressure acting on the function of persistent genes, in a permanent state of flux of genes in bacterial genomes, maintaining their size fairly constant, that drives persistent genes clustering. A further selective stabilization process might contribute to maintaining the clustering.

  4. Correlation-based iterative clustering methods for time course data: The identification of temporal gene response modules for influenza infection in humans

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    Michelle Carey

    2016-10-01

    Full Text Available Many pragmatic clustering methods have been developed to group data vectors or objects into clusters so that the objects in one cluster are very similar and objects in different clusters are distinct based on some similarity measure. The availability of time course data has motivated researchers to develop methods, such as mixture and mixed-effects modelling approaches, that incorporate the temporal information contained in the shape of the trajectory of the data. However, there is still a need for the development of time-course clustering methods that can adequately deal with inhomogeneous clusters (some clusters are quite large and others are quite small. Here we propose two such methods, hierarchical clustering (IHC and iterative pairwise-correlation clustering (IPC. We evaluate and compare the proposed methods to the Markov Cluster Algorithm (MCL and the generalised mixed-effects model (GMM using simulation studies and an application to a time course gene expression data set from a study containing human subjects who were challenged by a live influenza virus. We identify four types of temporal gene response modules to influenza infection in humans, i.e., single-gene modules (SGM, small-size modules (SSM, medium-size modules (MSM and large-size modules (LSM. The LSM contain genes that perform various fundamental biological functions that are consistent across subjects. The SSM and SGM contain genes that perform either different or similar biological functions that have complex temporal responses to the virus and are unique to each subject. We show that the temporal response of the genes in the LSM have either simple patterns with a single peak or trough a consequence of the transient stimuli sustained or state-transitioning patterns pertaining to developmental cues and that these modules can differentiate the severity of disease outcomes. Additionally, the size of gene response modules follows a power-law distribution with a consistent

  5. Genetic relationships among native americans based on b-globin gene cluster haplotype frequencies

    OpenAIRE

    Mousinho-Ribeiro Rita de Cassia; Pante-de-Sousa Gabriella; Santos Eduardo José Melo dos; Guerreiro João Farias

    2003-01-01

    The distribution of b-globin gene haplotypes was studied in 209 Amerindians from eight tribes of the Brazilian Amazon: Asurini from Xingú, Awá-Guajá, Parakanã, Urubú-Kaapór, Zoé, Kayapó (Xikrin from the Bacajá village), Katuena, and Tiriyó. Nine different haplotypes were found, two of which (n. 11 and 13) had not been previously identified in Brazilian indigenous populations. Haplotype 2 (+ - - - -) was the most common in all groups studied, with frequencies varying from 70% to 100%, followed...

  6. Genetic relationships among native americans based on beta-globin gene cluster haplotype frequencies

    Directory of Open Access Journals (Sweden)

    Rita de Cassia Mousinho-Ribeiro

    2003-01-01

    Full Text Available The distribution of b-globin gene haplotypes was studied in 209 Amerindians from eight tribes of the Brazilian Amazon: Asurini from Xingú, Awá-Guajá, Parakanã, Urubú-Kaapór, Zoé, Kayapó (Xikrin from the Bacajá village, Katuena, and Tiriyó. Nine different haplotypes were found, two of which (n. 11 and 13 had not been previously identified in Brazilian indigenous populations. Haplotype 2 (+ - - - - was the most common in all groups studied, with frequencies varying from 70% to 100%, followed by haplotype 6 (- + + - +, with frequencies between 7% and 18%. The frequency distribution of the b-globin gene haplotypes in the eighteen Brazilian Amerindian populations studied to date is characterized by a reduced number of haplotypes (average of 3.5 and low levels of heterozygosity and intrapopulational differentiation, with a single clearly predominant haplotype in most tribes (haplotype 2. The Parakanã, Urubú-Kaapór, Tiriyó and Xavante tribes constitute exceptions, presenting at least four haplotypes with relatively high frequencies. The closest genetic relationships were observed between the Brazilian and the Colombian Amerindians (Wayuu, Kamsa and Inga, and, to a lesser extent, with the Huichol of Mexico. North-American Amerindians are more differentiated and clearly separated from all other tribes, except the Xavante, from Brazil, and the Mapuche, from Argentina. A restricted pool of ancestral haplotypes may explain the low diversity observed among most present-day Brazilian and Colombian Amerindian groups, while interethnic admixture could be the most important factor to explain the high number of haplotypes and high levels of diversity observed in some South-American and most North-American tribes.

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

    Science.gov (United States)

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

    2014-04-04

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

  8. IMG-ABC: A Knowledge Base To Fuel Discovery of Biosynthetic Gene Clusters and Novel Secondary Metabolites.

    Science.gov (United States)

    Hadjithomas, Michalis; Chen, I-Min Amy; Chu, Ken; Ratner, Anna; Palaniappan, Krishna; Szeto, Ernest; Huang, Jinghua; Reddy, T B K; Cimermančič, Peter; Fischbach, Michael A; Ivanova, Natalia N; Markowitz, Victor M; Kyrpides, Nikos C; Pati, Amrita

    2015-07-14

    In the discovery of secondary metabolites, analysis of sequence data is a promising exploration path that remains largely underutilized due to the lack of computational platforms that enable such a systematic approach on a large scale. In this work, we present IMG-ABC (https://img.jgi.doe.gov/abc), an atlas of biosynthetic gene clusters within the Integrated Microbial Genomes (IMG) system, which is aimed at harnessing the power of "big" genomic data for discovering small molecules. IMG-ABC relies on IMG's comprehensive integrated structural and functional genomic data for the analysis of biosynthetic gene clusters (BCs) and associated secondary metabolites (SMs). SMs and BCs serve as the two main classes of objects in IMG-ABC, each with a rich collection of attributes. A unique feature of IMG-ABC is the incorporation of both experimentally validated and computationally predicted BCs in genomes as well as metagenomes, thus identifying BCs in uncultured populations and rare taxa. We demonstrate the strength of IMG-ABC's focused integrated analysis tools in enabling the exploration of microbial secondary metabolism on a global scale, through the discovery of phenazine-producing clusters for the first time in Alphaproteobacteria. IMG-ABC strives to fill the long-existent void of resources for computational exploration of the secondary metabolism universe; its underlying scalable framework enables traversal of uncovered phylogenetic and chemical structure space, serving as a doorway to a new era in the discovery of novel molecules. IMG-ABC is the largest publicly available database of predicted and experimental biosynthetic gene clusters and the secondary metabolites they produce. The system also includes powerful search and analysis tools that are integrated with IMG's extensive genomic/metagenomic data and analysis tool kits. As new research on biosynthetic gene clusters and secondary metabolites is published and more genomes are sequenced, IMG-ABC will continue to

  9. Genome based analysis of type-I polyketide synthase and nonribosomal peptide synthetase gene clusters in seven strains of five representative Nocardia species.

    Science.gov (United States)

    Komaki, Hisayuki; Ichikawa, Natsuko; Hosoyama, Akira; Takahashi-Nakaguchi, Azusa; Matsuzawa, Tetsuhiro; Suzuki, Ken-ichiro; Fujita, Nobuyuki; Gonoi, Tohru

    2014-04-30

    Actinobacteria of the genus Nocardia usually live in soil or water and play saprophytic roles, but they also opportunistically infect the respiratory system, skin, and other organs of humans and animals. Primarily because of the clinical importance of the strains, some Nocardia genomes have been sequenced, and genome sequences have accumulated. Genome sizes of Nocardia strains are similar to those of Streptomyces strains, the producers of most antibiotics. In the present work, we compared secondary metabolite biosynthesis gene clusters of type-I polyketide synthase (PKS-I) and nonribosomal peptide synthetase (NRPS) among genomes of representative Nocardia species/strains based on domain organization and amino acid sequence homology. Draft genome sequences of Nocardia asteroides NBRC 15531(T), Nocardia otitidiscaviarum IFM 11049, Nocardia brasiliensis NBRC 14402(T), and N. brasiliensis IFM 10847 were read and compared with published complete genome sequences of Nocardia farcinica IFM 10152, Nocardia cyriacigeorgica GUH-2, and N. brasiliensis HUJEG-1. Genome sizes are as follows: N. farcinica, 6.0 Mb; N. cyriacigeorgica, 6.2 Mb; N. asteroides, 7.0 Mb; N. otitidiscaviarum, 7.8 Mb; and N. brasiliensis, 8.9 - 9.4 Mb. Predicted numbers of PKS-I, NRPS, and PKS-I/NRPS hybrid clusters ranged between 4-11, 7-13, and 1-6, respectively, depending on strains, and tended to increase with increasing genome size. Domain and module structures of representative or unique clusters are discussed in the text. We conclude the following: 1) genomes of Nocardia strains carry as many PKS-I and NRPS gene clusters as those of Streptomyces strains, 2) the number of PKS-I and NRPS gene clusters in Nocardia strains varies substantially depending on species, and N. brasiliensis strains carry the largest numbers of clusters among the species studied, 3) the seven Nocardia strains studied in the present work have seven common PKS-I and/or NRPS clusters, some of whose products are yet to be studied

  10. Pichia stipitis genomics, transcriptomics, and gene clusters

    Science.gov (United States)

    Thomas W. Jeffries; Jennifer R. Headman Van Vleet

    2009-01-01

    Genome sequencing and subsequent global gene expression studies have advanced our understanding of the lignocellulose-fermenting yeast Pichia stipitis. These studies have provided an insight into its central carbon metabolism, and analysis of its genome has revealed numerous functional gene clusters and tandem repeats. Specialized physiological traits are often the...

  11. De novo clustering methods outperform reference-based methods for assigning 16S rRNA gene sequences to operational taxonomic units

    Directory of Open Access Journals (Sweden)

    Sarah L. Westcott

    2015-12-01

    Full Text Available Background. 16S rRNA gene sequences are routinely assigned to operational taxonomic units (OTUs that are then used to analyze complex microbial communities. A number of methods have been employed to carry out the assignment of 16S rRNA gene sequences to OTUs leading to confusion over which method is optimal. A recent study suggested that a clustering method should be selected based on its ability to generate stable OTU assignments that do not change as additional sequences are added to the dataset. In contrast, we contend that the quality of the OTU assignments, the ability of the method to properly represent the distances between the sequences, is more important.Methods. Our analysis implemented six de novo clustering algorithms including the single linkage, complete linkage, average linkage, abundance-based greedy clustering, distance-based greedy clustering, and Swarm and the open and closed-reference methods. Using two previously published datasets we used the Matthew’s Correlation Coefficient (MCC to assess the stability and quality of OTU assignments.Results. The stability of OTU assignments did not reflect the quality of the assignments. Depending on the dataset being analyzed, the average linkage and the distance and abundance-based greedy clustering methods generated OTUs that were more likely to represent the actual distances between sequences than the open and closed-reference methods. We also demonstrated that for the greedy algorithms VSEARCH produced assignments that were comparable to those produced by USEARCH making VSEARCH a viable free and open source alternative to USEARCH. Further interrogation of the reference-based methods indicated that when USEARCH or VSEARCH were used to identify the closest reference, the OTU assignments were sensitive to the order of the reference sequences because the reference sequences can be identical over the region being considered. More troubling was the observation that while both USEARCH and

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

    OpenAIRE

    Wang, Yunli; Pan, Youlian

    2014-01-01

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

  13. Subtyping Salmonella enterica serovar enteritidis isolates from different sources by using sequence typing based on virulence genes and clustered regularly interspaced short palindromic repeats (CRISPRs).

    Science.gov (United States)

    Liu, Fenyun; Kariyawasam, Subhashinie; Jayarao, Bhushan M; Barrangou, Rodolphe; Gerner-Smidt, Peter; Ribot, Efrain M; Knabel, Stephen J; Dudley, Edward G

    2011-07-01

    Salmonella enterica subsp. enterica serovar Enteritidis is a major cause of food-borne salmonellosis in the United States. Two major food vehicles for S. Enteritidis are contaminated eggs and chicken meat. Improved subtyping methods are needed to accurately track specific strains of S. Enteritidis related to human salmonellosis throughout the chicken and egg food system. A sequence typing scheme based on virulence genes (fimH and sseL) and clustered regularly interspaced short palindromic repeats (CRISPRs)-CRISPR-including multi-virulence-locus sequence typing (designated CRISPR-MVLST)-was used to characterize 35 human clinical isolates, 46 chicken isolates, 24 egg isolates, and 63 hen house environment isolates of S. Enteritidis. A total of 27 sequence types (STs) were identified among the 167 isolates. CRISPR-MVLST identified three persistent and predominate STs circulating among U.S. human clinical isolates and chicken, egg, and hen house environmental isolates in Pennsylvania, and an ST that was found only in eggs and humans. It also identified a potential environment-specific sequence type. Moreover, cluster analysis based on fimH and sseL identified a number of clusters, of which several were found in more than one outbreak, as well as 11 singletons. Further research is needed to determine if CRISPR-MVLST might help identify the ecological origins of S. Enteritidis strains that contaminate chickens and eggs.

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

    Science.gov (United States)

    2012-01-01

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

  15. Cluster Based Text Classification Model

    DEFF Research Database (Denmark)

    Nizamani, Sarwat; Memon, Nasrullah; Wiil, Uffe Kock

    2011-01-01

    We propose a cluster based classification model for suspicious email detection and other text classification tasks. The text classification tasks comprise many training examples that require a complex classification model. Using clusters for classification makes the model simpler and increases...... the accuracy at the same time. The test example is classified using simpler and smaller model. The training examples in a particular cluster share the common vocabulary. At the time of clustering, we do not take into account the labels of the training examples. After the clusters have been created......, the classifier is trained on each cluster having reduced dimensionality and less number of examples. The experimental results show that the proposed model outperforms the existing classification models for the task of suspicious email detection and topic categorization on the Reuters-21578 and 20 Newsgroups...

  16. QTL global meta-analysis: are trait determining genes clustered?

    Directory of Open Access Journals (Sweden)

    Adelson David L

    2009-04-01

    Full Text Available Abstract Background A key open question in biology is if genes are physically clustered with respect to their known functions or phenotypic effects. This is of particular interest for Quantitative Trait Loci (QTL where a QTL region could contain a number of genes that contribute to the trait being measured. Results We observed a significant increase in gene density within QTL regions compared to non-QTL regions and/or the entire bovine genome. By grouping QTL from the Bovine QTL Viewer database into 8 categories of non-redundant regions, we have been able to analyze gene density and gene function distribution, based on Gene Ontology (GO with relation to their location within QTL regions, outside of QTL regions and across the entire bovine genome. We identified a number of GO terms that were significantly over represented within particular QTL categories. Furthermore, select GO terms expected to be associated with the QTL category based on common biological knowledge have also proved to be significantly over represented in QTL regions. Conclusion Our analysis provides evidence of over represented GO terms in QTL regions. This increased GO term density indicates possible clustering of gene functions within QTL regions of the bovine genome. Genes with similar functions may be grouped in specific locales and could be contributing to QTL traits. Moreover, we have identified over-represented GO terminology that from a biological standpoint, makes sense with respect to QTL category type.

  17. Some statistical properties of gene expression clustering for array data

    DEFF Research Database (Denmark)

    Abreu, G C G; Pinheiro, A; Drummond, R D

    2010-01-01

    DNA array data without a corresponding statistical error measure. We propose an easy-to-implement and simple-to-use technique that uses bootstrap re-sampling to evaluate the statistical error of the nodes provided by SOM-based clustering. Comparisons between SOM and parametric clustering are presented...... for simulated as well as for two real data sets. We also implement a bootstrap-based pre-processing procedure for SOM, that improves the false discovery ratio of differentially expressed genes. Code in Matlab is freely available, as well as some supplementary material, at the following address: https...

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

    Science.gov (United States)

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

  19. Physical and genetic map of the major nif gene cluster from Azotobacter vinelandii.

    OpenAIRE

    Jacobson, M R; Brigle, K E; Bennett, L T; Setterquist, R A; Wilson, M S; Cash, V L; Beynon, J; Newton, W E; Dean, D R

    1989-01-01

    Determination of a 28,793-base-pair DNA sequence of a region from the Azotobacter vinelandii genome that includes and flanks the nitrogenase structural gene region was completed. This information was used to revise the previously proposed organization of the major nif cluster. The major nif cluster from A. vinelandii encodes 15 nif-specific genes whose products bear significant structural identity to the corresponding nif-specific gene products from Klebsiella pneumoniae. These genes include ...

  20. Normalization based K means Clustering Algorithm

    OpenAIRE

    Virmani, Deepali; Taneja, Shweta; Malhotra, Geetika

    2015-01-01

    K-means is an effective clustering technique used to separate similar data into groups based on initial centroids of clusters. In this paper, Normalization based K-means clustering algorithm(N-K means) is proposed. Proposed N-K means clustering algorithm applies normalization prior to clustering on the available data as well as the proposed approach calculates initial centroids based on weights. Experimental results prove the betterment of proposed N-K means clustering algorithm over existing...

  1. 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

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

    Directory of Open Access Journals (Sweden)

    Mikhail Pyatnitskiy

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

  3. Text Clustering Algorithm Based on Random Cluster Core

    Directory of Open Access Journals (Sweden)

    Huang Long-Jun

    2016-01-01

    Full Text Available Nowadays clustering has become a popular text mining algorithm, but the huge data can put forward higher requirements for the accuracy and performance of text mining. In view of the performance bottleneck of traditional text clustering algorithm, this paper proposes a text clustering algorithm with random features. This is a kind of clustering algorithm based on text density, at the same time using the neighboring heuristic rules, the concept of random cluster is introduced, which effectively reduces the complexity of the distance calculation.

  4. Projection-based curve clustering

    International Nuclear Information System (INIS)

    Auder, Benjamin; Fischer, Aurelie

    2012-01-01

    This paper focuses on unsupervised curve classification in the context of nuclear industry. At the Commissariat a l'Energie Atomique (CEA), Cadarache (France), the thermal-hydraulic computer code CATHARE is used to study the reliability of reactor vessels. The code inputs are physical parameters and the outputs are time evolution curves of a few other physical quantities. As the CATHARE code is quite complex and CPU time-consuming, it has to be approximated by a regression model. This regression process involves a clustering step. In the present paper, the CATHARE output curves are clustered using a k-means scheme, with a projection onto a lower dimensional space. We study the properties of the empirically optimal cluster centres found by the clustering method based on projections, compared with the 'true' ones. The choice of the projection basis is discussed, and an algorithm is implemented to select the best projection basis among a library of orthonormal bases. The approach is illustrated on a simulated example and then applied to the industrial problem. (authors)

  5. 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

    background correction is preferable, in particular if the gene selection is successful. However, this is an area that needs to be studied further in order to draw any general conclusions. Conclusions The choice of cluster analysis, and in particular gene selection, has a large impact on the ability to cluster individuals correctly based on expression profiles. Normalization has a positive effect, but the relative performance of different normalizations is an area that needs more research. In summary, although clustering, gene selection and normalization are considered standard methods in bioinformatics, our comprehensive analysis shows that selecting the right methods, and the right combinations of methods, is far from trivial and that much is still unexplored in what is considered to be the most basic analysis of genomic data.

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

    Science.gov (United States)

    2010-01-01

    preferable, in particular if the gene selection is successful. However, this is an area that needs to be studied further in order to draw any general conclusions. Conclusions The choice of cluster analysis, and in particular gene selection, has a large impact on the ability to cluster individuals correctly based on expression profiles. Normalization has a positive effect, but the relative performance of different normalizations is an area that needs more research. In summary, although clustering, gene selection and normalization are considered standard methods in bioinformatics, our comprehensive analysis shows that selecting the right methods, and the right combinations of methods, is far from trivial and that much is still unexplored in what is considered to be the most basic analysis of genomic data. PMID:20937082

  7. Hox gene cluster of the ascidian, Halocynthia roretzi, reveals multiple ancient steps of cluster disintegration during ascidian evolution.

    Science.gov (United States)

    Sekigami, Yuka; Kobayashi, Takuya; Omi, Ai; Nishitsuji, Koki; Ikuta, Tetsuro; Fujiyama, Asao; Satoh, Noriyuki; Saiga, Hidetoshi

    2017-01-01

    Hox gene clusters with at least 13 paralog group (PG) members are common in vertebrate genomes and in that of amphioxus. Ascidians, which belong to the subphylum Tunicata (Urochordata), are phylogenetically positioned between vertebrates and amphioxus, and traditionally divided into two groups: the Pleurogona and the Enterogona. An enterogonan ascidian, Ciona intestinalis ( Ci ), possesses nine Hox genes localized on two chromosomes; thus, the Hox gene cluster is disintegrated. We investigated the Hox gene cluster of a pleurogonan ascidian, Halocynthia roretzi ( Hr ) to investigate whether Hox gene cluster disintegration is common among ascidians, and if so, how such disintegration occurred during ascidian or tunicate evolution. Our phylogenetic analysis reveals that the Hr Hox gene complement comprises nine members, including one with a relatively divergent Hox homeodomain sequence. Eight of nine Hr Hox genes were orthologous to Ci-Hox1 , 2, 3, 4, 5, 10, 12 and 13. Following the phylogenetic classification into 13 PGs, we designated Hr Hox genes as Hox1, 2, 3, 4, 5, 10, 11/12/13.a , 11/12/13.b and HoxX . To address the chromosomal arrangement of the nine Hox genes, we performed two-color chromosomal fluorescent in situ hybridization, which revealed that the nine Hox genes are localized on a single chromosome in Hr , distinct from their arrangement in Ci . We further examined the order of the nine Hox genes on the chromosome by chromosome/scaffold walking. This analysis suggested a gene order of Hox1 , 11/12/13.b, 11/12/13.a, 10, 5, X, followed by either Hox4, 3, 2 or Hox2, 3, 4 on the chromosome. Based on the present results and those previously reported in Ci , we discuss the establishment of the Hox gene complement and disintegration of Hox gene clusters during the course of ascidian or tunicate evolution. The Hox gene cluster and the genome must have experienced extensive reorganization during the course of evolution from the ancestral tunicate to Hr and Ci

  8. Evolution and Diversity of Biosynthetic Gene Clusters in Fusarium

    Directory of Open Access Journals (Sweden)

    Koen Hoogendoorn

    2018-06-01

    Full Text Available Plant pathogenic fungi in the Fusarium genus cause severe damage to crops, resulting in great financial losses and health hazards. Specialized metabolites synthesized by these fungi are known to play key roles in the infection process, and to provide survival advantages inside and outside the host. However, systematic studies of the evolution of specialized metabolite-coding potential across Fusarium have been scarce. Here, we apply a combination of bioinformatic approaches to identify biosynthetic gene clusters (BGCs across publicly available genomes from Fusarium, to group them into annotated families and to study gain/loss events of BGC families throughout the history of the genus. Comparison with MIBiG reference BGCs allowed assignment of 29 gene cluster families (GCFs to pathways responsible for the production of known compounds, while for 57 GCFs, the molecular products remain unknown. Comparative analysis of BGC repertoires using ancestral state reconstruction raised several new hypotheses on how BGCs contribute to Fusarium pathogenicity or host specificity, sometimes surprisingly so: for example, a gene cluster for the biosynthesis of hexadehydro-astechrome was identified in the genome of the biocontrol strain Fusarium oxysporum Fo47, while being absent in that of the tomato pathogen F. oxysporum f.sp. lycopersici. Several BGCs were also identified on supernumerary chromosomes; heterologous expression of genes for three terpene synthases encoded on the Fusarium poae supernumerary chromosome and subsequent GC/MS analysis showed that these genes are functional and encode enzymes that each are able to synthesize koraiol; this observed functional redundancy supports the hypothesis that localization of copies of BGCs on supernumerary chromosomes provides freedom for evolutionary innovations to occur, while the original function remains conserved. Altogether, this systematic overview of biosynthetic diversity in Fusarium paves the way for

  9. Conditions for the evolution of gene clusters in bacterial genomes.

    Directory of Open Access Journals (Sweden)

    Sara Ballouz

    2010-02-01

    Full Text Available Genes encoding proteins in a common pathway are often found near each other along bacterial chromosomes. Several explanations have been proposed to account for the evolution of these structures. For instance, natural selection may directly favour gene clusters through a variety of mechanisms, such as increased efficiency of coregulation. An alternative and controversial hypothesis is the selfish operon model, which asserts that clustered arrangements of genes are more easily transferred to other species, thus improving the prospects for survival of the cluster. According to another hypothesis (the persistence model, genes that are in close proximity are less likely to be disrupted by deletions. Here we develop computational models to study the conditions under which gene clusters can evolve and persist. First, we examine the selfish operon model by re-implementing the simulation and running it under a wide range of conditions. Second, we introduce and study a Moran process in which there is natural selection for gene clustering and rearrangement occurs by genome inversion events. Finally, we develop and study a model that includes selection and inversion, which tracks the occurrence and fixation of rearrangements. Surprisingly, gene clusters fail to evolve under a wide range of conditions. Factors that promote the evolution of gene clusters include a low number of genes in the pathway, a high population size, and in the case of the selfish operon model, a high horizontal transfer rate. The computational analysis here has shown that the evolution of gene clusters can occur under both direct and indirect selection as long as certain conditions hold. Under these conditions the selfish operon model is still viable as an explanation for the evolution of gene clusters.

  10. Conditions for the Evolution of Gene Clusters in Bacterial Genomes

    Science.gov (United States)

    Ballouz, Sara; Francis, Andrew R.; Lan, Ruiting; Tanaka, Mark M.

    2010-01-01

    Genes encoding proteins in a common pathway are often found near each other along bacterial chromosomes. Several explanations have been proposed to account for the evolution of these structures. For instance, natural selection may directly favour gene clusters through a variety of mechanisms, such as increased efficiency of coregulation. An alternative and controversial hypothesis is the selfish operon model, which asserts that clustered arrangements of genes are more easily transferred to other species, thus improving the prospects for survival of the cluster. According to another hypothesis (the persistence model), genes that are in close proximity are less likely to be disrupted by deletions. Here we develop computational models to study the conditions under which gene clusters can evolve and persist. First, we examine the selfish operon model by re-implementing the simulation and running it under a wide range of conditions. Second, we introduce and study a Moran process in which there is natural selection for gene clustering and rearrangement occurs by genome inversion events. Finally, we develop and study a model that includes selection and inversion, which tracks the occurrence and fixation of rearrangements. Surprisingly, gene clusters fail to evolve under a wide range of conditions. Factors that promote the evolution of gene clusters include a low number of genes in the pathway, a high population size, and in the case of the selfish operon model, a high horizontal transfer rate. The computational analysis here has shown that the evolution of gene clusters can occur under both direct and indirect selection as long as certain conditions hold. Under these conditions the selfish operon model is still viable as an explanation for the evolution of gene clusters. PMID:20168992

  11. Time-series clustering of gene expression in irradiated and bystander fibroblasts: an application of FBPA clustering

    Directory of Open Access Journals (Sweden)

    Markatou Marianthi

    2011-01-01

    Full Text Available Abstract Background The radiation bystander effect is an important component of the overall biological response of tissues and organisms to ionizing radiation, but the signaling mechanisms between irradiated and non-irradiated bystander cells are not fully understood. In this study, we measured a time-series of gene expression after α-particle irradiation and applied the Feature Based Partitioning around medoids Algorithm (FBPA, a new clustering method suitable for sparse time series, to identify signaling modules that act in concert in the response to direct irradiation and bystander signaling. We compared our results with those of an alternate clustering method, Short Time series Expression Miner (STEM. Results While computational evaluations of both clustering results were similar, FBPA provided more biological insight. After irradiation, gene clusters were enriched for signal transduction, cell cycle/cell death and inflammation/immunity processes; but only FBPA separated clusters by function. In bystanders, gene clusters were enriched for cell communication/motility, signal transduction and inflammation processes; but biological functions did not separate as clearly with either clustering method as they did in irradiated samples. Network analysis confirmed p53 and NF-κB transcription factor-regulated gene clusters in irradiated and bystander cells and suggested novel regulators, such as KDM5B/JARID1B (lysine (K-specific demethylase 5B and HDACs (histone deacetylases, which could epigenetically coordinate gene expression after irradiation. Conclusions In this study, we have shown that a new time series clustering method, FBPA, can provide new leads to the mechanisms regulating the dynamic cellular response to radiation. The findings implicate epigenetic control of gene expression in addition to transcription factor networks.

  12. Bioinformatics Prediction of Polyketide Synthase Gene Clusters from Mycosphaerella fijiensis.

    Science.gov (United States)

    Noar, Roslyn D; Daub, Margaret E

    2016-01-01

    Mycosphaerella fijiensis, causal agent of black Sigatoka disease of banana, is a Dothideomycete fungus closely related to fungi that produce polyketides important for plant pathogenicity. We utilized the M. fijiensis genome sequence to predict PKS genes and their gene clusters and make bioinformatics predictions about the types of compounds produced by these clusters. Eight PKS gene clusters were identified in the M. fijiensis genome, placing M. fijiensis into the 23rd percentile for the number of PKS genes compared to other Dothideomycetes. Analysis of the PKS domains identified three of the PKS enzymes as non-reducing and two as highly reducing. Gene clusters contained types of genes frequently found in PKS clusters including genes encoding transporters, oxidoreductases, methyltransferases, and non-ribosomal peptide synthases. Phylogenetic analysis identified a putative PKS cluster encoding melanin biosynthesis. None of the other clusters were closely aligned with genes encoding known polyketides, however three of the PKS genes fell into clades with clusters encoding alternapyrone, fumonisin, and solanapyrone produced by Alternaria and Fusarium species. A search for homologs among available genomic sequences from 103 Dothideomycetes identified close homologs (>80% similarity) for six of the PKS sequences. One of the PKS sequences was not similar (< 60% similarity) to sequences in any of the 103 genomes, suggesting that it encodes a unique compound. Comparison of the M. fijiensis PKS sequences with those of two other banana pathogens, M. musicola and M. eumusae, showed that these two species have close homologs to five of the M. fijiensis PKS sequences, but three others were not found in either species. RT-PCR and RNA-Seq analysis showed that the melanin PKS cluster was down-regulated in infected banana as compared to growth in culture. Three other clusters, however were strongly upregulated during disease development in banana, suggesting that they may encode

  13. Bioinformatics Prediction of Polyketide Synthase Gene Clusters from Mycosphaerella fijiensis.

    Directory of Open Access Journals (Sweden)

    Roslyn D Noar

    Full Text Available Mycosphaerella fijiensis, causal agent of black Sigatoka disease of banana, is a Dothideomycete fungus closely related to fungi that produce polyketides important for plant pathogenicity. We utilized the M. fijiensis genome sequence to predict PKS genes and their gene clusters and make bioinformatics predictions about the types of compounds produced by these clusters. Eight PKS gene clusters were identified in the M. fijiensis genome, placing M. fijiensis into the 23rd percentile for the number of PKS genes compared to other Dothideomycetes. Analysis of the PKS domains identified three of the PKS enzymes as non-reducing and two as highly reducing. Gene clusters contained types of genes frequently found in PKS clusters including genes encoding transporters, oxidoreductases, methyltransferases, and non-ribosomal peptide synthases. Phylogenetic analysis identified a putative PKS cluster encoding melanin biosynthesis. None of the other clusters were closely aligned with genes encoding known polyketides, however three of the PKS genes fell into clades with clusters encoding alternapyrone, fumonisin, and solanapyrone produced by Alternaria and Fusarium species. A search for homologs among available genomic sequences from 103 Dothideomycetes identified close homologs (>80% similarity for six of the PKS sequences. One of the PKS sequences was not similar (< 60% similarity to sequences in any of the 103 genomes, suggesting that it encodes a unique compound. Comparison of the M. fijiensis PKS sequences with those of two other banana pathogens, M. musicola and M. eumusae, showed that these two species have close homologs to five of the M. fijiensis PKS sequences, but three others were not found in either species. RT-PCR and RNA-Seq analysis showed that the melanin PKS cluster was down-regulated in infected banana as compared to growth in culture. Three other clusters, however were strongly upregulated during disease development in banana, suggesting that

  14. Profiling of secondary metabolite gene clusters regulated by LaeA in Aspergillus niger FGSC A1279 based on genome sequencing and transcriptome analysis.

    Science.gov (United States)

    Wang, Bin; Lv, Yangyong; Li, Xuejie; Lin, Yiying; Deng, Hai; Pan, Li

    The global regulator LaeA controls the production of many fungal secondary metabolites, possibly via chromatin remodeling. Here we aimed to survey the secondary metabolite profile regulated by LaeA in Aspergillus niger FGSC A1279 by genome sequencing and comparative transcriptomics between the laeA deletion (ΔlaeA) and overexpressing (OE-laeA) mutants. Genome sequencing revealed four putative polyketide synthase genes specific to FGSC A1279, suggesting that the corresponding polyketide compounds might be unique to FGSC A1279. RNA-seq data revealed 281 putative secondary metabolite genes upregulated in the OE-laeA mutants, including 22 secondary metabolite backbone genes. LC-MS chemical profiling illustrated that many secondary metabolites were produced in OE-laeA mutants compared to wild type and ΔlaeA mutants, providing potential resources for drug discovery. KEGG analysis annotated 16 secondary metabolite clusters putatively linked to metabolic pathways. Furthermore, 34 of 61 Zn 2 Cys 6 transcription factors located in secondary metabolite clusters were differentially expressed between ΔlaeA and OE-laeA mutants. Three secondary metabolite clusters (cluster 18, 30 and 33) containing Zn 2 Cys 6 transcription factors that were upregulated in OE-laeA mutants were putatively linked to KEGG pathways, suggesting that Zn 2 Cys 6 transcription factors might play an important role in synthesizing secondary metabolites regulated by LaeA. Taken together, LaeA dramatically influences the secondary metabolite profile in FGSC A1279. Copyright © 2017 Institut Pasteur. Published by Elsevier Masson SAS. All rights reserved.

  15. Comparison of two schemes for automatic keyword extraction from MEDLINE for functional gene clustering.

    Science.gov (United States)

    Liu, Ying; Ciliax, Brian J; Borges, Karin; Dasigi, Venu; Ram, Ashwin; Navathe, Shamkant B; Dingledine, Ray

    2004-01-01

    One of the key challenges of microarray studies is to derive biological insights from the unprecedented quatities of data on gene-expression patterns. Clustering genes by functional keyword association can provide direct information about the nature of the functional links among genes within the derived clusters. However, the quality of the keyword lists extracted from biomedical literature for each gene significantly affects the clustering results. We extracted keywords from MEDLINE that describes the most prominent functions of the genes, and used the resulting weights of the keywords as feature vectors for gene clustering. By analyzing the resulting cluster quality, we compared two keyword weighting schemes: normalized z-score and term frequency-inverse document frequency (TFIDF). The best combination of background comparison set, stop list and stemming algorithm was selected based on precision and recall metrics. In a test set of four known gene groups, a hierarchical algorithm correctly assigned 25 of 26 genes to the appropriate clusters based on keywords extracted by the TDFIDF weighting scheme, but only 23 og 26 with the z-score method. To evaluate the effectiveness of the weighting schemes for keyword extraction for gene clusters from microarray profiles, 44 yeast genes that are differentially expressed during the cell cycle were used as a second test set. Using established measures of cluster quality, the results produced from TFIDF-weighted keywords had higher purity, lower entropy, and higher mutual information than those produced from normalized z-score weighted keywords. The optimized algorithms should be useful for sorting genes from microarray lists into functionally discrete clusters.

  16. A scale invariant clustering of genes on human chromosome 7

    Directory of Open Access Journals (Sweden)

    Kendal Wayne S

    2004-01-01

    Full Text Available Abstract Background Vertebrate genes often appear to cluster within the background of nontranscribed genomic DNA. Here an analysis of the physical distribution of gene structures on human chromosome 7 was performed to confirm the presence of clustering, and to elucidate possible underlying statistical and biological mechanisms. Results Clustering of genes was confirmed by virtue of a variance of the number of genes per unit physical length that exceeded the respective mean. Further evidence for clustering came from a power function relationship between the variance and mean that possessed an exponent of 1.51. This power function implied that the spatial distribution of genes on chromosome 7 was scale invariant, and that the underlying statistical distribution had a Poisson-gamma (PG form. A PG distribution for the spatial scattering of genes was validated by stringent comparisons of both the predicted variance to mean power function and its cumulative distribution function to data derived from chromosome 7. Conclusion The PG distribution was consistent with at least two different biological models: In the microrearrangement model, the number of genes per unit length of chromosome represented the contribution of a random number of smaller chromosomal segments that had originated by random breakage and reconstruction of more primitive chromosomes. Each of these smaller segments would have necessarily contained (on average a gamma distributed number of genes. In the gene cluster model, genes would be scattered randomly to begin with. Over evolutionary timescales, tandem duplication, mutation, insertion, deletion and rearrangement could act at these gene sites through a stochastic birth death and immigration process to yield a PG distribution. On the basis of the gene position data alone it was not possible to identify the biological model which best explained the observed clustering. However, the underlying PG statistical model implicated neutral

  17. Differential Retention of Gene Functions in a Secondary Metabolite Cluster.

    Science.gov (United States)

    Reynolds, Hannah T; Slot, Jason C; Divon, Hege H; Lysøe, Erik; Proctor, Robert H; Brown, Daren W

    2017-08-01

    In fungi, distribution of secondary metabolite (SM) gene clusters is often associated with host- or environment-specific benefits provided by SMs. In the plant pathogen Alternaria brassicicola (Dothideomycetes), the DEP cluster confers an ability to synthesize the SM depudecin, a histone deacetylase inhibitor that contributes weakly to virulence. The DEP cluster includes genes encoding enzymes, a transporter, and a transcription regulator. We investigated the distribution and evolution of the DEP cluster in 585 fungal genomes and found a wide but sporadic distribution among Dothideomycetes, Sordariomycetes, and Eurotiomycetes. We confirmed DEP gene expression and depudecin production in one fungus, Fusarium langsethiae. Phylogenetic analyses suggested 6-10 horizontal gene transfers (HGTs) of the cluster, including a transfer that led to the presence of closely related cluster homologs in Alternaria and Fusarium. The analyses also indicated that HGTs were frequently followed by loss/pseudogenization of one or more DEP genes. Independent cluster inactivation was inferred in at least four fungal classes. Analyses of transitions among functional, pseudogenized, and absent states of DEP genes among Fusarium species suggest enzyme-encoding genes are lost at higher rates than the transporter (DEP3) and regulatory (DEP6) genes. The phenotype of an experimentally-induced DEP3 mutant of Fusarium did not support the hypothesis that selective retention of DEP3 and DEP6 protects fungi from exogenous depudecin. Together, the results suggest that HGT and gene loss have contributed significantly to DEP cluster distribution, and that some DEP genes provide a greater fitness benefit possibly due to a differential tendency to form network connections. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution 2017. This work is written by US Government employees and is in the public domain in the US.

  18. Statistical indicators of collective behavior and functional clusters in gene networks of yeast

    Science.gov (United States)

    Živković, J.; Tadić, B.; Wick, N.; Thurner, S.

    2006-03-01

    We analyze gene expression time-series data of yeast (S. cerevisiae) measured along two full cell-cycles. We quantify these data by using q-exponentials, gene expression ranking and a temporal mean-variance analysis. We construct gene interaction networks based on correlation coefficients and study the formation of the corresponding giant components and minimum spanning trees. By coloring genes according to their cell function we find functional clusters in the correlation networks and functional branches in the associated trees. Our results suggest that a percolation point of functional clusters can be identified on these gene expression correlation networks.

  19. Spanning Tree Based Attribute Clustering

    DEFF Research Database (Denmark)

    Zeng, Yifeng; Jorge, Cordero Hernandez

    2009-01-01

    Attribute clustering has been previously employed to detect statistical dependence between subsets of variables. We propose a novel attribute clustering algorithm motivated by research of complex networks, called the Star Discovery algorithm. The algorithm partitions and indirectly discards...... inconsistent edges from a maximum spanning tree by starting appropriate initial modes, therefore generating stable clusters. It discovers sound clusters through simple graph operations and achieves significant computational savings. We compare the Star Discovery algorithm against earlier attribute clustering...

  20. HOXA genes cluster: clinical implications of the smallest deletion

    OpenAIRE

    Pezzani, Lidia; Milani, Donatella; Manzoni, Francesca; Baccarin, Marco; Silipigni, Rosamaria; Guerneri, Silvana; Esposito, Susanna

    2015-01-01

    Background HOXA genes cluster plays a fundamental role in embryologic development. Deletion of the entire cluster is known to cause a clinically recognizable syndrome with mild developmental delay, characteristic facies, small feet with unusually short and big halluces, abnormal thumbs, and urogenital malformations. The clinical manifestations may vary with different ranges of deletions of HOXA cluster and flanking regions. Case presentation We report a girl with the smallest deletion reporte...

  1. Minimum Information about a Biosynthetic Gene cluster : commentary

    NARCIS (Netherlands)

    Medema, Marnix H; Kottmann, Renzo; Yilmaz, Pelin; Cummings, Matthew; Biggins, John B; Blin, Kai; de Bruijn, Irene; Chooi, Yit Heng; Claesen, Jan; Coates, R Cameron; Cruz-Morales, Pablo; Duddela, Srikanth; Dusterhus, Stephanie; Edwards, Daniel J; Fewer, David P; Garg, Neha; Geiger, Christoph; Gomez-Escribano, Juan Pablo; Greule, Anja; Hadjithomas, Michalis; Haines, Anthony S; Helfrich, Eric J N; Hillwig, Matthew L; Ishida, Keishi; Jones, Adam C; Jones, Carla S; Jungmann, Katrin; Kegler, Carsten; Kim, Hyun Uk; Kotter, Peter; Krug, Daniel; Masschelein, Joleen; Melnik, Alexey V; Mantovani, Simone M; Monroe, Emily A; Moore, Marcus; Moss, Nathan; Nutzmann, Hans-Wilhelm; Pan, Guohui; Pati, Amrita; Petras, Daniel; Reen, F Jerry; Rosconi, Federico; Rui, Zhe; Tian, Zhenhua; Tobias, Nicholas J; Tsunematsu, Yuta; Wiemann, Philipp; Wyckoff, Elizabeth; Yan, Xiaohui; Yim, Grace; Yu, Fengan; Xie, Yunchang; Aigle, Bertrand; Apel, Alexander K; Balibar, Carl J; Balskus, Emily P; Barona-Gomez, Francisco; Bechthold, Andreas; Bode, Helge B; Borriss, Rainer; Brady, Sean F; Brakhage, Axel A; Caffrey, Patrick; Cheng, Yi-Qiang; Clardy, Jon; Cox, Russell J; De Mot, Rene; Donadio, Stefano; Donia, Mohamed S; van der Donk, Wilfred A; Dorrestein, Pieter C; Doyle, Sean; Driessen, Arnold J M; Ehling-Schulz, Monika; Entian, Karl-Dieter; Fischbach, Michael A; Gerwick, Lena; Gerwick, William H; Gross, Harald; Gust, Bertolt; Hertweck, Christian; Hofte, Monica; Jensen, Susan E; Ju, Jianhua; Katz, Leonard; Kaysser, Leonard; Klassen, Jonathan L; Keller, Nancy P; Kormanec, Jan; Kuipers, Oscar P; Kuzuyama, Tomohisa; Kyrpides, Nikos C; Kwon, Hyung-Jin; Lautru, Sylvie; Lavigne, Rob; Lee, Chia Y; Linquan, Bai; Liu, Xinyu; Liu, Wen; Luzhetskyy, Andriy; Mahmud, Taifo; Mast, Yvonne; Mendez, Carmen; Metsa-Ketela, Mikko; Micklefield, Jason; Mitchell, Douglas A; Moore, Bradley S; Moreira, Leonilde M; Muller, Rolf; Neilan, Brett A; Nett, Markus; Nielsen, Jens; O'Gara, Fergal; Oikawa, Hideaki; Osbourn, Anne; Osburne, Marcia S; Ostash, Bohdan; Payne, Shelley M; Pernodet, Jean-Luc; Petricek, Miroslav; Piel, Jorn; Ploux, Olivier; Raaijmakers, Jos M; Salas, Jose A; Schmitt, Esther K; Scott, Barry; Seipke, Ryan F; Shen, Ben; Sherman, David H; Sivonen, Kaarina; Smanski, Michael J; Sosio, Margherita; Stegmann, Evi; Sussmuth, Roderich D; Tahlan, Kapil; Thomas, Christopher M; Tang, Yi; Truman, Andrew W; Viaud, Muriel; Walton, Jonathan D; Walsh, Christopher T; Weber, Tilmann; van Wezel, Gilles P; Wilkinson, Barrie; Willey, Joanne M; Wohlleben, Wolfgang; Wright, Gerard D; Ziemert, Nadine; Zhang, Changsheng; Zotchev, Sergey B; Breitling, Rainer; Takano, Eriko; Glockner, Frank Oliver

    A wide variety of enzymatic pathways that produce specialized metabolites in bacteria, fungi and plants are known to be encoded in biosynthetic gene clusters. Information about these clusters, pathways and metabolites is currently dispersed throughout the literature, making it difficult to exploit.

  2. Progressive Exponential Clustering-Based Steganography

    Directory of Open Access Journals (Sweden)

    Li Yue

    2010-01-01

    Full Text Available Cluster indexing-based steganography is an important branch of data-hiding techniques. Such schemes normally achieve good balance between high embedding capacity and low embedding distortion. However, most cluster indexing-based steganographic schemes utilise less efficient clustering algorithms for embedding data, which causes redundancy and leaves room for increasing the embedding capacity further. In this paper, a new clustering algorithm, called progressive exponential clustering (PEC, is applied to increase the embedding capacity by avoiding redundancy. Meanwhile, a cluster expansion algorithm is also developed in order to further increase the capacity without sacrificing imperceptibility.

  3. Hox gene clusters in the Indonesian coelacanth, Latimeria menadoensis

    Science.gov (United States)

    Koh, Esther G. L.; Lam, Kevin; Christoffels, Alan; Erdmann, Mark V.; Brenner, Sydney; Venkatesh, Byrappa

    2003-01-01

    The Hox genes encode transcription factors that play a key role in specifying body plans of metazoans. They are organized into clusters that contain up to 13 paralogue group members. The complex morphology of vertebrates has been attributed to the duplication of Hox clusters during vertebrate evolution. In contrast to the single Hox cluster in the amphioxus (Branchiostoma floridae), an invertebrate-chordate, mammals have four clusters containing 39 Hox genes. Ray-finned fishes (Actinopterygii) such as zebrafish and fugu possess more than four Hox clusters. The coelacanth occupies a basal phylogenetic position among lobe-finned fishes (Sarcopterygii), which gave rise to the tetrapod lineage. The lobe fins of sarcopterygians are considered to be the evolutionary precursors of tetrapod limbs. Thus, the characterization of Hox genes in the coelacanth should provide insights into the origin of tetrapod limbs. We have cloned the complete second exon of 33 Hox genes from the Indonesian coelacanth, Latimeria menadoensis, by extensive PCR survey and genome walking. Phylogenetic analysis shows that 32 of these genes have orthologs in the four mammalian HOX clusters, including three genes (HoxA6, D1, and D8) that are absent in ray-finned fishes. The remaining coelacanth gene is an ortholog of hoxc1 found in zebrafish but absent in mammals. Our results suggest that coelacanths have four Hox clusters bearing a gene complement more similar to mammals than to ray-finned fishes, but with an additional gene, HoxC1, which has been lost during the evolution of mammals from lobe-finned fishes. PMID:12547909

  4. Deletion and Gene Expression Analyses Define the Paxilline Biosynthetic Gene Cluster in Penicillium paxilli

    Directory of Open Access Journals (Sweden)

    Emily J. Parker

    2013-08-01

    Full Text Available The indole-diterpene paxilline is an abundant secondary metabolite synthesized by Penicillium paxilli. In total, 21 genes have been identified at the PAX locus of which six have been previously confirmed to have a functional role in paxilline biosynthesis. A combination of bioinformatics, gene expression and targeted gene replacement analyses were used to define the boundaries of the PAX gene cluster. Targeted gene replacement identified seven genes, paxG, paxA, paxM, paxB, paxC, paxP and paxQ that were all required for paxilline production, with one additional gene, paxD, required for regular prenylation of the indole ring post paxilline synthesis. The two putative transcription factors, PP104 and PP105, were not co-regulated with the pax genes and based on targeted gene replacement, including the double knockout, did not have a role in paxilline production. The relationship of indole dimethylallyl transferases involved in prenylation of indole-diterpenes such as paxilline or lolitrem B, can be found as two disparate clades, not supported by prenylation type (e.g., regular or reverse. This paper provides insight into the P. paxilli indole-diterpene locus and reviews the recent advances identified in paxilline biosynthesis.

  5. Classical Music Clustering Based on Acoustic Features

    OpenAIRE

    Wang, Xindi; Haque, Syed Arefinul

    2017-01-01

    In this paper we cluster 330 classical music pieces collected from MusicNet database based on their musical note sequence. We use shingling and chord trajectory matrices to create signature for each music piece and performed spectral clustering to find the clusters. Based on different resolution, the output clusters distinctively indicate composition from different classical music era and different composing style of the musicians.

  6. An Effective Tri-Clustering Algorithm Combining Expression Data with Gene Regulation Information

    Directory of Open Access Journals (Sweden)

    Ao Li

    2009-04-01

    Full Text Available Motivation: Bi-clustering algorithms aim to identify sets of genes sharing similar expression patterns across a subset of conditions. However direct interpretation or prediction of gene regulatory mechanisms may be difficult as only gene expression data is used. Information about gene regulators may also be available, most commonly about which transcription factors may bind to the promoter region and thus control the expression level of a gene. Thus a method to integrate gene expression and gene regulation information is desirable for clustering and analyzing. Methods: By incorporating gene regulatory information with gene expression data, we define regulated expression values (REV as indicators of how a gene is regulated by a specific factor. Existing bi-clustering methods are extended to a three dimensional data space by developing a heuristic TRI-Clustering algorithm. An additional approach named Automatic Boundary Searching algorithm (ABS is introduced to automatically determine the boundary threshold. Results: Results based on incorporating ChIP-chip data representing transcription factor-gene interactions show that the algorithms are efficient and robust for detecting tri-clusters. Detailed analysis of the tri-cluster extracted from yeast sporulation REV data shows genes in this cluster exhibited significant differences during the middle and late stages. The implicated regulatory network was then reconstructed for further study of defined regulatory mechanisms. Topological and statistical analysis of this network demonstrated evidence of significant changes of TF activities during the different stages of yeast sporulation, and suggests this approach might be a general way to study regulatory networks undergoing transformations.

  7. Variations in CCL3L gene cluster sequence and non-specific gene copy numbers

    Directory of Open Access Journals (Sweden)

    Edberg Jeffrey C

    2010-03-01

    Full Text Available Abstract Background Copy number variations (CNVs of the gene CC chemokine ligand 3-like1 (CCL3L1 have been implicated in HIV-1 susceptibility, but the association has been inconsistent. CCL3L1 shares homology with a cluster of genes localized to chromosome 17q12, namely CCL3, CCL3L2, and, CCL3L3. These genes are involved in host defense and inflammatory processes. Several CNV assays have been developed for the CCL3L1 gene. Findings Through pairwise and multiple alignments of these genes, we have shown that the homology between these genes ranges from 50% to 99% in complete gene sequences and from 70-100% in the exonic regions, with CCL3L1 and CCL3L3 being identical. By use of MEGA 4 and BioEdit, we aligned sense primers, anti-sense primers, and probes used in several previously described assays against pre-multiple alignments of all four chemokine genes. Each set of probes and primers aligned and matched with overlapping sequences in at least two of the four genes, indicating that previously utilized RT-PCR based CNV assays are not specific for only CCL3L1. The four available assays measured median copies of 2 and 3-4 in European and African American, respectively. The concordance between the assays ranged from 0.44-0.83 suggesting individual discordant calls and inconsistencies with the assays from the expected gene coverage from the known sequence. Conclusions This indicates that some of the inconsistencies in the association studies could be due to assays that provide heterogenous results. Sequence information to determine CNV of the three genes separately would allow to test whether their association with the pathogenesis of a human disease or phenotype is affected by an individual gene or by a combination of these genes.

  8. Gravitation field algorithm and its application in gene cluster

    Directory of Open Access Journals (Sweden)

    Zheng Ming

    2010-09-01

    Full Text Available Abstract Background Searching optima is one of the most challenging tasks in clustering genes from available experimental data or given functions. SA, GA, PSO and other similar efficient global optimization methods are used by biotechnologists. All these algorithms are based on the imitation of natural phenomena. Results This paper proposes a novel searching optimization algorithm called Gravitation Field Algorithm (GFA which is derived from the famous astronomy theory Solar Nebular Disk Model (SNDM of planetary formation. GFA simulates the Gravitation field and outperforms GA and SA in some multimodal functions optimization problem. And GFA also can be used in the forms of unimodal functions. GFA clusters the dataset well from the Gene Expression Omnibus. Conclusions The mathematical proof demonstrates that GFA could be convergent in the global optimum by probability 1 in three conditions for one independent variable mass functions. In addition to these results, the fundamental optimization concept in this paper is used to analyze how SA and GA affect the global search and the inherent defects in SA and GA. Some results and source code (in Matlab are publicly available at http://ccst.jlu.edu.cn/CSBG/GFA.

  9. Integrating Data Clustering and Visualization for the Analysis of 3D Gene Expression Data

    Energy Technology Data Exchange (ETDEWEB)

    Data Analysis and Visualization (IDAV) and the Department of Computer Science, University of California, Davis, One Shields Avenue, Davis CA 95616, USA,; nternational Research Training Group ``Visualization of Large and Unstructured Data Sets,' ' University of Kaiserslautern, Germany; Computational Research Division, Lawrence Berkeley National Laboratory, One Cyclotron Road, Berkeley, CA 94720, USA; Genomics Division, Lawrence Berkeley National Laboratory, One Cyclotron Road, Berkeley CA 94720, USA; Life Sciences Division, Lawrence Berkeley National Laboratory, One Cyclotron Road, Berkeley CA 94720, USA,; Computer Science Division,University of California, Berkeley, CA, USA,; Computer Science Department, University of California, Irvine, CA, USA,; All authors are with the Berkeley Drosophila Transcription Network Project, Lawrence Berkeley National Laboratory,; Rubel, Oliver; Weber, Gunther H.; Huang, Min-Yu; Bethel, E. Wes; Biggin, Mark D.; Fowlkes, Charless C.; Hendriks, Cris L. Luengo; Keranen, Soile V. E.; Eisen, Michael B.; Knowles, David W.; Malik, Jitendra; Hagen, Hans; Hamann, Bernd

    2008-05-12

    The recent development of methods for extracting precise measurements of spatial gene expression patterns from three-dimensional (3D) image data opens the way for new analyses of the complex gene regulatory networks controlling animal development. We present an integrated visualization and analysis framework that supports user-guided data clustering to aid exploration of these new complex datasets. The interplay of data visualization and clustering-based data classification leads to improved visualization and enables a more detailed analysis than previously possible. We discuss (i) integration of data clustering and visualization into one framework; (ii) application of data clustering to 3D gene expression data; (iii) evaluation of the number of clusters k in the context of 3D gene expression clustering; and (iv) improvement of overall analysis quality via dedicated post-processing of clustering results based on visualization. We discuss the use of this framework to objectively define spatial pattern boundaries and temporal profiles of genes and to analyze how mRNA patterns are controlled by their regulatory transcription factors.

  10. Characterization of the largest effector gene cluster of Ustilago maydis.

    Directory of Open Access Journals (Sweden)

    Thomas Brefort

    2014-07-01

    Full Text Available In the genome of the biotrophic plant pathogen Ustilago maydis, many of the genes coding for secreted protein effectors modulating virulence are arranged in gene clusters. The vast majority of these genes encode novel proteins whose expression is coupled to plant colonization. The largest of these gene clusters, cluster 19A, encodes 24 secreted effectors. Deletion of the entire cluster results in severe attenuation of virulence. Here we present the functional analysis of this genomic region. We show that a 19A deletion mutant behaves like an endophyte, i.e. is still able to colonize plants and complete the infection cycle. However, tumors, the most conspicuous symptoms of maize smut disease, are only rarely formed and fungal biomass in infected tissue is significantly reduced. The generation and analysis of strains carrying sub-deletions identified several genes significantly contributing to tumor formation after seedling infection. Another of the effectors could be linked specifically to anthocyanin induction in the infected tissue. As the individual contributions of these genes to tumor formation were small, we studied the response of maize plants to the whole cluster mutant as well as to several individual mutants by array analysis. This revealed distinct plant responses, demonstrating that the respective effectors have discrete plant targets. We propose that the analysis of plant responses to effector mutant strains that lack a strong virulence phenotype may be a general way to visualize differences in effector function.

  11. Identification of nitrogen-fixing genes and gene clusters from metagenomic library of acid mine drainage.

    Science.gov (United States)

    Dai, Zhimin; Guo, Xue; Yin, Huaqun; Liang, Yili; Cong, Jing; Liu, Xueduan

    2014-01-01

    Biological nitrogen fixation is an essential function of acid mine drainage (AMD) microbial communities. However, most acidophiles in AMD environments are uncultured microorganisms and little is known about the diversity of nitrogen-fixing genes and structure of nif gene cluster in AMD microbial communities. In this study, we used metagenomic sequencing to isolate nif genes in the AMD microbial community from Dexing Copper Mine, China. Meanwhile, a metagenome microarray containing 7,776 large-insertion fosmids was constructed to screen novel nif gene clusters. Metagenomic analyses revealed that 742 sequences were identified as nif genes including structural subunit genes nifH, nifD, nifK and various additional genes. The AMD community is massively dominated by the genus Acidithiobacillus. However, the phylogenetic diversity of nitrogen-fixing microorganisms is much higher than previously thought in the AMD community. Furthermore, a 32.5-kb genomic sequence harboring nif, fix and associated genes was screened by metagenome microarray. Comparative genome analysis indicated that most nif genes in this cluster are most similar to those of Herbaspirillum seropedicae, but the organization of the nif gene cluster had significant differences from H. seropedicae. Sequence analysis and reverse transcription PCR also suggested that distinct transcription units of nif genes exist in this gene cluster. nifQ gene falls into the same transcription unit with fixABCX genes, which have not been reported in other diazotrophs before. All of these results indicated that more novel diazotrophs survive in the AMD community.

  12. Identification of nitrogen-fixing genes and gene clusters from metagenomic library of acid mine drainage.

    Directory of Open Access Journals (Sweden)

    Zhimin Dai

    Full Text Available Biological nitrogen fixation is an essential function of acid mine drainage (AMD microbial communities. However, most acidophiles in AMD environments are uncultured microorganisms and little is known about the diversity of nitrogen-fixing genes and structure of nif gene cluster in AMD microbial communities. In this study, we used metagenomic sequencing to isolate nif genes in the AMD microbial community from Dexing Copper Mine, China. Meanwhile, a metagenome microarray containing 7,776 large-insertion fosmids was constructed to screen novel nif gene clusters. Metagenomic analyses revealed that 742 sequences were identified as nif genes including structural subunit genes nifH, nifD, nifK and various additional genes. The AMD community is massively dominated by the genus Acidithiobacillus. However, the phylogenetic diversity of nitrogen-fixing microorganisms is much higher than previously thought in the AMD community. Furthermore, a 32.5-kb genomic sequence harboring nif, fix and associated genes was screened by metagenome microarray. Comparative genome analysis indicated that most nif genes in this cluster are most similar to those of Herbaspirillum seropedicae, but the organization of the nif gene cluster had significant differences from H. seropedicae. Sequence analysis and reverse transcription PCR also suggested that distinct transcription units of nif genes exist in this gene cluster. nifQ gene falls into the same transcription unit with fixABCX genes, which have not been reported in other diazotrophs before. All of these results indicated that more novel diazotrophs survive in the AMD community.

  13. Identification of Nitrogen-Fixing Genes and Gene Clusters from Metagenomic Library of Acid Mine Drainage

    Science.gov (United States)

    Yin, Huaqun; Liang, Yili; Cong, Jing; Liu, Xueduan

    2014-01-01

    Biological nitrogen fixation is an essential function of acid mine drainage (AMD) microbial communities. However, most acidophiles in AMD environments are uncultured microorganisms and little is known about the diversity of nitrogen-fixing genes and structure of nif gene cluster in AMD microbial communities. In this study, we used metagenomic sequencing to isolate nif genes in the AMD microbial community from Dexing Copper Mine, China. Meanwhile, a metagenome microarray containing 7,776 large-insertion fosmids was constructed to screen novel nif gene clusters. Metagenomic analyses revealed that 742 sequences were identified as nif genes including structural subunit genes nifH, nifD, nifK and various additional genes. The AMD community is massively dominated by the genus Acidithiobacillus. However, the phylogenetic diversity of nitrogen-fixing microorganisms is much higher than previously thought in the AMD community. Furthermore, a 32.5-kb genomic sequence harboring nif, fix and associated genes was screened by metagenome microarray. Comparative genome analysis indicated that most nif genes in this cluster are most similar to those of Herbaspirillum seropedicae, but the organization of the nif gene cluster had significant differences from H. seropedicae. Sequence analysis and reverse transcription PCR also suggested that distinct transcription units of nif genes exist in this gene cluster. nifQ gene falls into the same transcription unit with fixABCX genes, which have not been reported in other diazotrophs before. All of these results indicated that more novel diazotrophs survive in the AMD community. PMID:24498417

  14. Efficient clustering aggregation based on data fragments.

    Science.gov (United States)

    Wu, Ou; Hu, Weiming; Maybank, Stephen J; Zhu, Mingliang; Li, Bing

    2012-06-01

    Clustering aggregation, known as clustering ensembles, has emerged as a powerful technique for combining different clustering results to obtain a single better clustering. Existing clustering aggregation algorithms are applied directly to data points, in what is referred to as the point-based approach. The algorithms are inefficient if the number of data points is large. We define an efficient approach for clustering aggregation based on data fragments. In this fragment-based approach, a data fragment is any subset of the data that is not split by any of the clustering results. To establish the theoretical bases of the proposed approach, we prove that clustering aggregation can be performed directly on data fragments under two widely used goodness measures for clustering aggregation taken from the literature. Three new clustering aggregation algorithms are described. The experimental results obtained using several public data sets show that the new algorithms have lower computational complexity than three well-known existing point-based clustering aggregation algorithms (Agglomerative, Furthest, and LocalSearch); nevertheless, the new algorithms do not sacrifice the accuracy.

  15. GenCLiP 2.0: a web server for functional clustering of genes and construction of molecular networks based on free terms.

    Science.gov (United States)

    Wang, Jia-Hong; Zhao, Ling-Feng; Lin, Pei; Su, Xiao-Rong; Chen, Shi-Jun; Huang, Li-Qiang; Wang, Hua-Feng; Zhang, Hai; Hu, Zhen-Fu; Yao, Kai-Tai; Huang, Zhong-Xi

    2014-09-01

    Identifying biological functions and molecular networks in a gene list and how the genes may relate to various topics is of considerable value to biomedical researchers. Here, we present a web-based text-mining server, GenCLiP 2.0, which can analyze human genes with enriched keywords and molecular interactions. Compared with other similar tools, GenCLiP 2.0 offers two unique features: (i) analysis of gene functions with free terms (i.e. any terms in the literature) generated by literature mining or provided by the user and (ii) accurate identification and integration of comprehensive molecular interactions from Medline abstracts, to construct molecular networks and subnetworks related to the free terms. http://ci.smu.edu.cn. Supplementary data are available at Bioinformatics online. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

  16. Ensemble attribute profile clustering: discovering and characterizing groups of genes with similar patterns of biological features

    Directory of Open Access Journals (Sweden)

    Bissell MJ

    2006-03-01

    Full Text Available Abstract Background Ensemble attribute profile clustering is a novel, text-based strategy for analyzing a user-defined list of genes and/or proteins. The strategy exploits annotation data present in gene-centered corpora and utilizes ideas from statistical information retrieval to discover and characterize properties shared by subsets of the list. The practical utility of this method is demonstrated by employing it in a retrospective study of two non-overlapping sets of genes defined by a published investigation as markers for normal human breast luminal epithelial cells and myoepithelial cells. Results Each genetic locus was characterized using a finite set of biological properties and represented as a vector of features indicating attributes associated with the locus (a gene attribute profile. In this study, the vector space models for a pre-defined list of genes were constructed from the Gene Ontology (GO terms and the Conserved Domain Database (CDD protein domain terms assigned to the loci by the gene-centered corpus LocusLink. This data set of GO- and CDD-based gene attribute profiles, vectors of binary random variables, was used to estimate multiple finite mixture models and each ensuing model utilized to partition the profiles into clusters. The resultant partitionings were combined using a unanimous voting scheme to produce consensus clusters, sets of profiles that co-occured consistently in the same cluster. Attributes that were important in defining the genes assigned to a consensus cluster were identified. The clusters and their attributes were inspected to ascertain the GO and CDD terms most associated with subsets of genes and in conjunction with external knowledge such as chromosomal location, used to gain functional insights into human breast biology. The 52 luminal epithelial cell markers and 89 myoepithelial cell markers are disjoint sets of genes. Ensemble attribute profile clustering-based analysis indicated that both lists

  17. Scalable Density-Based Subspace Clustering

    DEFF Research Database (Denmark)

    Müller, Emmanuel; Assent, Ira; Günnemann, Stephan

    2011-01-01

    For knowledge discovery in high dimensional databases, subspace clustering detects clusters in arbitrary subspace projections. Scalability is a crucial issue, as the number of possible projections is exponential in the number of dimensions. We propose a scalable density-based subspace clustering...... method that steers mining to few selected subspace clusters. Our novel steering technique reduces subspace processing by identifying and clustering promising subspaces and their combinations directly. Thereby, it narrows down the search space while maintaining accuracy. Thorough experiments on real...... and synthetic databases show that steering is efficient and scalable, with high quality results. For future work, our steering paradigm for density-based subspace clustering opens research potential for speeding up other subspace clustering approaches as well....

  18. Calcitonin gene-related peptide antagonism and cluster headache

    DEFF Research Database (Denmark)

    Ashina, Håkan; Newman, Lawrence; Ashina, Sait

    2017-01-01

    Calcitonin gene-related peptide (CGRP) is a key signaling molecule involved in migraine pathophysiology. Efficacy of CGRP monoclonal antibodies and antagonists in migraine treatment has fueled an increasing interest in the prospect of treating cluster headache (CH) with CGRP antagonism. The exact...... role of CGRP and its mechanism of action in CH have not been fully clarified. A search for original studies and randomized controlled trials (RCTs) published in English was performed in PubMed and in ClinicalTrials.gov . The search term used was "cluster headache and calcitonin gene related peptide......" and "primary headaches and calcitonin gene related peptide." Reference lists of identified articles were also searched for additional relevant papers. Human experimental studies have reported elevated plasma CGRP levels during both spontaneous and glyceryl trinitrate-induced cluster attacks. CGRP may play...

  19. A recently transferred cluster of bacterial genes in Trichomonas vaginalis - lateral gene transfer and the fate of acquired genes

    Science.gov (United States)

    2014-01-01

    Background Lateral Gene Transfer (LGT) has recently gained recognition as an important contributor to some eukaryote proteomes, but the mechanisms of acquisition and fixation in eukaryotic genomes are still uncertain. A previously defined norm for LGTs in microbial eukaryotes states that the majority are genes involved in metabolism, the LGTs are typically localized one by one, surrounded by vertically inherited genes on the chromosome, and phylogenetics shows that a broad collection of bacterial lineages have contributed to the transferome. Results A unique 34 kbp long fragment with 27 clustered genes (TvLF) of prokaryote origin was identified in the sequenced genome of the protozoan parasite Trichomonas vaginalis. Using a PCR based approach we confirmed the presence of the orthologous fragment in four additional T. vaginalis strains. Detailed sequence analyses unambiguously suggest that TvLF is the result of one single, recent LGT event. The proposed donor is a close relative to the firmicute bacterium Peptoniphilus harei. High nucleotide sequence similarity between T. vaginalis strains, as well as to P. harei, and the absence of homologs in other Trichomonas species, suggests that the transfer event took place after the radiation of the genus Trichomonas. Some genes have undergone pseudogenization and degradation, indicating that they may not be retained in the future. Functional annotations reveal that genes involved in informational processes are particularly prone to degradation. Conclusions We conclude that, although the majority of eukaryote LGTs are single gene occurrences, they may be acquired in clusters of several genes that are subsequently cleansed of evolutionarily less advantageous genes. PMID:24898731

  20. Fine Mapping of Two Wheat Powdery Mildew Resistance Genes Located at the Pm1 Cluster

    Directory of Open Access Journals (Sweden)

    Junchao Liang

    2016-07-01

    Full Text Available Powdery mildew caused by (DC. f. sp. ( is a globally devastating foliar disease of wheat ( L.. More than a dozen genes against this disease, identified from wheat germplasms of different ploidy levels, have been mapped to the region surrounding the locus on the long arm of chromosome 7A, which forms a resistance (-gene cluster. and from einkorn wheat ( L. were two of the genes belonging to this cluster. This study was initiated to fine map these two genes toward map-based cloning. Comparative genomics study showed that macrocolinearity exists between L. chromosome 1 (Bd1 and the – region, which allowed us to develop markers based on the wheat sequences orthologous to genes contained in the Bd1 region. With these and other newly developed and published markers, high-resolution maps were constructed for both and using large F populations. Moreover, a physical map of was constructed through chromosome walking with bacterial artificial chromosome (BAC clones and comparative mapping. Eventually, and were restricted to a 0.12- and 0.86-cM interval, respectively. Based on the closely linked common markers, , , and (another powdery mildew resistance gene in the cluster were not allelic to one another. Severe recombination suppression and disruption of synteny were noted in the region encompassing . These results provided useful information for map-based cloning of the genes in the cluster and interpretation of their evolution.

  1. IGSA: Individual Gene Sets Analysis, including Enrichment and Clustering.

    Science.gov (United States)

    Wu, Lingxiang; Chen, Xiujie; Zhang, Denan; Zhang, Wubing; Liu, Lei; Ma, Hongzhe; Yang, Jingbo; Xie, Hongbo; Liu, Bo; Jin, Qing

    2016-01-01

    Analysis of gene sets has been widely applied in various high-throughput biological studies. One weakness in the traditional methods is that they neglect the heterogeneity of genes expressions in samples which may lead to the omission of some specific and important gene sets. It is also difficult for them to reflect the severities of disease and provide expression profiles of gene sets for individuals. We developed an application software called IGSA that leverages a powerful analytical capacity in gene sets enrichment and samples clustering. IGSA calculates gene sets expression scores for each sample and takes an accumulating clustering strategy to let the samples gather into the set according to the progress of disease from mild to severe. We focus on gastric, pancreatic and ovarian cancer data sets for the performance of IGSA. We also compared the results of IGSA in KEGG pathways enrichment with David, GSEA, SPIA, ssGSEA and analyzed the results of IGSA clustering and different similarity measurement methods. Notably, IGSA is proved to be more sensitive and specific in finding significant pathways, and can indicate related changes in pathways with the severity of disease. In addition, IGSA provides with significant gene sets profile for each sample.

  2. Genetic association of HCRTR2, ADH4 and CLOCK genes with cluster headache: a Chinese population-based case-control study.

    Science.gov (United States)

    Fan, Zhiliang; Hou, Lei; Wan, Dongjun; Ao, Ran; Zhao, Dengfa; Yu, Shengyuan

    2018-01-09

    Cluster headache (CH), a rare primary headache disorder, is currently thought to be a genetic susceptibility which play a role in CH susceptibility. A large numbers of genetic association studies have confirmed that the HCRTR2 (Hypocretin Receptor 2) SNP rs2653349, and the ADH4 (Alcohol Dehydrogenase 4) SNP rs1126671 and rs1800759 polymorphisms are linked to CH. In addition, the CLOCK (Circadian Locomotor Output Cycles Kaput) gene is becoming a research hotspot for CH due to encoding a transcription factor that serves as a basic driving force for circadian rhythm in humans. The purpose of this study was to evaluate the association between CH and the HCRTR2, ADH4 and CLOCK genes in a Chinese CH case-control sample. We genotyped polymorphisms of nine single nucleotide polymorphisms (SNPs) in the HCRTR2, ADH4 and CLOCK genes to perform an association study on a Chinese Han CH case-control sample (112 patients and 192 controls),using Sequenom MALDI-TOF mass spectrometry iPLEX platform. The frequencies and distributions of genotypes and haplotypes were statistically compared between the case and control groups to identify associations with CH. The effects of SNPs on CH were further investigated by multiple logistic regression. The frequency of the HCRTR2 SNP rs3800539 GA genotype was significantly higher in cases than in controls (48.2% vs.37.0%). The GA genotypes was associated with a higher CH risk (OR = 1.483, 95% CI: 0.564-3.387, p = 0.038), however, after Bonferroni correction, the association lost statistical significance. Haplotype analysis of the HCRTR2 SNPs showed that among eight haplotypes, only H1-GTGGGG was linked to a reduced CH risk (44.7% vs. 53.1%, OR = 0.689, 95% CI =0.491~0.966, p = 0.030). No significant association of ADH4, CLOCK SNPs with CH was statistically detected in the present study. Association between HCRTR2, ADH4,CLOCK gene polymorphisms and CH was not significant in the present study, however, haplotype analysis indicated

  3. The Local Maximum Clustering Method and Its Application in Microarray Gene Expression Data Analysis

    Directory of Open Access Journals (Sweden)

    Chen Yidong

    2004-01-01

    Full Text Available An unsupervised data clustering method, called the local maximum clustering (LMC method, is proposed for identifying clusters in experiment data sets based on research interest. A magnitude property is defined according to research purposes, and data sets are clustered around each local maximum of the magnitude property. By properly defining a magnitude property, this method can overcome many difficulties in microarray data clustering such as reduced projection in similarities, noises, and arbitrary gene distribution. To critically evaluate the performance of this clustering method in comparison with other methods, we designed three model data sets with known cluster distributions and applied the LMC method as well as the hierarchic clustering method, the -mean clustering method, and the self-organized map method to these model data sets. The results show that the LMC method produces the most accurate clustering results. As an example of application, we applied the method to cluster the leukemia samples reported in the microarray study of Golub et al. (1999.

  4. CORECLUSTER: A Degeneracy Based Graph Clustering Framework

    OpenAIRE

    Giatsidis , Christos; Malliaros , Fragkiskos; Thilikos , Dimitrios M. ,; Vazirgiannis , Michalis

    2014-01-01

    International audience; Graph clustering or community detection constitutes an important task forinvestigating the internal structure of graphs, with a plethora of applications in several domains. Traditional tools for graph clustering, such asspectral methods, typically suffer from high time and space complexity. In thisarticle, we present \\textsc{CoreCluster}, an efficient graph clusteringframework based on the concept of graph degeneracy, that can be used along withany known graph clusteri...

  5. Gene identification and protein classification in microbial metagenomic sequence data via incremental clustering

    Directory of Open Access Journals (Sweden)

    Li Weizhong

    2008-04-01

    Full Text Available Abstract Background The identification and study of proteins from metagenomic datasets can shed light on the roles and interactions of the source organisms in their communities. However, metagenomic datasets are characterized by the presence of organisms with varying GC composition, codon usage biases etc., and consequently gene identification is challenging. The vast amount of sequence data also requires faster protein family classification tools. Results We present a computational improvement to a sequence clustering approach that we developed previously to identify and classify protein coding genes in large microbial metagenomic datasets. The clustering approach can be used to identify protein coding genes in prokaryotes, viruses, and intron-less eukaryotes. The computational improvement is based on an incremental clustering method that does not require the expensive all-against-all compute that was required by the original approach, while still preserving the remote homology detection capabilities. We present evaluations of the clustering approach in protein-coding gene identification and classification, and also present the results of updating the protein clusters from our previous work with recent genomic and metagenomic sequences. The clustering results are available via CAMERA, (http://camera.calit2.net. Conclusion The clustering paradigm is shown to be a very useful tool in the analysis of microbial metagenomic data. The incremental clustering method is shown to be much faster than the original approach in identifying genes, grouping sequences into existing protein families, and also identifying novel families that have multiple members in a metagenomic dataset. These clusters provide a basis for further studies of protein families.

  6. The ergot alkaloid gene cluster: Functional analyses and evolutionary aspects

    Czech Academy of Sciences Publication Activity Database

    Lorenz, N.; Haarmann, T.; Pažoutová, Sylvie; Jung, M.; Tudzynski, P.

    2009-01-01

    Roč. 70, 15-16 (2009), s. 1822-1832 ISSN 0031-9422 Institutional research plan: CEZ:AV0Z50200510 Keywords : Claviceps purpurea * Ergot fungus * Ergot alkaloid gene cluster Subject RIV: EE - Microbiology, Virology Impact factor: 3.104, year: 2009

  7. Origin and distribution of epipolythiodioxopiperazine (ETP gene clusters in filamentous ascomycetes

    Directory of Open Access Journals (Sweden)

    Gardiner Donald M

    2007-09-01

    Full Text Available Abstract Background Genes responsible for biosynthesis of fungal secondary metabolites are usually tightly clustered in the genome and co-regulated with metabolite production. Epipolythiodioxopiperazines (ETPs are a class of secondary metabolite toxins produced by disparate ascomycete fungi and implicated in several animal and plant diseases. Gene clusters responsible for their production have previously been defined in only two fungi. Fungal genome sequence data have been surveyed for the presence of putative ETP clusters and cluster data have been generated from several fungal taxa where genome sequences are not available. Phylogenetic analysis of cluster genes has been used to investigate the assembly and heredity of these gene clusters. Results Putative ETP gene clusters are present in 14 ascomycete taxa, but absent in numerous other ascomycetes examined. These clusters are discontinuously distributed in ascomycete lineages. Gene content is not absolutely fixed, however, common genes are identified and phylogenies of six of these are separately inferred. In each phylogeny almost all cluster genes form monophyletic clades with non-cluster fungal paralogues being the nearest outgroups. This relatedness of cluster genes suggests that a progenitor ETP gene cluster assembled within an ancestral taxon. Within each of the cluster clades, the cluster genes group together in consistent subclades, however, these relationships do not always reflect the phylogeny of ascomycetes. Micro-synteny of several of the genes within the clusters provides further support for these subclades. Conclusion ETP gene clusters appear to have a single origin and have been inherited relatively intact rather than assembling independently in the different ascomycete lineages. This progenitor cluster has given rise to a small number of distinct phylogenetic classes of clusters that are represented in a discontinuous pattern throughout ascomycetes. The disjunct heredity of

  8. Transcriptional interference networks coordinate the expression of functionally related genes clustered in the same genomic loci.

    Science.gov (United States)

    Boldogköi, Zsolt

    2012-01-01

    The regulation of gene expression is essential for normal functioning of biological systems in every form of life. Gene expression is primarily controlled at the level of transcription, especially at the phase of initiation. Non-coding RNAs are one of the major players at every level of genetic regulation, including the control of chromatin organization, transcription, various post-transcriptional processes, and translation. In this study, the Transcriptional Interference Network (TIN) hypothesis was put forward in an attempt to explain the global expression of antisense RNAs and the overall occurrence of tandem gene clusters in the genomes of various biological systems ranging from viruses to mammalian cells. The TIN hypothesis suggests the existence of a novel layer of genetic regulation, based on the interactions between the transcriptional machineries of neighboring genes at their overlapping regions, which are assumed to play a fundamental role in coordinating gene expression within a cluster of functionally linked genes. It is claimed that the transcriptional overlaps between adjacent genes are much more widespread in genomes than is thought today. The Waterfall model of the TIN hypothesis postulates a unidirectional effect of upstream genes on the transcription of downstream genes within a cluster of tandemly arrayed genes, while the Seesaw model proposes a mutual interdependence of gene expression between the oppositely oriented genes. The TIN represents an auto-regulatory system with an exquisitely timed and highly synchronized cascade of gene expression in functionally linked genes located in close physical proximity to each other. In this study, we focused on herpesviruses. The reason for this lies in the compressed nature of viral genes, which allows a tight regulation and an easier investigation of the transcriptional interactions between genes. However, I believe that the same or similar principles can be applied to cellular organisms too.

  9. Identification and analysis of the paulomycin biosynthetic gene cluster and titer improvement of the paulomycins in Streptomyces paulus NRRL 8115.

    Directory of Open Access Journals (Sweden)

    Jine Li

    Full Text Available The paulomycins are a group of glycosylated compounds featuring a unique paulic acid moiety. To locate their biosynthetic gene clusters, the genomes of two paulomycin producers, Streptomyces paulus NRRL 8115 and Streptomyces sp. YN86, were sequenced. The paulomycin biosynthetic gene clusters were defined by comparative analyses of the two genomes together with the genome of the third paulomycin producer Streptomyces albus J1074. Subsequently, the identity of the paulomycin biosynthetic gene cluster was confirmed by inactivation of two genes involved in biosynthesis of the paulomycose branched chain (pau11 and the ring A moiety (pau18 in Streptomyces paulus NRRL 8115. After determining the gene cluster boundaries, a convergent biosynthetic model was proposed for paulomycin based on the deduced functions of the pau genes. Finally, a paulomycin high-producing strain was constructed by expressing an activator-encoding gene (pau13 in S. paulus, setting the stage for future investigations.

  10. Evolutionary conservation of regulatory elements in vertebrate HOX gene clusters

    Energy Technology Data Exchange (ETDEWEB)

    Santini, Simona; Boore, Jeffrey L.; Meyer, Axel

    2003-12-31

    Due to their high degree of conservation, comparisons of DNA sequences among evolutionarily distantly-related genomes permit to identify functional regions in noncoding DNA. Hox genes are optimal candidate sequences for comparative genome analyses, because they are extremely conserved in vertebrates and occur in clusters. We aligned (Pipmaker) the nucleotide sequences of HoxA clusters of tilapia, pufferfish, striped bass, zebrafish, horn shark, human and mouse (over 500 million years of evolutionary distance). We identified several highly conserved intergenic sequences, likely to be important in gene regulation. Only a few of these putative regulatory elements have been previously described as being involved in the regulation of Hox genes, while several others are new elements that might have regulatory functions. The majority of these newly identified putative regulatory elements contain short fragments that are almost completely conserved and are identical to known binding sites for regulatory proteins (Transfac). The conserved intergenic regions located between the most rostrally expressed genes in the developing embryo are longer and better retained through evolution. We document that presumed regulatory sequences are retained differentially in either A or A clusters resulting from a genome duplication in the fish lineage. This observation supports both the hypothesis that the conserved elements are involved in gene regulation and the Duplication-Deletion-Complementation model.

  11. Conservation of gene linkage in dispersed vertebrate NK homeobox clusters.

    Science.gov (United States)

    Wotton, Karl R; Weierud, Frida K; Juárez-Morales, José L; Alvares, Lúcia E; Dietrich, Susanne; Lewis, Katharine E

    2009-10-01

    Nk homeobox genes are important regulators of many different developmental processes including muscle, heart, central nervous system and sensory organ development. They are thought to have arisen as part of the ANTP megacluster, which also gave rise to Hox and ParaHox genes, and at least some NK genes remain tightly linked in all animals examined so far. The protostome-deuterostome ancestor probably contained a cluster of nine Nk genes: (Msx)-(Nk4/tinman)-(Nk3/bagpipe)-(Lbx/ladybird)-(Tlx/c15)-(Nk7)-(Nk6/hgtx)-(Nk1/slouch)-(Nk5/Hmx). Of these genes, only NKX2.6-NKX3.1, LBX1-TLX1 and LBX2-TLX2 remain tightly linked in humans. However, it is currently unclear whether this is unique to the human genome as we do not know which of these Nk genes are clustered in other vertebrates. This makes it difficult to assess whether the remaining linkages are due to selective pressures or because chance rearrangements have "missed" certain genes. In this paper, we identify all of the paralogs of these ancestrally clustered NK genes in several distinct vertebrates. We demonstrate that tight linkages of Lbx1-Tlx1, Lbx2-Tlx2 and Nkx3.1-Nkx2.6 have been widely maintained in both the ray-finned and lobe-finned fish lineages. Moreover, the recently duplicated Hmx2-Hmx3 genes are also tightly linked. Finally, we show that Lbx1-Tlx1 and Hmx2-Hmx3 are flanked by highly conserved noncoding elements, suggesting that shared regulatory regions may have resulted in evolutionary pressure to maintain these linkages. Consistent with this, these pairs of genes have overlapping expression domains. In contrast, Lbx2-Tlx2 and Nkx3.1-Nkx2.6, which do not seem to be coexpressed, are also not associated with conserved noncoding sequences, suggesting that an alternative mechanism may be responsible for the continued clustering of these genes.

  12. ADVANCED CLUSTER BASED IMAGE SEGMENTATION

    Directory of Open Access Journals (Sweden)

    D. Kesavaraja

    2011-11-01

    Full Text Available This paper presents efficient and portable implementations of a useful image segmentation technique which makes use of the faster and a variant of the conventional connected components algorithm which we call parallel Components. In the Modern world majority of the doctors are need image segmentation as the service for various purposes and also they expect this system is run faster and secure. Usually Image segmentation Algorithms are not working faster. In spite of several ongoing researches in Conventional Segmentation and its Algorithms might not be able to run faster. So we propose a cluster computing environment for parallel image Segmentation to provide faster result. This paper is the real time implementation of Distributed Image Segmentation in Clustering of Nodes. We demonstrate the effectiveness and feasibility of our method on a set of Medical CT Scan Images. Our general framework is a single address space, distributed memory programming model. We use efficient techniques for distributing and coalescing data as well as efficient combinations of task and data parallelism. The image segmentation algorithm makes use of an efficient cluster process which uses a novel approach for parallel merging. Our experimental results are consistent with the theoretical analysis and practical results. It provides the faster execution time for segmentation, when compared with Conventional method. Our test data is different CT scan images from the Medical database. More efficient implementations of Image Segmentation will likely result in even faster execution times.

  13. Genetically based location from triploid populations and gene ontology of a 3.3-mb genome region linked to Alternaria brown spot resistance in citrus reveal clusters of resistance genes.

    Directory of Open Access Journals (Sweden)

    José Cuenca

    Full Text Available Genetic analysis of phenotypical traits and marker-trait association in polyploid species is generally considered as a challenge. In the present work, different approaches were combined taking advantage of the particular genetic structures of 2n gametes resulting from second division restitution (SDR to map a genome region linked to Alternaria brown spot (ABS resistance in triploid citrus progeny. ABS in citrus is a serious disease caused by the tangerine pathotype of the fungus Alternaria alternata. This pathogen produces ACT-toxin, which induces necrotic lesions on fruit and young leaves, defoliation and fruit drop in susceptible genotypes. It is a strong concern for triploid breeding programs aiming to produce seedless mandarin cultivars. The monolocus dominant inheritance of susceptibility, proposed on the basis of diploid population studies, was corroborated in triploid progeny. Bulk segregant analysis coupled with genome scan using a large set of genetically mapped SNP markers and targeted genetic mapping by half tetrad analysis, using SSR and SNP markers, allowed locating a 3.3 Mb genomic region linked to ABS resistance near the centromere of chromosome III. Clusters of resistance genes were identified by gene ontology analysis of this genomic region. Some of these genes are good candidates to control the dominant susceptibility to the ACT-toxin. SSR and SNP markers were developed for efficient early marker-assisted selection of ABS resistant hybrids.

  14. Genetically based location from triploid populations and gene ontology of a 3.3-mb genome region linked to Alternaria brown spot resistance in citrus reveal clusters of resistance genes.

    Science.gov (United States)

    Cuenca, José; Aleza, Pablo; Vicent, Antonio; Brunel, Dominique; Ollitrault, Patrick; Navarro, Luis

    2013-01-01

    Genetic analysis of phenotypical traits and marker-trait association in polyploid species is generally considered as a challenge. In the present work, different approaches were combined taking advantage of the particular genetic structures of 2n gametes resulting from second division restitution (SDR) to map a genome region linked to Alternaria brown spot (ABS) resistance in triploid citrus progeny. ABS in citrus is a serious disease caused by the tangerine pathotype of the fungus Alternaria alternata. This pathogen produces ACT-toxin, which induces necrotic lesions on fruit and young leaves, defoliation and fruit drop in susceptible genotypes. It is a strong concern for triploid breeding programs aiming to produce seedless mandarin cultivars. The monolocus dominant inheritance of susceptibility, proposed on the basis of diploid population studies, was corroborated in triploid progeny. Bulk segregant analysis coupled with genome scan using a large set of genetically mapped SNP markers and targeted genetic mapping by half tetrad analysis, using SSR and SNP markers, allowed locating a 3.3 Mb genomic region linked to ABS resistance near the centromere of chromosome III. Clusters of resistance genes were identified by gene ontology analysis of this genomic region. Some of these genes are good candidates to control the dominant susceptibility to the ACT-toxin. SSR and SNP markers were developed for efficient early marker-assisted selection of ABS resistant hybrids.

  15. Gene duplication, modularity and adaptation in the evolution of the aflatoxin gene cluster

    Directory of Open Access Journals (Sweden)

    Jakobek Judy L

    2007-07-01

    Full Text Available Abstract Background The biosynthesis of aflatoxin (AF involves over 20 enzymatic reactions in a complex polyketide pathway that converts acetate and malonate to the intermediates sterigmatocystin (ST and O-methylsterigmatocystin (OMST, the respective penultimate and ultimate precursors of AF. Although these precursors are chemically and structurally very similar, their accumulation differs at the species level for Aspergilli. Notable examples are A. nidulans that synthesizes only ST, A. flavus that makes predominantly AF, and A. parasiticus that generally produces either AF or OMST. Whether these differences are important in the evolutionary/ecological processes of species adaptation and diversification is unknown. Equally unknown are the specific genomic mechanisms responsible for ordering and clustering of genes in the AF pathway of Aspergillus. Results To elucidate the mechanisms that have driven formation of these clusters, we performed systematic searches of aflatoxin cluster homologs across five Aspergillus genomes. We found a high level of gene duplication and identified seven modules consisting of highly correlated gene pairs (aflA/aflB, aflR/aflS, aflX/aflY, aflF/aflE, aflT/aflQ, aflC/aflW, and aflG/aflL. With the exception of A. nomius, contrasts of mean Ka/Ks values across all cluster genes showed significant differences in selective pressure between section Flavi and non-section Flavi species. A. nomius mean Ka/Ks values were more similar to partial clusters in A. fumigatus and A. terreus. Overall, mean Ka/Ks values were significantly higher for section Flavi than for non-section Flavi species. Conclusion Our results implicate several genomic mechanisms in the evolution of ST, OMST and AF cluster genes. Gene modules may arise from duplications of a single gene, whereby the function of the pre-duplication gene is retained in the copy (aflF/aflE or the copies may partition the ancestral function (aflA/aflB. In some gene modules, the

  16. Clustering based on adherence data.

    Science.gov (United States)

    Kiwuwa-Muyingo, Sylvia; Oja, Hannu; Walker, Sarah A; Ilmonen, Pauliina; Levin, Jonathan; Todd, Jim

    2011-03-08

    Adherence to a medical treatment means the extent to which a patient follows the instructions or recommendations by health professionals. There are direct and indirect ways to measure adherence which have been used for clinical management and research. Typically adherence measures are monitored over a long follow-up or treatment period, and some measurements may be missing due to death or other reasons. A natural question then is how to describe adherence behavior over the whole period in a simple way. In the literature, measurements over a period are usually combined just by using averages like percentages of compliant days or percentages of doses taken. In the paper we adapt an approach where patient adherence measures are seen as a stochastic process. Repeated measures are then analyzed as a Markov chain with finite number of states rather than as independent and identically distributed observations, and the transition probabilities between the states are assumed to fully describe the behavior of a patient. The patients can then be clustered or classified using their estimated transition probabilities. These natural clusters can be used to describe the adherence of the patients, to find predictors for adherence, and to predict the future events. The new approach is illustrated and shown to be useful with a simple analysis of a data set from the DART (Development of AntiRetroviral Therapy in Africa) trial in Uganda and Zimbabwe.

  17. Robust MST-Based Clustering Algorithm.

    Science.gov (United States)

    Liu, Qidong; Zhang, Ruisheng; Zhao, Zhili; Wang, Zhenghai; Jiao, Mengyao; Wang, Guangjing

    2018-06-01

    Minimax similarity stresses the connectedness of points via mediating elements rather than favoring high mutual similarity. The grouping principle yields superior clustering results when mining arbitrarily-shaped clusters in data. However, it is not robust against noises and outliers in the data. There are two main problems with the grouping principle: first, a single object that is far away from all other objects defines a separate cluster, and second, two connected clusters would be regarded as two parts of one cluster. In order to solve such problems, we propose robust minimum spanning tree (MST)-based clustering algorithm in this letter. First, we separate the connected objects by applying a density-based coarsening phase, resulting in a low-rank matrix in which the element denotes the supernode by combining a set of nodes. Then a greedy method is presented to partition those supernodes through working on the low-rank matrix. Instead of removing the longest edges from MST, our algorithm groups the data set based on the minimax similarity. Finally, the assignment of all data points can be achieved through their corresponding supernodes. Experimental results on many synthetic and real-world data sets show that our algorithm consistently outperforms compared clustering algorithms.

  18. Sequencing, physical organization and kinetic expression of the patulin biosynthetic gene cluster from Penicillium expansum

    International Nuclear Information System (INIS)

    Tannous, J.; El Khoury, R.; El Khoury, A.; Lteif, R.; Snini, S.; Lippi, Y.; Oswald, I.; Olivier, P.; Atoui, A.

    2014-01-01

    Patulin is a polyketide-derived mycotoxin produced by numerous filamentous fungi. Among them, Penicillium expansum is by far the most problematic species. This fungus is a destructive phytopathogen capable of growing on fruit, provoking the blue mold decay of apples and producing significant amounts of patulin. The biosynthetic pathway of this mycotoxin is chemically well-characterized, but its genetic bases remain largely unknown with only few characterized genes in less economic relevant species. The present study consisted of the identification and positional organization of the patulin gene cluster in P. expansum strain NRRL 35695. Several amplification reactions were performed with degenerative primers that were designed based on sequences from the orthologous genes available in other species. An improved genome Walking approach was used in order to sequence the remaining adjacent genes of the cluster. RACE-PCR was also carried out from mRNAs to determine the start and stop codons of the coding sequences. The patulin gene cluster in P. expansum consists of 15 genes in the following order: patH, patG, patF, patE, patD, patC, patB, patA, patM, patN, patO, patL, patI, patJ, and patK. These genes share 60–70% of identity with orthologous genes grouped differently, within a putative patulin cluster described in a non-producing strain of Aspergillus clavatus. The kinetics of patulin cluster genes expression was studied under patulin-permissive conditions (natural apple-based medium) and patulin-restrictive conditions (Eagle's minimal essential medium), and demonstrated a significant association between gene expression and patulin production. In conclusion, the sequence of the patulin cluster in P. expansum constitutes a key step for a better understanding of themechanisms leading to patulin production in this fungus. It will allow the role of each gene to be elucidated, and help to define strategies to reduce patulin production in apple-based products

  19. Transcriptional analysis of exopolysaccharides biosynthesis gene clusters in Lactobacillus plantarum.

    Science.gov (United States)

    Vastano, Valeria; Perrone, Filomena; Marasco, Rosangela; Sacco, Margherita; Muscariello, Lidia

    2016-04-01

    Exopolysaccharides (EPS) from lactic acid bacteria contribute to specific rheology and texture of fermented milk products and find applications also in non-dairy foods and in therapeutics. Recently, four clusters of genes (cps) associated with surface polysaccharide production have been identified in Lactobacillus plantarum WCFS1, a probiotic and food-associated lactobacillus. These clusters are involved in cell surface architecture and probably in release and/or exposure of immunomodulating bacterial molecules. Here we show a transcriptional analysis of these clusters. Indeed, RT-PCR experiments revealed that the cps loci are organized in five operons. Moreover, by reverse transcription-qPCR analysis performed on L. plantarum WCFS1 (wild type) and WCFS1-2 (ΔccpA), we demonstrated that expression of three cps clusters is under the control of the global regulator CcpA. These results, together with the identification of putative CcpA target sequences (catabolite responsive element CRE) in the regulatory region of four out of five transcriptional units, strongly suggest for the first time a role of the master regulator CcpA in EPS gene transcription among lactobacilli.

  20. Co-evolution of secondary metabolite gene clusters and their host

    DEFF Research Database (Denmark)

    Kjærbølling, Inge; Vesth, Tammi Camilla; Frisvad, Jens Christian

    Secondary metabolite gene cluster evolution is mainly driven by two events: gene duplication and annexation and horizontal gene transfer. Here we use comparative genomics of Aspergillus species to investigate the evolution of secondary metabolite (SM) gene clusters across a wide spectrum of speci....... We investigate the dynamic evolutionary relationship between the cluster and the host by examining the genes within the cluster and the number of homologous genes found within the host and in closely related species.......Secondary metabolite gene cluster evolution is mainly driven by two events: gene duplication and annexation and horizontal gene transfer. Here we use comparative genomics of Aspergillus species to investigate the evolution of secondary metabolite (SM) gene clusters across a wide spectrum of species...

  1. Genome-scale analysis of positional clustering of mouse testis-specific genes

    Directory of Open Access Journals (Sweden)

    Lee Bernett TK

    2005-01-01

    Full Text Available Abstract Background Genes are not randomly distributed on a chromosome as they were thought even after removal of tandem repeats. The positional clustering of co-expressed genes is known in prokaryotes and recently reported in several eukaryotic organisms such as Caenorhabditis elegans, Drosophila melanogaster, and Homo sapiens. In order to further investigate the mode of tissue-specific gene clustering in higher eukaryotes, we have performed a genome-scale analysis of positional clustering of the mouse testis-specific genes. Results Our computational analysis shows that a large proportion of testis-specific genes are clustered in groups of 2 to 5 genes in the mouse genome. The number of clusters is much higher than expected by chance even after removal of tandem repeats. Conclusion Our result suggests that testis-specific genes tend to cluster on the mouse chromosomes. This provides another piece of evidence for the hypothesis that clusters of tissue-specific genes do exist.

  2. Motif-Independent De Novo Detection of Secondary Metabolite Gene Clusters – Towards Identification of Novel Secondary Metabolisms from Filamentous Fungi -

    Directory of Open Access Journals (Sweden)

    Myco eUmemura

    2015-05-01

    Full Text Available Secondary metabolites are produced mostly by clustered genes that are essential to their biosynthesis. The transcriptional expression of these genes is often cooperatively regulated by a transcription factor located inside or close to a cluster. Most of the secondary metabolism biosynthesis (SMB gene clusters identified to date contain so-called core genes with distinctive sequence features, such as polyketide synthase (PKS and non-ribosomal peptide synthetase (NRPS. Recent efforts in sequencing fungal genomes have revealed far more SMB gene clusters than expected based on the number of core genes in the genomes. Several bioinformatics tools have been developed to survey SMB gene clusters using the sequence motif information of the core genes, including SMURF and antiSMASH.More recently, accompanied by the development of sequencing techniques allowing to obtain large-scale genomic and transcriptomic data, motif-independent prediction methods of SMB gene clusters, including MIDDAS-M, have been developed. Most these methods detect the clusters in which the genes are cooperatively regulated at transcriptional levels, thus allowing the identification of novel SMB gene clusters regardless of the presence of the core genes. Another type of the method, MIPS-CG, uses the characteristics of SMB genes, which are highly enriched in non-syntenic blocks (NSBs, enabling the prediction even without transcriptome data although the results have not been evaluated in detail. Considering that large portion of SMB gene clusters might be sufficiently expressed only in limited uncommon conditions, it seems that prediction of SMB gene clusters by bioinformatics and successive experimental validation is an only way to efficiently uncover hidden SMB gene clusters. Here, we describe and discuss possible novel approaches for the determination of SMB gene clusters that have not been identified using conventional methods.

  3. Cluster Based Vector Attribute Filtering

    NARCIS (Netherlands)

    Kiwanuka, Fred N.; Wilkinson, Michael H.F.

    2016-01-01

    Morphological attribute filters operate on images based on properties or attributes of connected components. Until recently, attribute filtering was based on a single global threshold on a scalar property to remove or retain objects. A single threshold struggles in case no single property or

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

    Directory of Open Access Journals (Sweden)

    Li Guo

    2014-01-01

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

  5. The Serratia gene cluster encoding biosynthesis of the red antibiotic, prodigiosin, shows species- and strain-dependent genome context variation

    DEFF Research Database (Denmark)

    Harris, Abigail K P; Williamson, Neil R; Slater, Holly

    2004-01-01

    The prodigiosin biosynthesis gene cluster (pig cluster) from two strains of Serratia (S. marcescens ATCC 274 and Serratia sp. ATCC 39006) has been cloned, sequenced and expressed in heterologous hosts. Sequence analysis of the respective pig clusters revealed 14 ORFs in S. marcescens ATCC 274...... and 15 ORFs in Serratia sp. ATCC 39006. In each Serratia species, predicted gene products showed similarity to polyketide synthases (PKSs), non-ribosomal peptide synthases (NRPSs) and the Red proteins of Streptomyces coelicolor A3(2). Comparisons between the two Serratia pig clusters and the red cluster...... from Str. coelicolor A3(2) revealed some important differences. A modified scheme for the biosynthesis of prodigiosin, based on the pathway recently suggested for the synthesis of undecylprodigiosin, is proposed. The distribution of the pig cluster within several Serratia sp. isolates is demonstrated...

  6. Open reading frame 176 in the photosynthesis gene cluster of Rhodobacter capsulatus encodes idi, a gene for isopentenyl diphosphate isomerase.

    OpenAIRE

    Hahn, F M; Baker, J A; Poulter, C D

    1996-01-01

    Isopentenyl diphosphate (IPP) isomerase catalyzes an essential activation step in the isoprenoid biosynthetic pathway. A database search based on probes from the highly conserved regions in three eukaryotic IPP isomerases revealed substantial similarity with ORF176 in the photosynthesis gene cluster in Rhodobacter capsulatus. The open reading frame was cloned into an Escherichia coli expression vector. The encoded 20-kDa protein, which was purified in two steps by ion exchange and hydrophobic...

  7. Gene expression data clustering and it’s application in differential analysis of leukemia

    Directory of Open Access Journals (Sweden)

    M. Vahedi

    2008-02-01

    Full Text Available Introduction: DNA microarray technique is one of the most important categories in bioinformatics,which allows the possibility of monitoring thousands of expressed genes has been resulted in creatinggiant data bases of gene expression data, recently. Statistical analysis of such databases includednormalization, clustering, classification and etc.Materials and Methods: Golub et al (1999 collected data bases of leukemia based on the method ofoligonucleotide. The data is on the internet. In this paper, we analyzed gene expression data. It wasclustered by several methods including multi-dimensional scaling, hierarchical and non-hierarchicalclustering. Data set included 20 Acute Lymphoblastic Leukemia (ALL patients and 14 Acute MyeloidLeukemia (AML patients. The results of tow methods of clustering were compared with regard to realgrouping (ALL & AML. R software was used for data analysis.Results: Specificity and sensitivity of divisive hierarchical clustering in diagnosing of ALL patientswere 75% and 92%, respectively. Specificity and sensitivity of partitioning around medoids indiagnosing of ALL patients were 90% and 93%, respectively. These results showed a wellaccomplishment of both methods of clustering. It is considerable that, due to clustering methodsresults, one of the samples was placed in ALL groups, which was in AML group in clinical test.Conclusion: With regard to concordance of the results with real grouping of data, therefore we canuse these methods in the cases where we don't have accurate information of real grouping of data.Moreover, Results of clustering might distinct subgroups of data in such a way that would be necessaryfor concordance with clinical outcomes, laboratory results and so on.

  8. GenClust: A genetic algorithm for clustering gene expression data

    Directory of Open Access Journals (Sweden)

    Raimondi Alessandra

    2005-12-01

    Full Text Available Abstract Background Clustering is a key step in the analysis of gene expression data, and in fact, many classical clustering algorithms are used, or more innovative ones have been designed and validated for the task. Despite the widespread use of artificial intelligence techniques in bioinformatics and, more generally, data analysis, there are very few clustering algorithms based on the genetic paradigm, yet that paradigm has great potential in finding good heuristic solutions to a difficult optimization problem such as clustering. Results GenClust is a new genetic algorithm for clustering gene expression data. It has two key features: (a a novel coding of the search space that is simple, compact and easy to update; (b it can be used naturally in conjunction with data driven internal validation methods. We have experimented with the FOM methodology, specifically conceived for validating clusters of gene expression data. The validity of GenClust has been assessed experimentally on real data sets, both with the use of validation measures and in comparison with other algorithms, i.e., Average Link, Cast, Click and K-means. Conclusion Experiments show that none of the algorithms we have used is markedly superior to the others across data sets and validation measures; i.e., in many cases the observed differences between the worst and best performing algorithm may be statistically insignificant and they could be considered equivalent. However, there are cases in which an algorithm may be better than others and therefore worthwhile. In particular, experiments for GenClust show that, although simple in its data representation, it converges very rapidly to a local optimum and that its ability to identify meaningful clusters is comparable, and sometimes superior, to that of more sophisticated algorithms. In addition, it is well suited for use in conjunction with data driven internal validation measures and, in particular, the FOM methodology.

  9. An enhanced deterministic K-Means clustering algorithm for cancer subtype prediction from gene expression data.

    Science.gov (United States)

    Nidheesh, N; Abdul Nazeer, K A; Ameer, P M

    2017-12-01

    Clustering algorithms with steps involving randomness usually give different results on different executions for the same dataset. This non-deterministic nature of algorithms such as the K-Means clustering algorithm limits their applicability in areas such as cancer subtype prediction using gene expression data. It is hard to sensibly compare the results of such algorithms with those of other algorithms. The non-deterministic nature of K-Means is due to its random selection of data points as initial centroids. We propose an improved, density based version of K-Means, which involves a novel and systematic method for selecting initial centroids. The key idea of the algorithm is to select data points which belong to dense regions and which are adequately separated in feature space as the initial centroids. We compared the proposed algorithm to a set of eleven widely used single clustering algorithms and a prominent ensemble clustering algorithm which is being used for cancer data classification, based on the performances on a set of datasets comprising ten cancer gene expression datasets. The proposed algorithm has shown better overall performance than the others. There is a pressing need in the Biomedical domain for simple, easy-to-use and more accurate Machine Learning tools for cancer subtype prediction. The proposed algorithm is simple, easy-to-use and gives stable results. Moreover, it provides comparatively better predictions of cancer subtypes from gene expression data. Copyright © 2017 Elsevier Ltd. All rights reserved.

  10. At the base of colinear Hox gene expression : cis-features and trans-factors orchestrating the initial phase of Hox cluster activation

    NARCIS (Netherlands)

    Neijts, Roel; Deschamps, Jacqueline

    2017-01-01

    Hox genes are crucial players in the generation and pattering of the vertebrate trunk and posterior body during embryogenesis. Their initial expression takes place shortly after the establishment of the primitive streak, in the posterior-most part of the mouse embryo and is a determinant step for

  11. A Cluster- Based Secure Active Network Environment

    Institute of Scientific and Technical Information of China (English)

    CHEN Xiao-lin; ZHOU Jing-yang; DAI Han; LU Sang-lu; CHEN Gui-hai

    2005-01-01

    We introduce a cluster-based secure active network environment (CSANE) which separates the processing of IP packets from that of active packets in active routers. In this environment, the active code authorized or trusted by privileged users is executed in the secure execution environment (EE) of the active router, while others are executed in the secure EE of the nodes in the distributed shared memory (DSM) cluster. With the supports of a multi-process Java virtual machine and KeyNote, untrusted active packets are controlled to securely consume resource. The DSM consistency management makes that active packets can be parallelly processed in the DSM cluster as if they were processed one by one in ANTS (Active Network Transport System). We demonstrate that CSANE has good security and scalability, but imposing little changes on traditional routers.

  12. Semantic based cluster content discovery in description first clustering algorithm

    International Nuclear Information System (INIS)

    Khan, M.W.; Asif, H.M.S.

    2017-01-01

    In the field of data analytics grouping of like documents in textual data is a serious problem. A lot of work has been done in this field and many algorithms have purposed. One of them is a category of algorithms which firstly group the documents on the basis of similarity and then assign the meaningful labels to those groups. Description first clustering algorithm belong to the category in which the meaningful description is deduced first and then relevant documents are assigned to that description. LINGO (Label Induction Grouping Algorithm) is the algorithm of description first clustering category which is used for the automatic grouping of documents obtained from search results. It uses LSI (Latent Semantic Indexing); an IR (Information Retrieval) technique for induction of meaningful labels for clusters and VSM (Vector Space Model) for cluster content discovery. In this paper we present the LINGO while it is using LSI during cluster label induction and cluster content discovery phase. Finally, we compare results obtained from the said algorithm while it uses VSM and Latent semantic analysis during cluster content discovery phase. (author)

  13. Inactivation of human α-globin gene expression by a de novo deletion located upstream of the α-globin gene cluster

    International Nuclear Information System (INIS)

    Liebhaber, S.A.; Weiss, I.; Cash, F.E.; Griese, E.U.; Horst, J.; Ayyub, H.; Higgs, D.R.

    1990-01-01

    Synthesis of normal human hemoglobin A, α 2 β 2 , is based upon balanced expression of genes in the α-globin gene cluster on chromosome 15 and the β-globin gene cluster on chromosome 11. Full levels of erythroid-specific activation of the β-globin cluster depend on sequences located at a considerable distance 5' to the β-globin gene, referred to as the locus-activating or dominant control region. The existence of an analogous element(s) upstream of the α-globin cluster has been suggested from observations on naturally occurring deletions and experimental studies. The authors have identified an individual with α-thalassemia in whom structurally normal α-globin genes have been inactivated in cis by a discrete de novo 35-kilobase deletion located ∼30 kilobases 5' from the α-globin gene cluster. They conclude that this deletion inactivates expression of the α-globin genes by removing one or more of the previously identified upstream regulatory sequences that are critical to expression of the α-globin genes

  14. Acquisition and evolution of plant pathogenesis-associated gene clusters and candidate determinants of tissue-specificity in xanthomonas.

    Directory of Open Access Journals (Sweden)

    Hong Lu

    Full Text Available Xanthomonas is a large genus of plant-associated and plant-pathogenic bacteria. Collectively, members cause diseases on over 392 plant species. Individually, they exhibit marked host- and tissue-specificity. The determinants of this specificity are unknown.To assess potential contributions to host- and tissue-specificity, pathogenesis-associated gene clusters were compared across genomes of eight Xanthomonas strains representing vascular or non-vascular pathogens of rice, brassicas, pepper and tomato, and citrus. The gum cluster for extracellular polysaccharide is conserved except for gumN and sequences downstream. The xcs and xps clusters for type II secretion are conserved, except in the rice pathogens, in which xcs is missing. In the otherwise conserved hrp cluster, sequences flanking the core genes for type III secretion vary with respect to insertion sequence element and putative effector gene content. Variation at the rpf (regulation of pathogenicity factors cluster is more pronounced, though genes with established functional relevance are conserved. A cluster for synthesis of lipopolysaccharide varies highly, suggesting multiple horizontal gene transfers and reassortments, but this variation does not correlate with host- or tissue-specificity. Phylogenetic trees based on amino acid alignments of gum, xps, xcs, hrp, and rpf cluster products generally reflect strain phylogeny. However, amino acid residues at four positions correlate with tissue specificity, revealing hpaA and xpsD as candidate determinants. Examination of genome sequences of xanthomonads Xylella fastidiosa and Stenotrophomonas maltophilia revealed that the hrp, gum, and xcs clusters are recent acquisitions in the Xanthomonas lineage.Our results provide insight into the ancestral Xanthomonas genome and indicate that differentiation with respect to host- and tissue-specificity involved not major modifications or wholesale exchange of clusters, but subtle changes in a small

  15. Recurrent adenylation domain replacement in the microcystin synthetase gene cluster

    Directory of Open Access Journals (Sweden)

    Laakso Kati

    2007-10-01

    Full Text Available Abstract Background Microcystins are small cyclic heptapeptide toxins produced by a range of distantly related cyanobacteria. Microcystins are synthesized on large NRPS-PKS enzyme complexes. Many structural variants of microcystins are produced simulatenously. A recombination event between the first module of mcyB (mcyB1 and mcyC in the microcystin synthetase gene cluster is linked to the simultaneous production of microcystin variants in strains of the genus Microcystis. Results Here we undertook a phylogenetic study to investigate the order and timing of recombination between the mcyB1 and mcyC genes in a diverse selection of microcystin producing cyanobacteria. Our results provide support for complex evolutionary processes taking place at the mcyB1 and mcyC adenylation domains which recognize and activate the amino acids found at X and Z positions. We find evidence for recent recombination between mcyB1 and mcyC in strains of the genera Anabaena, Microcystis, and Hapalosiphon. We also find clear evidence for independent adenylation domain conversion of mcyB1 by unrelated peptide synthetase modules in strains of the genera Nostoc and Microcystis. The recombination events replace only the adenylation domain in each case and the condensation domains of mcyB1 and mcyC are not transferred together with the adenylation domain. Our findings demonstrate that the mcyB1 and mcyC adenylation domains are recombination hotspots in the microcystin synthetase gene cluster. Conclusion Recombination is thought to be one of the main mechanisms driving the diversification of NRPSs. However, there is very little information on how recombination takes place in nature. This study demonstrates that functional peptide synthetases are created in nature through transfer of adenylation domains without the concomitant transfer of condensation domains.

  16. Structure-related clustering of gene expression fingerprints of thp-1 cells exposed to smaller polycyclic aromatic hydrocarbons.

    Science.gov (United States)

    Wan, B; Yarbrough, J W; Schultz, T W

    2008-01-01

    This study was undertaken to test the hypothesis that structurally similar PAHs induce similar gene expression profiles. THP-1 cells were exposed to a series of 12 selected PAHs at 50 microM for 24 hours and gene expressions profiles were analyzed using both unsupervised and supervised methods. Clustering analysis of gene expression profiles revealed that the 12 tested chemicals were grouped into five clusters. Within each cluster, the gene expression profiles are more similar to each other than to the ones outside the cluster. One-methylanthracene and 1-methylfluorene were found to have the most similar profiles; dibenzothiophene and dibenzofuran were found to share common profiles with fluorine. As expression pattern comparisons were expanded, similarity in genomic fingerprint dropped off dramatically. Prediction analysis of microarrays (PAM) based on the clustering pattern generated 49 predictor genes that can be used for sample discrimination. Moreover, a significant analysis of Microarrays (SAM) identified 598 genes being modulated by tested chemicals with a variety of biological processes, such as cell cycle, metabolism, and protein binding and KEGG pathways being significantly (p < 0.05) affected. It is feasible to distinguish structurally different PAHs based on their genomic fingerprints, which are mechanism based.

  17. Bacillus sp.CDB3 isolated from cattle dip-sites possesses two ars gene clusters

    Institute of Scientific and Technical Information of China (English)

    Somanath Bhat; Xi Luo; Zhiqiang Xu; Lixia Liu; Ren Zhang

    2011-01-01

    Contamination of soil and water by arsenic is a global problem.In Australia, the dipping of cattle in arsenic-containing solution to control cattle ticks in last centenary has left many sites heavily contaminated with arsenic and other toxicants.We had previously isolated five soil bacterial strains (CDB1-5) highly resistant to arsenic.To understand the resistance mechanism, molecular studies have been carried out.Two chromosome-encoded arsenic resistance (ars) gene clusters have been cloned from CDB3 (Bacillus sp.).They both function in Escherichia coli and cluster 1 exerts a much higher resistance to the toxic metalloid.Cluster 2 is smaller possessing four open reading frames (ORFs) arsRorf2BC, similar to that identified in Bacillus subtilis Skin element.Among the eight ORFs in cluster 1 five are analogs of common ars genes found in other bacteria, however, organized in a unique order arsRBCDA instead of arsRDABC.Three other putative genes are located directly downstream and designated as arsTIP based on the homologies of their theoretical translation sequences respectively to thioredoxin reductases, iron-sulphur cluster proteins and protein phosphatases.The latter two are novel of any known ars operons.The arsD gene from Bacillus species was cloned for the first time and the predict protein differs from the well studied E.coli ArsD by lacking two pairs of C-terrninal cysteine residues.Its functional involvement in arsenic resistance has been confirmed by a deletion experiment.There exists also an inverted repeat in the intergenic region between arsC and arsD implying some unknown transcription regulation.

  18. The gsdf gene locus harbors evolutionary conserved and clustered genes preferentially expressed in fish previtellogenic oocytes.

    Science.gov (United States)

    Gautier, Aude; Le Gac, Florence; Lareyre, Jean-Jacques

    2011-02-01

    display a different cellular localization compared to that of the gsdf gene indicating that the later gene is not co-regulated. Interestingly, our study identifies new clustered genes that are specifically expressed in previtellogenic oocytes (nup54, aff1, klhl8, sdad1). Copyright © 2010 Elsevier B.V. All rights reserved.

  19. Information Clustering Based on Fuzzy Multisets.

    Science.gov (United States)

    Miyamoto, Sadaaki

    2003-01-01

    Proposes a fuzzy multiset model for information clustering with application to information retrieval on the World Wide Web. Highlights include search engines; term clustering; document clustering; algorithms for calculating cluster centers; theoretical properties concerning clustering algorithms; and examples to show how the algorithms work.…

  20. Genomic organization, tissue distribution and functional characterization of the rat Pate gene cluster.

    Directory of Open Access Journals (Sweden)

    Angireddy Rajesh

    Full Text Available The cysteine rich prostate and testis expressed (Pate proteins identified till date are thought to resemble the three fingered protein/urokinase-type plasminogen activator receptor proteins. In this study, for the first time, we report the identification, cloning and characterization of rat Pate gene cluster and also determine the expression pattern. The rat Pate genes are clustered on chromosome 8 and their predicted proteins retained the ten cysteine signature characteristic to TFP/Ly-6 protein family. PATE and PATE-F three dimensional protein structure was found to be similar to that of the toxin bucandin. Though Pate gene expression is thought to be prostate and testis specific, we observed that rat Pate genes are also expressed in seminal vesicle and epididymis and in tissues beyond the male reproductive tract. In the developing rats (20-60 day old, expression of Pate genes seem to be androgen dependent in the epididymis and testis. In the adult rat, androgen ablation resulted in down regulation of the majority of Pate genes in the epididymides. PATE and PATE-F proteins were found to be expressed abundantly in the male reproductive tract of rats and on the sperm. Recombinant PATE protein exhibited potent antibacterial activity, whereas PATE-F did not exhibit any antibacterial activity. Pate expression was induced in the epididymides when challenged with LPS. Based on our results, we conclude that rat PATE proteins may contribute to the reproductive and defense functions.

  1. Weighted voting-based consensus clustering for chemical structure databases

    Science.gov (United States)

    Saeed, Faisal; Ahmed, Ali; Shamsir, Mohd Shahir; Salim, Naomie

    2014-06-01

    The cluster-based compound selection is used in the lead identification process of drug discovery and design. Many clustering methods have been used for chemical databases, but there is no clustering method that can obtain the best results under all circumstances. However, little attention has been focused on the use of combination methods for chemical structure clustering, which is known as consensus clustering. Recently, consensus clustering has been used in many areas including bioinformatics, machine learning and information theory. This process can improve the robustness, stability, consistency and novelty of clustering. For chemical databases, different consensus clustering methods have been used including the co-association matrix-based, graph-based, hypergraph-based and voting-based methods. In this paper, a weighted cumulative voting-based aggregation algorithm (W-CVAA) was developed. The MDL Drug Data Report (MDDR) benchmark chemical dataset was used in the experiments and represented by the AlogP and ECPF_4 descriptors. The results from the clustering methods were evaluated by the ability of the clustering to separate biologically active molecules in each cluster from inactive ones using different criteria, and the effectiveness of the consensus clustering was compared to that of Ward's method, which is the current standard clustering method in chemoinformatics. This study indicated that weighted voting-based consensus clustering can overcome the limitations of the existing voting-based methods and improve the effectiveness of combining multiple clusterings of chemical structures.

  2. Heterologous expression of pikromycin biosynthetic gene cluster using Streptomyces artificial chromosome system.

    Science.gov (United States)

    Pyeon, Hye-Rim; Nah, Hee-Ju; Kang, Seung-Hoon; Choi, Si-Sun; Kim, Eung-Soo

    2017-05-31

    Heterologous expression of biosynthetic gene clusters of natural microbial products has become an essential strategy for titer improvement and pathway engineering of various potentially-valuable natural products. A Streptomyces artificial chromosomal conjugation vector, pSBAC, was previously successfully applied for precise cloning and tandem integration of a large polyketide tautomycetin (TMC) biosynthetic gene cluster (Nah et al. in Microb Cell Fact 14(1):1, 2015), implying that this strategy could be employed to develop a custom overexpression scheme of natural product pathway clusters present in actinomycetes. To validate the pSBAC system as a generally-applicable heterologous overexpression system for a large-sized polyketide biosynthetic gene cluster in Streptomyces, another model polyketide compound, the pikromycin biosynthetic gene cluster, was preciously cloned and heterologously expressed using the pSBAC system. A unique HindIII restriction site was precisely inserted at one of the border regions of the pikromycin biosynthetic gene cluster within the chromosome of Streptomyces venezuelae, followed by site-specific recombination of pSBAC into the flanking region of the pikromycin gene cluster. Unlike the previous cloning process, one HindIII site integration step was skipped through pSBAC modification. pPik001, a pSBAC containing the pikromycin biosynthetic gene cluster, was directly introduced into two heterologous hosts, Streptomyces lividans and Streptomyces coelicolor, resulting in the production of 10-deoxymethynolide, a major pikromycin derivative. When two entire pikromycin biosynthetic gene clusters were tandemly introduced into the S. lividans chromosome, overproduction of 10-deoxymethynolide and the presence of pikromycin, which was previously not detected, were both confirmed. Moreover, comparative qRT-PCR results confirmed that the transcription of pikromycin biosynthetic genes was significantly upregulated in S. lividans containing tandem

  3. Output ordering and prioritisation system (OOPS): ranking biosynthetic gene clusters to enhance bioactive metabolite discovery.

    Science.gov (United States)

    Peña, Alejandro; Del Carratore, Francesco; Cummings, Matthew; Takano, Eriko; Breitling, Rainer

    2017-12-18

    The rapid increase of publicly available microbial genome sequences has highlighted the presence of hundreds of thousands of biosynthetic gene clusters (BGCs) encoding valuable secondary metabolites. The experimental characterization of new BGCs is extremely laborious and struggles to keep pace with the in silico identification of potential BGCs. Therefore, the prioritisation of promising candidates among computationally predicted BGCs represents a pressing need. Here, we propose an output ordering and prioritisation system (OOPS) which helps sorting identified BGCs by a wide variety of custom-weighted biological and biochemical criteria in a flexible and user-friendly interface. OOPS facilitates a judicious prioritisation of BGCs using G+C content, coding sequence length, gene number, cluster self-similarity and codon bias parameters, as well as enabling the user to rank BGCs based upon BGC type, novelty, and taxonomic distribution. Effective prioritisation of BGCs will help to reduce experimental attrition rates and improve the breadth of bioactive metabolites characterized.

  4. Glycosulfatase-Encoding Gene Cluster in Bifidobacterium breve UCC2003.

    Science.gov (United States)

    Egan, Muireann; Jiang, Hao; O'Connell Motherway, Mary; Oscarson, Stefan; van Sinderen, Douwe

    2016-11-15

    Bifidobacteria constitute a specific group of commensal bacteria typically found in the gastrointestinal tract (GIT) of humans and other mammals. Bifidobacterium breve strains are numerically prevalent among the gut microbiota of many healthy breastfed infants. In the present study, we investigated glycosulfatase activity in a bacterial isolate from a nursling stool sample, B. breve UCC2003. Two putative sulfatases were identified on the genome of B. breve UCC2003. The sulfated monosaccharide N-acetylglucosamine-6-sulfate (GlcNAc-6-S) was shown to support the growth of B. breve UCC2003, while N-acetylglucosamine-3-sulfate, N-acetylgalactosamine-3-sulfate, and N-acetylgalactosamine-6-sulfate did not support appreciable growth. By using a combination of transcriptomic and functional genomic approaches, a gene cluster designated ats2 was shown to be specifically required for GlcNAc-6-S metabolism. Transcription of the ats2 cluster is regulated by a repressor open reading frame kinase (ROK) family transcriptional repressor. This study represents the first description of glycosulfatase activity within the Bifidobacterium genus. Bifidobacteria are saccharolytic organisms naturally found in the digestive tract of mammals and insects. Bifidobacterium breve strains utilize a variety of plant- and host-derived carbohydrates that allow them to be present as prominent members of the infant gut microbiota as well as being present in the gastrointestinal tract of adults. In this study, we introduce a previously unexplored area of carbohydrate metabolism in bifidobacteria, namely, the metabolism of sulfated carbohydrates. B. breve UCC2003 was shown to metabolize N-acetylglucosamine-6-sulfate (GlcNAc-6-S) through one of two sulfatase-encoding gene clusters identified on its genome. GlcNAc-6-S can be found in terminal or branched positions of mucin oligosaccharides, the glycoprotein component of the mucous layer that covers the digestive tract. The results of this study provide

  5. Invasive Species Management on Military Lands: Clustered Regularly Interspaced Short Palindromic Repeat/ CRISPR associated protein 9 (CRISPR/Cas9) based Gene Drives

    Science.gov (United States)

    2017-06-30

    of the crRNA base pairs with tar- get DNA, whereas the 3’ end forms a double- stranded stem with the tra- crRNA to facilitate Cas9 recruitment...or y Ping Gong June 2017 Approved for public release; distribution is unlimited. The U.S. Army Engineer Research and Development...Gong Environmental Laboratory U.S. Army Engineer Research and Development Center 3909 Halls Ferry Road Vicksburg, MS 39180 Final report

  6. Structures of three different neutral polysaccharides of Acinetobacter baumannii, NIPH190, NIPH201, and NIPH615, assigned to K30, K45, and K48 capsule types, respectively, based on capsule biosynthesis gene clusters.

    Science.gov (United States)

    Shashkov, Alexander S; Kenyon, Johanna J; Arbatsky, Nikolay P; Shneider, Mikhail M; Popova, Anastasiya V; Miroshnikov, Konstantin A; Volozhantsev, Nikolay V; Knirel, Yuriy A

    2015-11-19

    Neutral capsular polysaccharides (CPSs) were isolated from Acinetobacter baumannii NIPH190, NIPH201, and NIPH615. The CPSs were found to contain common monosaccharides only and to be branched with a side-chain 1→3-linked β-d-glucopyranose residue. Structures of the oligosaccharide repeat units (K units) of the CPSs were elucidated by 1D and 2D (1)H and (13)C NMR spectroscopy. Novel CPS biosynthesis gene clusters, designated KL30, KL45, and KL48, were found at the K locus in the genome sequences of NIPH190, NIPH201, and NIPH615, respectively. The genetic content of each gene cluster correlated with the structure of the CPS unit established, and therefore, the capsular types of the strains studied were designated as K30, K45, and K48, respectively. The initiating sugar of each K unit was predicted, and glycosyltransferases encoded by each gene cluster were assigned to the formation of the linkages between sugars in the corresponding K unit. Copyright © 2015 Elsevier Ltd. All rights reserved.

  7. GraphTeams: a method for discovering spatial gene clusters in Hi-C sequencing data.

    Science.gov (United States)

    Schulz, Tizian; Stoye, Jens; Doerr, Daniel

    2018-05-08

    Hi-C sequencing offers novel, cost-effective means to study the spatial conformation of chromosomes. We use data obtained from Hi-C experiments to provide new evidence for the existence of spatial gene clusters. These are sets of genes with associated functionality that exhibit close proximity to each other in the spatial conformation of chromosomes across several related species. We present the first gene cluster model capable of handling spatial data. Our model generalizes a popular computational model for gene cluster prediction, called δ-teams, from sequences to graphs. Following previous lines of research, we subsequently extend our model to allow for several vertices being associated with the same label. The model, called δ-teams with families, is particular suitable for our application as it enables handling of gene duplicates. We develop algorithmic solutions for both models. We implemented the algorithm for discovering δ-teams with families and integrated it into a fully automated workflow for discovering gene clusters in Hi-C data, called GraphTeams. We applied it to human and mouse data to find intra- and interchromosomal gene cluster candidates. The results include intrachromosomal clusters that seem to exhibit a closer proximity in space than on their chromosomal DNA sequence. We further discovered interchromosomal gene clusters that contain genes from different chromosomes within the human genome, but are located on a single chromosome in mouse. By identifying δ-teams with families, we provide a flexible model to discover gene cluster candidates in Hi-C data. Our analysis of Hi-C data from human and mouse reveals several known gene clusters (thus validating our approach), but also few sparsely studied or possibly unknown gene cluster candidates that could be the source of further experimental investigations.

  8. Characterization of the biosynthetic gene cluster for cryptic phthoxazolin A in Streptomyces avermitilis.

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    Dian Anggraini Suroto

    Full Text Available Phthoxazolin A, an oxazole-containing polyketide, has a broad spectrum of anti-oomycete activity and herbicidal activity. We recently identified phthoxazolin A as a cryptic metabolite of Streptomyces avermitilis that produces the important anthelmintic agent avermectin. Even though genome data of S. avermitilis is publicly available, no plausible biosynthetic gene cluster for phthoxazolin A is apparent in the sequence data. Here, we identified and characterized the phthoxazolin A (ptx biosynthetic gene cluster through genome sequencing, comparative genomic analysis, and gene disruption. Sequence analysis uncovered that the putative ptx biosynthetic genes are laid on an extra genomic region that is not found in the public database, and 8 open reading frames in the extra genomic region could be assigned roles in the biosynthesis of the oxazole ring, triene polyketide and carbamoyl moieties. Disruption of the ptxA gene encoding a discrete acyltransferase resulted in a complete loss of phthoxazolin A production, confirming that the trans-AT type I PKS system is responsible for the phthoxazolin A biosynthesis. Based on the predicted functional domains in the ptx assembly line, we propose the biosynthetic pathway of phthoxazolin A.

  9. Membership determination of open clusters based on a spectral clustering method

    Science.gov (United States)

    Gao, Xin-Hua

    2018-06-01

    We present a spectral clustering (SC) method aimed at segregating reliable members of open clusters in multi-dimensional space. The SC method is a non-parametric clustering technique that performs cluster division using eigenvectors of the similarity matrix; no prior knowledge of the clusters is required. This method is more flexible in dealing with multi-dimensional data compared to other methods of membership determination. We use this method to segregate the cluster members of five open clusters (Hyades, Coma Ber, Pleiades, Praesepe, and NGC 188) in five-dimensional space; fairly clean cluster members are obtained. We find that the SC method can capture a small number of cluster members (weak signal) from a large number of field stars (heavy noise). Based on these cluster members, we compute the mean proper motions and distances for the Hyades, Coma Ber, Pleiades, and Praesepe clusters, and our results are in general quite consistent with the results derived by other authors. The test results indicate that the SC method is highly suitable for segregating cluster members of open clusters based on high-precision multi-dimensional astrometric data such as Gaia data.

  10. Voting-based consensus clustering for combining multiple clusterings of chemical structures

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    Saeed Faisal

    2012-12-01

    Full Text Available Abstract Background Although many consensus clustering methods have been successfully used for combining multiple classifiers in many areas such as machine learning, applied statistics, pattern recognition and bioinformatics, few consensus clustering methods have been applied for combining multiple clusterings of chemical structures. It is known that any individual clustering method will not always give the best results for all types of applications. So, in this paper, three voting and graph-based consensus clusterings were used for combining multiple clusterings of chemical structures to enhance the ability of separating biologically active molecules from inactive ones in each cluster. Results The cumulative voting-based aggregation algorithm (CVAA, cluster-based similarity partitioning algorithm (CSPA and hyper-graph partitioning algorithm (HGPA were examined. The F-measure and Quality Partition Index method (QPI were used to evaluate the clusterings and the results were compared to the Ward’s clustering method. The MDL Drug Data Report (MDDR dataset was used for experiments and was represented by two 2D fingerprints, ALOGP and ECFP_4. The performance of voting-based consensus clustering method outperformed the Ward’s method using F-measure and QPI method for both ALOGP and ECFP_4 fingerprints, while the graph-based consensus clustering methods outperformed the Ward’s method only for ALOGP using QPI. The Jaccard and Euclidean distance measures were the methods of choice to generate the ensembles, which give the highest values for both criteria. Conclusions The results of the experiments show that consensus clustering methods can improve the effectiveness of chemical structures clusterings. The cumulative voting-based aggregation algorithm (CVAA was the method of choice among consensus clustering methods.

  11. Transcriptional interference networks coordinate the expression of functionally-related genes clustered in the same genomic loci

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    Zsolt eBoldogkoi

    2012-07-01

    Full Text Available The regulation of gene expression is essential for normal functioning of biological systems in every form of life. Gene expression is primarily controlled at the level of transcription, especially at the phase of initiation. Non-coding RNAs are one of the major players at every level of genetic regulation, including the control of chromatin organisation, transcription, various post-transcriptional processes and translation. In this study, the Transcriptional Interference Network (TIN hypothesis was put forward in an attempt to explain the global expression of antisense RNAs and the overall occurrence of tandem gene clusters in the genomes of various biological systems ranging from viruses to mammalian cells. The TIN hypothesis suggests the existence of a novel layer of genetic regulation, based on the interactions between the transcriptional machineries of neighbouring genes at their overlapping regions, which are assumed to play a fundamental role in coordinating gene expression within a cluster of functionally-linked genes. It is claimed that the transcriptional overlaps between adjacent genes are much more widespread in genomes than is thought today. The Waterfall model of the TIN hypothesis postulates a unidirectional effect of upstream genes on the transcription of downstream genes within a cluster of tandemly-arrayed genes, while the Seesaw model proposes a mutual interdependence of gene expression between the oppositely-oriented genes. The TIN represents an auto-regulatory system with an exquisitely timed and highly synchronised cascade of gene expression in functionally-linked genes located in close physical proximity to each other. In this study, we focused on herpesviruses. The reason for this lies in the compressed nature of viral genes, which allows a tight regulation and an easier investigation of the transcriptional interactions between genes. However, I believe that the same or similar principles can be applied to cellular

  12. Clustering gene expression time series data using an infinite Gaussian process mixture model.

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    McDowell, Ian C; Manandhar, Dinesh; Vockley, Christopher M; Schmid, Amy K; Reddy, Timothy E; Engelhardt, Barbara E

    2018-01-01

    Transcriptome-wide time series expression profiling is used to characterize the cellular response to environmental perturbations. The first step to analyzing transcriptional response data is often to cluster genes with similar responses. Here, we present a nonparametric model-based method, Dirichlet process Gaussian process mixture model (DPGP), which jointly models data clusters with a Dirichlet process and temporal dependencies with Gaussian processes. We demonstrate the accuracy of DPGP in comparison to state-of-the-art approaches using hundreds of simulated data sets. To further test our method, we apply DPGP to published microarray data from a microbial model organism exposed to stress and to novel RNA-seq data from a human cell line exposed to the glucocorticoid dexamethasone. We validate our clusters by examining local transcription factor binding and histone modifications. Our results demonstrate that jointly modeling cluster number and temporal dependencies can reveal shared regulatory mechanisms. DPGP software is freely available online at https://github.com/PrincetonUniversity/DP_GP_cluster.

  13. Clustering gene expression time series data using an infinite Gaussian process mixture model.

    Directory of Open Access Journals (Sweden)

    Ian C McDowell

    2018-01-01

    Full Text Available Transcriptome-wide time series expression profiling is used to characterize the cellular response to environmental perturbations. The first step to analyzing transcriptional response data is often to cluster genes with similar responses. Here, we present a nonparametric model-based method, Dirichlet process Gaussian process mixture model (DPGP, which jointly models data clusters with a Dirichlet process and temporal dependencies with Gaussian processes. We demonstrate the accuracy of DPGP in comparison to state-of-the-art approaches using hundreds of simulated data sets. To further test our method, we apply DPGP to published microarray data from a microbial model organism exposed to stress and to novel RNA-seq data from a human cell line exposed to the glucocorticoid dexamethasone. We validate our clusters by examining local transcription factor binding and histone modifications. Our results demonstrate that jointly modeling cluster number and temporal dependencies can reveal shared regulatory mechanisms. DPGP software is freely available online at https://github.com/PrincetonUniversity/DP_GP_cluster.

  14. Genetic clusters and sex-biased gene flow in a unicolonial Formica ant

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    Chapuisat Michel

    2009-03-01

    Full Text Available Abstract Background Animal societies are diverse, ranging from small family-based groups to extraordinarily large social networks in which many unrelated individuals interact. At the extreme of this continuum, some ant species form unicolonial populations in which workers and queens can move among multiple interconnected nests without eliciting aggression. Although unicoloniality has been mostly studied in invasive ants, it also occurs in some native non-invasive species. Unicoloniality is commonly associated with very high queen number, which may result in levels of relatedness among nestmates being so low as to raise the question of the maintenance of altruism by kin selection in such systems. However, the actual relatedness among cooperating individuals critically depends on effective dispersal and the ensuing pattern of genetic structuring. In order to better understand the evolution of unicoloniality in native non-invasive ants, we investigated the fine-scale population genetic structure and gene flow in three unicolonial populations of the wood ant F. paralugubris. Results The analysis of geo-referenced microsatellite genotypes and mitochondrial haplotypes revealed the presence of cryptic clusters of genetically-differentiated nests in the three populations of F. paralugubris. Because of this spatial genetic heterogeneity, members of the same clusters were moderately but significantly related. The comparison of nuclear (microsatellite and mitochondrial differentiation indicated that effective gene flow was male-biased in all populations. Conclusion The three unicolonial populations exhibited male-biased and mostly local gene flow. The high number of queens per nest, exchanges among neighbouring nests and restricted long-distance gene flow resulted in large clusters of genetically similar nests. The positive relatedness among clustermates suggests that kin selection may still contribute to the maintenance of altruism in unicolonial

  15. Gene cluster analysis for the biosynthesis of elgicins, novel lantibiotics produced by paenibacillus elgii B69

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    Teng Yi

    2012-03-01

    Full Text Available Abstract Background The recent increase in bacterial resistance to antibiotics has promoted the exploration of novel antibacterial materials. As a result, many researchers are undertaking work to identify new lantibiotics because of their potent antimicrobial activities. The objective of this study was to provide details of a lantibiotic-like gene cluster in Paenibacillus elgii B69 and to produce the antibacterial substances coded by this gene cluster based on culture screening. Results Analysis of the P. elgii B69 genome sequence revealed the presence of a lantibiotic-like gene cluster composed of five open reading frames (elgT1, elgC, elgT2, elgB, and elgA. Screening of culture extracts for active substances possessing the predicted properties of the encoded product led to the isolation of four novel peptides (elgicins AI, AII, B, and C with a broad inhibitory spectrum. The molecular weights of these peptides were 4536, 4593, 4706, and 4820 Da, respectively. The N-terminal sequence of elgicin B was Leu-Gly-Asp-Tyr, which corresponded to the partial sequence of the peptide ElgA encoded by elgA. Edman degradation suggested that the product elgicin B is derived from ElgA. By correlating the results of electrospray ionization-mass spectrometry analyses of elgicins AI, AII, and C, these peptides are deduced to have originated from the same precursor, ElgA. Conclusions A novel lantibiotic-like gene cluster was shown to be present in P. elgii B69. Four new lantibiotics with a broad inhibitory spectrum were isolated, and these appear to be promising antibacterial agents.

  16. Comparative analysis of clustering methods for gene expression time course data

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    Ivan G. Costa

    2004-01-01

    Full Text Available This work performs a data driven comparative study of clustering methods used in the analysis of gene expression time courses (or time series. Five clustering methods found in the literature of gene expression analysis are compared: agglomerative hierarchical clustering, CLICK, dynamical clustering, k-means and self-organizing maps. In order to evaluate the methods, a k-fold cross-validation procedure adapted to unsupervised methods is applied. The accuracy of the results is assessed by the comparison of the partitions obtained in these experiments with gene annotation, such as protein function and series classification.

  17. A phylogenomic gene cluster resource: The phylogeneticallyinferred groups (PhlGs) database

    Energy Technology Data Exchange (ETDEWEB)

    Dehal, Paramvir S.; Boore, Jeffrey L.

    2005-08-25

    We present here the PhIGs database, a phylogenomic resource for sequenced genomes. Although many methods exist for clustering gene families, very few attempt to create truly orthologous clusters sharing descent from a single ancestral gene across a range of evolutionary depths. Although these non-phylogenetic gene family clusters have been used broadly for gene annotation, errors are known to be introduced by the artifactual association of slowly evolving paralogs and lack of annotation for those more rapidly evolving. A full phylogenetic framework is necessary for accurate inference of function and for many studies that address pattern and mechanism of the evolution of the genome. The automated generation of evolutionary gene clusters, creation of gene trees, determination of orthology and paralogy relationships, and the correlation of this information with gene annotations, expression information, and genomic context is an important resource to the scientific community.

  18. The complete coenzyme B12 biosynthesis gene cluster of Lactobacillus reuteri CRL 1098

    NARCIS (Netherlands)

    Santos, dos F.; Vera, J.L.; Heijden, van der R.; Valdez, G.F.; Vos, de W.M.; Sesma, F.; Hugenholtz, J.

    2008-01-01

    The coenzyme B12 production pathway in Lactobacillus reuteri has been deduced using a combination of genetic, biochemical and bioinformatics approaches. The coenzyme B12 gene cluster of Lb. reuteri CRL1098 has the unique feature of clustering together the cbi, cob and hem genes. It consists of 29

  19. Variation in sequence and location of the fumonisin mycotoxin niosynthetic gene cluster in Fusarium

    NARCIS (Netherlands)

    Proctor, R.H.; Hove, van F.; Susca, A.; Stea, A.; Busman, M.; Lee, van der T.A.J.; Waalwijk, C.; Moretti, A.

    2010-01-01

    In Fusarium, the ability to produce fumonisins is governed by a 17-gene fumonisin biosynthetic gene (FUM) cluster. Here, we examined the cluster in F. oxysporum strain O-1890 and nine other species selected to represent a wide range of the genetic diversity within the GFSC.

  20. Dominant control region of the human β- like globin gene cluster

    NARCIS (Netherlands)

    Blom van Assendelft, Margaretha van

    1989-01-01

    The structure and regulation of the human β -like globin gene cluster has been studied extensively. Genetic disorders connected with this gene cluster are responsible for human diseases associated with high levels of morbidity and mortality, such as β-thalassaemia and sickle cell anaemia. The work

  1. Constructing storyboards based on hierarchical clustering analysis

    Science.gov (United States)

    Hasebe, Satoshi; Sami, Mustafa M.; Muramatsu, Shogo; Kikuchi, Hisakazu

    2005-07-01

    There are growing needs for quick preview of video contents for the purpose of improving accessibility of video archives as well as reducing network traffics. In this paper, a storyboard that contains a user-specified number of keyframes is produced from a given video sequence. It is based on hierarchical cluster analysis of feature vectors that are derived from wavelet coefficients of video frames. Consistent use of extracted feature vectors is the key to avoid a repetition of computationally-intensive parsing of the same video sequence. Experimental results suggest that a significant reduction in computational time is gained by this strategy.

  2. CBHRP: A Cluster Based Routing Protocol for Wireless Sensor Network

    OpenAIRE

    Rashed, M. G.; Kabir, M. Hasnat; Rahim, M. Sajjadur; Ullah, Sk. Enayet

    2012-01-01

    A new two layer hierarchical routing protocol called Cluster Based Hierarchical Routing Protocol (CBHRP) is proposed in this paper. It is an extension of LEACH routing protocol. We introduce cluster head-set idea for cluster-based routing where several clusters are formed with the deployed sensors to collect information from target field. On rotation basis, a head-set member receives data from the neighbor nodes and transmits the aggregated results to the distance base station. This protocol ...

  3. A Novel Cluster Head Selection Algorithm Based on Fuzzy Clustering and Particle Swarm Optimization.

    Science.gov (United States)

    Ni, Qingjian; Pan, Qianqian; Du, Huimin; Cao, Cen; Zhai, Yuqing

    2017-01-01

    An important objective of wireless sensor network is to prolong the network life cycle, and topology control is of great significance for extending the network life cycle. Based on previous work, for cluster head selection in hierarchical topology control, we propose a solution based on fuzzy clustering preprocessing and particle swarm optimization. More specifically, first, fuzzy clustering algorithm is used to initial clustering for sensor nodes according to geographical locations, where a sensor node belongs to a cluster with a determined probability, and the number of initial clusters is analyzed and discussed. Furthermore, the fitness function is designed considering both the energy consumption and distance factors of wireless sensor network. Finally, the cluster head nodes in hierarchical topology are determined based on the improved particle swarm optimization. Experimental results show that, compared with traditional methods, the proposed method achieved the purpose of reducing the mortality rate of nodes and extending the network life cycle.

  4. Clusters of orthologous genes for 41 archaeal genomes and implications for evolutionary genomics of archaea

    Directory of Open Access Journals (Sweden)

    Wolf Yuri I

    2007-11-01

    Full Text Available Abstract Background An evolutionary classification of genes from sequenced genomes that distinguishes between orthologs and paralogs is indispensable for genome annotation and evolutionary reconstruction. Shortly after multiple genome sequences of bacteria, archaea, and unicellular eukaryotes became available, an attempt on such a classification was implemented in Clusters of Orthologous Groups of proteins (COGs. Rapid accumulation of genome sequences creates opportunities for refining COGs but also represents a challenge because of error amplification. One of the practical strategies involves construction of refined COGs for phylogenetically compact subsets of genomes. Results New Archaeal Clusters of Orthologous Genes (arCOGs were constructed for 41 archaeal genomes (13 Crenarchaeota, 27 Euryarchaeota and one Nanoarchaeon using an improved procedure that employs a similarity tree between smaller, group-specific clusters, semi-automatically partitions orthology domains in multidomain proteins, and uses profile searches for identification of remote orthologs. The annotation of arCOGs is a consensus between three assignments based on the COGs, the CDD database, and the annotations of homologs in the NR database. The 7538 arCOGs, on average, cover ~88% of the genes in a genome compared to a ~76% coverage in COGs. The finer granularity of ortholog identification in the arCOGs is apparent from the fact that 4538 arCOGs correspond to 2362 COGs; ~40% of the arCOGs are new. The archaeal gene core (protein-coding genes found in all 41 genome consists of 166 arCOGs. The arCOGs were used to reconstruct gene loss and gene gain events during archaeal evolution and gene sets of ancestral forms. The Last Archaeal Common Ancestor (LACA is conservatively estimated to possess 996 genes compared to 1245 and 1335 genes for the last common ancestors of Crenarchaeota and Euryarchaeota, respectively. It is inferred that LACA was a chemoautotrophic hyperthermophile

  5. A mixture model-based approach to the clustering of microarray expression data.

    Science.gov (United States)

    McLachlan, G J; Bean, R W; Peel, D

    2002-03-01

    This paper introduces the software EMMIX-GENE that has been developed for the specific purpose of a model-based approach to the clustering of microarray expression data, in particular, of tissue samples on a very large number of genes. The latter is a nonstandard problem in parametric cluster analysis because the dimension of the feature space (the number of genes) is typically much greater than the number of tissues. A feasible approach is provided by first selecting a subset of the genes relevant for the clustering of the tissue samples by fitting mixtures of t distributions to rank the genes in order of increasing size of the likelihood ratio statistic for the test of one versus two components in the mixture model. The imposition of a threshold on the likelihood ratio statistic used in conjunction with a threshold on the size of a cluster allows the selection of a relevant set of genes. However, even this reduced set of genes will usually be too large for a normal mixture model to be fitted directly to the tissues, and so the use of mixtures of factor analyzers is exploited to reduce effectively the dimension of the feature space of genes. The usefulness of the EMMIX-GENE approach for the clustering of tissue samples is demonstrated on two well-known data sets on colon and leukaemia tissues. For both data sets, relevant subsets of the genes are able to be selected that reveal interesting clusterings of the tissues that are either consistent with the external classification of the tissues or with background and biological knowledge of these sets. EMMIX-GENE is available at http://www.maths.uq.edu.au/~gjm/emmix-gene/

  6. CAR gene cluster and transcript levels of carotenogenic genes in Rhodotorula mucilaginosa.

    Science.gov (United States)

    Landolfo, Sara; Ianiri, Giuseppe; Camiolo, Salvatore; Porceddu, Andrea; Mulas, Giuliana; Chessa, Rossella; Zara, Giacomo; Mannazzu, Ilaria

    2018-01-01

    A molecular approach was applied to the study of the carotenoid biosynthetic pathway of Rhodotorula mucilaginosa. At first, functional annotation of the genome of R. mucilaginosa C2.5t1 was carried out and gene ontology categories were assigned to 4033 predicted proteins. Then, a set of genes involved in different steps of carotenogenesis was identified and those coding for phytoene desaturase, phytoene synthase/lycopene cyclase and carotenoid dioxygenase (CAR genes) proved to be clustered within a region of ~10 kb. Quantitative PCR of the genes involved in carotenoid biosynthesis showed that genes coding for 3-hydroxy-3-methylglutharyl-CoA reductase and mevalonate kinase are induced during exponential phase while no clear trend of induction was observed for phytoene synthase/lycopene cyclase and phytoene dehydrogenase encoding genes. Thus, in R. mucilaginosa the induction of genes involved in the early steps of carotenoid biosynthesis is transient and accompanies the onset of carotenoid production, while that of CAR genes does not correlate with the amount of carotenoids produced. The transcript levels of genes coding for carotenoid dioxygenase, superoxide dismutase and catalase A increased during the accumulation of carotenoids, thus suggesting the activation of a mechanism aimed at the protection of cell structures from oxidative stress during carotenoid biosynthesis. The data presented herein, besides being suitable for the elucidation of the mechanisms that underlie carotenoid biosynthesis, will contribute to boosting the biotechnological potential of this yeast by improving the outcome of further research efforts aimed at also exploring other features of interest.

  7. Cloning and Characterization of the Polyether Salinomycin Biosynthesis Gene Cluster of Streptomyces albus XM211

    Science.gov (United States)

    Jiang, Chunyan; Wang, Hougen; Kang, Qianjin; Liu, Jing

    2012-01-01

    Salinomycin is widely used in animal husbandry as a food additive due to its antibacterial and anticoccidial activities. However, its biosynthesis had only been studied by feeding experiments with isotope-labeled precursors. A strategy with degenerate primers based on the polyether-specific epoxidase sequences was successfully developed to clone the salinomycin gene cluster. Using this strategy, a putative epoxidase gene, slnC, was cloned from the salinomycin producer Streptomyces albus XM211. The targeted replacement of slnC and subsequent trans-complementation proved its involvement in salinomycin biosynthesis. A 127-kb DNA region containing slnC was sequenced, including genes for polyketide assembly and release, oxidative cyclization, modification, export, and regulation. In order to gain insight into the salinomycin biosynthesis mechanism, 13 gene replacements and deletions were conducted. Including slnC, 7 genes were identified as essential for salinomycin biosynthesis and putatively responsible for polyketide chain release, oxidative cyclization, modification, and regulation. Moreover, 6 genes were found to be relevant to salinomycin biosynthesis and possibly involved in precursor supply, removal of aberrant extender units, and regulation. Sequence analysis and a series of gene replacements suggest a proposed pathway for the biosynthesis of salinomycin. The information presented here expands the understanding of polyether biosynthesis mechanisms and paves the way for targeted engineering of salinomycin activity and productivity. PMID:22156425

  8. Cluster Ensemble-Based Image Segmentation

    Directory of Open Access Journals (Sweden)

    Xiaoru Wang

    2013-07-01

    Full Text Available Image segmentation is the foundation of computer vision applications. In this paper, we propose a new cluster ensemble-based image segmentation algorithm, which overcomes several problems of traditional methods. We make two main contributions in this paper. First, we introduce the cluster ensemble concept to fuse the segmentation results from different types of visual features effectively, which can deliver a better final result and achieve a much more stable performance for broad categories of images. Second, we exploit the PageRank idea from Internet applications and apply it to the image segmentation task. This can improve the final segmentation results by combining the spatial information of the image and the semantic similarity of regions. Our experiments on four public image databases validate the superiority of our algorithm over conventional single type of feature or multiple types of features-based algorithms, since our algorithm can fuse multiple types of features effectively for better segmentation results. Moreover, our method is also proved to be very competitive in comparison with other state-of-the-art segmentation algorithms.

  9. Stigmergy based behavioural coordination for satellite clusters

    Science.gov (United States)

    Tripp, Howard; Palmer, Phil

    2010-04-01

    Multi-platform swarm/cluster missions are an attractive prospect for improved science return as they provide a natural capability for temporal, spatial and signal separation with further engineering and economic advantages. As spacecraft numbers increase and/or the round-trip communications delay from Earth lengthens, the traditional "remote-control" approach begins to break down. It is therefore essential to push control into space; to make spacecraft more autonomous. An autonomous group of spacecraft requires coordination, but standard terrestrial paradigms such as negotiation, require high levels of inter-spacecraft communication, which is nontrivial in space. This article therefore introduces the principals of stigmergy as a novel method for coordinating a cluster. Stigmergy is an agent-based, behavioural approach that allows for infrequent communication with decisions based on local information. Behaviours are selected dynamically using a genetic algorithm onboard. supervisors/ground stations occasionally adjust parameters and disseminate a "common environment" that is used for local decisions. After outlining the system, an analysis of some crucial parameters such as communications overhead and number of spacecraft is presented to demonstrate scalability. Further scenarios are considered to demonstrate the natural ability to deal with dynamic situations such as the failure of spacecraft, changing mission objectives and responding to sudden bursts of high priority tasks.

  10. Cosmological constraints with clustering-based redshifts

    Science.gov (United States)

    Kovetz, Ely D.; Raccanelli, Alvise; Rahman, Mubdi

    2017-07-01

    We demonstrate that observations lacking reliable redshift information, such as photometric and radio continuum surveys, can produce robust measurements of cosmological parameters when empowered by clustering-based redshift estimation. This method infers the redshift distribution based on the spatial clustering of sources, using cross-correlation with a reference data set with known redshifts. Applying this method to the existing Sloan Digital Sky Survey (SDSS) photometric galaxies, and projecting to future radio continuum surveys, we show that sources can be efficiently divided into several redshift bins, increasing their ability to constrain cosmological parameters. We forecast constraints on the dark-energy equation of state and on local non-Gaussianity parameters. We explore several pertinent issues, including the trade-off between including more sources and minimizing the overlap between bins, the shot-noise limitations on binning and the predicted performance of the method at high redshifts, and most importantly pay special attention to possible degeneracies with the galaxy bias. Remarkably, we find that once this technique is implemented, constraints on dynamical dark energy from the SDSS imaging catalogue can be competitive with, or better than, those from the spectroscopic BOSS survey and even future planned experiments. Further, constraints on primordial non-Gaussianity from future large-sky radio-continuum surveys can outperform those from the Planck cosmic microwave background experiment and rival those from future spectroscopic galaxy surveys. The application of this method thus holds tremendous promise for cosmology.

  11. Orbit Clustering Based on Transfer Cost

    Science.gov (United States)

    Gustafson, Eric D.; Arrieta-Camacho, Juan J.; Petropoulos, Anastassios E.

    2013-01-01

    We propose using cluster analysis to perform quick screening for combinatorial global optimization problems. The key missing component currently preventing cluster analysis from use in this context is the lack of a useable metric function that defines the cost to transfer between two orbits. We study several proposed metrics and clustering algorithms, including k-means and the expectation maximization algorithm. We also show that proven heuristic methods such as the Q-law can be modified to work with cluster analysis.

  12. Hierarchical video summarization based on context clustering

    Science.gov (United States)

    Tseng, Belle L.; Smith, John R.

    2003-11-01

    A personalized video summary is dynamically generated in our video personalization and summarization system based on user preference and usage environment. The three-tier personalization system adopts the server-middleware-client architecture in order to maintain, select, adapt, and deliver rich media content to the user. The server stores the content sources along with their corresponding MPEG-7 metadata descriptions. In this paper, the metadata includes visual semantic annotations and automatic speech transcriptions. Our personalization and summarization engine in the middleware selects the optimal set of desired video segments by matching shot annotations and sentence transcripts with user preferences. Besides finding the desired contents, the objective is to present a coherent summary. There are diverse methods for creating summaries, and we focus on the challenges of generating a hierarchical video summary based on context information. In our summarization algorithm, three inputs are used to generate the hierarchical video summary output. These inputs are (1) MPEG-7 metadata descriptions of the contents in the server, (2) user preference and usage environment declarations from the user client, and (3) context information including MPEG-7 controlled term list and classification scheme. In a video sequence, descriptions and relevance scores are assigned to each shot. Based on these shot descriptions, context clustering is performed to collect consecutively similar shots to correspond to hierarchical scene representations. The context clustering is based on the available context information, and may be derived from domain knowledge or rules engines. Finally, the selection of structured video segments to generate the hierarchical summary efficiently balances between scene representation and shot selection.

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

    Science.gov (United States)

    Do, Jin Hwan; Choi, Dong-Kug

    2008-04-30

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

  14. ATNT: an enhanced system for expression of polycistronic secondary metabolite gene clusters in Aspergillus niger.

    Science.gov (United States)

    Geib, Elena; Brock, Matthias

    2017-01-01

    Fungi are treasure chests for yet unexplored natural products. However, exploitation of their real potential remains difficult as a significant proportion of biosynthetic gene clusters appears silent under standard laboratory conditions. Therefore, elucidation of novel products requires gene activation or heterologous expression. For heterologous gene expression, we previously developed an expression platform in Aspergillus niger that is based on the transcriptional regulator TerR and its target promoter P terA . In this study, we extended this system by regulating expression of terR  by the doxycycline inducible Tet-on system. Reporter genes cloned under the control of the target promoter P terA remained silent in the absence of doxycycline, but were strongly expressed when doxycycline was added. Reporter quantification revealed that the coupled system results in about five times higher expression rates compared to gene expression under direct control of the Tet-on system. As production of secondary metabolites generally requires the expression of several biosynthetic genes, the suitability of the self-cleaving viral peptide sequence P2A was tested in this optimised expression system. P2A allowed polycistronic expression of genes required for Asp-melanin formation in combination with the gene coding for the red fluorescent protein tdTomato. Gene expression and Asp-melanin formation was prevented in the absence of doxycycline and strongly induced by addition of doxycycline. Fluorescence studies confirmed the correct subcellular localisation of the respective enzymes. This tightly regulated but strongly inducible expression system enables high level production of secondary metabolites most likely even those with toxic potential. Furthermore, this system is compatible with polycistronic gene expression and, thus, suitable for the discovery of novel natural products.

  15. SU-E-J-98: Radiogenomics: Correspondence Between Imaging and Genetic Features Based On Clustering Analysis

    International Nuclear Information System (INIS)

    Harmon, S; Wendelberger, B; Jeraj, R

    2014-01-01

    Purpose: Radiogenomics aims to establish relationships between patient genotypes and imaging phenotypes. An open question remains on how best to integrate information from these distinct datasets. This work investigates if similarities in genetic features across patients correspond to similarities in PET-imaging features, assessed with various clustering algorithms. Methods: [ 18 F]FDG PET data was obtained for 26 NSCLC patients from a public database (TCIA). Tumors were contoured using an in-house segmentation algorithm combining gradient and region-growing techniques; resulting ROIs were used to extract 54 PET-based features. Corresponding genetic microarray data containing 48,778 elements were also obtained for each tumor. Given mismatch in feature sizes, two dimension reduction techniques were also applied to the genetic data: principle component analysis (PCA) and selective filtering of 25 NSCLC-associated genes-ofinterest (GOI). Gene datasets (full, PCA, and GOI) and PET feature datasets were independently clustered using K-means and hierarchical clustering using variable number of clusters (K). Jaccard Index (JI) was used to score similarity of cluster assignments across different datasets. Results: Patient clusters from imaging data showed poor similarity to clusters from gene datasets, regardless of clustering algorithms or number of clusters (JI mean = 0.3429±0.1623). Notably, we found clustering algorithms had different sensitivities to data reduction techniques. Using hierarchical clustering, the PCA dataset showed perfect cluster agreement to the full-gene set (JI =1) for all values of K, and the agreement between the GOI set and the full-gene set decreased as number of clusters increased (JI=0.9231 and 0.5769 for K=2 and 5, respectively). K-means clustering assignments were highly sensitive to data reduction and showed poor stability for different values of K (JI range : 0.2301–1). Conclusion: Using commonly-used clustering algorithms, we found

  16. SU-E-J-98: Radiogenomics: Correspondence Between Imaging and Genetic Features Based On Clustering Analysis

    Energy Technology Data Exchange (ETDEWEB)

    Harmon, S; Wendelberger, B [University of Wisconsin-Madison, Madison, WI (United States); Jeraj, R [University of Wisconsin-Madison, Madison, WI (United States); University of Ljubljana (Slovenia)

    2014-06-01

    Purpose: Radiogenomics aims to establish relationships between patient genotypes and imaging phenotypes. An open question remains on how best to integrate information from these distinct datasets. This work investigates if similarities in genetic features across patients correspond to similarities in PET-imaging features, assessed with various clustering algorithms. Methods: [{sup 18}F]FDG PET data was obtained for 26 NSCLC patients from a public database (TCIA). Tumors were contoured using an in-house segmentation algorithm combining gradient and region-growing techniques; resulting ROIs were used to extract 54 PET-based features. Corresponding genetic microarray data containing 48,778 elements were also obtained for each tumor. Given mismatch in feature sizes, two dimension reduction techniques were also applied to the genetic data: principle component analysis (PCA) and selective filtering of 25 NSCLC-associated genes-ofinterest (GOI). Gene datasets (full, PCA, and GOI) and PET feature datasets were independently clustered using K-means and hierarchical clustering using variable number of clusters (K). Jaccard Index (JI) was used to score similarity of cluster assignments across different datasets. Results: Patient clusters from imaging data showed poor similarity to clusters from gene datasets, regardless of clustering algorithms or number of clusters (JI{sub mean}= 0.3429±0.1623). Notably, we found clustering algorithms had different sensitivities to data reduction techniques. Using hierarchical clustering, the PCA dataset showed perfect cluster agreement to the full-gene set (JI =1) for all values of K, and the agreement between the GOI set and the full-gene set decreased as number of clusters increased (JI=0.9231 and 0.5769 for K=2 and 5, respectively). K-means clustering assignments were highly sensitive to data reduction and showed poor stability for different values of K (JI{sub range}: 0.2301–1). Conclusion: Using commonly-used clustering algorithms

  17. Comparing clustering models in bank customers: Based on Fuzzy relational clustering approach

    Directory of Open Access Journals (Sweden)

    Ayad Hendalianpour

    2016-11-01

    Full Text Available Clustering is absolutely useful information to explore data structures and has been employed in many places. It organizes a set of objects into similar groups called clusters, and the objects within one cluster are both highly similar and dissimilar with the objects in other clusters. The K-mean, C-mean, Fuzzy C-mean and Kernel K-mean algorithms are the most popular clustering algorithms for their easy implementation and fast work, but in some cases we cannot use these algorithms. Regarding this, in this paper, a hybrid model for customer clustering is presented that is applicable in five banks of Fars Province, Shiraz, Iran. In this way, the fuzzy relation among customers is defined by using their features described in linguistic and quantitative variables. As follows, the customers of banks are grouped according to K-mean, C-mean, Fuzzy C-mean and Kernel K-mean algorithms and the proposed Fuzzy Relation Clustering (FRC algorithm. The aim of this paper is to show how to choose the best clustering algorithms based on density-based clustering and present a new clustering algorithm for both crisp and fuzzy variables. Finally, we apply the proposed approach to five datasets of customer's segmentation in banks. The result of the FCR shows the accuracy and high performance of FRC compared other clustering methods.

  18. In planta functions of cytochrome P450 monooxygenase genes in the phytocassane biosynthetic gene cluster on rice chromosome 2.

    Science.gov (United States)

    Ye, Zhongfeng; Yamazaki, Kohei; Minoda, Hiromi; Miyamoto, Koji; Miyazaki, Sho; Kawaide, Hiroshi; Yajima, Arata; Nojiri, Hideaki; Yamane, Hisakazu; Okada, Kazunori

    2018-06-01

    In response to environmental stressors such as blast fungal infections, rice produces phytoalexins, an antimicrobial diterpenoid compound. Together with momilactones, phytocassanes are among the major diterpenoid phytoalexins. The biosynthetic genes of diterpenoid phytoalexin are organized on the chromosome in functional gene clusters, comprising diterpene cyclase, dehydrogenase, and cytochrome P450 monooxygenase genes. Their functions have been studied extensively using in vitro enzyme assay systems. Specifically, P450 genes (CYP71Z6, Z7; CYP76M5, M6, M7, M8) on rice chromosome 2 have multifunctional activities associated with ent-copalyl diphosphate-related diterpene hydrocarbons, but the in planta contribution of these genes to diterpenoid phytoalexin production remains unknown. Here, we characterized cyp71z7 T-DNA mutant and CYP76M7/M8 RNAi lines to find that potential phytoalexin intermediates accumulated in these P450-suppressed rice plants. The results suggested that in planta, CYP71Z7 is responsible for C2-hydroxylation of phytocassanes and that CYP76M7/M8 is involved in C11α-hydroxylation of 3-hydroxy-cassadiene. Based on these results, we proposed potential routes of phytocassane biosynthesis in planta.

  19. CC_TRS: Continuous Clustering of Trajectory Stream Data Based on Micro Cluster Life

    Directory of Open Access Journals (Sweden)

    Musaab Riyadh

    2017-01-01

    Full Text Available The rapid spreading of positioning devices leads to the generation of massive spatiotemporal trajectories data. In some scenarios, spatiotemporal data are received in stream manner. Clustering of stream data is beneficial for different applications such as traffic management and weather forecasting. In this article, an algorithm for Continuous Clustering of Trajectory Stream Data Based on Micro Cluster Life is proposed. The algorithm consists of two phases. There is the online phase where temporal micro clusters are used to store summarized spatiotemporal information for each group of similar segments. The clustering task in online phase is based on temporal micro cluster lifetime instead of time window technique which divides stream data into time bins and clusters each bin separately. For offline phase, a density based clustering approach is used to generate macro clusters depending on temporal micro clusters. The evaluation of the proposed algorithm on real data sets shows the efficiency and the effectiveness of the proposed algorithm and proved it is efficient alternative to time window technique.

  20. AutoSOME: a clustering method for identifying gene expression modules without prior knowledge of cluster number

    Directory of Open Access Journals (Sweden)

    Cooper James B

    2010-03-01

    Full Text Available Abstract Background Clustering the information content of large high-dimensional gene expression datasets has widespread application in "omics" biology. Unfortunately, the underlying structure of these natural datasets is often fuzzy, and the computational identification of data clusters generally requires knowledge about cluster number and geometry. Results We integrated strategies from machine learning, cartography, and graph theory into a new informatics method for automatically clustering self-organizing map ensembles of high-dimensional data. Our new method, called AutoSOME, readily identifies discrete and fuzzy data clusters without prior knowledge of cluster number or structure in diverse datasets including whole genome microarray data. Visualization of AutoSOME output using network diagrams and differential heat maps reveals unexpected variation among well-characterized cancer cell lines. Co-expression analysis of data from human embryonic and induced pluripotent stem cells using AutoSOME identifies >3400 up-regulated genes associated with pluripotency, and indicates that a recently identified protein-protein interaction network characterizing pluripotency was underestimated by a factor of four. Conclusions By effectively extracting important information from high-dimensional microarray data without prior knowledge or the need for data filtration, AutoSOME can yield systems-level insights from whole genome microarray expression studies. Due to its generality, this new method should also have practical utility for a variety of data-intensive applications, including the results of deep sequencing experiments. AutoSOME is available for download at http://jimcooperlab.mcdb.ucsb.edu/autosome.

  1. Leveraging long sequencing reads to investigate R-gene clustering and variation in sugar beet

    Science.gov (United States)

    Host-pathogen interactions are of prime importance to modern agriculture. Plants utilize various types of resistance genes to mitigate pathogen damage. Identification of the specific gene responsible for a specific resistance can be difficult due to duplication and clustering within R-gene families....

  2. Cluster Based Hierarchical Routing Protocol for Wireless Sensor Network

    OpenAIRE

    Rashed, Md. Golam; Kabir, M. Hasnat; Rahim, Muhammad Sajjadur; Ullah, Shaikh Enayet

    2012-01-01

    The efficient use of energy source in a sensor node is most desirable criteria for prolong the life time of wireless sensor network. In this paper, we propose a two layer hierarchical routing protocol called Cluster Based Hierarchical Routing Protocol (CBHRP). We introduce a new concept called head-set, consists of one active cluster head and some other associate cluster heads within a cluster. The head-set members are responsible for control and management of the network. Results show that t...

  3. ICGE: an R package for detecting relevant clusters and atypical units in gene expression

    Directory of Open Access Journals (Sweden)

    Irigoien Itziar

    2012-02-01

    Full Text Available Abstract Background Gene expression technologies have opened up new ways to diagnose and treat cancer and other diseases. Clustering algorithms are a useful approach with which to analyze genome expression data. They attempt to partition the genes into groups exhibiting similar patterns of variation in expression level. An important problem associated with gene classification is to discern whether the clustering process can find a relevant partition as well as the identification of new genes classes. There are two key aspects to classification: the estimation of the number of clusters, and the decision as to whether a new unit (gene, tumor sample... belongs to one of these previously identified clusters or to a new group. Results ICGE is a user-friendly R package which provides many functions related to this problem: identify the number of clusters using mixed variables, usually found by applied biomedical researchers; detect whether the data have a cluster structure; identify whether a new unit belongs to one of the pre-identified clusters or to a novel group, and classify new units into the corresponding cluster. The functions in the ICGE package are accompanied by help files and easy examples to facilitate its use. Conclusions We demonstrate the utility of ICGE by analyzing simulated and real data sets. The results show that ICGE could be very useful to a broad research community.

  4. Horizontal transfer of a nitrate assimilation gene cluster and ecological transitions in fungi: a phylogenetic study.

    Directory of Open Access Journals (Sweden)

    Jason C Slot

    Full Text Available High affinity nitrate assimilation genes in fungi occur in a cluster (fHANT-AC that can be coordinately regulated. The clustered genes include nrt2, which codes for a high affinity nitrate transporter; euknr, which codes for nitrate reductase; and NAD(PH-nir, which codes for nitrite reductase. Homologs of genes in the fHANT-AC occur in other eukaryotes and prokaryotes, but they have only been found clustered in the oomycete Phytophthora (heterokonts. We performed independent and concatenated phylogenetic analyses of homologs of all three genes in the fHANT-AC. Phylogenetic analyses limited to fungal sequences suggest that the fHANT-AC has been transferred horizontally from a basidiomycete (mushrooms and smuts to an ancestor of the ascomycetous mold Trichoderma reesei. Phylogenetic analyses of sequences from diverse eukaryotes and eubacteria, and cluster structure, are consistent with a hypothesis that the fHANT-AC was assembled in a lineage leading to the oomycetes and was subsequently transferred to the Dikarya (Ascomycota+Basidiomycota, which is a derived fungal clade that includes the vast majority of terrestrial fungi. We propose that the acquisition of high affinity nitrate assimilation contributed to the success of Dikarya on land by allowing exploitation of nitrate in aerobic soils, and the subsequent transfer of a complete assimilation cluster improved the fitness of T. reesei in a new niche. Horizontal transmission of this cluster of functionally integrated genes supports the "selfish operon" hypothesis for maintenance of gene clusters.

  5. Clustering-based approaches to SAGE data mining

    Directory of Open Access Journals (Sweden)

    Wang Haiying

    2008-07-01

    Full Text Available Abstract Serial analysis of gene expression (SAGE is one of the most powerful tools for global gene expression profiling. It has led to several biological discoveries and biomedical applications, such as the prediction of new gene functions and the identification of biomarkers in human cancer research. Clustering techniques have become fundamental approaches in these applications. This paper reviews relevant clustering techniques specifically designed for this type of data. It places an emphasis on current limitations and opportunities in this area for supporting biologically-meaningful data mining and visualisation.

  6. MADIBA: A web server toolkit for biological interpretation of Plasmodium and plant gene clusters

    Directory of Open Access Journals (Sweden)

    Louw Abraham I

    2008-02-01

    Full Text Available Abstract Background Microarray technology makes it possible to identify changes in gene expression of an organism, under various conditions. Data mining is thus essential for deducing significant biological information such as the identification of new biological mechanisms or putative drug targets. While many algorithms and software have been developed for analysing gene expression, the extraction of relevant information from experimental data is still a substantial challenge, requiring significant time and skill. Description MADIBA (MicroArray Data Interface for Biological Annotation facilitates the assignment of biological meaning to gene expression clusters by automating the post-processing stage. A relational database has been designed to store the data from gene to pathway for Plasmodium, rice and Arabidopsis. Tools within the web interface allow rapid analyses for the identification of the Gene Ontology terms relevant to each cluster; visualising the metabolic pathways where the genes are implicated, their genomic localisations, putative common transcriptional regulatory elements in the upstream sequences, and an analysis specific to the organism being studied. Conclusion MADIBA is an integrated, online tool that will assist researchers in interpreting their results and understand the meaning of the co-expression of a cluster of genes. Functionality of MADIBA was validated by analysing a number of gene clusters from several published experiments – expression profiling of the Plasmodium life cycle, and salt stress treatments of Arabidopsis and rice. In most of the cases, the same conclusions found by the authors were quickly and easily obtained after analysing the gene clusters with MADIBA.

  7. Activation and clustering of a Plasmodium falciparum var gene are affected by subtelomeric sequences.

    Science.gov (United States)

    Duffy, Michael F; Tang, Jingyi; Sumardy, Fransisca; Nguyen, Hanh H T; Selvarajah, Shamista A; Josling, Gabrielle A; Day, Karen P; Petter, Michaela; Brown, Graham V

    2017-01-01

    The Plasmodium falciparum var multigene family encodes the cytoadhesive, variant antigen PfEMP1. P. falciparum antigenic variation and cytoadhesion specificity are controlled by epigenetic switching between the single, or few, simultaneously expressed var genes. Most var genes are maintained in perinuclear clusters of heterochromatic telomeres. The active var gene(s) occupy a single, perinuclear var expression site. It is unresolved whether the var expression site forms in situ at a telomeric cluster or whether it is an extant compartment to which single chromosomes travel, thus controlling var switching. Here we show that transcription of a var gene did not require decreased colocalisation with clusters of telomeres, supporting var expression site formation in situ. However following recombination within adjacent subtelomeric sequences, the same var gene was persistently activated and did colocalise less with telomeric clusters. Thus, participation in stable, heterochromatic, telomere clusters and var switching are independent but are both affected by subtelomeric sequences. The var expression site colocalised with the euchromatic mark H3K27ac to a greater extent than it did with heterochromatic H3K9me3. H3K27ac was enriched within the active var gene promoter even when the var gene was transiently repressed in mature parasites and thus H3K27ac may contribute to var gene epigenetic memory. © 2016 Federation of European Biochemical Societies.

  8. Communication Base Station Log Analysis Based on Hierarchical Clustering

    Directory of Open Access Journals (Sweden)

    Zhang Shao-Hua

    2017-01-01

    Full Text Available Communication base stations generate massive data every day, these base station logs play an important value in mining of the business circles. This paper use data mining technology and hierarchical clustering algorithm to group the scope of business circle for the base station by recording the data of these base stations.Through analyzing the data of different business circle based on feature extraction and comparing different business circle category characteristics, which can choose a suitable area for operators of commercial marketing.

  9. Characterization and detection of a widely distributed gene cluster that predicts anaerobic choline utilization by human gut bacteria.

    Science.gov (United States)

    Martínez-del Campo, Ana; Bodea, Smaranda; Hamer, Hilary A; Marks, Jonathan A; Haiser, Henry J; Turnbaugh, Peter J; Balskus, Emily P

    2015-04-14

    Elucidation of the molecular mechanisms underlying the human gut microbiota's effects on health and disease has been complicated by difficulties in linking metabolic functions associated with the gut community as a whole to individual microorganisms and activities. Anaerobic microbial choline metabolism, a disease-associated metabolic pathway, exemplifies this challenge, as the specific human gut microorganisms responsible for this transformation have not yet been clearly identified. In this study, we established the link between a bacterial gene cluster, the choline utilization (cut) cluster, and anaerobic choline metabolism in human gut isolates by combining transcriptional, biochemical, bioinformatic, and cultivation-based approaches. Quantitative reverse transcription-PCR analysis and in vitro biochemical characterization of two cut gene products linked the entire cluster to growth on choline and supported a model for this pathway. Analyses of sequenced bacterial genomes revealed that the cut cluster is present in many human gut bacteria, is predictive of choline utilization in sequenced isolates, and is widely but discontinuously distributed across multiple bacterial phyla. Given that bacterial phylogeny is a poor marker for choline utilization, we were prompted to develop a degenerate PCR-based method for detecting the key functional gene choline TMA-lyase (cutC) in genomic and metagenomic DNA. Using this tool, we found that new choline-metabolizing gut isolates universally possessed cutC. We also demonstrated that this gene is widespread in stool metagenomic data sets. Overall, this work represents a crucial step toward understanding anaerobic choline metabolism in the human gut microbiota and underscores the importance of examining this microbial community from a function-oriented perspective. Anaerobic choline utilization is a bacterial metabolic activity that occurs in the human gut and is linked to multiple diseases. While bacterial genes responsible for

  10. BioCluster: Tool for Identification and Clustering of Enterobacteriaceae Based on Biochemical Data

    Directory of Open Access Journals (Sweden)

    Ahmed Abdullah

    2015-06-01

    Full Text Available Presumptive identification of different Enterobacteriaceae species is routinely achieved based on biochemical properties. Traditional practice includes manual comparison of each biochemical property of the unknown sample with known reference samples and inference of its identity based on the maximum similarity pattern with the known samples. This process is labor-intensive, time-consuming, error-prone, and subjective. Therefore, automation of sorting and similarity in calculation would be advantageous. Here we present a MATLAB-based graphical user interface (GUI tool named BioCluster. This tool was designed for automated clustering and identification of Enterobacteriaceae based on biochemical test results. In this tool, we used two types of algorithms, i.e., traditional hierarchical clustering (HC and the Improved Hierarchical Clustering (IHC, a modified algorithm that was developed specifically for the clustering and identification of Enterobacteriaceae species. IHC takes into account the variability in result of 1–47 biochemical tests within this Enterobacteriaceae family. This tool also provides different options to optimize the clustering in a user-friendly way. Using computer-generated synthetic data and some real data, we have demonstrated that BioCluster has high accuracy in clustering and identifying enterobacterial species based on biochemical test data. This tool can be freely downloaded at http://microbialgen.du.ac.bd/biocluster/.

  11. Two different secondary metabolism gene clusters occupied the same ancestral locus in fungal dermatophytes of the arthrodermataceae.

    Science.gov (United States)

    Zhang, Han; Rokas, Antonis; Slot, Jason C

    2012-01-01

    Dermatophyte fungi of the family Arthrodermataceae (Eurotiomycetes) colonize keratinized tissue, such as skin, frequently causing superficial mycoses in humans and other mammals, reptiles, and birds. Competition with native microflora likely underlies the propensity of these dermatophytes to produce a diversity of antibiotics and compounds for scavenging iron, which is extremely scarce, as well as the presence of an unusually large number of putative secondary metabolism gene clusters, most of which contain non-ribosomal peptide synthetases (NRPS), in their genomes. To better understand the historical origins and diversification of NRPS-containing gene clusters we examined the evolution of a variable locus (VL) that exists in one of three alternative conformations among the genomes of seven dermatophyte species. The first conformation of the VL (termed VLA) contains only 539 base pairs of sequence and lacks protein-coding genes, whereas the other two conformations (termed VLB and VLC) span 36 Kb and 27 Kb and contain 12 and 10 genes, respectively. Interestingly, both VLB and VLC appear to contain distinct secondary metabolism gene clusters; VLB contains a NRPS gene as well as four porphyrin metabolism genes never found to be physically linked in the genomes of 128 other fungal species, whereas VLC also contains a NRPS gene as well as several others typically found associated with secondary metabolism gene clusters. Phylogenetic evidence suggests that the VL locus was present in the ancestor of all seven species achieving its present distribution through subsequent differential losses or retentions of specific conformations. We propose that the existence of variable loci, similar to the one we studied, in fungal genomes could potentially explain the dramatic differences in secondary metabolic diversity between closely related species of filamentous fungi, and contribute to host adaptation and the generation of metabolic diversity.

  12. Conserved syntenic clusters of protein coding genes are missing in birds.

    Science.gov (United States)

    Lovell, Peter V; Wirthlin, Morgan; Wilhelm, Larry; Minx, Patrick; Lazar, Nathan H; Carbone, Lucia; Warren, Wesley C; Mello, Claudio V

    2014-01-01

    Birds are one of the most highly successful and diverse groups of vertebrates, having evolved a number of distinct characteristics, including feathers and wings, a sturdy lightweight skeleton and unique respiratory and urinary/excretion systems. However, the genetic basis of these traits is poorly understood. Using comparative genomics based on extensive searches of 60 avian genomes, we have found that birds lack approximately 274 protein coding genes that are present in the genomes of most vertebrate lineages and are for the most part organized in conserved syntenic clusters in non-avian sauropsids and in humans. These genes are located in regions associated with chromosomal rearrangements, and are largely present in crocodiles, suggesting that their loss occurred subsequent to the split of dinosaurs/birds from crocodilians. Many of these genes are associated with lethality in rodents, human genetic disorders, or biological functions targeting various tissues. Functional enrichment analysis combined with orthogroup analysis and paralog searches revealed enrichments that were shared by non-avian species, present only in birds, or shared between all species. Together these results provide a clearer definition of the genetic background of extant birds, extend the findings of previous studies on missing avian genes, and provide clues about molecular events that shaped avian evolution. They also have implications for fields that largely benefit from avian studies, including development, immune system, oncogenesis, and brain function and cognition. With regards to the missing genes, birds can be considered ‘natural knockouts’ that may become invaluable model organisms for several human diseases.

  13. Directed natural product biosynthesis gene cluster capture and expression in the model bacterium Bacillus subtilis

    KAUST Repository

    Li, Yongxin; Li, Zhongrui; Yamanaka, Kazuya; Xu, Ying; Zhang, Weipeng; Vlamakis, Hera; Kolter, Roberto; Moore, Bradley S.; Qian, Pei-Yuan

    2015-01-01

    validating this direct cloning plug-and-playa approach with surfactin, we genetically interrogated amicoumacin biosynthetic gene cluster from the marine isolate Bacillus subtilis 1779. Its heterologous expression allowed us to explore an unusual maturation

  14. Variation in the fumonisin biosynthetic gene cluster in fumonisin-producing and nonproducing black aspergilli.

    Science.gov (United States)

    Susca, Antonia; Proctor, Robert H; Butchko, Robert A E; Haidukowski, Miriam; Stea, Gaetano; Logrieco, Antonio; Moretti, Antonio

    2014-12-01

    The ability to produce fumonisin mycotoxins varies among members of the black aspergilli. Previously, analyses of selected genes in the fumonisin biosynthetic gene (fum) cluster in black aspergilli from California grapes indicated that fumonisin-nonproducing isolates of Aspergillus welwitschiae lack six fum genes, but nonproducing isolates of Aspergillus niger do not. In the current study, analyses of black aspergilli from grapes from the Mediterranean Basin indicate that the genomic context of the fum cluster is the same in isolates of A. niger and A. welwitschiae regardless of fumonisin-production ability and that full-length clusters occur in producing isolates of both species and nonproducing isolates of A. niger. In contrast, the cluster has undergone an eight-gene deletion in fumonisin-nonproducing isolates of A. welwitschiae. Phylogenetic analyses suggest each species consists of a mixed population of fumonisin-producing and nonproducing individuals, and that existence of both production phenotypes may provide a selective advantage to these species. Differences in gene content of fum cluster homologues and phylogenetic relationships of fum genes suggest that the mutation(s) responsible for the nonproduction phenotype differs, and therefore arose independently, in the two species. Partial fum cluster homologues were also identified in genome sequences of four other black Aspergillus species. Gene content of these partial clusters and phylogenetic relationships of fum sequences indicate that non-random partial deletion of the cluster has occurred multiple times among the species. This in turn suggests that an intact cluster and fumonisin production were once more widespread among black aspergilli. Copyright © 2014 Elsevier Inc. All rights reserved.

  15. Characterization of the fumonisin B2 biosynthetic gene cluster in Aspergillus niger and A. awamori.

    Science.gov (United States)

    Aspergillus niger and A. awamori strains isolated from grapes cultivated in Mediterranean basin were examined for fumonisin B2 (FB2) production and presence/absence of sequences within the fumonisin biosynthetic gene (fum) cluster. Presence of 13 regions in the fum cluster was evaluated by PCR assay...

  16. Clusters of Antibiotic Resistance Genes Enriched Together Stay Together in Swine Agriculture.

    Science.gov (United States)

    Johnson, Timothy A; Stedtfeld, Robert D; Wang, Qiong; Cole, James R; Hashsham, Syed A; Looft, Torey; Zhu, Yong-Guan; Tiedje, James M

    2016-04-12

    Antibiotic resistance is a worldwide health risk, but the influence of animal agriculture on the genetic context and enrichment of individual antibiotic resistance alleles remains unclear. Using quantitative PCR followed by amplicon sequencing, we quantified and sequenced 44 genes related to antibiotic resistance, mobile genetic elements, and bacterial phylogeny in microbiomes from U.S. laboratory swine and from swine farms from three Chinese regions. We identified highly abundant resistance clusters: groups of resistance and mobile genetic element alleles that cooccur. For example, the abundance of genes conferring resistance to six classes of antibiotics together with class 1 integrase and the abundance of IS6100-type transposons in three Chinese regions are directly correlated. These resistance cluster genes likely colocalize in microbial genomes in the farms. Resistance cluster alleles were dramatically enriched (up to 1 to 10% as abundant as 16S rRNA) and indicate that multidrug-resistant bacteria are likely the norm rather than an exception in these communities. This enrichment largely occurred independently of phylogenetic composition; thus, resistance clusters are likely present in many bacterial taxa. Furthermore, resistance clusters contain resistance genes that confer resistance to antibiotics independently of their particular use on the farms. Selection for these clusters is likely due to the use of only a subset of the broad range of chemicals to which the clusters confer resistance. The scale of animal agriculture and its wastes, the enrichment and horizontal gene transfer potential of the clusters, and the vicinity of large human populations suggest that managing this resistance reservoir is important for minimizing human risk. Agricultural antibiotic use results in clusters of cooccurring resistance genes that together confer resistance to multiple antibiotics. The use of a single antibiotic could select for an entire suite of resistance genes if

  17. APPECT: An Approximate Backbone-Based Clustering Algorithm for Tags

    DEFF Research Database (Denmark)

    Zong, Yu; Xu, Guandong; Jin, Pin

    2011-01-01

    algorithm for Tags (APPECT). The main steps of APPECT are: (1) we execute the K-means algorithm on a tag similarity matrix for M times and collect a set of tag clustering results Z={C1,C2,…,Cm}; (2) we form the approximate backbone of Z by executing a greedy search; (3) we fix the approximate backbone...... as the initial tag clustering result and then assign the rest tags into the corresponding clusters based on the similarity. Experimental results on three real world datasets namely MedWorm, MovieLens and Dmoz demonstrate the effectiveness and the superiority of the proposed method against the traditional...... Agglomerative Clustering on tagging data, which possess the inherent drawbacks, such as the sensitivity of initialization. In this paper, we instead make use of the approximate backbone of tag clustering results to find out better tag clusters. In particular, we propose an APProximate backbonE-based Clustering...

  18. Patterns of genetic diversity and differentiation in resistance gene clusters of two hybridizing European Populus species

    OpenAIRE

    Casey, Céline; Stölting, Kai N.; Barbará, Thelma; González-Martínez, Santiago C.; Lexer, Christian

    2015-01-01

    Resistance genes (R-genes) are essential for long-lived organisms such as forest trees, which are exposed to diverse herbivores and pathogens. In short-lived model species, R-genes have been shown to be involved in species isolation. Here, we studied more than 400 trees from two natural hybrid zones of the European Populus species Populus alba and Populus tremula for microsatellite markers located in three R-gene clusters, including one cluster situated in the incipient sex chromosome region....

  19. Large clusters of co-expressed genes in the Drosophila genome.

    Science.gov (United States)

    Boutanaev, Alexander M; Kalmykova, Alla I; Shevelyov, Yuri Y; Nurminsky, Dmitry I

    2002-12-12

    Clustering of co-expressed, non-homologous genes on chromosomes implies their co-regulation. In lower eukaryotes, co-expressed genes are often found in pairs. Clustering of genes that share aspects of transcriptional regulation has also been reported in higher eukaryotes. To advance our understanding of the mode of coordinated gene regulation in multicellular organisms, we performed a genome-wide analysis of the chromosomal distribution of co-expressed genes in Drosophila. We identified a total of 1,661 testes-specific genes, one-third of which are clustered on chromosomes. The number of clusters of three or more genes is much higher than expected by chance. We observed a similar trend for genes upregulated in the embryo and in the adult head, although the expression pattern of individual genes cannot be predicted on the basis of chromosomal position alone. Our data suggest that the prevalent mechanism of transcriptional co-regulation in higher eukaryotes operates with extensive chromatin domains that comprise multiple genes.

  20. Unusual Gene Order and Organization of the Sea Urchin HoxCluster

    Energy Technology Data Exchange (ETDEWEB)

    Richardson, Paul M.; Lucas, Susan; Cameron, R. Andrew; Rowen,Lee; Nesbitt, Ryan; Bloom, Scott; Rast, Jonathan P.; Berney, Kevin; Arenas-Mena, Cesar; Martinez, Pedro; Davidson, Eric H.; Peterson, KevinJ.; Hood, Leroy

    2005-05-10

    The highly consistent gene order and axial colinear expression patterns found in vertebrate hox gene clusters are less well conserved across the rest of bilaterians. We report the first deuterostome instance of an intact hox cluster with a unique gene order where the paralog groups are not expressed in a sequential manner. The finished sequence from BAC clones from the genome of the sea urchin, Strongylocentrotus purpuratus, reveals a gene order wherein the anterior genes (Hox1, Hox2 and Hox3) lie nearest the posterior genes in the cluster such that the most 3' gene is Hox5. (The gene order is : 5'-Hox1,2, 3, 11/13c, 11/13b, '11/13a, 9/10, 8, 7, 6, 5 - 3)'. The finished sequence result is corroborated by restriction mapping evidence and BAC-end scaffold analyses. Comparisons with a putative ancestral deuterostome Hox gene cluster suggest that the rearrangements leading to the sea urchin gene order were many and complex.

  1. Lampreys, the jawless vertebrates, contain only two ParaHox gene clusters.

    Science.gov (United States)

    Zhang, Huixian; Ravi, Vydianathan; Tay, Boon-Hui; Tohari, Sumanty; Pillai, Nisha E; Prasad, Aravind; Lin, Qiang; Brenner, Sydney; Venkatesh, Byrappa

    2017-08-22

    ParaHox genes ( Gsx , Pdx , and Cdx ) are an ancient family of developmental genes closely related to the Hox genes. They play critical roles in the patterning of brain and gut. The basal chordate, amphioxus, contains a single ParaHox cluster comprising one member of each family, whereas nonteleost jawed vertebrates contain four ParaHox genomic loci with six or seven ParaHox genes. Teleosts, which have experienced an additional whole-genome duplication, contain six ParaHox genomic loci with six ParaHox genes. Jawless vertebrates, represented by lampreys and hagfish, are the most ancient group of vertebrates and are crucial for understanding the origin and evolution of vertebrate gene families. We have previously shown that lampreys contain six Hox gene loci. Here we report that lampreys contain only two ParaHox gene clusters (designated as α- and β-clusters) bearing five ParaHox genes ( Gsxα , Pdxα , Cdxα , Gsxβ , and Cdxβ ). The order and orientation of the three genes in the α-cluster are identical to that of the single cluster in amphioxus. However, the orientation of Gsxβ in the β-cluster is inverted. Interestingly, Gsxβ is expressed in the eye, unlike its homologs in jawed vertebrates, which are expressed mainly in the brain. The lamprey Pdxα is expressed in the pancreas similar to jawed vertebrate Pdx genes, indicating that the pancreatic expression of Pdx was acquired before the divergence of jawless and jawed vertebrate lineages. It is likely that the lamprey Pdxα plays a crucial role in pancreas specification and insulin production similar to the Pdx of jawed vertebrates.

  2. Gene structure and expression characteristic of a novel odorant receptor gene cluster in the parasitoid wasp Microplitis mediator (Hymenoptera: Braconidae).

    Science.gov (United States)

    Wang, S-N; Shan, S; Zheng, Y; Peng, Y; Lu, Z-Y; Yang, Y-Q; Li, R-J; Zhang, Y-J; Guo, Y-Y

    2017-08-01

    Odorant receptors (ORs) expressed in the antennae of parasitoid wasps are responsible for detection of various lipophilic airborne molecules. In the present study, 107 novel OR genes were identified from Microplitis mediator antennal transcriptome data. Phylogenetic analysis of the set of OR genes from M. mediator and Microplitis demolitor revealed that M. mediator OR (MmedOR) genes can be classified into different subfamilies, and the majority of MmedORs in each subfamily shared high sequence identities and clear orthologous relationships to M. demolitor ORs. Within a subfamily, six MmedOR genes, MmedOR98, 124, 125, 126, 131 and 155, shared a similar gene structure and were tightly linked in the genome. To evaluate whether the clustered MmedOR genes share common regulatory features, the transcription profile and expression characteristics of the six closely related OR genes were investigated in M. mediator. Rapid amplification of cDNA ends-PCR experiments revealed that the OR genes within the cluster were transcribed as single mRNAs, and a bicistronic mRNA for two adjacent genes (MmedOR124 and MmedOR98) was also detected in female antennae by reverse transcription PCR. In situ hybridization experiments indicated that each OR gene within the cluster was expressed in a different number of cells. Moreover, there was no co-expression of the two highly related OR genes, MmedOR124 and MmedOR98, which appeared to be individually expressed in a distinct population of neurons. Overall, there were distinct expression profiles of closely related MmedOR genes from the same cluster in M. mediator. These data provide a basic understanding of the olfactory coding in parasitoid wasps. © 2017 The Royal Entomological Society.

  3. Average correlation clustering algorithm (ACCA) for grouping of co-regulated genes with similar pattern of variation in their expression values.

    Science.gov (United States)

    Bhattacharya, Anindya; De, Rajat K

    2010-08-01

    Distance based clustering algorithms can group genes that show similar expression values under multiple experimental conditions. They are unable to identify a group of genes that have similar pattern of variation in their expression values. Previously we developed an algorithm called divisive correlation clustering algorithm (DCCA) to tackle this situation, which is based on the concept of correlation clustering. But this algorithm may also fail for certain cases. In order to overcome these situations, we propose a new clustering algorithm, called average correlation clustering algorithm (ACCA), which is able to produce better clustering solution than that produced by some others. ACCA is able to find groups of genes having more common transcription factors and similar pattern of variation in their expression values. Moreover, ACCA is more efficient than DCCA with respect to the time of execution. Like DCCA, we use the concept of correlation clustering concept introduced by Bansal et al. ACCA uses the correlation matrix in such a way that all genes in a cluster have the highest average correlation values with the genes in that cluster. We have applied ACCA and some well-known conventional methods including DCCA to two artificial and nine gene expression datasets, and compared the performance of the algorithms. The clustering results of ACCA are found to be more significantly relevant to the biological annotations than those of the other methods. Analysis of the results show the superiority of ACCA over some others in determining a group of genes having more common transcription factors and with similar pattern of variation in their expression profiles. Availability of the software: The software has been developed using C and Visual Basic languages, and can be executed on the Microsoft Windows platforms. The software may be downloaded as a zip file from http://www.isical.ac.in/~rajat. Then it needs to be installed. Two word files (included in the zip file) need to

  4. KBERG: KnowledgeBase for Estrogen Responsive Genes

    DEFF Research Database (Denmark)

    Tang, Suisheng; Zhang, Zhuo; Tan, Sin Lam

    2007-01-01

    Estrogen has a profound impact on human physiology affecting transcription of numerous genes. To decipher functional characteristics of estrogen responsive genes, we developed KnowledgeBase for Estrogen Responsive Genes (KBERG). Genes in KBERG were derived from Estrogen Responsive Gene Database...... (ERGDB) and were analyzed from multiple aspects. We explored the possible transcription regulation mechanism by capturing highly conserved promoter motifs across orthologous genes, using promoter regions that cover the range of [-1200, +500] relative to the transcription start sites. The motif detection...... is based on ab initio discovery of common cis-elements from the orthologous gene cluster from human, mouse and rat, thus reflecting a degree of promoter sequence preservation during evolution. The identified motifs are linked to transcription factor binding sites based on the TRANSFAC database. In addition...

  5. Clustering-based classification of road traffic accidents using hierarchical clustering and artificial neural networks.

    Science.gov (United States)

    Taamneh, Madhar; Taamneh, Salah; Alkheder, Sharaf

    2017-09-01

    Artificial neural networks (ANNs) have been widely used in predicting the severity of road traffic crashes. All available information about previously occurred accidents is typically used for building a single prediction model (i.e., classifier). Too little attention has been paid to the differences between these accidents, leading, in most cases, to build less accurate predictors. Hierarchical clustering is a well-known clustering method that seeks to group data by creating a hierarchy of clusters. Using hierarchical clustering and ANNs, a clustering-based classification approach for predicting the injury severity of road traffic accidents was proposed. About 6000 road accidents occurred over a six-year period from 2008 to 2013 in Abu Dhabi were used throughout this study. In order to reduce the amount of variation in data, hierarchical clustering was applied on the data set to organize it into six different forms, each with different number of clusters (i.e., clusters from 1 to 6). Two ANN models were subsequently built for each cluster of accidents in each generated form. The first model was built and validated using all accidents (training set), whereas only 66% of the accidents were used to build the second model, and the remaining 34% were used to test it (percentage split). Finally, the weighted average accuracy was computed for each type of models in each from of data. The results show that when testing the models using the training set, clustering prior to classification achieves (11%-16%) more accuracy than without using clustering, while the percentage split achieves (2%-5%) more accuracy. The results also suggest that partitioning the accidents into six clusters achieves the best accuracy if both types of models are taken into account.

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

    Science.gov (United States)

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

    2015-02-01

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

  7. Two Horizontally Transferred Xenobiotic Resistance Gene Clusters Associated with Detoxification of Benzoxazolinones by Fusarium Species

    Science.gov (United States)

    Glenn, Anthony E.; Davis, C. Britton; Gao, Minglu; Gold, Scott E.; Mitchell, Trevor R.; Proctor, Robert H.; Stewart, Jane E.; Snook, Maurice E.

    2016-01-01

    Microbes encounter a broad spectrum of antimicrobial compounds in their environments and often possess metabolic strategies to detoxify such xenobiotics. We have previously shown that Fusarium verticillioides, a fungal pathogen of maize known for its production of fumonisin mycotoxins, possesses two unlinked loci, FDB1 and FDB2, necessary for detoxification of antimicrobial compounds produced by maize, including the γ-lactam 2-benzoxazolinone (BOA). In support of these earlier studies, microarray analysis of F. verticillioides exposed to BOA identified the induction of multiple genes at FDB1 and FDB2, indicating the loci consist of gene clusters. One of the FDB1 cluster genes encoded a protein having domain homology to the metallo-β-lactamase (MBL) superfamily. Deletion of this gene (MBL1) rendered F. verticillioides incapable of metabolizing BOA and thus unable to grow on BOA-amended media. Deletion of other FDB1 cluster genes, in particular AMD1 and DLH1, did not affect BOA degradation. Phylogenetic analyses and topology testing of the FDB1 and FDB2 cluster genes suggested two horizontal transfer events among fungi, one being transfer of FDB1 from Fusarium to Colletotrichum, and the second being transfer of the FDB2 cluster from Fusarium to Aspergillus. Together, the results suggest that plant-derived xenobiotics have exerted evolutionary pressure on these fungi, leading to horizontal transfer of genes that enhance fitness or virulence. PMID:26808652

  8. Cluster-based global firms' use of local capabilities

    DEFF Research Database (Denmark)

    Andersen, Poul Houman; Bøllingtoft, Anne

    2011-01-01

    Purpose – Despite growing interest in clusters role for the global competitiveness of firms, there has been little research into how globalization affects cluster-based firms’ (CBFs) use of local knowledge resources and the combination of local and global knowledge used. Using the cluster......’s knowledge base as a mediating variable, the purpose of this paper is to examine how globalization affected the studied firms’ use of local cluster-based knowledge, integration of local and global knowledge, and networking capabilities. Design/methodology/approach – Qualitative case studies of nine firms...... in three clusters strongly affected by increasing global division of labour. Findings – The paper suggests that globalization has affected how firms use local resources and combine local and global knowledge. Unexpectedly, clustered firms with explicit procedures and established global fora for exchanging...

  9. The Genome of Tolypocladium inflatum: Evolution, Organization, and Expression of the Cyclosporin Biosynthetic Gene Cluster

    Science.gov (United States)

    Bushley, Kathryn E.; Raja, Rajani; Jaiswal, Pankaj; Cumbie, Jason S.; Nonogaki, Mariko; Boyd, Alexander E.; Owensby, C. Alisha; Knaus, Brian J.; Elser, Justin; Miller, Daniel; Di, Yanming; McPhail, Kerry L.; Spatafora, Joseph W.

    2013-01-01

    The ascomycete fungus Tolypocladium inflatum, a pathogen of beetle larvae, is best known as the producer of the immunosuppressant drug cyclosporin. The draft genome of T. inflatum strain NRRL 8044 (ATCC 34921), the isolate from which cyclosporin was first isolated, is presented along with comparative analyses of the biosynthesis of cyclosporin and other secondary metabolites in T. inflatum and related taxa. Phylogenomic analyses reveal previously undetected and complex patterns of homology between the nonribosomal peptide synthetase (NRPS) that encodes for cyclosporin synthetase (simA) and those of other secondary metabolites with activities against insects (e.g., beauvericin, destruxins, etc.), and demonstrate the roles of module duplication and gene fusion in diversification of NRPSs. The secondary metabolite gene cluster responsible for cyclosporin biosynthesis is described. In addition to genes necessary for cyclosporin biosynthesis, it harbors a gene for a cyclophilin, which is a member of a family of immunophilins known to bind cyclosporin. Comparative analyses support a lineage specific origin of the cyclosporin gene cluster rather than horizontal gene transfer from bacteria or other fungi. RNA-Seq transcriptome analyses in a cyclosporin-inducing medium delineate the boundaries of the cyclosporin cluster and reveal high levels of expression of the gene cluster cyclophilin. In medium containing insect hemolymph, weaker but significant upregulation of several genes within the cyclosporin cluster, including the highly expressed cyclophilin gene, was observed. T. inflatum also represents the first reference draft genome of Ophiocordycipitaceae, a third family of insect pathogenic fungi within the fungal order Hypocreales, and supports parallel and qualitatively distinct radiations of insect pathogens. The T. inflatum genome provides additional insight into the evolution and biosynthesis of cyclosporin and lays a foundation for further investigations of the role

  10. Heterogeneic dynamics of the structures of multiple gene clusters in two pathogenetically different lines originating from the same phytoplasma.

    Science.gov (United States)

    Arashida, Ryo; Kakizawa, Shigeyuki; Hoshi, Ayaka; Ishii, Yoshiko; Jung, Hee-Young; Kagiwada, Satoshi; Yamaji, Yasuyuki; Oshima, Kenro; Namba, Shigetou

    2008-04-01

    Phytoplasmas are phloem-limited plant pathogens that are transmitted by insect vectors and are associated with diseases in hundreds of plant species. Despite their small sizes, phytoplasma genomes have repeat-rich sequences, which are due to several genes that are encoded as multiple copies. These multiple genes exist in a gene cluster, the potential mobile unit (PMU). PMUs are present at several distinct regions in the phytoplasma genome. The multicopy genes encoded by PMUs (herein named mobile unit genes [MUGs]) and similar genes elsewhere in the genome (herein named fundamental genes [FUGs]) are likely to have the same function based on their annotations. In this manuscript we show evidence that MUGs and FUGs do not cluster together within the same clade. Each MUG is in a cluster with a short branch length, suggesting that MUGs are recently diverged paralogs, whereas the origin of FUGs is different from that of MUGs. We also compared the genome structures around the lplA gene in two derivative lines of the 'Candidatus Phytoplasma asteris' OY strain, the severe-symptom line W (OY-W) and the mild-symptom line M (OY-M). The gene organizations of the nucleotide sequences upstream of the lplA genes of OY-W and OY-M were dramatically different. The tra5 insertion sequence, an element of PMUs, was found only in this region in OY-W. These results suggest that transposition of entire PMUs and PMU sections has occurred frequently in the OY phytoplasma genome. The difference in the pathogenicities of OY-W and OY-M might be caused by the duplication and transposition of PMUs, followed by genome rearrangement.

  11. Improving local clustering based top-L link prediction methods via asymmetric link clustering information

    Science.gov (United States)

    Wu, Zhihao; Lin, Youfang; Zhao, Yiji; Yan, Hongyan

    2018-02-01

    Networks can represent a wide range of complex systems, such as social, biological and technological systems. Link prediction is one of the most important problems in network analysis, and has attracted much research interest recently. Many link prediction methods have been proposed to solve this problem with various techniques. We can note that clustering information plays an important role in solving the link prediction problem. In previous literatures, we find node clustering coefficient appears frequently in many link prediction methods. However, node clustering coefficient is limited to describe the role of a common-neighbor in different local networks, because it cannot distinguish different clustering abilities of a node to different node pairs. In this paper, we shift our focus from nodes to links, and propose the concept of asymmetric link clustering (ALC) coefficient. Further, we improve three node clustering based link prediction methods via the concept of ALC. The experimental results demonstrate that ALC-based methods outperform node clustering based methods, especially achieving remarkable improvements on food web, hamster friendship and Internet networks. Besides, comparing with other methods, the performance of ALC-based methods are very stable in both globalized and personalized top-L link prediction tasks.

  12. Flowbca : A flow-based cluster algorithm in Stata

    NARCIS (Netherlands)

    Meekes, J.; Hassink, W.H.J.

    In this article, we introduce the Stata implementation of a flow-based cluster algorithm written in Mata. The main purpose of the flowbca command is to identify clusters based on relational data of flows. We illustrate the command by providing multiple applications, from the research fields of

  13. Directed natural product biosynthesis gene cluster capture and expression in the model bacterium Bacillus subtilis

    Science.gov (United States)

    Li, Yongxin; Li, Zhongrui; Yamanaka, Kazuya; Xu, Ying; Zhang, Weipeng; Vlamakis, Hera; Kolter, Roberto; Moore, Bradley S.; Qian, Pei-Yuan

    2015-03-01

    Bacilli are ubiquitous low G+C environmental Gram-positive bacteria that produce a wide assortment of specialized small molecules. Although their natural product biosynthetic potential is high, robust molecular tools to support the heterologous expression of large biosynthetic gene clusters in Bacillus hosts are rare. Herein we adapt transformation-associated recombination (TAR) in yeast to design a single genomic capture and expression vector for antibiotic production in Bacillus subtilis. After validating this direct cloning ``plug-and-play'' approach with surfactin, we genetically interrogated amicoumacin biosynthetic gene cluster from the marine isolate Bacillus subtilis 1779. Its heterologous expression allowed us to explore an unusual maturation process involving the N-acyl-asparagine pro-drug intermediates preamicoumacins, which are hydrolyzed by the asparagine-specific peptidase into the active component amicoumacin A. This work represents the first direct cloning based heterologous expression of natural products in the model organism B. subtilis and paves the way to the development of future genome mining efforts in this genus.

  14. Directed natural product biosynthesis gene cluster capture and expression in the model bacterium Bacillus subtilis

    KAUST Repository

    Li, Yongxin

    2015-03-24

    Bacilli are ubiquitous low G+C environmental Gram-positive bacteria that produce a wide assortment of specialized small molecules. Although their natural product biosynthetic potential is high, robust molecular tools to support the heterologous expression of large biosynthetic gene clusters in Bacillus hosts are rare. Herein we adapt transformation-associated recombination (TAR) in yeast to design a single genomic capture and expression vector for antibiotic production in Bacillus subtilis. After validating this direct cloning plug-and-playa approach with surfactin, we genetically interrogated amicoumacin biosynthetic gene cluster from the marine isolate Bacillus subtilis 1779. Its heterologous expression allowed us to explore an unusual maturation process involving the N-acyl-asparagine pro-drug intermediates preamicoumacins, which are hydrolyzed by the asparagine-specific peptidase into the active component amicoumacin A. This work represents the first direct cloning based heterologous expression of natural products in the model organism B. subtilis and paves the way to the development of future genome mining efforts in this genus.

  15. Comparison of Expression of Secondary Metabolite Biosynthesis Cluster Genes in Aspergillus flavus, A. parasiticus, and A. oryzae

    OpenAIRE

    Ehrlich, Kenneth C.; Mack, Brian M.

    2014-01-01

    Fifty six secondary metabolite biosynthesis gene clusters are predicted to be in the Aspergillus flavus genome. In spite of this, the biosyntheses of only seven metabolites, including the aflatoxins, kojic acid, cyclopiazonic acid and aflatrem, have been assigned to a particular gene cluster. We used RNA-seq to compare expression of secondary metabolite genes in gene clusters for the closely related fungi A. parasiticus, A. oryzae, and A. flavus S and L sclerotial morphotypes. The data help ...

  16. Increasing Power by Sharing Information from Genetic Background and Treatment in Clustering of Gene Expression Time Series

    OpenAIRE

    Sura Zaki Alrashid; Muhammad Arifur Rahman; Nabeel H Al-Aaraji; Neil D Lawrence; Paul R Heath

    2018-01-01

    Clustering of gene expression time series gives insight into which genes may be co-regulated, allowing us to discern the activity of pathways in a given microarray experiment. Of particular interest is how a given group of genes varies with different conditions or genetic background. This paper develops
a new clustering method that allows each cluster to be parameterised according to whether the behaviour of the genes across conditions is correlated or anti-correlated. By specifying correlati...

  17. Assessment of clusters of transcription factor binding sites in relationship to human promoter, CpG islands and gene expression

    Directory of Open Access Journals (Sweden)

    Sakaki Yoshiyuki

    2004-02-01

    Full Text Available Abstract Background Gene expression is regulated mainly by transcription factors (TFs that interact with regulatory cis-elements on DNA sequences. To identify functional regulatory elements, computer searching can predict TF binding sites (TFBS using position weight matrices (PWMs that represent positional base frequencies of collected experimentally determined TFBS. A disadvantage of this approach is the large output of results for genomic DNA. One strategy to identify genuine TFBS is to utilize local concentrations of predicted TFBS. It is unclear whether there is a general tendency for TFBS to cluster at promoter regions, although this is the case for certain TFBS. Also unclear is the identification of TFs that have TFBS concentrated in promoters and to what level this occurs. This study hopes to answer some of these questions. Results We developed the cluster score measure to evaluate the correlation between predicted TFBS clusters and promoter sequences for each PWM. Non-promoter sequences were used as a control. Using the cluster score, we identified a PWM group called PWM-PCP, in which TFBS clusters positively correlate with promoters, and another PWM group called PWM-NCP, in which TFBS clusters negatively correlate with promoters. The PWM-PCP group comprises 47% of the 199 vertebrate PWMs, while the PWM-NCP group occupied 11 percent. After reducing the effect of CpG islands (CGI against the clusters using partial correlation coefficients among three properties (promoter, CGI and predicted TFBS cluster, we identified two PWM groups including those strongly correlated with CGI and those not correlated with CGI. Conclusion Not all PWMs predict TFBS correlated with human promoter sequences. Two main PWM groups were identified: (1 those that show TFBS clustered in promoters associated with CGI, and (2 those that show TFBS clustered in promoters independent of CGI. Assessment of PWM matches will allow more positive interpretation of TFBS in

  18. PROSPECTS OF THE REGIONAL INTEGRATION POLICY BASED ON CLUSTER FORMATION

    Directory of Open Access Journals (Sweden)

    Elena Tsepilova

    2018-01-01

    Full Text Available The purpose of this article is to develop the theoretical foundations of regional integration policy and to determine its prospects on the basis of cluster formation. The authors use such research methods as systematization, comparative and complex analysis, synthesis, statistical method. Within the framework of the research, the concept of regional integration policy is specified, and its integration core – cluster – is allocated. The authors work out an algorithm of regional clustering, which will ensure the growth of economy and tax income. Measures have been proposed to optimize the organizational mechanism of interaction between the participants of the territorial cluster and the authorities that allow to ensure the effective functioning of clusters, including taxation clusters. Based on the results of studying the existing methods for assessing the effectiveness of cluster policy, the authors propose their own approach to evaluating the consequences of implementing the regional integration policy, according to which the list of quantitative and qualitative indicators is defined. The present article systematizes the experience and results of the cluster policy of certain European countries, that made it possible to determine the prospects and synergetic effect from the development of clusters as an integration foundation of regional policy in the Russian Federation. The authors carry out the analysis of activity of cluster formations using the example of the Rostov region – a leader in the formation of conditions for the cluster policy development in the Southern Federal District. 11 clusters and cluster initiatives are developing in this region. As a result, the authors propose measures for support of the already existing clusters and creation of the new ones.

  19. The medaka novel immune-type receptor (NITR gene clusters reveal an extraordinary degree of divergence in variable domains

    Directory of Open Access Journals (Sweden)

    Litman Gary W

    2008-06-01

    Full Text Available Abstract Background Novel immune-type receptor (NITR genes are members of diversified multigene families that are found in bony fish and encode type I transmembrane proteins containing one or two extracellular immunoglobulin (Ig domains. The majority of NITRs can be classified as inhibitory receptors that possess cytoplasmic immunoreceptor tyrosine-based inhibition motifs (ITIMs. A much smaller number of NITRs can be classified as activating receptors by the lack of cytoplasmic ITIMs and presence of a positively charged residue within their transmembrane domain, which permits partnering with an activating adaptor protein. Results Forty-four NITR genes in medaka (Oryzias latipes are located in three gene clusters on chromosomes 10, 18 and 21 and can be organized into 24 families including inhibitory and activating forms. The particularly large dataset acquired in medaka makes direct comparison possible to another complete dataset acquired in zebrafish in which NITRs are localized in two clusters on different chromosomes. The two largest medaka NITR gene clusters share conserved synteny with the two zebrafish NITR gene clusters. Shared synteny between NITRs and CD8A/CD8B is limited but consistent with a potential common ancestry. Conclusion Comprehensive phylogenetic analyses between the complete datasets of NITRs from medaka and zebrafish indicate multiple species-specific expansions of different families of NITRs. The patterns of sequence variation among gene family members are consistent with recent birth-and-death events. Similar effects have been observed with mammalian immunoglobulin (Ig, T cell antigen receptor (TCR and killer cell immunoglobulin-like receptor (KIR genes. NITRs likely diverged along an independent pathway from that of the somatically rearranging antigen binding receptors but have undergone parallel evolution of V family diversity.

  20. Ortholog-based screening and identification of genes related to intracellular survival.

    Science.gov (United States)

    Yang, Xiaowen; Wang, Jiawei; Bing, Guoxia; Bie, Pengfei; De, Yanyan; Lyu, Yanli; Wu, Qingmin

    2018-04-20

    Bioinformatics and comparative genomics analysis methods were used to predict unknown pathogen genes based on homology with identified or functionally clustered genes. In this study, the genes of common pathogens were analyzed to screen and identify genes associated with intracellular survival through sequence similarity, phylogenetic tree analysis and the λ-Red recombination system test method. The total 38,952 protein-coding genes of common pathogens were divided into 19,775 clusters. As demonstrated through a COG analysis, information storage and processing genes might play an important role intracellular survival. Only 19 clusters were present in facultative intracellular pathogens, and not all were present in extracellular pathogens. Construction of a phylogenetic tree selected 18 of these 19 clusters. Comparisons with the DEG database and previous research revealed that seven other clusters are considered essential gene clusters and that seven other clusters are associated with intracellular survival. Moreover, this study confirmed that clusters screened by orthologs with similar function could be replaced with an approved uvrY gene and its orthologs, and the results revealed that the usg gene is associated with intracellular survival. The study improves the current understanding of intracellular pathogens characteristics and allows further exploration of the intracellular survival-related gene modules in these pathogens. Copyright © 2018. Published by Elsevier B.V.

  1. Sequencing and Transcriptional Analysis of the Biosynthesis Gene Cluster of Putrescine-Producing Lactococcus lactis ▿ †

    Science.gov (United States)

    Ladero, Victor; Rattray, Fergal P.; Mayo, Baltasar; Martín, María Cruz; Fernández, María; Alvarez, Miguel A.

    2011-01-01

    Lactococcus lactis is a prokaryotic microorganism with great importance as a culture starter and has become the model species among the lactic acid bacteria. The long and safe history of use of L. lactis in dairy fermentations has resulted in the classification of this species as GRAS (General Regarded As Safe) or QPS (Qualified Presumption of Safety). However, our group has identified several strains of L. lactis subsp. lactis and L. lactis subsp. cremoris that are able to produce putrescine from agmatine via the agmatine deiminase (AGDI) pathway. Putrescine is a biogenic amine that confers undesirable flavor characteristics and may even have toxic effects. The AGDI cluster of L. lactis is composed of a putative regulatory gene, aguR, followed by the genes (aguB, aguD, aguA, and aguC) encoding the catabolic enzymes. These genes are transcribed as an operon that is induced in the presence of agmatine. In some strains, an insertion (IS) element interrupts the transcription of the cluster, which results in a non-putrescine-producing phenotype. Based on this knowledge, a PCR-based test was developed in order to differentiate nonproducing L. lactis strains from those with a functional AGDI cluster. The analysis of the AGDI cluster and their flanking regions revealed that the capacity to produce putrescine via the AGDI pathway could be a specific characteristic that was lost during the adaptation to the milk environment by a process of reductive genome evolution. PMID:21803900

  2. Identification and manipulation of the pleuromutilin gene cluster from Clitopilus passeckerianus for increased rapid antibiotic production

    Science.gov (United States)

    Bailey, Andy M.; Alberti, Fabrizio; Kilaru, Sreedhar; Collins, Catherine M.; de Mattos-Shipley, Kate; Hartley, Amanda J.; Hayes, Patrick; Griffin, Alison; Lazarus, Colin M.; Cox, Russell J.; Willis, Christine L.; O'Dwyer, Karen; Spence, David W.; Foster, Gary D.

    2016-05-01

    Semi-synthetic derivatives of the tricyclic diterpene antibiotic pleuromutilin from the basidiomycete Clitopilus passeckerianus are important in combatting bacterial infections in human and veterinary medicine. These compounds belong to the only new class of antibiotics for human applications, with novel mode of action and lack of cross-resistance, representing a class with great potential. Basidiomycete fungi, being dikaryotic, are not generally amenable to strain improvement. We report identification of the seven-gene pleuromutilin gene cluster and verify that using various targeted approaches aimed at increasing antibiotic production in C. passeckerianus, no improvement in yield was achieved. The seven-gene pleuromutilin cluster was reconstructed within Aspergillus oryzae giving production of pleuromutilin in an ascomycete, with a significant increase (2106%) in production. This is the first gene cluster from a basidiomycete to be successfully expressed in an ascomycete, and paves the way for the exploitation of a metabolically rich but traditionally overlooked group of fungi.

  3. Structure based alignment and clustering of proteins (STRALCP)

    Science.gov (United States)

    Zemla, Adam T.; Zhou, Carol E.; Smith, Jason R.; Lam, Marisa W.

    2013-06-18

    Disclosed are computational methods of clustering a set of protein structures based on local and pair-wise global similarity values. Pair-wise local and global similarity values are generated based on pair-wise structural alignments for each protein in the set of protein structures. Initially, the protein structures are clustered based on pair-wise local similarity values. The protein structures are then clustered based on pair-wise global similarity values. For each given cluster both a representative structure and spans of conserved residues are identified. The representative protein structure is used to assign newly-solved protein structures to a group. The spans are used to characterize conservation and assign a "structural footprint" to the cluster.

  4. Clustering Gene Expression Time Series with Coregionalization: Speed propagation of ALS

    OpenAIRE

    Rahman, Muhammad Arifur; Heath, Paul R.; Lawrence, Neil D.

    2018-01-01

    Clustering of gene expression time series gives insight into which genes may be coregulated, allowing us to discern the activity of pathways in a given microarray experiment. Of particular interest is how a given group of genes varies with different model conditions or genetic background. Amyotrophic lateral sclerosis (ALS), an irreversible diverse neurodegenerative disorder showed consistent phenotypic differences and the disease progression is heterogeneous with significant variability. Thi...

  5. Cluster algebras bases on vertex operator algebras

    Czech Academy of Sciences Publication Activity Database

    Zuevsky, Alexander

    2016-01-01

    Roč. 30, 28-29 (2016), č. článku 1640030. ISSN 0217-9792 Institutional support: RVO:67985840 Keywords : cluster alegbras * vertex operator algebras * Riemann surfaces Subject RIV: BA - General Mathematics Impact factor: 0.736, year: 2016 http://www.worldscientific.com/doi/abs/10.1142/S0217979216400300

  6. Seniority-based coupled cluster theory

    International Nuclear Information System (INIS)

    Henderson, Thomas M.; Scuseria, Gustavo E.; Bulik, Ireneusz W.; Stein, Tamar

    2014-01-01

    Doubly occupied configuration interaction (DOCI) with optimized orbitals often accurately describes strong correlations while working in a Hilbert space much smaller than that needed for full configuration interaction. However, the scaling of such calculations remains combinatorial with system size. Pair coupled cluster doubles (pCCD) is very successful in reproducing DOCI energetically, but can do so with low polynomial scaling (N 3 , disregarding the two-electron integral transformation from atomic to molecular orbitals). We show here several examples illustrating the success of pCCD in reproducing both the DOCI energy and wave function and show how this success frequently comes about. What DOCI and pCCD lack are an effective treatment of dynamic correlations, which we here add by including higher-seniority cluster amplitudes which are excluded from pCCD. This frozen pair coupled cluster approach is comparable in cost to traditional closed-shell coupled cluster methods with results that are competitive for weakly correlated systems and often superior for the description of strongly correlated systems

  7. An Intelligent Clustering Based Methodology for Confusable ...

    African Journals Online (AJOL)

    Journal of the Nigerian Association of Mathematical Physics ... The system assigns patients with severity levels in all the clusters. ... The system compares favorably with diagnosis arrived at by experienced physicians and also provides patients' level of severity in each confusable disease and the degree of confusability of ...

  8. A Flocking Based algorithm for Document Clustering Analysis

    Energy Technology Data Exchange (ETDEWEB)

    Cui, Xiaohui [ORNL; Gao, Jinzhu [ORNL; Potok, Thomas E [ORNL

    2006-01-01

    Social animals or insects in nature often exhibit a form of emergent collective behavior known as flocking. In this paper, we present a novel Flocking based approach for document clustering analysis. Our Flocking clustering algorithm uses stochastic and heuristic principles discovered from observing bird flocks or fish schools. Unlike other partition clustering algorithm such as K-means, the Flocking based algorithm does not require initial partitional seeds. The algorithm generates a clustering of a given set of data through the embedding of the high-dimensional data items on a two-dimensional grid for easy clustering result retrieval and visualization. Inspired by the self-organized behavior of bird flocks, we represent each document object with a flock boid. The simple local rules followed by each flock boid result in the entire document flock generating complex global behaviors, which eventually result in a clustering of the documents. We evaluate the efficiency of our algorithm with both a synthetic dataset and a real document collection that includes 100 news articles collected from the Internet. Our results show that the Flocking clustering algorithm achieves better performance compared to the K- means and the Ant clustering algorithm for real document clustering.

  9. A CLUSTERING OF DJA STOCKS - THE APPLICATION IN FINANCE OF A METHOD FIRST USED IN GENE TRAJECTORY STUDY

    Directory of Open Access Journals (Sweden)

    Silaghi Gheorghe Cosmin

    2009-05-01

    Full Text Available Previously we employed the Gene Trajectory Clustering methodology to search for different associations of the stocks composing the DJA index, with the aim of finding different, logic clusters, supported by economic reasons, preferably different than the

  10. Result diversification based on query-specific cluster ranking

    NARCIS (Netherlands)

    He, J.; Meij, E.; de Rijke, M.

    2011-01-01

    Result diversification is a retrieval strategy for dealing with ambiguous or multi-faceted queries by providing documents that cover as many facets of the query as possible. We propose a result diversification framework based on query-specific clustering and cluster ranking, in which diversification

  11. Result Diversification Based on Query-Specific Cluster Ranking

    NARCIS (Netherlands)

    J. He (Jiyin); E. Meij; M. de Rijke (Maarten)

    2011-01-01

    htmlabstractResult diversification is a retrieval strategy for dealing with ambiguous or multi-faceted queries by providing documents that cover as many facets of the query as possible. We propose a result diversification framework based on query-specific clustering and cluster ranking,

  12. Likelihood-based inference for clustered line transect data

    DEFF Research Database (Denmark)

    Waagepetersen, Rasmus; Schweder, Tore

    2006-01-01

    The uncertainty in estimation of spatial animal density from line transect surveys depends on the degree of spatial clustering in the animal population. To quantify the clustering we model line transect data as independent thinnings of spatial shot-noise Cox processes. Likelihood-based inference...

  13. Likelihood-based inference for clustered line transect data

    DEFF Research Database (Denmark)

    Waagepetersen, Rasmus Plenge; Schweder, Tore

    The uncertainty in estimation of spatial animal density from line transect surveys depends on the degree of spatial clustering in the animal population. To quantify the clustering we model line transect data as independent thinnings of spatial shot-noise Cox processes. Likelihood-based inference...

  14. Molecular evolution of the nif gene cluster carrying nifI1 and nifI2 genes in the Gram-positive phototrophic bacterium Heliobacterium chlorum.

    Science.gov (United States)

    Enkh-Amgalan, Jigjiddorj; Kawasaki, Hiroko; Seki, Tatsuji

    2006-01-01

    A major nif cluster was detected in the strictly anaerobic, Gram-positive phototrophic bacterium Heliobacterium chlorum. The cluster consisted of 11 genes arranged within a 10 kb region in the order nifI1, nifI2, nifH, nifD, nifK, nifE, nifN, nifX, fdx, nifB and nifV. The phylogenetic position of Hbt. chlorum was the same in the NifH, NifD, NifK, NifE and NifN trees; Hbt. chlorum formed a cluster with Desulfitobacterium hafniense, the closest neighbour of heliobacteria based on the 16S rRNA phylogeny, and two species of the genus Geobacter belonging to the Deltaproteobacteria. Two nifI genes, known to occur in the nif clusters of methanogenic archaea between nifH and nifD, were found upstream of the nifH gene of Hbt. chlorum. The organization of the nif operon and the phylogeny of individual and concatenated gene products showed that the Hbt. chlorum nif operon carrying nifI genes upstream of the nifH gene was an intermediate between the nif operon with nifI downstream of nifH (group II and III of the nitrogenase classification) and the nif operon lacking nifI (group I). Thus, the phylogenetic position of Hbt. chlorum nitrogenase may reflect an evolutionary stage of a divergence of the two nitrogenase groups, with group I consisting of the aerobic diazotrophs and group II consisting of strictly anaerobic prokaryotes.

  15. Resistance gene candidates identified by PCR with degenerate oligonucleotide primers map to clusters of resistance genes in lettuce.

    Science.gov (United States)

    Shen, K A; Meyers, B C; Islam-Faridi, M N; Chin, D B; Stelly, D M; Michelmore, R W

    1998-08-01

    The recent cloning of genes for resistance against diverse pathogens from a variety of plants has revealed that many share conserved sequence motifs. This provides the possibility of isolating numerous additional resistance genes by polymerase chain reaction (PCR) with degenerate oligonucleotide primers. We amplified resistance gene candidates (RGCs) from lettuce with multiple combinations of primers with low degeneracy designed from motifs in the nucleotide binding sites (NBSs) of RPS2 of Arabidopsis thaliana and N of tobacco. Genomic DNA, cDNA, and bacterial artificial chromosome (BAC) clones were successfully used as templates. Four families of sequences were identified that had the same similarity to each other as to resistance genes from other species. The relationship of the amplified products to resistance genes was evaluated by several sequence and genetic criteria. The amplified products contained open reading frames with additional sequences characteristic of NBSs. Hybridization of RGCs to genomic DNA and to BAC clones revealed large numbers of related sequences. Genetic analysis demonstrated the existence of clustered multigene families for each of the four RGC sequences. This parallels classical genetic data on clustering of disease resistance genes. Two of the four families mapped to known clusters of resistance genes; these two families were therefore studied in greater detail. Additional evidence that these RGCs could be resistance genes was gained by the identification of leucine-rich repeat (LRR) regions in sequences adjoining the NBS similar to those in RPM1 and RPS2 of A. thaliana. Fluorescent in situ hybridization confirmed the clustered genomic distribution of these sequences. The use of PCR with degenerate oligonucleotide primers is therefore an efficient method to identify numerous RGCs in plants.

  16. Fuzzy Rules for Ant Based Clustering Algorithm

    Directory of Open Access Journals (Sweden)

    Amira Hamdi

    2016-01-01

    Full Text Available This paper provides a new intelligent technique for semisupervised data clustering problem that combines the Ant System (AS algorithm with the fuzzy c-means (FCM clustering algorithm. Our proposed approach, called F-ASClass algorithm, is a distributed algorithm inspired by foraging behavior observed in ant colonyT. The ability of ants to find the shortest path forms the basis of our proposed approach. In the first step, several colonies of cooperating entities, called artificial ants, are used to find shortest paths in a complete graph that we called graph-data. The number of colonies used in F-ASClass is equal to the number of clusters in dataset. Hence, the partition matrix of dataset founded by artificial ants is given in the second step, to the fuzzy c-means technique in order to assign unclassified objects generated in the first step. The proposed approach is tested on artificial and real datasets, and its performance is compared with those of K-means, K-medoid, and FCM algorithms. Experimental section shows that F-ASClass performs better according to the error rate classification, accuracy, and separation index.

  17. Genetic recombination as a major cause of mutagenesis in the human globin gene clusters.

    Science.gov (United States)

    Borg, Joseph; Georgitsi, Marianthi; Aleporou-Marinou, Vassiliki; Kollia, Panagoula; Patrinos, George P

    2009-12-01

    Homologous recombination is a frequent phenomenon in multigene families and as such it occurs several times in both the alpha- and beta-like globin gene families. In numerous occasions, genetic recombination has been previously implicated as a major mechanism that drives mutagenesis in the human globin gene clusters, either in the form of unequal crossover or gene conversion. Unequal crossover results in the increase or decrease of the human globin gene copies, accompanied in the majority of cases with minor phenotypic consequences, while gene conversion contributes either to maintaining sequence homogeneity or generating sequence diversity. The role of genetic recombination, particularly gene conversion in the evolution of the human globin gene families has been discussed elsewhere. Here, we summarize our current knowledge and review existing experimental evidence outlining the role of genetic recombination in the mutagenic process in the human globin gene families.

  18. Methods for simultaneously identifying coherent local clusters with smooth global patterns in gene expression profiles

    Directory of Open Access Journals (Sweden)

    Lee Yun-Shien

    2008-03-01

    Full Text Available Abstract Background The hierarchical clustering tree (HCT with a dendrogram 1 and the singular value decomposition (SVD with a dimension-reduced representative map 2 are popular methods for two-way sorting the gene-by-array matrix map employed in gene expression profiling. While HCT dendrograms tend to optimize local coherent clustering patterns, SVD leading eigenvectors usually identify better global grouping and transitional structures. Results This study proposes a flipping mechanism for a conventional agglomerative HCT using a rank-two ellipse (R2E, an improved SVD algorithm for sorting purpose seriation by Chen 3 as an external reference. While HCTs always produce permutations with good local behaviour, the rank-two ellipse seriation gives the best global grouping patterns and smooth transitional trends. The resulting algorithm automatically integrates the desirable properties of each method so that users have access to a clustering and visualization environment for gene expression profiles that preserves coherent local clusters and identifies global grouping trends. Conclusion We demonstrate, through four examples, that the proposed method not only possesses better numerical and statistical properties, it also provides more meaningful biomedical insights than other sorting algorithms. We suggest that sorted proximity matrices for genes and arrays, in addition to the gene-by-array expression matrix, can greatly aid in the search for comprehensive understanding of gene expression structures. Software for the proposed methods can be obtained at http://gap.stat.sinica.edu.tw/Software/GAP.

  19. A remarkably stable TipE gene cluster: evolution of insect Para sodium channel auxiliary subunits

    Directory of Open Access Journals (Sweden)

    Li Jia

    2011-11-01

    Full Text Available Abstract Background First identified in fruit flies with temperature-sensitive paralysis phenotypes, the Drosophila melanogaster TipE locus encodes four voltage-gated sodium (NaV channel auxiliary subunits. This cluster of TipE-like genes on chromosome 3L, and a fifth family member on chromosome 3R, are important for the optional expression and functionality of the Para NaV channel but appear quite distinct from auxiliary subunits in vertebrates. Here, we exploited available arthropod genomic resources to trace the origin of TipE-like genes by mapping their evolutionary histories and examining their genomic architectures. Results We identified a remarkably conserved synteny block of TipE-like orthologues with well-maintained local gene arrangements from 21 insect species. Homologues in the water flea, Daphnia pulex, suggest an ancestral pancrustacean repertoire of four TipE-like genes; a subsequent gene duplication may have generated functional redundancy allowing gene losses in the silk moth and mosquitoes. Intronic nesting of the insect TipE gene cluster probably occurred following the divergence from crustaceans, but in the flour beetle and silk moth genomes the clusters apparently escaped from nesting. Across Pancrustacea, TipE gene family members have experienced intronic nesting, escape from nesting, retrotransposition, translocation, and gene loss events while generally maintaining their local gene neighbourhoods. D. melanogaster TipE-like genes exhibit coordinated spatial and temporal regulation of expression distinct from their host gene but well-correlated with their regulatory target, the Para NaV channel, suggesting that functional constraints may preserve the TipE gene cluster. We identified homology between TipE-like NaV channel regulators and vertebrate Slo-beta auxiliary subunits of big-conductance calcium-activated potassium (BKCa channels, which suggests that ion channel regulatory partners have evolved distinct lineage

  20. Adaptive density trajectory cluster based on time and space distance

    Science.gov (United States)

    Liu, Fagui; Zhang, Zhijie

    2017-10-01

    There are some hotspot problems remaining in trajectory cluster for discovering mobile behavior regularity, such as the computation of distance between sub trajectories, the setting of parameter values in cluster algorithm and the uncertainty/boundary problem of data set. As a result, based on the time and space, this paper tries to define the calculation method of distance between sub trajectories. The significance of distance calculation for sub trajectories is to clearly reveal the differences in moving trajectories and to promote the accuracy of cluster algorithm. Besides, a novel adaptive density trajectory cluster algorithm is proposed, in which cluster radius is computed through using the density of data distribution. In addition, cluster centers and number are selected by a certain strategy automatically, and uncertainty/boundary problem of data set is solved by designed weighted rough c-means. Experimental results demonstrate that the proposed algorithm can perform the fuzzy trajectory cluster effectively on the basis of the time and space distance, and obtain the optimal cluster centers and rich cluster results information adaptably for excavating the features of mobile behavior in mobile and sociology network.

  1. Cluster-based spectrum sensing for cognitive radios with imperfect channel to cluster-head

    KAUST Repository

    Ben Ghorbel, Mahdi

    2012-04-01

    Spectrum sensing is considered as the first and main step for cognitive radio systems to achieve an efficient use of spectrum. Cooperation and clustering among cognitive radio users are two techniques that can be employed with spectrum sensing in order to improve the sensing performance by reducing miss-detection and false alarm. In this paper, within the framework of a clustering-based cooperative spectrum sensing scheme, we study the effect of errors in transmitting the local decisions from the secondary users to the cluster heads (or the fusion center), while considering non-identical channel conditions between the secondary users. Closed-form expressions for the global probabilities of detection and false alarm at the cluster head are derived. © 2012 IEEE.

  2. Cluster-based spectrum sensing for cognitive radios with imperfect channel to cluster-head

    KAUST Repository

    Ben Ghorbel, Mahdi; Nam, Haewoon; Alouini, Mohamed-Slim

    2012-01-01

    Spectrum sensing is considered as the first and main step for cognitive radio systems to achieve an efficient use of spectrum. Cooperation and clustering among cognitive radio users are two techniques that can be employed with spectrum sensing in order to improve the sensing performance by reducing miss-detection and false alarm. In this paper, within the framework of a clustering-based cooperative spectrum sensing scheme, we study the effect of errors in transmitting the local decisions from the secondary users to the cluster heads (or the fusion center), while considering non-identical channel conditions between the secondary users. Closed-form expressions for the global probabilities of detection and false alarm at the cluster head are derived. © 2012 IEEE.

  3. Transcriptional regulation of gene expression clusters in motor neurons following spinal cord injury

    Directory of Open Access Journals (Sweden)

    Westerdahl Ann-Charlotte

    2010-06-01

    Full Text Available Abstract Background Spinal cord injury leads to neurological dysfunctions affecting the motor, sensory as well as the autonomic systems. Increased excitability of motor neurons has been implicated in injury-induced spasticity, where the reappearance of self-sustained plateau potentials in the absence of modulatory inputs from the brain correlates with the development of spasticity. Results Here we examine the dynamic transcriptional response of motor neurons to spinal cord injury as it evolves over time to unravel common gene expression patterns and their underlying regulatory mechanisms. For this we use a rat-tail-model with complete spinal cord transection causing injury-induced spasticity, where gene expression profiles are obtained from labeled motor neurons extracted with laser microdissection 0, 2, 7, 21 and 60 days post injury. Consensus clustering identifies 12 gene clusters with distinct time expression profiles. Analysis of these gene clusters identifies early immunological/inflammatory and late developmental responses as well as a regulation of genes relating to neuron excitability that support the development of motor neuron hyper-excitability and the reappearance of plateau potentials in the late phase of the injury response. Transcription factor motif analysis identifies differentially expressed transcription factors involved in the regulation of each gene cluster, shaping the expression of the identified biological processes and their associated genes underlying the changes in motor neuron excitability. Conclusions This analysis provides important clues to the underlying mechanisms of transcriptional regulation responsible for the increased excitability observed in motor neurons in the late chronic phase of spinal cord injury suggesting alternative targets for treatment of spinal cord injury. Several transcription factors were identified as potential regulators of gene clusters containing elements related to motor neuron hyper

  4. Transcriptional regulation of gene expression clusters in motor neurons following spinal cord injury.

    Science.gov (United States)

    Ryge, Jesper; Winther, Ole; Wienecke, Jacob; Sandelin, Albin; Westerdahl, Ann-Charlotte; Hultborn, Hans; Kiehn, Ole

    2010-06-09

    Spinal cord injury leads to neurological dysfunctions affecting the motor, sensory as well as the autonomic systems. Increased excitability of motor neurons has been implicated in injury-induced spasticity, where the reappearance of self-sustained plateau potentials in the absence of modulatory inputs from the brain correlates with the development of spasticity. Here we examine the dynamic transcriptional response of motor neurons to spinal cord injury as it evolves over time to unravel common gene expression patterns and their underlying regulatory mechanisms. For this we use a rat-tail-model with complete spinal cord transection causing injury-induced spasticity, where gene expression profiles are obtained from labeled motor neurons extracted with laser microdissection 0, 2, 7, 21 and 60 days post injury. Consensus clustering identifies 12 gene clusters with distinct time expression profiles. Analysis of these gene clusters identifies early immunological/inflammatory and late developmental responses as well as a regulation of genes relating to neuron excitability that support the development of motor neuron hyper-excitability and the reappearance of plateau potentials in the late phase of the injury response. Transcription factor motif analysis identifies differentially expressed transcription factors involved in the regulation of each gene cluster, shaping the expression of the identified biological processes and their associated genes underlying the changes in motor neuron excitability. This analysis provides important clues to the underlying mechanisms of transcriptional regulation responsible for the increased excitability observed in motor neurons in the late chronic phase of spinal cord injury suggesting alternative targets for treatment of spinal cord injury. Several transcription factors were identified as potential regulators of gene clusters containing elements related to motor neuron hyper-excitability, the manipulation of which potentially could be

  5. Evaluation of gene-expression clustering via mutual information distance measure

    Directory of Open Access Journals (Sweden)

    Maimon Oded

    2007-03-01

    Full Text Available Abstract Background The definition of a distance measure plays a key role in the evaluation of different clustering solutions of gene expression profiles. In this empirical study we compare different clustering solutions when using the Mutual Information (MI measure versus the use of the well known Euclidean distance and Pearson correlation coefficient. Results Relying on several public gene expression datasets, we evaluate the homogeneity and separation scores of different clustering solutions. It was found that the use of the MI measure yields a more significant differentiation among erroneous clustering solutions. The proposed measure was also used to analyze the performance of several known clustering algorithms. A comparative study of these algorithms reveals that their "best solutions" are ranked almost oppositely when using different distance measures, despite the found correspondence between these measures when analysing the averaged scores of groups of solutions. Conclusion In view of the results, further attention should be paid to the selection of a proper distance measure for analyzing the clustering of gene expression data.

  6. Comprehensive annotation of secondary metabolite biosynthetic genes and gene clusters of Aspergillus nidulans, A. fumigatus, A. niger and A. oryzae

    Science.gov (United States)

    2013-01-01

    Background Secondary metabolite production, a hallmark of filamentous fungi, is an expanding area of research for the Aspergilli. These compounds are potent chemicals, ranging from deadly toxins to therapeutic antibiotics to potential anti-cancer drugs. The genome sequences for multiple Aspergilli have been determined, and provide a wealth of predictive information about secondary metabolite production. Sequence analysis and gene overexpression strategies have enabled the discovery of novel secondary metabolites and the genes involved in their biosynthesis. The Aspergillus Genome Database (AspGD) provides a central repository for gene annotation and protein information for Aspergillus species. These annotations include Gene Ontology (GO) terms, phenotype data, gene names and descriptions and they are crucial for interpreting both small- and large-scale data and for aiding in the design of new experiments that further Aspergillus research. Results We have manually curated Biological Process GO annotations for all genes in AspGD with recorded functions in secondary metabolite production, adding new GO terms that specifically describe each secondary metabolite. We then leveraged these new annotations to predict roles in secondary metabolism for genes lacking experimental characterization. As a starting point for manually annotating Aspergillus secondary metabolite gene clusters, we used antiSMASH (antibiotics and Secondary Metabolite Analysis SHell) and SMURF (Secondary Metabolite Unknown Regions Finder) algorithms to identify potential clusters in A. nidulans, A. fumigatus, A. niger and A. oryzae, which we subsequently refined through manual curation. Conclusions This set of 266 manually curated secondary metabolite gene clusters will facilitate the investigation of novel Aspergillus secondary metabolites. PMID:23617571

  7. Unique nucleotide polymorphism of ankyrin gene cluster in ...

    Indian Academy of Sciences (India)

    gene order is nonrandomly distributed in eukaryote genomes. (Lercher et al. 2002 ... Birth in a birth-and-death process relates to the origin of paralogues, presumably ... are small, or the rate of concerted evolution is very slow (Nei et al. 2000).

  8. Improving Tensor Based Recommenders with Clustering

    DEFF Research Database (Denmark)

    Leginus, Martin; Dolog, Peter; Zemaitis, Valdas

    2012-01-01

    Social tagging systems (STS) model three types of entities (i.e. tag-user-item) and relationships between them are encoded into a 3-order tensor. Latent relationships and patterns can be discovered by applying tensor factorization techniques like Higher Order Singular Value Decomposition (HOSVD),...... of the recommendations and execution time are improved and memory requirements are decreased. The clustering is motivated by the fact that many tags in a tag space are semantically similar thus the tags can be grouped. Finally, promising experimental results are presented...

  9. Identification of new genes in a cell envelope-cell division gene cluster of Escherichia coli: cell envelope gene murG.

    Science.gov (United States)

    Salmond, G P; Lutkenhaus, J F; Donachie, W D

    1980-01-01

    We report the identification, cloning, and mapping of a new cell envelope gene, murG. This lies in a group of five genes of similar phenotype (in the order murE murF murG murC ddl) all concerned with peptidoglycan biosynthesis. This group is in a larger cluster of at least 10 genes, all of which are involved in some way with cell envelope growth. Images PMID:6998962

  10. Kernel method for clustering based on optimal target vector

    International Nuclear Information System (INIS)

    Angelini, Leonardo; Marinazzo, Daniele; Pellicoro, Mario; Stramaglia, Sebastiano

    2006-01-01

    We introduce Ising models, suitable for dichotomic clustering, with couplings that are (i) both ferro- and anti-ferromagnetic (ii) depending on the whole data-set and not only on pairs of samples. Couplings are determined exploiting the notion of optimal target vector, here introduced, a link between kernel supervised and unsupervised learning. The effectiveness of the method is shown in the case of the well-known iris data-set and in benchmarks of gene expression levels, where it works better than existing methods for dichotomic clustering

  11. Weighted similarity-based clustering of chemical structures and bioactivity data in early drug discovery.

    Science.gov (United States)

    Perualila-Tan, Nolen Joy; Shkedy, Ziv; Talloen, Willem; Göhlmann, Hinrich W H; Moerbeke, Marijke Van; Kasim, Adetayo

    2016-08-01

    The modern process of discovering candidate molecules in early drug discovery phase includes a wide range of approaches to extract vital information from the intersection of biology and chemistry. A typical strategy in compound selection involves compound clustering based on chemical similarity to obtain representative chemically diverse compounds (not incorporating potency information). In this paper, we propose an integrative clustering approach that makes use of both biological (compound efficacy) and chemical (structural features) data sources for the purpose of discovering a subset of compounds with aligned structural and biological properties. The datasets are integrated at the similarity level by assigning complementary weights to produce a weighted similarity matrix, serving as a generic input in any clustering algorithm. This new analysis work flow is semi-supervised method since, after the determination of clusters, a secondary analysis is performed wherein it finds differentially expressed genes associated to the derived integrated cluster(s) to further explain the compound-induced biological effects inside the cell. In this paper, datasets from two drug development oncology projects are used to illustrate the usefulness of the weighted similarity-based clustering approach to integrate multi-source high-dimensional information to aid drug discovery. Compounds that are structurally and biologically similar to the reference compounds are discovered using this proposed integrative approach.

  12. MPIGeneNet: Parallel Calculation of Gene Co-Expression Networks on Multicore Clusters.

    Science.gov (United States)

    Gonzalez-Dominguez, Jorge; Martin, Maria J

    2017-10-10

    In this work we present MPIGeneNet, a parallel tool that applies Pearson's correlation and Random Matrix Theory to construct gene co-expression networks. It is based on the state-of-the-art sequential tool RMTGeneNet, which provides networks with high robustness and sensitivity at the expenses of relatively long runtimes for large scale input datasets. MPIGeneNet returns the same results as RMTGeneNet but improves the memory management, reduces the I/O cost, and accelerates the two most computationally demanding steps of co-expression network construction by exploiting the compute capabilities of common multicore CPU clusters. Our performance evaluation on two different systems using three typical input datasets shows that MPIGeneNet is significantly faster than RMTGeneNet. As an example, our tool is up to 175.41 times faster on a cluster with eight nodes, each one containing two 12-core Intel Haswell processors. Source code of MPIGeneNet, as well as a reference manual, are available at https://sourceforge.net/projects/mpigenenet/.

  13. A genome-wide analysis of nonribosomal peptide synthetase gene clusters and their peptides in a Planktothrix rubescens strain

    Directory of Open Access Journals (Sweden)

    Nederbragt Alexander J

    2009-08-01

    Full Text Available Abstract Background Cyanobacteria often produce several different oligopeptides, with unknown biological functions, by nonribosomal peptide synthetases (NRPS. Although some cyanobacterial NRPS gene cluster types are well described, the entire NRPS genomic content within a single cyanobacterial strain has never been investigated. Here we have combined a genome-wide analysis using massive parallel pyrosequencing ("454" and mass spectrometry screening of oligopeptides produced in the strain Planktothrix rubescens NIVA CYA 98 in order to identify all putative gene clusters for oligopeptides. Results Thirteen types of oligopeptides were uncovered by mass spectrometry (MS analyses. Microcystin, cyanopeptolin and aeruginosin synthetases, highly similar to already characterized NRPS, were present in the genome. Two novel NRPS gene clusters were associated with production of anabaenopeptins and microginins, respectively. Sequence-depth of the genome and real-time PCR data revealed three copies of the microginin gene cluster. Since NRPS gene cluster candidates for microviridin and oscillatorin synthesis could not be found, putative (gene encoded precursor peptide sequences to microviridin and oscillatorin were found in the genes mdnA and oscA, respectively. The genes flanking the microviridin and oscillatorin precursor genes encode putative modifying enzymes of the precursor oligopeptides. We therefore propose ribosomal pathways involving modifications and cyclisation for microviridin and oscillatorin. The microviridin, anabaenopeptin and cyanopeptolin gene clusters are situated in close proximity to each other, constituting an oligopeptide island. Conclusion Altogether seven nonribosomal peptide synthetase (NRPS gene clusters and two gene clusters putatively encoding ribosomal oligopeptide biosynthetic pathways were revealed. Our results demonstrate that whole genome shotgun sequencing combined with MS-directed determination of oligopeptides successfully

  14. Evidence-based treatments for cluster headache

    Directory of Open Access Journals (Sweden)

    Gooriah R

    2015-11-01

    Full Text Available Rubesh Gooriah, Alina Buture, Fayyaz Ahmed Department of Neurology, Hull Royal Infirmary, Kingston upon Hull, UK Abstract: Cluster headache (CH, one of the most painful syndromes known to man, is managed with acute and preventive medications. The brief duration and severity of the attacks command the use of rapid-acting pain relievers. Inhalation of oxygen and subcutaneous sumatriptan are the two most effective acute therapeutic options for sufferers of CH. Several preventive medications are available, the most effective of which is verapamil. However, most of these agents are not backed by strong clinical evidence. In some patients, these options can be ineffective, especially in those who develop chronic CH. Surgical procedures for the chronic refractory form of the disorder should then be contemplated, the most promising of which is hypothalamic deep brain stimulation. We hereby review the pathogenesis of CH and the evidence behind the treatment options for this debilitating condition. Keywords: cluster headache, pathogenesis, vasoactive intestinal peptide, suprachiasmatic nucleus

  15. A Web service substitution method based on service cluster nets

    Science.gov (United States)

    Du, YuYue; Gai, JunJing; Zhou, MengChu

    2017-11-01

    Service substitution is an important research topic in the fields of Web services and service-oriented computing. This work presents a novel method to analyse and substitute Web services. A new concept, called a Service Cluster Net Unit, is proposed based on Web service clusters. A service cluster is converted into a Service Cluster Net Unit. Then it is used to analyse whether the services in the cluster can satisfy some service requests. Meanwhile, the substitution methods of an atomic service and a composite service are proposed. The correctness of the proposed method is proved, and the effectiveness is shown and compared with the state-of-the-art method via an experiment. It can be readily applied to e-commerce service substitution to meet the business automation needs.

  16. XML documents cluster research based on frequent subpatterns

    Science.gov (United States)

    Ding, Tienan; Li, Wei; Li, Xiongfei

    2015-12-01

    XML data is widely used in the information exchange field of Internet, and XML document data clustering is the hot research topic. In the XML document clustering process, measure differences between two XML documents is time costly, and impact the efficiency of XML document clustering. This paper proposed an XML documents clustering method based on frequent patterns of XML document dataset, first proposed a coding tree structure for encoding the XML document, and translate frequent pattern mining from XML documents into frequent pattern mining from string. Further, using the cosine similarity calculation method and cohesive hierarchical clustering method for XML document dataset by frequent patterns. Because of frequent patterns are subsets of the original XML document data, so the time consumption of XML document similarity measure is reduced. The experiment runs on synthetic dataset and the real datasets, the experimental result shows that our method is efficient.

  17. Clustering economies based on multiple criteria decision making techniques

    Directory of Open Access Journals (Sweden)

    Mansour Momeni

    2011-10-01

    Full Text Available One of the primary concerns on many countries is to determine different important factors affecting economic growth. In this paper, we study some factors such as unemployment rate, inflation ratio, population growth, average annual income, etc to cluster different countries. The proposed model of this paper uses analytical hierarchy process (AHP to prioritize the criteria and then uses a K-mean technique to cluster 59 countries based on the ranked criteria into four groups. The first group includes countries with high standards such as Germany and Japan. In the second cluster, there are some developing countries with relatively good economic growth such as Saudi Arabia and Iran. The third cluster belongs to countries with faster rates of growth compared with the countries located in the second group such as China, India and Mexico. Finally, the fourth cluster includes countries with relatively very low rates of growth such as Jordan, Mali, Niger, etc.

  18. Local Community Detection Algorithm Based on Minimal Cluster

    Directory of Open Access Journals (Sweden)

    Yong Zhou

    2016-01-01

    Full Text Available In order to discover the structure of local community more effectively, this paper puts forward a new local community detection algorithm based on minimal cluster. Most of the local community detection algorithms begin from one node. The agglomeration ability of a single node must be less than multiple nodes, so the beginning of the community extension of the algorithm in this paper is no longer from the initial node only but from a node cluster containing this initial node and nodes in the cluster are relatively densely connected with each other. The algorithm mainly includes two phases. First it detects the minimal cluster and then finds the local community extended from the minimal cluster. Experimental results show that the quality of the local community detected by our algorithm is much better than other algorithms no matter in real networks or in simulated networks.

  19. REGIONAL DEVELOPMENT BASED ON CLUSTER IN LIVESTOCK DEVELOPMENT. CLUSTER IN LIVESTOCK SECTOR IN THE KYRGYZ REPUBLIC

    Directory of Open Access Journals (Sweden)

    Meerim SYDYKOVA

    2014-11-01

    Full Text Available In most developing countries, where agriculture is the main economical source, clusters have been found as a booster to develop their economy. The Asian countries are now starting to implement agro-food clusters into the mainstream of changes in agriculture, farming and food industry. The long-term growth of meat production in the Kyrgyz Republic during the last decade, as well as the fact that agriculture has become one of the prioritized sectors of the economy, proved the importance of livestock sector in the economy of the Kyrgyz Republic. The research question is “Does the Kyrgyz Republic has strong economic opportunities and prerequisites in agriculture in order to implement an effective agro cluster in the livestock sector?” Paper focuses on describing the prerequisites of the Kyrgyz Republic in agriculture to implement livestock cluster. The main objective of the paper is to analyse the livestock sector of the Kyrgyz Republic and observe the capacity of this sector to implement agro-cluster. The study focuses on investigating livestock sector and a complex S.W.O.T. The analysis was carried out based on local and regional database and official studies. The results of research demonstrate the importance of livestock cluster for national economy. It can be concluded that cluster implementation could provide to its all members with benefits if they could build strong collaborative relationship in order to facilitate the access to the labour market and implicitly, the access to exchange of good practices. Their ability of potential cluster members to act as a convergence pole is critical for acquiring practical skills necessary for the future development of the livestock sector.

  20. Isolation of Hox cluster genes from insects reveals an accelerated sequence evolution rate.

    Directory of Open Access Journals (Sweden)

    Heike Hadrys

    Full Text Available Among gene families it is the Hox genes and among metazoan animals it is the insects (Hexapoda that have attracted particular attention for studying the evolution of development. Surprisingly though, no Hox genes have been isolated from 26 out of 35 insect orders yet, and the existing sequences derive mainly from only two orders (61% from Hymenoptera and 22% from Diptera. We have designed insect specific primers and isolated 37 new partial homeobox sequences of Hox cluster genes (lab, pb, Hox3, ftz, Antp, Scr, abd-a, Abd-B, Dfd, and Ubx from six insect orders, which are crucial to insect phylogenetics. These new gene sequences provide a first step towards comparative Hox gene studies in insects. Furthermore, comparative distance analyses of homeobox sequences reveal a correlation between gene divergence rate and species radiation success with insects showing the highest rate of homeobox sequence evolution.

  1. Lung Cancer Signature Biomarkers: tissue specific semantic similarity based clustering of Digital Differential Display (DDD data

    Directory of Open Access Journals (Sweden)

    Srivastava Mousami

    2012-11-01

    Full Text Available Abstract Background The tissue-specific Unigene Sets derived from more than one million expressed sequence tags (ESTs in the NCBI, GenBank database offers a platform for identifying significantly and differentially expressed tissue-specific genes by in-silico methods. Digital differential display (DDD rapidly creates transcription profiles based on EST comparisons and numerically calculates, as a fraction of the pool of ESTs, the relative sequence abundance of known and novel genes. However, the process of identifying the most likely tissue for a specific disease in which to search for candidate genes from the pool of differentially expressed genes remains difficult. Therefore, we have used ‘Gene Ontology semantic similarity score’ to measure the GO similarity between gene products of lung tissue-specific candidate genes from control (normal and disease (cancer sets. This semantic similarity score matrix based on hierarchical clustering represents in the form of a dendrogram. The dendrogram cluster stability was assessed by multiple bootstrapping. Multiple bootstrapping also computes a p-value for each cluster and corrects the bias of the bootstrap probability. Results Subsequent hierarchical clustering by the multiple bootstrapping method (α = 0.95 identified seven clusters. The comparative, as well as subtractive, approach revealed a set of 38 biomarkers comprising four distinct lung cancer signature biomarker clusters (panel 1–4. Further gene enrichment analysis of the four panels revealed that each panel represents a set of lung cancer linked metastasis diagnostic biomarkers (panel 1, chemotherapy/drug resistance biomarkers (panel 2, hypoxia regulated biomarkers (panel 3 and lung extra cellular matrix biomarkers (panel 4. Conclusions Expression analysis reveals that hypoxia induced lung cancer related biomarkers (panel 3, HIF and its modulating proteins (TGM2, CSNK1A1, CTNNA1, NAMPT/Visfatin, TNFRSF1A, ETS1, SRC-1, FN1, APLP2, DMBT1

  2. Cluster-based DBMS Management Tool with High-Availability

    Directory of Open Access Journals (Sweden)

    Jae-Woo Chang

    2005-02-01

    Full Text Available A management tool which is needed for monitoring and managing cluster-based DBMSs has been little studied. So, we design and implement a cluster-based DBMS management tool with high-availability that monitors the status of nodes in a cluster system as well as the status of DBMS instances in a node. The tool enables users to recognize a single virtual system image and provides them with the status of all the nodes and resources in the system by using a graphic user interface (GUI. By using a load balancer, our management tool can increase the performance of a cluster-based DBMS as well as can overcome the limitation of the existing parallel DBMSs.

  3. Defining reference sequences for Nocardia species by similarity and clustering analyses of 16S rRNA gene sequence data.

    Directory of Open Access Journals (Sweden)

    Manal Helal

    Full Text Available BACKGROUND: The intra- and inter-species genetic diversity of bacteria and the absence of 'reference', or the most representative, sequences of individual species present a significant challenge for sequence-based identification. The aims of this study were to determine the utility, and compare the performance of several clustering and classification algorithms to identify the species of 364 sequences of 16S rRNA gene with a defined species in GenBank, and 110 sequences of 16S rRNA gene with no defined species, all within the genus Nocardia. METHODS: A total of 364 16S rRNA gene sequences of Nocardia species were studied. In addition, 110 16S rRNA gene sequences assigned only to the Nocardia genus level at the time of submission to GenBank were used for machine learning classification experiments. Different clustering algorithms were compared with a novel algorithm or the linear mapping (LM of the distance matrix. Principal Components Analysis was used for the dimensionality reduction and visualization. RESULTS: The LM algorithm achieved the highest performance and classified the set of 364 16S rRNA sequences into 80 clusters, the majority of which (83.52% corresponded with the original species. The most representative 16S rRNA sequences for individual Nocardia species have been identified as 'centroids' in respective clusters from which the distances to all other sequences were minimized; 110 16S rRNA gene sequences with identifications recorded only at the genus level were classified using machine learning methods. Simple kNN machine learning demonstrated the highest performance and classified Nocardia species sequences with an accuracy of 92.7% and a mean frequency of 0.578. CONCLUSION: The identification of centroids of 16S rRNA gene sequence clusters using novel distance matrix clustering enables the identification of the most representative sequences for each individual species of Nocardia and allows the quantitation of inter- and intra

  4. Molecular comparison of the structural proteins encoding gene clusters of two related Lactobacillus delbrueckii bacteriophages.

    Science.gov (United States)

    Vasala, A; Dupont, L; Baumann, M; Ritzenthaler, P; Alatossava, T

    1993-01-01

    Virulent phage LL-H and temperate phage mv4 are two related bacteriophages of Lactobacillus delbrueckii. The gene clusters encoding structural proteins of these two phages have been sequenced and further analyzed. Six open reading frames (ORF-1 to ORF-6) were detected. Protein sequencing and Western immunoblotting experiments confirmed that ORF-3 (g34) encoded the main capsid protein Gp34. The presence of a putative late promoter in front of the phage LL-H g34 gene was suggested by primer extension experiments. Comparative sequence analysis between phage LL-H and phage mv4 revealed striking similarities in the structure and organization of this gene cluster, suggesting that the genes encoding phage structural proteins belong to a highly conservative module. Images PMID:8497043

  5. Automatic extraction of gene ontology annotation and its correlation with clusters in protein networks

    Directory of Open Access Journals (Sweden)

    Mazo Ilya

    2007-07-01

    Full Text Available Abstract Background Uncovering cellular roles of a protein is a task of tremendous importance and complexity that requires dedicated experimental work as well as often sophisticated data mining and processing tools. Protein functions, often referred to as its annotations, are believed to manifest themselves through topology of the networks of inter-proteins interactions. In particular, there is a growing body of evidence that proteins performing the same function are more likely to interact with each other than with proteins with other functions. However, since functional annotation and protein network topology are often studied separately, the direct relationship between them has not been comprehensively demonstrated. In addition to having the general biological significance, such demonstration would further validate the data extraction and processing methods used to compose protein annotation and protein-protein interactions datasets. Results We developed a method for automatic extraction of protein functional annotation from scientific text based on the Natural Language Processing (NLP technology. For the protein annotation extracted from the entire PubMed, we evaluated the precision and recall rates, and compared the performance of the automatic extraction technology to that of manual curation used in public Gene Ontology (GO annotation. In the second part of our presentation, we reported a large-scale investigation into the correspondence between communities in the literature-based protein networks and GO annotation groups of functionally related proteins. We found a comprehensive two-way match: proteins within biological annotation groups form significantly denser linked network clusters than expected by chance and, conversely, densely linked network communities exhibit a pronounced non-random overlap with GO groups. We also expanded the publicly available GO biological process annotation using the relations extracted by our NLP technology

  6. Accurate prediction of secondary metabolite gene clusters in filamentous fungi

    DEFF Research Database (Denmark)

    Andersen, Mikael Rørdam; Nielsen, Jakob Blæsbjerg; Klitgaard, Andreas

    2013-01-01

    Biosynthetic pathways of secondary metabolites from fungi are currently subject to an intense effort to elucidate the genetic basis for these compounds due to their large potential within pharmaceutics and synthetic biochemistry. The preferred method is methodical gene deletions to identify...... used A. nidulans for our method development and validation due to the wealth of available biochemical data, but the method can be applied to any fungus with a sequenced and assembled genome, thus supporting further secondary metabolite pathway elucidation in the fungal kingdom....

  7. Cluster-based analysis of multi-model climate ensembles

    Science.gov (United States)

    Hyde, Richard; Hossaini, Ryan; Leeson, Amber A.

    2018-06-01

    Clustering - the automated grouping of similar data - can provide powerful and unique insight into large and complex data sets, in a fast and computationally efficient manner. While clustering has been used in a variety of fields (from medical image processing to economics), its application within atmospheric science has been fairly limited to date, and the potential benefits of the application of advanced clustering techniques to climate data (both model output and observations) has yet to be fully realised. In this paper, we explore the specific application of clustering to a multi-model climate ensemble. We hypothesise that clustering techniques can provide (a) a flexible, data-driven method of testing model-observation agreement and (b) a mechanism with which to identify model development priorities. We focus our analysis on chemistry-climate model (CCM) output of tropospheric ozone - an important greenhouse gas - from the recent Atmospheric Chemistry and Climate Model Intercomparison Project (ACCMIP). Tropospheric column ozone from the ACCMIP ensemble was clustered using the Data Density based Clustering (DDC) algorithm. We find that a multi-model mean (MMM) calculated using members of the most-populous cluster identified at each location offers a reduction of up to ˜ 20 % in the global absolute mean bias between the MMM and an observed satellite-based tropospheric ozone climatology, with respect to a simple, all-model MMM. On a spatial basis, the bias is reduced at ˜ 62 % of all locations, with the largest bias reductions occurring in the Northern Hemisphere - where ozone concentrations are relatively large. However, the bias is unchanged at 9 % of all locations and increases at 29 %, particularly in the Southern Hemisphere. The latter demonstrates that although cluster-based subsampling acts to remove outlier model data, such data may in fact be closer to observed values in some locations. We further demonstrate that clustering can provide a viable and

  8. Inhomogeneity of epidemic spreading with entropy-based infected clusters.

    Science.gov (United States)

    Wen-Jie, Zhou; Xing-Yuan, Wang

    2013-12-01

    Considering the difference in the sizes of the infected clusters in the dynamic complex networks, the normalized entropy based on infected clusters (δ*) is proposed to characterize the inhomogeneity of epidemic spreading. δ* gives information on the variability of the infected clusters in the system. We investigate the variation in the inhomogeneity of the distribution of the epidemic with the absolute velocity v of moving agent, the infection density ρ, and the interaction radius r. By comparing δ* in the dynamic networks with δH* in homogeneous mode, the simulation experiments show that the inhomogeneity of epidemic spreading becomes smaller with the increase of v, ρ, r.

  9. Managing distance and covariate information with point-based clustering

    Directory of Open Access Journals (Sweden)

    Peter A. Whigham

    2016-09-01

    Full Text Available Abstract Background Geographic perspectives of disease and the human condition often involve point-based observations and questions of clustering or dispersion within a spatial context. These problems involve a finite set of point observations and are constrained by a larger, but finite, set of locations where the observations could occur. Developing a rigorous method for pattern analysis in this context requires handling spatial covariates, a method for constrained finite spatial clustering, and addressing bias in geographic distance measures. An approach, based on Ripley’s K and applied to the problem of clustering with deliberate self-harm (DSH, is presented. Methods Point-based Monte-Carlo simulation of Ripley’s K, accounting for socio-economic deprivation and sources of distance measurement bias, was developed to estimate clustering of DSH at a range of spatial scales. A rotated Minkowski L1 distance metric allowed variation in physical distance and clustering to be assessed. Self-harm data was derived from an audit of 2 years’ emergency hospital presentations (n = 136 in a New Zealand town (population ~50,000. Study area was defined by residential (housing land parcels representing a finite set of possible point addresses. Results Area-based deprivation was spatially correlated. Accounting for deprivation and distance bias showed evidence for clustering of DSH for spatial scales up to 500 m with a one-sided 95 % CI, suggesting that social contagion may be present for this urban cohort. Conclusions Many problems involve finite locations in geographic space that require estimates of distance-based clustering at many scales. A Monte-Carlo approach to Ripley’s K, incorporating covariates and models for distance bias, are crucial when assessing health-related clustering. The case study showed that social network structure defined at the neighbourhood level may account for aspects of neighbourhood clustering of DSH. Accounting for

  10. DSN Beowulf Cluster-Based VLBI Correlator

    Science.gov (United States)

    Rogstad, Stephen P.; Jongeling, Andre P.; Finley, Susan G.; White, Leslie A.; Lanyi, Gabor E.; Clark, John E.; Goodhart, Charles E.

    2009-01-01

    The NASA Deep Space Network (DSN) requires a broadband VLBI (very long baseline interferometry) correlator to process data routinely taken as part of the VLBI source Catalogue Maintenance and Enhancement task (CAT M&E) and the Time and Earth Motion Precision Observations task (TEMPO). The data provided by these measurements are a crucial ingredient in the formation of precision deep-space navigation models. In addition, a VLBI correlator is needed to provide support for other VLBI related activities for both internal and external customers. The JPL VLBI Correlator (JVC) was designed, developed, and delivered to the DSN as a successor to the legacy Block II Correlator. The JVC is a full-capability VLBI correlator that uses software processes running on multiple computers to cross-correlate two-antenna broadband noise data. Components of this new system (see Figure 1) consist of Linux PCs integrated into a Beowulf Cluster, an existing Mark5 data storage system, a RAID array, an existing software correlator package (SoftC) originally developed for Delta DOR Navigation processing, and various custom- developed software processes and scripts. Parallel processing on the JVC is achieved by assigning slave nodes of the Beowulf cluster to process separate scans in parallel until all scans have been processed. Due to the single stream sequential playback of the Mark5 data, some ramp-up time is required before all nodes can have access to required scan data. Core functions of each processing step are accomplished using optimized C programs. The coordination and execution of these programs across the cluster is accomplished using Pearl scripts, PostgreSQL commands, and a handful of miscellaneous system utilities. Mark5 data modules are loaded on Mark5 Data systems playback units, one per station. Data processing is started when the operator scans the Mark5 systems and runs a script that reads various configuration files and then creates an experiment-dependent status database

  11. plantiSMASH: automated identification, annotation and expression analysis of plant biosynthetic gene clusters

    DEFF Research Database (Denmark)

    Kautsar, Satria A.; Suarez Duran, Hernando G.; Blin, Kai

    2017-01-01

    exploration of the nature and dynamics of gene clustering in plant metabolism. Moreover, spurred by the continuing decrease in costs of plant genome sequencing, they will allow genome mining technologies to be applied to plant natural product discovery. The plantiSMASH web server, precalculated results...

  12. Synteny in toxigenic Fusarium species: the fumonisin gene cluster and the mating type region as examples

    NARCIS (Netherlands)

    Waalwijk, C.; Lee, van der T.A.J.; Vries, de P.M.; Hesselink, T.; Arts, J.; Kema, G.H.J.

    2004-01-01

    A comparative genomic approach was used to study the mating type locus and the gene cluster involved in toxin production ( fumonisin) in Fusarium proliferatum, a pathogen with a wide host range and a complex toxin profile. A BAC library, generated from F. proliferatum isolate ITEM 2287, was used to

  13. Insights into secondary metabolism from a global analysis of prokaryotic biosynthetic gene clusters

    NARCIS (Netherlands)

    Cimermancic, P.; Medema, Marnix; Claesen, J.; Kurika, K.; Wieland Brown, L.C.; Mavrommatis, K.; Pati, A.; Godfrey, P.A.; Koehrsen, M.; Clardy, J.; Birren, B. W.; Takano, Eriko; Sali, A.; Linington, R.G.; Fischbach, M.A.

    2014-01-01

    Although biosynthetic gene clusters (BGCs) have been discovered for hundreds of bacterial metabolites, our knowledge of their diversity remains limited. Here, we used a novel algorithm to systematically identify BGCs in the extensive extant microbial sequencing data. Network analysis of the

  14. Evolutionary history of the phl gene cluster in the plant-associated bacterium Pseudomonas fluorescens

    NARCIS (Netherlands)

    Moynihan, J.A.; Morrissey, J.P.; Coppoolse, E.; Stiekema, W.J.; O'Gara, F.; Boyd, E.F.

    2009-01-01

    Pseudomonas fluorescens is of agricultural and economic importance as a biological control agent largely because of its plant-association and production of secondary metabolites, in particular 2, 4-diacetylphloroglucinol (2, 4-DAPG). This polyketide, which is encoded by the eight gene phl cluster,

  15. Molecular population genetics of the β-esterase gene cluster of ...

    Indian Academy of Sciences (India)

    We suggest that the demographic history (bottleneck and admixture of genetically differentiated populations) is the major factor shaping the pattern of nucleotide polymorphism in the -esterase gene cluster. However there are some 'footprints' of directional and balancing selection shaping specific distribution of nucleotide ...

  16. Clusters of orthologous genes for 41 archaeal genomes and implications for evolutionary genomics of archaea

    OpenAIRE

    Wolf Yuri I; Novichkov Pavel S; Sorokin Alexander V; Makarova Kira S; Koonin Eugene V

    2007-01-01

    Abstract Background An evolutionary classification of genes from sequenced genomes that distinguishes between orthologs and paralogs is indispensable for genome annotation and evolutionary reconstruction. Shortly after multiple genome sequences of bacteria, archaea, and unicellular eukaryotes became available, an attempt on such a classification was implemented in Clusters of Orthologous Groups of proteins (COGs). Rapid accumulation of genome sequences creates opportunities for refining COGs ...

  17. The effect of alcohol on the differential expression of cluster of differentiation 14 gene, associated pathways, and genetic network.

    Directory of Open Access Journals (Sweden)

    Diana X Zhou

    Full Text Available Alcohol consumption affects human health in part by compromising the immune system. In this study, we examined the expression of the Cd14 (cluster of differentiation 14 gene, which is involved in the immune system through a proinflammatory cascade. Expression was evaluated in BXD mice treated with saline or acute 1.8 g/kg i.p. ethanol (12.5% v/v. Hippocampal gene expression data were generated to examine differential expression and to perform systems genetics analyses. The Cd14 gene expression showed significant changes among the BXD strains after ethanol treatment, and eQTL mapping revealed that Cd14 is a cis-regulated gene. We also identified eighteen ethanol-related phenotypes correlated with Cd14 expression related to either ethanol responses or ethanol consumption. Pathway analysis was performed to identify possible biological pathways involved in the response to ethanol and Cd14. We also constructed a genetic network for Cd14 using the top 20 correlated genes and present several genes possibly involved in Cd14 and ethanol responses based on differential gene expression. In conclusion, we found Cd14, along with several other genes and pathways, to be involved in ethanol responses in the hippocampus, such as increased susceptibility to lipopolysaccharides and neuroinflammation.

  18. Human microRNA target analysis and gene ontology clustering by GOmir, a novel stand-alone application.

    Science.gov (United States)

    Roubelakis, Maria G; Zotos, Pantelis; Papachristoudis, Georgios; Michalopoulos, Ioannis; Pappa, Kalliopi I; Anagnou, Nicholas P; Kossida, Sophia

    2009-06-16

    microRNAs (miRNAs) are single-stranded RNA molecules of about 20-23 nucleotides length found in a wide variety of organisms. miRNAs regulate gene expression, by interacting with target mRNAs at specific sites in order to induce cleavage of the message or inhibit translation. Predicting or verifying mRNA targets of specific miRNAs is a difficult process of great importance. GOmir is a novel stand-alone application consisting of two separate tools: JTarget and TAGGO. JTarget integrates miRNA target prediction and functional analysis by combining the predicted target genes from TargetScan, miRanda, RNAhybrid and PicTar computational tools as well as the experimentally supported targets from TarBase and also providing a full gene description and functional analysis for each target gene. On the other hand, TAGGO application is designed to automatically group gene ontology annotations, taking advantage of the Gene Ontology (GO), in order to extract the main attributes of sets of proteins. GOmir represents a new tool incorporating two separate Java applications integrated into one stand-alone Java application. GOmir (by using up to five different databases) introduces miRNA predicted targets accompanied by (a) full gene description, (b) functional analysis and (c) detailed gene ontology clustering. Additionally, a reverse search initiated by a potential target can also be conducted. GOmir can freely be downloaded BRFAA.

  19. COMPARISON AND EVALUATION OF CLUSTER BASED IMAGE SEGMENTATION TECHNIQUES

    OpenAIRE

    Hetangi D. Mehta*, Daxa Vekariya, Pratixa Badelia

    2017-01-01

    Image segmentation is the classification of an image into different groups. Numerous algorithms using different approaches have been proposed for image segmentation. A major challenge in segmentation evaluation comes from the fundamental conflict between generality and objectivity. A review is done on different types of clustering methods used for image segmentation. Also a methodology is proposed to classify and quantify different clustering algorithms based on their consistency in different...

  20. Cluster-based localization and tracking in ubiquitous computing systems

    CERN Document Server

    Martínez-de Dios, José Ramiro; Torres-González, Arturo; Ollero, Anibal

    2017-01-01

    Localization and tracking are key functionalities in ubiquitous computing systems and techniques. In recent years a very high variety of approaches, sensors and techniques for indoor and GPS-denied environments have been developed. This book briefly summarizes the current state of the art in localization and tracking in ubiquitous computing systems focusing on cluster-based schemes. Additionally, existing techniques for measurement integration, node inclusion/exclusion and cluster head selection are also described in this book.

  1. LCGbase: A Comprehensive Database for Lineage-Based Co-regulated Genes.

    Science.gov (United States)

    Wang, Dapeng; Zhang, Yubin; Fan, Zhonghua; Liu, Guiming; Yu, Jun

    2012-01-01

    Animal genes of different lineages, such as vertebrates and arthropods, are well-organized and blended into dynamic chromosomal structures that represent a primary regulatory mechanism for body development and cellular differentiation. The majority of genes in a genome are actually clustered, which are evolutionarily stable to different extents and biologically meaningful when evaluated among genomes within and across lineages. Until now, many questions concerning gene organization, such as what is the minimal number of genes in a cluster and what is the driving force leading to gene co-regulation, remain to be addressed. Here, we provide a user-friendly database-LCGbase (a comprehensive database for lineage-based co-regulated genes)-hosting information on evolutionary dynamics of gene clustering and ordering within animal kingdoms in two different lineages: vertebrates and arthropods. The database is constructed on a web-based Linux-Apache-MySQL-PHP framework and effective interactive user-inquiry service. Compared to other gene annotation databases with similar purposes, our database has three comprehensible advantages. First, our database is inclusive, including all high-quality genome assemblies of vertebrates and representative arthropod species. Second, it is human-centric since we map all gene clusters from other genomes in an order of lineage-ranks (such as primates, mammals, warm-blooded, and reptiles) onto human genome and start the database from well-defined gene pairs (a minimal cluster where the two adjacent genes are oriented as co-directional, convergent, and divergent pairs) to large gene clusters. Furthermore, users can search for any adjacent genes and their detailed annotations. Third, the database provides flexible parameter definitions, such as the distance of transcription start sites between two adjacent genes, which is extendable to genes that flanking the cluster across species. We also provide useful tools for sequence alignment, gene

  2. Genomic and expression analysis of the vanG-like gene cluster of Clostridium difficile.

    Science.gov (United States)

    Peltier, Johann; Courtin, Pascal; El Meouche, Imane; Catel-Ferreira, Manuella; Chapot-Chartier, Marie-Pierre; Lemée, Ludovic; Pons, Jean-Louis

    2013-07-01

    Primary antibiotic treatment of Clostridium difficile intestinal diseases requires metronidazole or vancomycin therapy. A cluster of genes homologous to enterococcal glycopeptides resistance vanG genes was found in the genome of C. difficile 630, although this strain remains sensitive to vancomycin. This vanG-like gene cluster was found to consist of five ORFs: the regulatory region consisting of vanR and vanS and the effector region consisting of vanG, vanXY and vanT. We found that 57 out of 83 C. difficile strains, representative of the main lineages of the species, harbour this vanG-like cluster. The cluster is expressed as an operon and, when present, is found at the same genomic location in all strains. The vanG, vanXY and vanT homologues in C. difficile 630 are co-transcribed and expressed to a low level throughout the growth phases in the absence of vancomycin. Conversely, the expression of these genes is strongly induced in the presence of subinhibitory concentrations of vancomycin, indicating that the vanG-like operon is functional at the transcriptional level in C. difficile. Hydrophilic interaction liquid chromatography (HILIC-HPLC) and MS analysis of cytoplasmic peptidoglycan precursors of C. difficile 630 grown without vancomycin revealed the exclusive presence of a UDP-MurNAc-pentapeptide with an alanine at the C terminus. UDP-MurNAc-pentapeptide [d-Ala] was also the only peptidoglycan precursor detected in C. difficile grown in the presence of vancomycin, corroborating the lack of vancomycin resistance. Peptidoglycan structures of a vanG-like mutant strain and of a strain lacking the vanG-like cluster did not differ from the C. difficile 630 strain, indicating that the vanG-like cluster also has no impact on cell-wall composition.

  3. Identification, characterization and metagenome analysis of oocyte-specific genes organized in clusters in the mouse genome

    Directory of Open Access Journals (Sweden)

    Vaiman Daniel

    2005-05-01

    Full Text Available Abstract Background Genes specifically expressed in the oocyte play key roles in oogenesis, ovarian folliculogenesis, fertilization and/or early embryonic development. In an attempt to identify novel oocyte-specific genes in the mouse, we have used an in silico subtraction methodology, and we have focused our attention on genes that are organized in genomic clusters. Results In the present work, five clusters have been studied: a cluster of thirteen genes characterized by an F-box domain localized on chromosome 9, a cluster of six genes related to T-cell leukaemia/lymphoma protein 1 (Tcl1 on chromosome 12, a cluster composed of a SPErm-associated glutamate (E-Rich (Speer protein expressed in the oocyte in the vicinity of four unknown genes specifically expressed in the testis on chromosome 14, a cluster composed of the oocyte secreted protein-1 (Oosp-1 gene and two Oosp-related genes on chromosome 19, all three being characterized by a partial N-terminal zona pellucida-like domain, and another small cluster of two genes on chromosome 19 as well, composed of a TWIK-Related spinal cord K+ channel encoding-gene, and an unknown gene predicted in silico to be testis-specific. The specificity of expression was confirmed by RT-PCR and in situ hybridization for eight and five of them, respectively. Finally, we showed by comparing all of the isolated and clustered oocyte-specific genes identified so far in the mouse genome, that the oocyte-specific clusters are significantly closer to telomeres than isolated oocyte-specific genes are. Conclusion We have studied five clusters of genes specifically expressed in female, some of them being also expressed in male germ-cells. Moreover, contrarily to non-clustered oocyte-specific genes, those that are organized in clusters tend to map near chromosome ends, suggesting that this specific near-telomere position of oocyte-clusters in rodents could constitute an evolutionary advantage. Understanding the biological

  4. Radiobiological analyse based on cell cluster models

    International Nuclear Information System (INIS)

    Lin Hui; Jing Jia; Meng Damin; Xu Yuanying; Xu Liangfeng

    2010-01-01

    The influence of cell cluster dimension on EUD and TCP for targeted radionuclide therapy was studied using the radiobiological method. The radiobiological features of tumor with activity-lack in core were evaluated and analyzed by associating EUD, TCP and SF.The results show that EUD will increase with the increase of tumor dimension under the activity homogeneous distribution. If the extra-cellular activity was taken into consideration, the EUD will increase 47%. Under the activity-lack in tumor center and the requirement of TCP=0.90, the α cross-fire influence of 211 At could make up the maximum(48 μm)3 activity-lack for Nucleus source, but(72 μm)3 for Cytoplasm, Cell Surface, Cell and Voxel sources. In clinic,the physician could prefer the suggested dose of Cell Surface source in case of the future of local tumor control for under-dose. Generally TCP could well exhibit the effect difference between under-dose and due-dose, but not between due-dose and over-dose, which makes TCP more suitable for the therapy plan choice. EUD could well exhibit the difference between different models and activity distributions,which makes it more suitable for the research work. When the user uses EUD to study the influence of activity inhomogeneous distribution, one should keep the consistency of the configuration and volume of the former and the latter models. (authors)

  5. antiSMASH 3.0—a comprehensive resource for the genome mining of biosynthetic gene clusters

    DEFF Research Database (Denmark)

    Weber, Tilmann; Blin, Kai; Duddela, Srikanth

    2015-01-01

    Microbial secondary metabolism constitutes a rich source of antibiotics, chemotherapeutics, insecticides and other high-value chemicals. Genome mining of gene clusters that encode the biosynthetic pathways for these metabolites has become a key methodology for novel compound discovery. In 2011, we...... introduced antiSMASH, a web server and stand-alone tool for the automatic genomic identification and analysis of biosynthetic gene clusters, available at http://antismash.secondarymetabolites.org. Here, we present version 3.0 of antiSMASH, which has undergone major improvements. A full integration...... of the recently published ClusterFinder algorithm now allows using this probabilistic algorithm to detect putative gene clusters of unknown types. Also, a new dereplication variant of the ClusterBlast module now identifies similarities of identified clusters to any of 1172 clusters with known end products...

  6. ENERGY OPTIMIZATION IN CLUSTER BASED WIRELESS SENSOR NETWORKS

    Directory of Open Access Journals (Sweden)

    T. SHANKAR

    2014-04-01

    Full Text Available Wireless sensor networks (WSN are made up of sensor nodes which are usually battery-operated devices, and hence energy saving of sensor nodes is a major design issue. To prolong the networks lifetime, minimization of energy consumption should be implemented at all layers of the network protocol stack starting from the physical to the application layer including cross-layer optimization. Optimizing energy consumption is the main concern for designing and planning the operation of the WSN. Clustering technique is one of the methods utilized to extend lifetime of the network by applying data aggregation and balancing energy consumption among sensor nodes of the network. This paper proposed new version of Low Energy Adaptive Clustering Hierarchy (LEACH, protocols called Advanced Optimized Low Energy Adaptive Clustering Hierarchy (AOLEACH, Optimal Deterministic Low Energy Adaptive Clustering Hierarchy (ODLEACH, and Varying Probability Distance Low Energy Adaptive Clustering Hierarchy (VPDL combination with Shuffled Frog Leap Algorithm (SFLA that enables selecting best optimal adaptive cluster heads using improved threshold energy distribution compared to LEACH protocol and rotating cluster head position for uniform energy dissipation based on energy levels. The proposed algorithm optimizing the life time of the network by increasing the first node death (FND time and number of alive nodes, thereby increasing the life time of the network.

  7. Microgrids Real-Time Pricing Based on Clustering Techniques

    Directory of Open Access Journals (Sweden)

    Hao Liu

    2018-05-01

    Full Text Available Microgrids are widely spreading in electricity markets worldwide. Besides the security and reliability concerns for these microgrids, their operators need to address consumers’ pricing. Considering the growth of smart grids and smart meter facilities, it is expected that microgrids will have some level of flexibility to determine real-time pricing for at least some consumers. As such, the key challenge is finding an optimal pricing model for consumers. This paper, accordingly, proposes a new pricing scheme in which microgrids are able to deploy clustering techniques in order to understand their consumers’ load profiles and then assign real-time prices based on their load profile patterns. An improved weighted fuzzy average k-means is proposed to cluster load curve of consumers in an optimal number of clusters, through which the load profile of each cluster is determined. Having obtained the load profile of each cluster, real-time prices are given to each cluster, which is the best price given to all consumers in that cluster.

  8. Simulation-based marginal likelihood for cluster strong lensing cosmology

    Science.gov (United States)

    Killedar, M.; Borgani, S.; Fabjan, D.; Dolag, K.; Granato, G.; Meneghetti, M.; Planelles, S.; Ragone-Figueroa, C.

    2018-01-01

    Comparisons between observed and predicted strong lensing properties of galaxy clusters have been routinely used to claim either tension or consistency with Λ cold dark matter cosmology. However, standard approaches to such cosmological tests are unable to quantify the preference for one cosmology over another. We advocate approximating the relevant Bayes factor using a marginal likelihood that is based on the following summary statistic: the posterior probability distribution function for the parameters of the scaling relation between Einstein radii and cluster mass, α and β. We demonstrate, for the first time, a method of estimating the marginal likelihood using the X-ray selected z > 0.5 Massive Cluster Survey clusters as a case in point and employing both N-body and hydrodynamic simulations of clusters. We investigate the uncertainty in this estimate and consequential ability to compare competing cosmologies, which arises from incomplete descriptions of baryonic processes, discrepancies in cluster selection criteria, redshift distribution and dynamical state. The relation between triaxial cluster masses at various overdensities provides a promising alternative to the strong lensing test.

  9. Clustering of two genes putatively involved in cyanate detoxification evolved recently and independently in multiple fungal lineages

    Science.gov (United States)

    Fungi that have the enzymes cyanase and carbonic anhydrase show a limited capacity to detoxify cyanate, a fungicide employed by both plants and humans. Here, we describe a novel two-gene cluster that comprises duplicated cyanase and carbonic anhydrase copies, which we name the CCA gene cluster, trac...

  10. A highly divergent gene cluster in honey bees encodes a novel silk family

    OpenAIRE

    Sutherland, Tara D.; Campbell, Peter M.; Weisman, Sarah; Trueman, Holly E.; Sriskantha, Alagacone; Wanjura, Wolfgang J.; Haritos, Victoria S.

    2006-01-01

    The pupal cocoon of the domesticated silk moth Bombyx mori is the best known and most extensively studied insect silk. It is not widely known that Apis mellifera larvae also produce silk. We have used a combination of genomic and proteomic techniques to identify four honey bee fiber genes (AmelFibroin1–4) and two silk-associated genes (AmelSA1 and 2). The four fiber genes are small, comprise a single exon each, and are clustered on a short genomic region where the open reading frames are GC-r...

  11. Strategies to regulate transcription factor-mediated gene positioning and interchromosomal clustering at the nuclear periphery.

    Science.gov (United States)

    Randise-Hinchliff, Carlo; Coukos, Robert; Sood, Varun; Sumner, Michael Chas; Zdraljevic, Stefan; Meldi Sholl, Lauren; Garvey Brickner, Donna; Ahmed, Sara; Watchmaker, Lauren; Brickner, Jason H

    2016-03-14

    In budding yeast, targeting of active genes to the nuclear pore complex (NPC) and interchromosomal clustering is mediated by transcription factor (TF) binding sites in the gene promoters. For example, the binding sites for the TFs Put3, Ste12, and Gcn4 are necessary and sufficient to promote positioning at the nuclear periphery and interchromosomal clustering. However, in all three cases, gene positioning and interchromosomal clustering are regulated. Under uninducing conditions, local recruitment of the Rpd3(L) histone deacetylase by transcriptional repressors blocks Put3 DNA binding. This is a general function of yeast repressors: 16 of 21 repressors blocked Put3-mediated subnuclear positioning; 11 of these required Rpd3. In contrast, Ste12-mediated gene positioning is regulated independently of DNA binding by mitogen-activated protein kinase phosphorylation of the Dig2 inhibitor, and Gcn4-dependent targeting is up-regulated by increasing Gcn4 protein levels. These different regulatory strategies provide either qualitative switch-like control or quantitative control of gene positioning over different time scales. © 2016 Randise-Hinchliff et al.

  12. A scan statistic to extract causal gene clusters from case-control genome-wide rare CNV data

    Directory of Open Access Journals (Sweden)

    Scherer Stephen W

    2011-05-01

    Full Text Available Abstract Background Several statistical tests have been developed for analyzing genome-wide association data by incorporating gene pathway information in terms of gene sets. Using these methods, hundreds of gene sets are typically tested, and the tested gene sets often overlap. This overlapping greatly increases the probability of generating false positives, and the results obtained are difficult to interpret, particularly when many gene sets show statistical significance. Results We propose a flexible statistical framework to circumvent these problems. Inspired by spatial scan statistics for detecting clustering of disease occurrence in the field of epidemiology, we developed a scan statistic to extract disease-associated gene clusters from a whole gene pathway. Extracting one or a few significant gene clusters from a global pathway limits the overall false positive probability, which results in increased statistical power, and facilitates the interpretation of test results. In the present study, we applied our method to genome-wide association data for rare copy-number variations, which have been strongly implicated in common diseases. Application of our method to a simulated dataset demonstrated the high accuracy of this method in detecting disease-associated gene clusters in a whole gene pathway. Conclusions The scan statistic approach proposed here shows a high level of accuracy in detecting gene clusters in a whole gene pathway. This study has provided a sound statistical framework for analyzing genome-wide rare CNV data by incorporating topological information on the gene pathway.

  13. Ontology-based topic clustering for online discussion data

    Science.gov (United States)

    Wang, Yongheng; Cao, Kening; Zhang, Xiaoming

    2013-03-01

    With the rapid development of online communities, mining and extracting quality knowledge from online discussions becomes very important for the industrial and marketing sector, as well as for e-commerce applications and government. Most of the existing techniques model a discussion as a social network of users represented by a user-based graph without considering the content of the discussion. In this paper we propose a new multilayered mode to analysis online discussions. The user-based and message-based representation is combined in this model. A novel frequent concept sets based clustering method is used to cluster the original online discussion network into topic space. Domain ontology is used to improve the clustering accuracy. Parallel methods are also used to make the algorithms scalable to very large data sets. Our experimental study shows that the model and algorithms are effective when analyzing large scale online discussion data.

  14. Event-based cluster synchronization of coupled genetic regulatory networks

    Science.gov (United States)

    Yue, Dandan; Guan, Zhi-Hong; Li, Tao; Liao, Rui-Quan; Liu, Feng; Lai, Qiang

    2017-09-01

    In this paper, the cluster synchronization of coupled genetic regulatory networks with a directed topology is studied by using the event-based strategy and pinning control. An event-triggered condition with a threshold consisting of the neighbors' discrete states at their own event time instants and a state-independent exponential decay function is proposed. The intra-cluster states information and extra-cluster states information are involved in the threshold in different ways. By using the Lyapunov function approach and the theories of matrices and inequalities, we establish the cluster synchronization criterion. It is shown that both the avoidance of continuous transmission of information and the exclusion of the Zeno behavior are ensured under the presented triggering condition. Explicit conditions on the parameters in the threshold are obtained for synchronization. The stability criterion of a single GRN is also given under the reduced triggering condition. Numerical examples are provided to validate the theoretical results.

  15. A novel clustering algorithm based on quantum games

    International Nuclear Information System (INIS)

    Li Qiang; He Yan; Jiang Jingping

    2009-01-01

    Enormous successes have been made by quantum algorithms during the last decade. In this paper, we combine the quantum game with the problem of data clustering, and then develop a quantum-game-based clustering algorithm, in which data points in a dataset are considered as players who can make decisions and implement quantum strategies in quantum games. After each round of a quantum game, each player's expected payoff is calculated. Later, he uses a link-removing-and-rewiring (LRR) function to change his neighbors and adjust the strength of links connecting to them in order to maximize his payoff. Further, algorithms are discussed and analyzed in two cases of strategies, two payoff matrixes and two LRR functions. Consequently, the simulation results have demonstrated that data points in datasets are clustered reasonably and efficiently, and the clustering algorithms have fast rates of convergence. Moreover, the comparison with other algorithms also provides an indication of the effectiveness of the proposed approach.

  16. A Data-origin Authentication Protocol Based on ONOS Cluster

    Directory of Open Access Journals (Sweden)

    Qin Hua

    2016-01-01

    Full Text Available This paper is aim to propose a data-origin authentication protocol based on ONOS cluster. ONOS is a SDN controller which can work under a distributed environment. However, the security of an ONOS cluster is seldom considered, and the communication in an ONOS cluster may suffer from lots of security threats. In this paper, we used a two-tier self-renewable hash chain for identity authentication and data-origin authentication. We analyse the security and overhead of our proposal and made a comparison with current security measure. It showed that with the help of our proposal, communication in an ONOS cluster could be protected from identity forging, replay attacks, data tampering, MITM attacks and repudiation, also the computational overhead would decrease apparently.

  17. Multi scales based sparse matrix spectral clustering image segmentation

    Science.gov (United States)

    Liu, Zhongmin; Chen, Zhicai; Li, Zhanming; Hu, Wenjin

    2018-04-01

    In image segmentation, spectral clustering algorithms have to adopt the appropriate scaling parameter to calculate the similarity matrix between the pixels, which may have a great impact on the clustering result. Moreover, when the number of data instance is large, computational complexity and memory use of the algorithm will greatly increase. To solve these two problems, we proposed a new spectral clustering image segmentation algorithm based on multi scales and sparse matrix. We devised a new feature extraction method at first, then extracted the features of image on different scales, at last, using the feature information to construct sparse similarity matrix which can improve the operation efficiency. Compared with traditional spectral clustering algorithm, image segmentation experimental results show our algorithm have better degree of accuracy and robustness.

  18. Genomic organization of the rat alpha 2u-globulin gene cluster.

    Science.gov (United States)

    McFadyen, D A; Addison, W; Locke, J

    1999-05-01

    The alpha 2u-globulin are a group of similar proteins, belonging to the lipocalin superfamily of proteins, that are synthesized in a subset of secretory tissues in rats. The many alpha 2u-globulin isoforms are encoded by a multigene family that exhibits extensive homology. Despite a high degree of sequence identity, individual family members show diverse expression patterns involving complex hormonal, tissue-specific, and developmental regulation. Analysis suggests that there are approximately 20 alpha 2u-globulin genes in the rat genome. We have used fluorescence in situ hybridization (FISH) to show that the alpha 2u-globulin genes are clustered at a single site on rat Chromosome (Chr) 5 (5q22-24). Southern blots of rat genomic DNA separated by pulsed field gel electrophoresis indicated that the alpha 2u-globulin genes are contained on two NruI fragments with a total size of 880 kbp. Analysis of three P1 clones containing alpha 2u-globulin genes indicated that the alpha 2u-globulin genes are tandemly arranged in a head-to-tail fashion. The organization of the alpha 2u-globulin genes in the rat as a tandem array of single genes differs from the homologous major urinary protein genes in the mouse, which are organized as tandem arrays of divergently oriented gene pairs. The structure of these gene clusters may have consequences for the proposed function, as a pheromone transporter, for the protein products encoded by these genes.

  19. Two Gene Clusters Coordinate Galactose and Lactose Metabolism in Streptococcus gordonii

    Science.gov (United States)

    Zeng, Lin; Martino, Nicole C.

    2012-01-01

    Streptococcus gordonii is an early colonizer of the human oral cavity and an abundant constituent of oral biofilms. Two tandemly arranged gene clusters, designated lac and gal, were identified in the S. gordonii DL1 genome, which encode genes of the tagatose pathway (lacABCD) and sugar phosphotransferase system (PTS) enzyme II permeases. Genes encoding a predicted phospho-β-galactosidase (LacG), a DeoR family transcriptional regulator (LacR), and a transcriptional antiterminator (LacT) were also present in the clusters. Growth and PTS assays supported that the permease designated EIILac transports lactose and galactose, whereas EIIGal transports galactose. The expression of the gene for EIIGal was markedly upregulated in cells growing on galactose. Using promoter-cat fusions, a role for LacR in the regulation of the expressions of both gene clusters was demonstrated, and the gal cluster was also shown to be sensitive to repression by CcpA. The deletion of lacT caused an inability to grow on lactose, apparently because of its role in the regulation of the expression of the genes for EIILac, but had little effect on galactose utilization. S. gordonii maintained a selective advantage over Streptococcus mutans in a mixed-species competition assay, associated with its possession of a high-affinity galactose PTS, although S. mutans could persist better at low pHs. Collectively, these results support the concept that the galactose and lactose systems of S. gordonii are subject to complex regulation and that a high-affinity galactose PTS may be advantageous when S. gordonii is competing against the caries pathogen S. mutans in oral biofilms. PMID:22660715

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

    Science.gov (United States)

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

    2018-02-23

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

  1. A nonparametric Bayesian approach for clustering bisulfate-based DNA methylation profiles.

    Science.gov (United States)

    Zhang, Lin; Meng, Jia; Liu, Hui; Huang, Yufei

    2012-01-01

    DNA methylation occurs in the context of a CpG dinucleotide. It is an important epigenetic modification, which can be inherited through cell division. The two major types of methylation include hypomethylation and hypermethylation. Unique methylation patterns have been shown to exist in diseases including various types of cancer. DNA methylation analysis promises to become a powerful tool in cancer diagnosis, treatment and prognostication. Large-scale methylation arrays are now available for studying methylation genome-wide. The Illumina methylation platform simultaneously measures cytosine methylation at more than 1500 CpG sites associated with over 800 cancer-related genes. Cluster analysis is often used to identify DNA methylation subgroups for prognosis and diagnosis. However, due to the unique non-Gaussian characteristics, traditional clustering methods may not be appropriate for DNA and methylation data, and the determination of optimal cluster number is still problematic. A Dirichlet process beta mixture model (DPBMM) is proposed that models the DNA methylation expressions as an infinite number of beta mixture distribution. The model allows automatic learning of the relevant parameters such as the cluster mixing proportion, the parameters of beta distribution for each cluster, and especially the number of potential clusters. Since the model is high dimensional and analytically intractable, we proposed a Gibbs sampling "no-gaps" solution for computing the posterior distributions, hence the estimates of the parameters. The proposed algorithm was tested on simulated data as well as methylation data from 55 Glioblastoma multiform (GBM) brain tissue samples. To reduce the computational burden due to the high data dimensionality, a dimension reduction method is adopted. The two GBM clusters yielded by DPBMM are based on data of different number of loci (P-value < 0.1), while hierarchical clustering cannot yield statistically significant clusters.

  2. Genetic variations and haplotype diversity of the UGT1 gene cluster in the Chinese population.

    Directory of Open Access Journals (Sweden)

    Jing Yang

    Full Text Available Vertebrates require tremendous molecular diversity to defend against numerous small hydrophobic chemicals. UDP-glucuronosyltransferases (UGTs are a large family of detoxification enzymes that glucuronidate xenobiotics and endobiotics, facilitating their excretion from the body. The UGT1 gene cluster contains a tandem array of variable first exons, each preceded by a specific promoter, and a common set of downstream constant exons, similar to the genomic organization of the protocadherin (Pcdh, immunoglobulin, and T-cell receptor gene clusters. To assist pharmacogenomics studies in Chinese, we sequenced nine first exons, promoter and intronic regions, and five common exons of the UGT1 gene cluster in a population sample of 253 unrelated Chinese individuals. We identified 101 polymorphisms and found 15 novel SNPs. We then computed allele frequencies for each polymorphism and reconstructed their linkage disequilibrium (LD map. The UGT1 cluster can be divided into five linkage blocks: Block 9 (UGT1A9, Block 9/7/6 (UGT1A9, UGT1A7, and UGT1A6, Block 5 (UGT1A5, Block 4/3 (UGT1A4 and UGT1A3, and Block 3' UTR. Furthermore, we inferred haplotypes and selected their tagSNPs. Finally, comparing our data with those of three other populations of the HapMap project revealed ethnic specificity of the UGT1 genetic diversity in Chinese. These findings have important implications for future molecular genetic studies of the UGT1 gene cluster as well as for personalized medical therapies in Chinese.

  3. MeSH key terms for validation and annotation of gene expression clusters

    Energy Technology Data Exchange (ETDEWEB)

    Rechtsteiner, A. (Andreas); Rocha, L. M. (Luis Mateus)

    2004-01-01

    Integration of different sources of information is a great challenge for the analysis of gene expression data, and for the field of Functional Genomics in general. As the availability of numerical data from high-throughput methods increases, so does the need for technologies that assist in the validation and evaluation of the biological significance of results extracted from these data. In mRNA assaying with microarrays, for example, numerical analysis often attempts to identify clusters of co-expressed genes. The important task to find the biological significance of the results and validate them has so far mostly fallen to the biological expert who had to perform this task manually. One of the most promising avenues to develop automated and integrative technology for such tasks lies in the application of modern Information Retrieval (IR) and Knowledge Management (KM) algorithms to databases with biomedical publications and data. Examples of databases available for the field are bibliographic databases c ntaining scientific publications (e.g. MEDLINE/PUBMED), databases containing sequence data (e.g. GenBank) and databases of semantic annotations (e.g. the Gene Ontology Consortium and Medical Subject Headings (MeSH)). We present here an approach that uses the MeSH terms and their concept hierarchies to validate and obtain functional information for gene expression clusters. The controlled and hierarchical MeSH vocabulary is used by the National Library of Medicine (NLM) to index all the articles cited in MEDLINE. Such indexing with a controlled vocabulary eliminates some of the ambiguity due to polysemy (terms that have multiple meanings) and synonymy (multiple terms have similar meaning) that would be encountered if terms would be extracted directly from the articles due to differing article contexts or author preferences and background. Further, the hierarchical organization of the MeSH terms can illustrate the conceptuallfunctional relationships of genes

  4. Sequencing and transcriptional analysis of the Streptococcus thermophilus histamine biosynthesis gene cluster: factors that affect differential hdcA expression

    DEFF Research Database (Denmark)

    Calles-Enríquez, Marina; Hjort, Benjamin Benn; Andersen, Pia Skov

    2010-01-01

    to produce histamine. The hdc clusters of S. thermophilus CHCC1524 and CHCC6483 were sequenced, and the factors that affect histamine biosynthesis and histidine-decarboxylating gene (hdcA) expression were studied. The hdc cluster began with the hdcA gene, was followed by a transporter (hdcP), and ended...... with the hdcB gene, which is of unknown function. The three genes were orientated in the same direction. The genetic organization of the hdc cluster showed a unique organization among the lactic acid bacterial group and resembled those of Staphylococcus and Clostridium species, thus indicating possible...... acquisition through a horizontal transfer mechanism. Transcriptional analysis of the hdc cluster revealed the existence of a polycistronic mRNA covering the three genes. The histidine-decarboxylating gene (hdcA) of S. thermophilus demonstrated maximum expression during the stationary growth phase, with high...

  5. OMERACT-based fibromyalgia symptom subgroups: an exploratory cluster analysis.

    Science.gov (United States)

    Vincent, Ann; Hoskin, Tanya L; Whipple, Mary O; Clauw, Daniel J; Barton, Debra L; Benzo, Roberto P; Williams, David A

    2014-10-16

    The aim of this study was to identify subsets of patients with fibromyalgia with similar symptom profiles using the Outcome Measures in Rheumatology (OMERACT) core symptom domains. Female patients with a diagnosis of fibromyalgia and currently meeting fibromyalgia research survey criteria completed the Brief Pain Inventory, the 30-item Profile of Mood States, the Medical Outcomes Sleep Scale, the Multidimensional Fatigue Inventory, the Multiple Ability Self-Report Questionnaire, the Fibromyalgia Impact Questionnaire-Revised (FIQ-R) and the Short Form-36 between 1 June 2011 and 31 October 2011. Hierarchical agglomerative clustering was used to identify subgroups of patients with similar symptom profiles. To validate the results from this sample, hierarchical agglomerative clustering was repeated in an external sample of female patients with fibromyalgia with similar inclusion criteria. A total of 581 females with a mean age of 55.1 (range, 20.1 to 90.2) years were included. A four-cluster solution best fit the data, and each clustering variable differed significantly (P FIQ-R total scores (P = 0.0004)). In our study, we incorporated core OMERACT symptom domains, which allowed for clustering based on a comprehensive symptom profile. Although our exploratory cluster solution needs confirmation in a longitudinal study, this approach could provide a rationale to support the study of individualized clinical evaluation and intervention.

  6. Agent-based method for distributed clustering of textual information

    Science.gov (United States)

    Potok, Thomas E [Oak Ridge, TN; Reed, Joel W [Knoxville, TN; Elmore, Mark T [Oak Ridge, TN; Treadwell, Jim N [Louisville, TN

    2010-09-28

    A computer method and system for storing, retrieving and displaying information has a multiplexing agent (20) that calculates a new document vector (25) for a new document (21) to be added to the system and transmits the new document vector (25) to master cluster agents (22) and cluster agents (23) for evaluation. These agents (22, 23) perform the evaluation and return values upstream to the multiplexing agent (20) based on the similarity of the document to documents stored under their control. The multiplexing agent (20) then sends the document (21) and the document vector (25) to the master cluster agent (22), which then forwards it to a cluster agent (23) or creates a new cluster agent (23) to manage the document (21). The system also searches for stored documents according to a search query having at least one term and identifying the documents found in the search, and displays the documents in a clustering display (80) of similarity so as to indicate similarity of the documents to each other.

  7. Risk Probability Estimating Based on Clustering

    DEFF Research Database (Denmark)

    Chen, Yong; Jensen, Christian D.; Gray, Elizabeth

    2003-01-01

    of prior experiences, recommendations from a trusted entity or the reputation of the other entity. In this paper we propose a dynamic mechanism for estimating the risk probability of a certain interaction in a given environment using hybrid neural networks. We argue that traditional risk assessment models...... from the insurance industry do not directly apply to ubiquitous computing environments. Instead, we propose a dynamic mechanism for risk assessment, which is based on pattern matching, classification and prediction procedures. This mechanism uses an estimator of risk probability, which is based...

  8. Genetic homogeneity of Clostridium botulinum type A1 strains with unique toxin gene clusters.

    Science.gov (United States)

    Raphael, Brian H; Luquez, Carolina; McCroskey, Loretta M; Joseph, Lavin A; Jacobson, Mark J; Johnson, Eric A; Maslanka, Susan E; Andreadis, Joanne D

    2008-07-01

    A group of five clonally related Clostridium botulinum type A strains isolated from different sources over a period of nearly 40 years harbored several conserved genetic properties. These strains contained a variant bont/A1 with five nucleotide polymorphisms compared to the gene in C. botulinum strain ATCC 3502. The strains also had a common toxin gene cluster composition (ha-/orfX+) similar to that associated with bont/A in type A strains containing an unexpressed bont/B [termed A(B) strains]. However, bont/B was not identified in the strains examined. Comparative genomic hybridization demonstrated identical genomic content among the strains relative to C. botulinum strain ATCC 3502. In addition, microarray data demonstrated the absence of several genes flanking the toxin gene cluster among the ha-/orfX+ A1 strains, suggesting the presence of genomic rearrangements with respect to this region compared to the C. botulinum ATCC 3502 strain. All five strains were shown to have identical flaA variable region nucleotide sequences. The pulsed-field gel electrophoresis patterns of the strains were indistinguishable when digested with SmaI, and a shift in the size of at least one band was observed in a single strain when digested with XhoI. These results demonstrate surprising genomic homogeneity among a cluster of unique C. botulinum type A strains of diverse origin.

  9. Carbon based nanostructures: diamond clusters structured with nanotubes

    Directory of Open Access Journals (Sweden)

    O.A. Shenderova

    2003-01-01

    Full Text Available Feasibility of designing composites from carbon nanotubes and nanodiamond clusters is discussed based on atomistic simulations. Depending on nanotube size and morphology, some types of open nanotubes can be chemically connected with different facets of diamond clusters. The geometrical relation between different types of nanotubes and different diamond facets for construction of mechanically stable composites with all bonds saturated is summarized. Potential applications of the suggested nanostructures are briefly discussed based on the calculations of their electronic properties using environment dependent self-consistent tight-binding approach.

  10. Graph-based clustering and data visualization algorithms

    CERN Document Server

    Vathy-Fogarassy, Ágnes

    2013-01-01

    This work presents a data visualization technique that combines graph-based topology representation and dimensionality reduction methods to visualize the intrinsic data structure in a low-dimensional vector space. The application of graphs in clustering and visualization has several advantages. A graph of important edges (where edges characterize relations and weights represent similarities or distances) provides a compact representation of the entire complex data set. This text describes clustering and visualization methods that are able to utilize information hidden in these graphs, based on

  11. Spatial expression of Hox cluster genes in the ontogeny of a sea urchin

    Science.gov (United States)

    Arenas-Mena, C.; Cameron, A. R.; Davidson, E. H.

    2000-01-01

    The Hox cluster of the sea urchin Strongylocentrous purpuratus contains ten genes in a 500 kb span of the genome. Only two of these genes are expressed during embryogenesis, while all of eight genes tested are expressed during development of the adult body plan in the larval stage. We report the spatial expression during larval development of the five 'posterior' genes of the cluster: SpHox7, SpHox8, SpHox9/10, SpHox11/13a and SpHox11/13b. The five genes exhibit a dynamic, largely mesodermal program of expression. Only SpHox7 displays extensive expression within the pentameral rudiment itself. A spatially sequential and colinear arrangement of expression domains is found in the somatocoels, the paired posterior mesodermal structures that will become the adult perivisceral coeloms. No such sequential expression pattern is observed in endodermal, epidermal or neural tissues of either the larva or the presumptive juvenile sea urchin. The spatial expression patterns of the Hox genes illuminate the evolutionary process by which the pentameral echinoderm body plan emerged from a bilateral ancestor.

  12. Linkage of the Nit1C gene cluster to bacterial cyanide assimilation as a nitrogen source.

    Science.gov (United States)

    Jones, Lauren B; Ghosh, Pallab; Lee, Jung-Hyun; Chou, Chia-Ni; Kunz, Daniel A

    2018-05-21

    A genetic linkage between a conserved gene cluster (Nit1C) and the ability of bacteria to utilize cyanide as the sole nitrogen source was demonstrated for nine different bacterial species. These included three strains whose cyanide nutritional ability has formerly been documented (Pseudomonas fluorescens Pf11764, Pseudomonas putida BCN3 and Klebsiella pneumoniae BCN33), and six not previously known to have this ability [Burkholderia (Paraburkholderia) xenovorans LB400, Paraburkholderia phymatum STM815, Paraburkholderia phytofirmans PsJN, Cupriavidus (Ralstonia) eutropha H16, Gluconoacetobacter diazotrophicus PA1 5 and Methylobacterium extorquens AM1]. For all bacteria, growth on or exposure to cyanide led to the induction of the canonical nitrilase (NitC) linked to the gene cluster, and in the case of Pf11764 in particular, transcript levels of cluster genes (nitBCDEFGH) were raised, and a nitC knock-out mutant failed to grow. Further studies demonstrated that the highly conserved nitB gene product was also significantly elevated. Collectively, these findings provide strong evidence for a genetic linkage between Nit1C and bacterial growth on cyanide, supporting use of the term cyanotrophy in describing what may represent a new nutritional paradigm in microbiology. A broader search of Nit1C genes in presently available genomes revealed its presence in 270 different bacteria, all contained within the domain Bacteria, including Gram-positive Firmicutes and Actinobacteria, and Gram-negative Proteobacteria and Cyanobacteria. Absence of the cluster in the Archaea is congruent with events that may have led to the inception of Nit1C occurring coincidentally with the first appearance of cyanogenic species on Earth, dating back 400-500 million years.

  13. A highly divergent gene cluster in honey bees encodes a novel silk family.

    Science.gov (United States)

    Sutherland, Tara D; Campbell, Peter M; Weisman, Sarah; Trueman, Holly E; Sriskantha, Alagacone; Wanjura, Wolfgang J; Haritos, Victoria S

    2006-11-01

    The pupal cocoon of the domesticated silk moth Bombyx mori is the best known and most extensively studied insect silk. It is not widely known that Apis mellifera larvae also produce silk. We have used a combination of genomic and proteomic techniques to identify four honey bee fiber genes (AmelFibroin1-4) and two silk-associated genes (AmelSA1 and 2). The four fiber genes are small, comprise a single exon each, and are clustered on a short genomic region where the open reading frames are GC-rich amid low GC intergenic regions. The genes encode similar proteins that are highly helical and predicted to form unusually tight coiled coils. Despite the similarity in size, structure, and composition of the encoded proteins, the genes have low primary sequence identity. We propose that the four fiber genes have arisen from gene duplication events but have subsequently diverged significantly. The silk-associated genes encode proteins likely to act as a glue (AmelSA1) and involved in silk processing (AmelSA2). Although the silks of honey bees and silkmoths both originate in larval labial glands, the silk proteins are completely different in their primary, secondary, and tertiary structures as well as the genomic arrangement of the genes encoding them. This implies independent evolutionary origins for these functionally related proteins.

  14. Genes involved in degradation of para-nitrophenol are differentially arranged in form of non-contiguous gene clusters in Burkholderia sp. strain SJ98.

    Directory of Open Access Journals (Sweden)

    Surendra Vikram

    Full Text Available Biodegradation of para-Nitrophenol (PNP proceeds via two distinct pathways, having 1,2,3-benzenetriol (BT and hydroquinone (HQ as their respective terminal aromatic intermediates. Genes involved in these pathways have already been studied in different PNP degrading bacteria. Burkholderia sp. strain SJ98 degrades PNP via both the pathways. Earlier, we have sequenced and analyzed a ~41 kb fragment from the genomic library of strain SJ98. This DNA fragment was found to harbor all the lower pathway genes; however, genes responsible for the initial transformation of PNP could not be identified within this fragment. Now, we have sequenced and annotated the whole genome of strain SJ98 and found two ORFs (viz., pnpA and pnpB showing maximum identity at amino acid level with p-nitrophenol 4-monooxygenase (PnpM and p-benzoquinone reductase (BqR. Unlike the other PNP gene clusters reported earlier in different bacteria, these two ORFs in SJ98 genome are physically separated from the other genes of PNP degradation pathway. In order to ascertain the identity of ORFs pnpA and pnpB, we have performed in-vitro assays using recombinant proteins heterologously expressed and purified to homogeneity. Purified PnpA was found to be a functional PnpM and transformed PNP into benzoquinone (BQ, while PnpB was found to be a functional BqR which catalyzed the transformation of BQ into hydroquinone (HQ. Noticeably, PnpM from strain SJ98 could also transform a number of PNP analogues. Based on the above observations, we propose that the genes for PNP degradation in strain SJ98 are arranged differentially in form of non-contiguous gene clusters. This is the first report for such arrangement for gene clusters involved in PNP degradation. Therefore, we propose that PNP degradation in strain SJ98 could be an important model system for further studies on differential evolution of PNP degradation functions.

  15. The Fdb3 transcription factor of the Fusarium Detoxification of Benzoxazolinone gene cluster is required for MBOA but not BOA degradation in Fusarium pseudograminearum.

    Science.gov (United States)

    Kettle, Andrew J; Carere, Jason; Batley, Jacqueline; Manners, John M; Kazan, Kemal; Gardiner, Donald M

    2016-03-01

    A number of cereals produce the benzoxazolinone class of phytoalexins. Fusarium species pathogenic towards these hosts can typically degrade these compounds via an aminophenol intermediate, and the ability to do so is encoded by a group of genes found in the Fusarium Detoxification of Benzoxazolinone (FDB) cluster. A zinc finger transcription factor encoded by one of the FDB cluster genes (FDB3) has been proposed to regulate the expression of other genes in the cluster and hence is potentially involved in benzoxazolinone degradation. Herein we show that Fdb3 is essential for the ability of Fusarium pseudograminearum to efficiently detoxify the predominant wheat benzoxazolinone, 6-methoxy-benzoxazolin-2-one (MBOA), but not benzoxazoline-2-one (BOA). Furthermore, additional genes thought to be part of the FDB gene cluster, based upon transcriptional response to benzoxazolinones, are regulated by Fdb3. However, deletion mutants for these latter genes remain capable of benzoxazolinone degradation, suggesting that they are not essential for this process. Crown Copyright © 2016. Published by Elsevier Inc. All rights reserved.

  16. clusters

    Indian Academy of Sciences (India)

    2017-09-27

    Sep 27, 2017 ... Author for correspondence (zh4403701@126.com). MS received 15 ... lic clusters using density functional theory (DFT)-GGA of the DMOL3 package. ... In the process of geometric optimization, con- vergence thresholds ..... and Postgraduate Research & Practice Innovation Program of. Jiangsu Province ...

  17. clusters

    Indian Academy of Sciences (India)

    environmental as well as technical problems during fuel gas utilization. ... adsorption on some alloys of Pd, namely PdAu, PdAg ... ried out on small neutral and charged Au24,26,27, Cu,28 ... study of Zanti et al.29 on Pdn (n = 1–9) clusters.

  18. Hierarchical clustering of breast cancer methylomes revealed differentially methylated and expressed breast cancer genes.

    Directory of Open Access Journals (Sweden)

    I-Hsuan Lin

    Full Text Available Oncogenic transformation of normal cells often involves epigenetic alterations, including histone modification and DNA methylation. We conducted whole-genome bisulfite sequencing to determine the DNA methylomes of normal breast, fibroadenoma, invasive ductal carcinomas and MCF7. The emergence, disappearance, expansion and contraction of kilobase-sized hypomethylated regions (HMRs and the hypomethylation of the megabase-sized partially methylated domains (PMDs are the major forms of methylation changes observed in breast tumor samples. Hierarchical clustering of HMR revealed tumor-specific hypermethylated clusters and differential methylated enhancers specific to normal or breast cancer cell lines. Joint analysis of gene expression and DNA methylation data of normal breast and breast cancer cells identified differentially methylated and expressed genes associated with breast and/or ovarian cancers in cancer-specific HMR clusters. Furthermore, aberrant patterns of X-chromosome inactivation (XCI was found in breast cancer cell lines as well as breast tumor samples in the TCGA BRCA (breast invasive carcinoma dataset. They were characterized with differentially hypermethylated XIST promoter, reduced expression of XIST, and over-expression of hypomethylated X-linked genes. High expressions of these genes were significantly associated with lower survival rates in breast cancer patients. Comprehensive analysis of the normal and breast tumor methylomes suggests selective targeting of DNA methylation changes during breast cancer progression. The weak causal relationship between DNA methylation and gene expression observed in this study is evident of more complex role of DNA methylation in the regulation of gene expression in human epigenetics that deserves further investigation.

  19. Gene co-expression analysis identifies gene clusters associated with isotropic and polarized growth in Aspergillus fumigatus conidia.

    Science.gov (United States)

    Baltussen, Tim J H; Coolen, Jordy P M; Zoll, Jan; Verweij, Paul E; Melchers, Willem J G

    2018-04-26

    Aspergillus fumigatus is a saprophytic fungus that extensively produces conidia. These microscopic asexually reproductive structures are small enough to reach the lungs. Germination of conidia followed by hyphal growth inside human lungs is a key step in the establishment of infection in immunocompromised patients. RNA-Seq was used to analyze the transcriptome of dormant and germinating A. fumigatus conidia. Construction of a gene co-expression network revealed four gene clusters (modules) correlated with a growth phase (dormant, isotropic growth, polarized growth). Transcripts levels of genes encoding for secondary metabolites were high in dormant conidia. During isotropic growth, transcript levels of genes involved in cell wall modifications increased. Two modules encoding for growth and cell cycle/DNA processing were associated with polarized growth. In addition, the co-expression network was used to identify highly connected intermodular hub genes. These genes may have a pivotal role in the respective module and could therefore be compelling therapeutic targets. Generally, cell wall remodeling is an important process during isotropic and polarized growth, characterized by an increase of transcripts coding for hyphal growth and cell cycle/DNA processing when polarized growth is initiated. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.

  20. Functional characterization of diverse ring-hydroxylating oxygenases and induction of complex aromatic catabolic gene clusters in Sphingobium sp. PNB

    Directory of Open Access Journals (Sweden)

    Pratick Khara

    2014-01-01

    Full Text Available Sphingobium sp. PNB, like other sphingomonads, has multiple ring-hydroxylating oxygenase (RHO genes. Three different fosmid clones have been sequenced to identify the putative genes responsible for the degradation of various aromatics in this bacterial strain. Comparison of the map of the catabolic genes with that of different sphingomonads revealed a similar arrangement of gene clusters that harbors seven sets of RHO terminal components and a sole set of electron transport (ET proteins. The presence of distinctly conserved amino acid residues in ferredoxin and in silico molecular docking analyses of ferredoxin with the well characterized terminal oxygenase components indicated the structural uniqueness of the ET component in sphingomonads. The predicted substrate specificities, derived from the phylogenetic relationship of each of the RHOs, were examined based on transformation of putative substrates and their structural homologs by the recombinant strains expressing each of the oxygenases and the sole set of available ET proteins. The RHO AhdA1bA2b was functionally characterized for the first time and was found to be capable of transforming ethylbenzene, propylbenzene, cumene, p-cymene and biphenyl, in addition to a number of polycyclic aromatic hydrocarbons. Overexpression of aromatic catabolic genes in strain PNB, revealed by real-time PCR analyses, is a way forward to understand the complex regulation of degradative genes in sphingomonads.

  1. Hierarchical Bayesian modelling of gene expression time series across irregularly sampled replicates and clusters.

    Science.gov (United States)

    Hensman, James; Lawrence, Neil D; Rattray, Magnus

    2013-08-20

    Time course data from microarrays and high-throughput sequencing experiments require simple, computationally efficient and powerful statistical models to extract meaningful biological signal, and for tasks such as data fusion and clustering. Existing methodologies fail to capture either the temporal or replicated nature of the experiments, and often impose constraints on the data collection process, such as regularly spaced samples, or similar sampling schema across replications. We propose hierarchical Gaussian processes as a general model of gene expression time-series, with application to a variety of problems. In particular, we illustrate the method's capacity for missing data imputation, data fusion and clustering.The method can impute data which is missing both systematically and at random: in a hold-out test on real data, performance is significantly better than commonly used imputation methods. The method's ability to model inter- and intra-cluster variance leads to more biologically meaningful clusters. The approach removes the necessity for evenly spaced samples, an advantage illustrated on a developmental Drosophila dataset with irregular replications. The hierarchical Gaussian process model provides an excellent statistical basis for several gene-expression time-series tasks. It has only a few additional parameters over a regular GP, has negligible additional complexity, is easily implemented and can be integrated into several existing algorithms. Our experiments were implemented in python, and are available from the authors' website: http://staffwww.dcs.shef.ac.uk/people/J.Hensman/.

  2. Using SNP genetic markers to elucidate the linkage of the Co-34/Phg-3 anthracnose and angular leaf spot resistance gene cluster with the Ur-14 resistance gene

    Science.gov (United States)

    The Ouro Negro common bean cultivar contains the Co-34/Phg-3 gene cluster that confers resistance to the anthracnose (ANT) and angular leaf spot (ALS) pathogens. These genes are tightly linked on chromosome 4. Ouro Negro also has the Ur-14 rust resistance gene, reportedly in the vicinity of Co- 34; ...

  3. High GC Content Cas9-Mediated Genome-Editing and Biosynthetic Gene Cluster Activation in Saccharopolyspora erythraea.

    Science.gov (United States)

    Liu, Yong; Wei, Wen-Ping; Ye, Bang-Ce

    2018-05-18

    The overexpression of bacterial secondary metabolite biosynthetic enzymes is the basis for industrial overproducing strains. Genome editing tools can be used to further improve gene expression and yield. Saccharopolyspora erythraea produces erythromycin, which has extensive clinical applications. In this study, the CRISPR-Cas9 system was used to edit genes in the S. erythraea genome. A temperature-sensitive plasmid containing the PermE promoter, to drive Cas9 expression, and the Pj23119 and PkasO promoters, to drive sgRNAs, was designed. Erythromycin esterase, encoded by S. erythraea SACE_1765, inactivates erythromycin by hydrolyzing the macrolactone ring. Sequencing and qRT-PCR confirmed that reporter genes were successfully inserted into the SACE_1765 gene. Deletion of SACE_1765 in a high-producing strain resulted in a 12.7% increase in erythromycin levels. Subsequent PermE- egfp knock-in at the SACE_0712 locus resulted in an 80.3% increase in erythromycin production compared with that of wild type. Further investigation showed that PermE promoter knock-in activated the erythromycin biosynthetic gene clusters at the SACE_0712 locus. Additionally, deletion of indA (SACE_1229) using dual sgRNA targeting without markers increased the editing efficiency to 65%. In summary, we have successfully applied Cas9-based genome editing to a bacterial strain, S. erythraea, with a high GC content. This system has potential application for both genome-editing and biosynthetic gene cluster activation in Actinobacteria.

  4. Nonuniform Sparse Data Clustering Cascade Algorithm Based on Dynamic Cumulative Entropy

    Directory of Open Access Journals (Sweden)

    Ning Li

    2016-01-01

    Full Text Available A small amount of prior knowledge and randomly chosen initial cluster centers have a direct impact on the accuracy of the performance of iterative clustering algorithm. In this paper we propose a new algorithm to compute initial cluster centers for k-means clustering and the best number of the clusters with little prior knowledge and optimize clustering result. It constructs the Euclidean distance control factor based on aggregation density sparse degree to select the initial cluster center of nonuniform sparse data and obtains initial data clusters by multidimensional diffusion density distribution. Multiobjective clustering approach based on dynamic cumulative entropy is adopted to optimize the initial data clusters and the best number of the clusters. The experimental results show that the newly proposed algorithm has good performance to obtain the initial cluster centers for the k-means algorithm and it effectively improves the clustering accuracy of nonuniform sparse data by about 5%.

  5. Parallel Density-Based Clustering for Discovery of Ionospheric Phenomena

    Science.gov (United States)

    Pankratius, V.; Gowanlock, M.; Blair, D. M.

    2015-12-01

    Ionospheric total electron content maps derived from global networks of dual-frequency GPS receivers can reveal a plethora of ionospheric features in real-time and are key to space weather studies and natural hazard monitoring. However, growing data volumes from expanding sensor networks are making manual exploratory studies challenging. As the community is heading towards Big Data ionospheric science, automation and Computer-Aided Discovery become indispensable tools for scientists. One problem of machine learning methods is that they require domain-specific adaptations in order to be effective and useful for scientists. Addressing this problem, our Computer-Aided Discovery approach allows scientists to express various physical models as well as perturbation ranges for parameters. The search space is explored through an automated system and parallel processing of batched workloads, which finds corresponding matches and similarities in empirical data. We discuss density-based clustering as a particular method we employ in this process. Specifically, we adapt Density-Based Spatial Clustering of Applications with Noise (DBSCAN). This algorithm groups geospatial data points based on density. Clusters of points can be of arbitrary shape, and the number of clusters is not predetermined by the algorithm; only two input parameters need to be specified: (1) a distance threshold, (2) a minimum number of points within that threshold. We discuss an implementation of DBSCAN for batched workloads that is amenable to parallelization on manycore architectures such as Intel's Xeon Phi accelerator with 60+ general-purpose cores. This manycore parallelization can cluster large volumes of ionospheric total electronic content data quickly. Potential applications for cluster detection include the visualization, tracing, and examination of traveling ionospheric disturbances or other propagating phenomena. Acknowledgments. We acknowledge support from NSF ACI-1442997 (PI V. Pankratius).

  6. [Gene deletion and functional analysis of the heptyl glycosyltransferase (waaF) gene in Vibrio parahemolyticus O-antigen cluster].

    Science.gov (United States)

    Zhao, Feng; Meng, Songsong; Zhou, Deqing

    2016-02-04

    To construct heptyl glycosyltransferase gene II (waaF) gene deletion mutant of Vibrio parahaemolyticus, and explore the function of the waaF gene in Vibrio parahaemolyticus. The waaF gene deletion mutant was constructed by chitin-based transformation technology using clinical isolates, and then the growth rate, morphology and serotypes were identified. The different sources (O3, O5 and O10) waaF gene complementations were constructed through E. coli S17λpir strains conjugative transferring with Vibrio parahaemolyticus, and the function of the waaF gene was further verified by serotypes. The waaF gene deletion mutant strain was successfully constructed and it grew normally. The growth rate and morphology of mutant were similar with the wild type strains (WT), but the mutant could not occurred agglutination reaction with O antisera. The O3 and O5 sources waaF gene complementations occurred agglutination reaction with O antisera, but the O10 sources waaF gene complementations was not. The waaF gene was related with O-antigen synthesis and it was the key gene of O-antigen synthesis pathway in Vibrio parahaemolyticus. The function of different sources waaF gene were not the same.

  7. Comparison of expression of secondary metabolite biosynthesis cluster genes in Aspergillus flavus, A. parasiticus, and A. oryzae.

    Science.gov (United States)

    Ehrlich, Kenneth C; Mack, Brian M

    2014-06-23

    Fifty six secondary metabolite biosynthesis gene clusters are predicted to be in the Aspergillus flavus genome. In spite of this, the biosyntheses of only seven metabolites, including the aflatoxins, kojic acid, cyclopiazonic acid and aflatrem, have been assigned to a particular gene cluster. We used RNA-seq to compare expression of secondary metabolite genes in gene clusters for the closely related fungi A. parasiticus, A. oryzae, and A. flavus S and L sclerotial morphotypes. The data help to refine the identification of probable functional gene clusters within these species. Our results suggest that A. flavus, a prevalent contaminant of maize, cottonseed, peanuts and tree nuts, is capable of producing metabolites which, besides aflatoxin, could be an underappreciated contributor to its toxicity.

  8. Mycobiota and identification of aflatoxin gene cluster in marketed spices in West Africa

    DEFF Research Database (Denmark)

    Gnonlonfin, G. J. B.; Adjovi, Y. C.; Tokpo, A. F.

    2013-01-01

    Fungal infection and aflatoxin contamination were evaluated on 114 samples of dried and milled spices such as ginger, garlic and black pepper from southern Benin and Togo collected in November 2008 -January 2009. These products are dried to preserve them for lean periods available throughout...... of Aspergillus were dominant on all marketed dried and milled spices irrespective of country. Gene characterization and amplification analysis showed that most of the Aspergillus flavus isolates possess the cluster genes for aflatoxin production. Aflatoxin B1 assessment by Thin Layer Chromatography showed...... further for other products such as dried and milled spices. Crown Copyright (C) 2013 Published by Elsevier Ltd. All rights reserved....

  9. Gene Clusters for Insecticidal Loline Alkaloids in the Grass-Endophytic Fungus Neotyphodium uncinatum

    OpenAIRE

    Spiering, Martin J.; Moon, Christina D.; Wilkinson, Heather H.; Schardl, Christopher L.

    2005-01-01

    Loline alkaloids are produced by mutualistic fungi symbiotic with grasses, and they protect the host plants from insects. Here we identify in the fungal symbiont, Neotyphodium uncinatum, two homologous gene clusters (LOL-1 and LOL-2) associated with loline-alkaloid production. Nine genes were identified in a 25-kb region of LOL-1 and designated (in order) lolF-1, lolC-1, lolD-1, lolO-1, lolA-1, lolU-1, lolP-1, lolT-1, and lolE-1. LOL-2 contained the homologs lolC-2 through lolE-2 in the same ...

  10. Crowd Analysis by Using Optical Flow and Density Based Clustering

    DEFF Research Database (Denmark)

    Santoro, Francesco; Pedro, Sergio; Tan, Zheng-Hua

    2010-01-01

    In this paper, we present a system to detect and track crowds in a video sequence captured by a camera. In a first step, we compute optical flows by means of pyramidal Lucas-Kanade feature tracking. Afterwards, a density based clustering is used to group similar vectors. In the last step...

  11. Functional dissection of HOXD cluster genes in regulation of neuroblastoma cell proliferation and differentiation.

    Directory of Open Access Journals (Sweden)

    Yunhong Zha

    Full Text Available Retinoic acid (RA can induce growth arrest and neuronal differentiation of neuroblastoma cells and has been used in clinic for treatment of neuroblastoma. It has been reported that RA induces the expression of several HOXD genes in human neuroblastoma cell lines, but their roles in RA action are largely unknown. The HOXD cluster contains nine genes (HOXD1, HOXD3, HOXD4, and HOXD8-13 that are positioned sequentially from 3' to 5', with HOXD1 at the 3' end and HOXD13 the 5' end. Here we show that all HOXD genes are induced by RA in the human neuroblastoma BE(2-C cells, with the genes located at the 3' end being activated generally earlier than those positioned more 5' within the cluster. Individual induction of HOXD8, HOXD9, HOXD10 or HOXD12 is sufficient to induce both growth arrest and neuronal differentiation, which is associated with downregulation of cell cycle-promoting genes and upregulation of neuronal differentiation genes. However, induction of other HOXD genes either has no effect (HOXD1 or has partial effects (HOXD3, HOXD4, HOXD11 and HOXD13 on BE(2-C cell proliferation or differentiation. We further show that knockdown of HOXD8 expression, but not that of HOXD9 expression, significantly inhibits the differentiation-inducing activity of RA. HOXD8 directly activates the transcription of HOXC9, a key effector of RA action in neuroblastoma cells. These findings highlight the distinct functions of HOXD genes in RA induction of neuroblastoma cell differentiation.

  12. Burkholderia thailandensis harbors two identical rhl gene clusters responsible for the biosynthesis of rhamnolipids

    Directory of Open Access Journals (Sweden)

    Woods Donald E

    2009-12-01

    Full Text Available Abstract Background Rhamnolipids are surface active molecules composed of rhamnose and β-hydroxydecanoic acid. These biosurfactants are produced mainly by Pseudomonas aeruginosa and have been thoroughly investigated since their early discovery. Recently, they have attracted renewed attention because of their involvement in various multicellular behaviors. Despite this high interest, only very few studies have focused on the production of rhamnolipids by Burkholderia species. Results Orthologs of rhlA, rhlB and rhlC, which are responsible for the biosynthesis of rhamnolipids in P. aeruginosa, have been found in the non-infectious Burkholderia thailandensis, as well as in the genetically similar important pathogen B. pseudomallei. In contrast to P. aeruginosa, both Burkholderia species contain these three genes necessary for rhamnolipid production within a single gene cluster. Furthermore, two identical, paralogous copies of this gene cluster are found on the second chromosome of these bacteria. Both Burkholderia spp. produce rhamnolipids containing 3-hydroxy fatty acid moieties with longer side chains than those described for P. aeruginosa. Additionally, the rhamnolipids produced by B. thailandensis contain a much larger proportion of dirhamnolipids versus monorhamnolipids when compared to P. aeruginosa. The rhamnolipids produced by B. thailandensis reduce the surface tension of water to 42 mN/m while displaying a critical micelle concentration value of 225 mg/L. Separate mutations in both rhlA alleles, which are responsible for the synthesis of the rhamnolipid precursor 3-(3-hydroxyalkanoyloxyalkanoic acid, prove that both copies of the rhl gene cluster are functional, but one contributes more to the total production than the other. Finally, a double ΔrhlA mutant that is completely devoid of rhamnolipid production is incapable of swarming motility, showing that both gene clusters contribute to this phenotype. Conclusions Collectively, these

  13. Core Business Selection Based on Ant Colony Clustering Algorithm

    Directory of Open Access Journals (Sweden)

    Yu Lan

    2014-01-01

    Full Text Available Core business is the most important business to the enterprise in diversified business. In this paper, we first introduce the definition and characteristics of the core business and then descript the ant colony clustering algorithm. In order to test the effectiveness of the proposed method, Tianjin Port Logistics Development Co., Ltd. is selected as the research object. Based on the current situation of the development of the company, the core business of the company can be acquired by ant colony clustering algorithm. Thus, the results indicate that the proposed method is an effective way to determine the core business for company.

  14. A Cluster Based Group Signature Mechanism For Secure Vanet Communication

    Directory of Open Access Journals (Sweden)

    Navjot Kaur

    2015-08-01

    Full Text Available Vehicular adhoc network is one of the recent area of research to administer safety to human lives controlling of messages and in disposal of messages to users and passengers. VANETs allows communication of moving vehicular nodes. Movement of nodes leads in changing network size and scenario. Whenever a new node joins the network there is a threat of malicious node attack. So we need an environment that is secure and trust worthy. Therefore a new cluster based secure technique is proposed where cluster head is responsible for providing communication between the vehicular nodes. Performance parameters used in this paper are message drop ratio packet delay ratio and verification time.

  15. Price Formation Based on Particle-Cluster Aggregation

    Science.gov (United States)

    Wang, Shijun; Zhang, Changshui

    In the present work, we propose a microscopic model of financial markets based on particle-cluster aggregation on a two-dimensional small-world information network in order to simulate the dynamics of the stock markets. "Stylized facts" of the financial market time series, such as fat-tail distribution of returns, volatility clustering and multifractality, are observed in the model. The results of the model agree with empirical data taken from historical records of the daily closures of the NYSE composite index.

  16. Structure and gene cluster of the O-antigen of Escherichia coli O54.

    Science.gov (United States)

    Naumenko, Olesya I; Guo, Xi; Senchenkova, Sof'ya N; Geng, Peng; Perepelov, Andrei V; Shashkov, Alexander S; Liu, Bin; Knirel, Yuriy A

    2018-06-15

    Mild acid hydrolysis of the lipopolysaccharide of Escherichia coli O54 afforded an O-polysaccharide, which was studied by sugar analysis, solvolysis with anhydrous trifluoroacetic acid, and 1 H and 13 C NMR spectroscopy. Solvolysis cleaved predominantly the linkage of β-d-Ribf and, to a lesser extent, that of β-d-GlcpNAc, whereas the other linkages, including the linkage of α-l-Rhap, were stable under selected conditions (40 °C, 5 h). The following structure of the O-polysaccharide was established: →4)-α-d-GalpA-(1 → 2)-α-l-Rhap-(1 → 2)-β-d-Ribf-(1 → 4)-β-d-Galp-(1 → 3)-β-d-GlcpNAc-(1→ The O-antigen gene cluster of E. coli O54 was analyzed and found to be consistent in general with the O-polysaccharide structure established but there were two exceptions: i) in the cluster, there were genes for phosphoserine phosphatase and serine transferase, which have no apparent role in the O-polysaccharide synthesis, and ii) no ribofuranosyltransferase gene was present in the cluster. Both uncommon features are shared by some other enteric bacteria. Copyright © 2018 Elsevier Ltd. All rights reserved.

  17. GENERALISED MODEL BASED CONFIDENCE INTERVALS IN TWO STAGE CLUSTER SAMPLING

    Directory of Open Access Journals (Sweden)

    Christopher Ouma Onyango

    2010-09-01

    Full Text Available Chambers and Dorfman (2002 constructed bootstrap confidence intervals in model based estimation for finite population totals assuming that auxiliary values are available throughout a target population and that the auxiliary values are independent. They also assumed that the cluster sizes are known throughout the target population. We now extend to two stage sampling in which the cluster sizes are known only for the sampled clusters, and we therefore predict the unobserved part of the population total. Jan and Elinor (2008 have done similar work, but unlike them, we use a general model, in which the auxiliary values are not necessarily independent. We demonstrate that the asymptotic properties of our proposed estimator and its coverage rates are better than those constructed under the model assisted local polynomial regression model.

  18. Improving cluster-based missing value estimation of DNA microarray data.

    Science.gov (United States)

    Brás, Lígia P; Menezes, José C

    2007-06-01

    We present a modification of the weighted K-nearest neighbours imputation method (KNNimpute) for missing values (MVs) estimation in microarray data based on the reuse of estimated data. The method was called iterative KNN imputation (IKNNimpute) as the estimation is performed iteratively using the recently estimated values. The estimation efficiency of IKNNimpute was assessed under different conditions (data type, fraction and structure of missing data) by the normalized root mean squared error (NRMSE) and the correlation coefficients between estimated and true values, and compared with that of other cluster-based estimation methods (KNNimpute and sequential KNN). We further investigated the influence of imputation on the detection of differentially expressed genes using SAM by examining the differentially expressed genes that are lost after MV estimation. The performance measures give consistent results, indicating that the iterative procedure of IKNNimpute can enhance the prediction ability of cluster-based methods in the presence of high missing rates, in non-time series experiments and in data sets comprising both time series and non-time series data, because the information of the genes having MVs is used more efficiently and the iterative procedure allows refining the MV estimates. More importantly, IKNN has a smaller detrimental effect on the detection of differentially expressed genes.

  19. AES based secure low energy adaptive clustering hierarchy for WSNs

    Science.gov (United States)

    Kishore, K. R.; Sarma, N. V. S. N.

    2013-01-01

    Wireless sensor networks (WSNs) provide a low cost solution in diversified application areas. The wireless sensor nodes are inexpensive tiny devices with limited storage, computational capability and power. They are being deployed in large scale in both military and civilian applications. Security of the data is one of the key concerns where large numbers of nodes are deployed. Here, an energy-efficient secure routing protocol, secure-LEACH (Low Energy Adaptive Clustering Hierarchy) for WSNs based on the Advanced Encryption Standard (AES) is being proposed. This crypto system is a session based one and a new session key is assigned for each new session. The network (WSN) is divided into number of groups or clusters and a cluster head (CH) is selected among the member nodes of each cluster. The measured data from the nodes is aggregated by the respective CH's and then each CH relays this data to another CH towards the gateway node in the WSN which in turn sends the same to the Base station (BS). In order to maintain confidentiality of data while being transmitted, it is necessary to encrypt the data before sending at every hop, from a node to the CH and from the CH to another CH or to the gateway node.

  20. Association of paraoxonase gene cluster polymorphisms with ALS in France, Quebec, and Sweden.

    Science.gov (United States)

    Valdmanis, P N; Kabashi, E; Dyck, A; Hince, P; Lee, J; Dion, P; D'Amour, M; Souchon, F; Bouchard, J-P; Salachas, F; Meininger, V; Andersen, P M; Camu, W; Dupré, N; Rouleau, G A

    2008-08-12

    The paraoxonase gene cluster on chromosome 7 comprising the PON1-3 genes is an attractive candidate for association in amyotrophic lateral sclerosis (ALS) given the role of paraoxonase genes during the response to oxidative stress and their contribution to the enzymatic break down of nerve toxins. Oxidative stress is considered one of the mechanisms involved in ALS pathogenesis. Evidence for this includes the fact that mutations of SOD1, which normally reduce the production of toxic superoxide anion, account for 12% to 23% of familial cases in ALS. In addition, PON variants were shown to be associated with susceptibility to ALS in several North American and European populations. We extended this analysis to examine 20 single nucleotide polymorphisms (SNPs) across the PON gene cluster in a set of patients from France (480 cases, 475 controls), Quebec (159 cases, 95 controls), and Sweden (558 cases, 506 controls). Although individual SNPs were not considered associated on their own, a haplotype of SNPs at the C-terminal portion of PON2 that includes the PON2 C311S amino acid change was significant in the French (p value 0.0075) and Quebec (p value 0.026) populations as well as all three populations combined (p value 1.69 x 10(-6)). Stratification of the samples showed that this variation was pertinent to ALS susceptibility as a whole, and not to a particular subset of patients. These findings contribute to the increasing weight of evidence that genetic variants in the paraoxonase gene cluster are associated with amyotrophic lateral sclerosis.

  1. Functional Genome Mining for Metabolites Encoded by Large Gene Clusters through Heterologous Expression of a Whole-Genome Bacterial Artificial Chromosome Library in Streptomyces spp.

    Science.gov (United States)

    Xu, Min; Wang, Yemin; Zhao, Zhilong; Gao, Guixi; Huang, Sheng-Xiong; Kang, Qianjin; He, Xinyi; Lin, Shuangjun; Pang, Xiuhua; Deng, Zixin

    2016-01-01

    ABSTRACT Genome sequencing projects in the last decade revealed numerous cryptic biosynthetic pathways for unknown secondary metabolites in microbes, revitalizing drug discovery from microbial metabolites by approaches called genome mining. In this work, we developed a heterologous expression and functional screening approach for genome mining from genomic bacterial artificial chromosome (BAC) libraries in Streptomyces spp. We demonstrate mining from a strain of Streptomyces rochei, which is known to produce streptothricins and borrelidin, by expressing its BAC library in the surrogate host Streptomyces lividans SBT5, and screening for antimicrobial activity. In addition to the successful capture of the streptothricin and borrelidin biosynthetic gene clusters, we discovered two novel linear lipopeptides and their corresponding biosynthetic gene cluster, as well as a novel cryptic gene cluster for an unknown antibiotic from S. rochei. This high-throughput functional genome mining approach can be easily applied to other streptomycetes, and it is very suitable for the large-scale screening of genomic BAC libraries for bioactive natural products and the corresponding biosynthetic pathways. IMPORTANCE Microbial genomes encode numerous cryptic biosynthetic gene clusters for unknown small metabolites with potential biological activities. Several genome mining approaches have been developed to activate and bring these cryptic metabolites to biological tests for future drug discovery. Previous sequence-guided procedures relied on bioinformatic analysis to predict potentially interesting biosynthetic gene clusters. In this study, we describe an efficient approach based on heterologous expression and functional screening of a whole-genome library for the mining of bioactive metabolites from Streptomyces. The usefulness of this function-driven approach was demonstrated by the capture of four large biosynthetic gene clusters for metabolites of various chemical types, including

  2. 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.

  3. Updated clusters of orthologous genes for Archaea: a complex ancestor of the Archaea and the byways of horizontal gene transfer

    Directory of Open Access Journals (Sweden)

    Wolf Yuri I

    2012-12-01

    Full Text Available Abstract Background Collections of Clusters of Orthologous Genes (COGs provide indispensable tools for comparative genomic analysis, evolutionary reconstruction and functional annotation of new genomes. Initially, COGs were made for all complete genomes of cellular life forms that were available at the time. However, with the accumulation of thousands of complete genomes, construction of a comprehensive COG set has become extremely computationally demanding and prone to error propagation, necessitating the switch to taxon-specific COG collections. Previously, we reported the collection of COGs for 41 genomes of Archaea (arCOGs. Here we present a major update of the arCOGs and describe evolutionary reconstructions to reveal general trends in the evolution of Archaea. Results The updated version of the arCOG database incorporates 91% of the pangenome of 120 archaea (251,032 protein-coding genes altogether into 10,335 arCOGs. Using this new set of arCOGs, we performed maximum likelihood reconstruction of the genome content of archaeal ancestral forms and gene gain and loss events in archaeal evolution. This reconstruction shows that the last Common Ancestor of the extant Archaea was an organism of greater complexity than most of the extant archaea, probably with over 2,500 protein-coding genes. The subsequent evolution of almost all archaeal lineages was apparently dominated by gene loss resulting in genome streamlining. Overall, in the evolution of Archaea as well as a representative set of bacteria that was similarly analyzed for comparison, gene losses are estimated to outnumber gene gains at least 4 to 1. Analysis of specific patterns of gene gain in Archaea shows that, although some groups, in particular Halobacteria, acquire substantially more genes than others, on the whole, gene exchange between major groups of Archaea appears to be largely random, with no major ‘highways’ of horizontal gene transfer. Conclusions The updated collection

  4. Gene expression patterns of oxidative phosphorylation complex I subunits are organized in clusters.

    Directory of Open Access Journals (Sweden)

    Yael Garbian

    Full Text Available After the radiation of eukaryotes, the NUO operon, controlling the transcription of the NADH dehydrogenase complex of the oxidative phosphorylation system (OXPHOS complex I, was broken down and genes encoding this protein complex were dispersed across the nuclear genome. Seven genes, however, were retained in the genome of the mitochondrion, the ancient symbiote of eukaryotes. This division, in combination with the three-fold increase in subunit number from bacteria (N = approximately 14 to man (N = 45, renders the transcription regulation of OXPHOS complex I a challenge. Recently bioinformatics analysis of the promoter regions of all OXPHOS genes in mammals supported patterns of co-regulation, suggesting that natural selection favored a mechanism facilitating the transcriptional regulatory control of genes encoding subunits of these large protein complexes. Here, using real time PCR of mitochondrial (mtDNA- and nuclear DNA (nDNA-encoded transcripts in a panel of 13 different human tissues, we show that the expression pattern of OXPHOS complex I genes is regulated in several clusters. Firstly, all mtDNA-encoded complex I subunits (N = 7 share a similar expression pattern, distinct from all tested nDNA-encoded subunits (N = 10. Secondly, two sub-clusters of nDNA-encoded transcripts with significantly different expression patterns were observed. Thirdly, the expression patterns of two nDNA-encoded genes, NDUFA4 and NDUFA5, notably diverged from the rest of the nDNA-encoded subunits, suggesting a certain degree of tissue specificity. Finally, the expression pattern of the mtDNA-encoded ND4L gene diverged from the rest of the tested mtDNA-encoded transcripts that are regulated by the same promoter, consistent with post-transcriptional regulation. These findings suggest, for the first time, that the regulation of complex I subunits expression in humans is complex rather than reflecting global co-regulation.

  5. Identification and functional analysis of gene cluster involvement in biosynthesis of the cyclic lipopeptide antibiotic pelgipeptin produced by Paenibacillus elgii

    Directory of Open Access Journals (Sweden)

    Qian Chao-Dong

    2012-09-01

    Full Text Available Abstract Background Pelgipeptin, a potent antibacterial and antifungal agent, is a non-ribosomally synthesised lipopeptide antibiotic. This compound consists of a β-hydroxy fatty acid and nine amino acids. To date, there is no information about its biosynthetic pathway. Results A potential pelgipeptin synthetase gene cluster (plp was identified from Paenibacillus elgii B69 through genome analysis. The gene cluster spans 40.8 kb with eight open reading frames. Among the genes in this cluster, three large genes, plpD, plpE, and plpF, were shown to encode non-ribosomal peptide synthetases (NRPSs, with one, seven, and one module(s, respectively. Bioinformatic analysis of the substrate specificity of all nine adenylation domains indicated that the sequence of the NRPS modules is well collinear with the order of amino acids in pelgipeptin. Additional biochemical analysis of four recombinant adenylation domains (PlpD A1, PlpE A1, PlpE A3, and PlpF A1 provided further evidence that the plp gene cluster involved in pelgipeptin biosynthesis. Conclusions In this study, a gene cluster (plp responsible for the biosynthesis of pelgipeptin was identified from the genome sequence of Paenibacillus elgii B69. The identification of the plp gene cluster provides an opportunity to develop novel lipopeptide antibiotics by genetic engineering.

  6. A similarity based agglomerative clustering algorithm in networks

    Science.gov (United States)

    Liu, Zhiyuan; Wang, Xiujuan; Ma, Yinghong

    2018-04-01

    The detection of clusters is benefit for understanding the organizations and functions of networks. Clusters, or communities, are usually groups of nodes densely interconnected but sparsely linked with any other clusters. To identify communities, an efficient and effective community agglomerative algorithm based on node similarity is proposed. The proposed method initially calculates similarities between each pair of nodes, and form pre-partitions according to the principle that each node is in the same community as its most similar neighbor. After that, check each partition whether it satisfies community criterion. For the pre-partitions who do not satisfy, incorporate them with others that having the biggest attraction until there are no changes. To measure the attraction ability of a partition, we propose an attraction index that based on the linked node's importance in networks. Therefore, our proposed method can better exploit the nodes' properties and network's structure. To test the performance of our algorithm, both synthetic and empirical networks ranging in different scales are tested. Simulation results show that the proposed algorithm can obtain superior clustering results compared with six other widely used community detection algorithms.

  7. Unsupervised active learning based on hierarchical graph-theoretic clustering.

    Science.gov (United States)

    Hu, Weiming; Hu, Wei; Xie, Nianhua; Maybank, Steve

    2009-10-01

    Most existing active learning approaches are supervised. Supervised active learning has the following problems: inefficiency in dealing with the semantic gap between the distribution of samples in the feature space and their labels, lack of ability in selecting new samples that belong to new categories that have not yet appeared in the training samples, and lack of adaptability to changes in the semantic interpretation of sample categories. To tackle these problems, we propose an unsupervised active learning framework based on hierarchical graph-theoretic clustering. In the framework, two promising graph-theoretic clustering algorithms, namely, dominant-set clustering and spectral clustering, are combined in a hierarchical fashion. Our framework has some advantages, such as ease of implementation, flexibility in architecture, and adaptability to changes in the labeling. Evaluations on data sets for network intrusion detection, image classification, and video classification have demonstrated that our active learning framework can effectively reduce the workload of manual classification while maintaining a high accuracy of automatic classification. It is shown that, overall, our framework outperforms the support-vector-machine-based supervised active learning, particularly in terms of dealing much more efficiently with new samples whose categories have not yet appeared in the training samples.

  8. Gene clusters for insecticidal loline alkaloids in the grass-endophytic fungus Neotyphodium uncinatum.

    Science.gov (United States)

    Spiering, Martin J; Moon, Christina D; Wilkinson, Heather H; Schardl, Christopher L

    2005-03-01

    Loline alkaloids are produced by mutualistic fungi symbiotic with grasses, and they protect the host plants from insects. Here we identify in the fungal symbiont, Neotyphodium uncinatum, two homologous gene clusters (LOL-1 and LOL-2) associated with loline-alkaloid production. Nine genes were identified in a 25-kb region of LOL-1 and designated (in order) lolF-1, lolC-1, lolD-1, lolO-1, lolA-1, lolU-1, lolP-1, lolT-1, and lolE-1. LOL-2 contained the homologs lolC-2 through lolE-2 in the same order and orientation. Also identified was lolF-2, but its possible linkage with either cluster was undetermined. Most lol genes were regulated in N. uncinatum and N. coenophialum, and all were expressed concomitantly with loline-alkaloid biosynthesis. A lolC-2 RNA-interference (RNAi) construct was introduced into N. uncinatum, and in two independent transformants, RNAi significantly decreased lolC expression (P lol-gene products indicate that the pathway has evolved from various different primary and secondary biosynthesis pathways.

  9. Difference-based clustering of short time-course microarray data with replicates

    Directory of Open Access Journals (Sweden)

    Kim Jihoon

    2007-07-01

    Full Text Available Abstract Background There are some limitations associated with conventional clustering methods for short time-course gene expression data. The current algorithms require prior domain knowledge and do not incorporate information from replicates. Moreover, the results are not always easy to interpret biologically. Results We propose a novel algorithm for identifying a subset of genes sharing a significant temporal expression pattern when replicates are used. Our algorithm requires no prior knowledge, instead relying on an observed statistic which is based on the first and second order differences between adjacent time-points. Here, a pattern is predefined as the sequence of symbols indicating direction and the rate of change between time-points, and each gene is assigned to a cluster whose members share a similar pattern. We evaluated the performance of our algorithm to those of K-means, Self-Organizing Map and the Short Time-series Expression Miner methods. Conclusions Assessments using simulated and real data show that our method outperformed aforementioned algorithms. Our approach is an appropriate solution for clustering short time-course microarray data with replicates.

  10. Interleukin‑1 gene cluster variants in hemodialysis patients with end stage renal disease: An association and meta‑analysis

    Directory of Open Access Journals (Sweden)

    G Tripathi

    2015-01-01

    Full Text Available We evaluated whether polymorphisms in interleukin (IL-1 gene cluster (IL-1 alpha [IL-1A], IL-1 beta [IL-1B], and IL-1 receptor antagonist [IL-1RN] are associated with end stage renal disease (ESRD. A total of 258 ESRD patients and 569 ethnicity matched controls were examined for IL-1 gene cluster. These were genotyped for five single-nucleotide gene polymorphisms in the IL-1A, IL-1B and IL-1RN genes and a variable number of tandem repeats (VNTR in the IL-1RN. The IL-1B − 3953 and IL-1RN + 8006 polymorphism frequencies were significantly different between the two groups. At IL-1B, the T allele of − 3953C/T was increased among ESRD (P = 0.0001. A logistic regression model demonstrated that two repeat (240 base pair [bp] of the IL-1Ra VNTR polymorphism was associated with ESRD (P = 0.0001. The C/C/C/C/C/1 haplotype was more prevalent in ESRD = 0.007. No linkage disequilibrium (LD was observed between six loci of IL-1 gene. We further conducted a meta-analysis of existing studies and found that there is a strong association of IL-1 RN VNTR 86 bp repeat polymorphism with susceptibility to ESRD (odds ratio = 2.04, 95% confidence interval = 1.48-2.82; P = 0.000. IL-1B − 5887, +8006 and the IL-1RN VNTR polymorphisms have been implicated as potential risk factors for ESRD. The meta-analysis showed a strong association of IL-1RN 86 bp VNTR polymorphism with susceptibility to ESRD.

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

    Directory of Open Access Journals (Sweden)

    Sakellariou Argiris

    2012-10-01

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

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

    DEFF Research Database (Denmark)

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

    2017-01-01

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

  13. The Cremeomycin Biosynthetic Gene Cluster Encodes a Pathway for Diazo Formation.

    Science.gov (United States)

    Waldman, Abraham J; Pechersky, Yakov; Wang, Peng; Wang, Jennifer X; Balskus, Emily P

    2015-10-12

    Diazo groups are found in a range of natural products that possess potent biological activities. Despite longstanding interest in these metabolites, diazo group biosynthesis is not well understood, in part because of difficulties in identifying specific genes linked to diazo formation. Here we describe the discovery of the gene cluster that produces the o-diazoquinone natural product cremeomycin and its heterologous expression in Streptomyces lividans. We used stable isotope feeding experiments and in vitro characterization of biosynthetic enzymes to decipher the order of events in this pathway and establish that diazo construction involves late-stage N-N bond formation. This work represents the first successful production of a diazo-containing metabolite in a heterologous host, experimentally linking a set of genes with diazo formation. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  14. Association of Interleukin-1 gene clusters polymorphisms with primary open-angle glaucoma: a meta-analysis.

    Science.gov (United States)

    Li, Junhua; Feng, Yifan; Sung, Mi Sun; Lee, Tae Hee; Park, Sang Woo

    2017-11-28

    Previous studies have associated the Interleukin-1 (IL-1) gene clusters polymorphisms with the risk of primary open-angle glaucoma (POAG). However, the results were not consistent. Here, we performed a meta-analysis to evaluate the role of IL-1 gene clusters polymorphisms in POAG susceptibility. PubMed, EMBASE and Cochrane Library (up to July 15, 2017) were searched by two independent investigators. All case-control studies investigating the association between single-nucleotide polymorphisms (SNPs) of IL-1 gene clusters and POAG risk were included. Odds ratios (ORs) with 95% confidence intervals (CIs) were calculated for quantifying the strength of association that has been involved in at least two studies. Five studies on IL-1β rs16944 (c. -511C > T) (1053 cases and 986 controls), 4 studies on IL-1α rs1800587 (c. -889C > T) (822 cases and 714 controls), and 4 studies on IL-1β rs1143634 (c. +3953C > T) (798 cases and 730 controls) were included. The results suggest that all three SNPs were not associated with POAG risk. Stratification analyses indicated that the rs1143634 has a suggestive associated with high tension glaucoma (HTG) under dominant (P = 0.03), heterozygote (P = 0.04) and allelic models (P = 0.02), however, the weak association was nullified after Bonferroni adjustments for multiple tests. Based on current meta-analysis, we indicated that there is lack of association between the three SNPs of IL-1 and POAG. However, this conclusion should be interpreted with caution and further well designed studies with large sample-size are required to validate the conclusion as low statistical powers.

  15. Comparison of loline alkaloid gene clusters across fungal endophytes: predicting the co-regulatory sequence motifs and the evolutionary history.

    Science.gov (United States)

    Kutil, Brandi L; Greenwald, Charles; Liu, Gang; Spiering, Martin J; Schardl, Christopher L; Wilkinson, Heather H

    2007-10-01

    LOL, a fungal secondary metabolite gene cluster found in Epichloë and Neotyphodium species, is responsible for production of insecticidal loline alkaloids. To analyze the genetic architecture and to predict the evolutionary history of LOL, we compared five clusters from four fungal species (single clusters from Epichloë festucae, Neotyphodium sp. PauTG-1, Neotyphodium coenophialum, and two clusters we previously characterized in Neotyphodium uncinatum). Using PhyloCon to compare putative lol gene promoter regions, we have identified four motifs conserved across the lol genes in all five clusters. Each motif has significant similarity to known fungal transcription factor binding sites in the TRANSFAC database. Conservation of these motifs is further support for the hypothesis that the lol genes are co-regulated. Interestingly, the history of asexual Neotyphodium spp. includes multiple interspecific hybridization events. Comparing clusters from three Neotyphodium species and E. festucae allowed us to determine which Epichloë ancestors are the most likely contributors of LOL in these asexual species. For example, while no present day Epichloë typhina isolates are known to produce lolines, our data support the hypothesis that the E. typhina ancestor(s) of three asexual endophyte species contained a LOL gene cluster. Thus, these data support a model of evolution in which the polymorphism in loline alkaloid production phenotypes among endophyte species is likely due to the loss of the trait over time.

  16. Transcriptional organization of the DNA region controlling expression of the K99 gene cluster.

    Science.gov (United States)

    Roosendaal, B; Damoiseaux, J; Jordi, W; de Graaf, F K

    1989-01-01

    The transcriptional organization of the K99 gene cluster was investigated in two ways. First, the DNA region, containing the transcriptional signals was analyzed using a transcription vector system with Escherichia coli galactokinase (GalK) as assayable marker and second, an in vitro transcription system was employed. A detailed analysis of the transcription signals revealed that a strong promoter PA and a moderate promoter PB are located upstream of fanA and fanB, respectively. No promoter activity was detected in the intercistronic region between fanB and fanC. Factor-dependent terminators of transcription were detected and are probably located in the intercistronic region between fanA and fanB (T1), and between fanB and fanC (T2). A third terminator (T3) was observed between fanC and fanD and has an efficiency of 90%. Analysis of the regulatory region in an in vitro transcription system confirmed the location of the respective transcription signals. A model for the transcriptional organization of the K99 cluster is presented. Indications were obtained that the trans-acting regulatory polypeptides FanA and FanB both function as anti-terminators. A model for the regulation of expression of the K99 gene cluster is postulated.

  17. Targeted insertion of the neomycin phosphotransferase gene into the tubulin gene cluster of Trypanosoma brucei

    NARCIS (Netherlands)

    ten Asbroek, A. L.; Ouellette, M.; Borst, P.

    1990-01-01

    Kinetoplastids are unicellular eukaryotes that include important parasites of man, such as trypanosomes and leishmanias. The study of these organisms received a recent boost from the development of transient transformation allowing the short-term expression of genes reintroduced into parasites like

  18. Loss of Major DNase I Hypersensitive Sites in Duplicatedglobin Gene Cluster Incompletely Silences HBB Gene Expression

    Czech Academy of Sciences Publication Activity Database

    Reading, N. S.; Shooter, C.; Song, J.; Miller, R.; Agarwal, A.; Láníková, Lucie; Clark, B.; Thein, S.L.; Divoký, V.; Prchal, J.T.

    2016-01-01

    Roč. 37, č. 11 (2016), s. 1153-1156 ISSN 1059-7794 R&D Projects: GA MŠk(CZ) LH15223 Institutional support: RVO:68378050 Keywords : globin genes * regulation * sickle cell disease * HBB duplication Subject RIV: EB - Genetics ; Molecular Biology Impact factor: 4.601, year: 2016

  19. Energy Aware Cluster Based Routing Scheme For Wireless Sensor Network

    Directory of Open Access Journals (Sweden)

    Roy Sohini

    2015-09-01

    Full Text Available Wireless Sensor Network (WSN has emerged as an important supplement to the modern wireless communication systems due to its wide range of applications. The recent researches are facing the various challenges of the sensor network more gracefully. However, energy efficiency has still remained a matter of concern for the researches. Meeting the countless security needs, timely data delivery and taking a quick action, efficient route selection and multi-path routing etc. can only be achieved at the cost of energy. Hierarchical routing is more useful in this regard. The proposed algorithm Energy Aware Cluster Based Routing Scheme (EACBRS aims at conserving energy with the help of hierarchical routing by calculating the optimum number of cluster heads for the network, selecting energy-efficient route to the sink and by offering congestion control. Simulation results prove that EACBRS performs better than existing hierarchical routing algorithms like Distributed Energy-Efficient Clustering (DEEC algorithm for heterogeneous wireless sensor networks and Energy Efficient Heterogeneous Clustered scheme for Wireless Sensor Network (EEHC.

  20. Collaborative filtering recommendation model based on fuzzy clustering algorithm

    Science.gov (United States)

    Yang, Ye; Zhang, Yunhua

    2018-05-01

    As one of the most widely used algorithms in recommender systems, collaborative filtering algorithm faces two serious problems, which are the sparsity of data and poor recommendation effect in big data environment. In traditional clustering analysis, the object is strictly divided into several classes and the boundary of this division is very clear. However, for most objects in real life, there is no strict definition of their forms and attributes of their class. Concerning the problems above, this paper proposes to improve the traditional collaborative filtering model through the hybrid optimization of implicit semantic algorithm and fuzzy clustering algorithm, meanwhile, cooperating with collaborative filtering algorithm. In this paper, the fuzzy clustering algorithm is introduced to fuzzy clustering the information of project attribute, which makes the project belong to different project categories with different membership degrees, and increases the density of data, effectively reduces the sparsity of data, and solves the problem of low accuracy which is resulted from the inaccuracy of similarity calculation. Finally, this paper carries out empirical analysis on the MovieLens dataset, and compares it with the traditional user-based collaborative filtering algorithm. The proposed algorithm has greatly improved the recommendation accuracy.

  1. A novel grain cluster-based homogenization scheme

    International Nuclear Information System (INIS)

    Tjahjanto, D D; Eisenlohr, P; Roters, F

    2010-01-01

    An efficient homogenization scheme, termed the relaxed grain cluster (RGC), for elasto-plastic deformations of polycrystals is presented. The scheme is based on a generalization of the grain cluster concept. A volume element consisting of eight (= 2 × 2 × 2) hexahedral grains is considered. The kinematics of the RGC scheme is formulated within a finite deformation framework, where the relaxation of the local deformation gradient of each individual grain is connected to the overall deformation gradient by the, so-called, interface relaxation vectors. The set of relaxation vectors is determined by the minimization of the constitutive energy (or work) density of the overall cluster. An additional energy density associated with the mismatch at the grain boundaries due to relaxations is incorporated as a penalty term into the energy minimization formulation. Effectively, this penalty term represents the kinematical condition of deformation compatibility at the grain boundaries. Simulations have been performed for a dual-phase grain cluster loaded in uniaxial tension. The results of the simulations are presented and discussed in terms of the effective stress–strain response and the overall deformation anisotropy as functions of the penalty energy parameters. In addition, the prediction of the RGC scheme is compared with predictions using other averaging schemes, as well as to the result of direct finite element (FE) simulation. The comparison indicates that the present RGC scheme is able to approximate FE simulation results of relatively fine discretization at about three orders of magnitude lower computational cost

  2. Increasing Power by Sharing Information from Genetic Background and Treatment in Clustering of Gene Expression Time Series

    Directory of Open Access Journals (Sweden)

    Sura Zaki Alrashid

    2018-02-01

    Full Text Available Clustering of gene expression time series gives insight into which genes may be co-regulated, allowing us to discern the activity of pathways in a given microarray experiment. Of particular interest is how a given group of genes varies with different conditions or genetic background. This paper develops
a new clustering method that allows each cluster to be parameterised according to whether the behaviour of the genes across conditions is correlated or anti-correlated. By specifying correlation between such genes,more information is gain within the cluster about how the genes interrelate. Amyotrophic lateral sclerosis (ALS is an irreversible neurodegenerative disorder that kills the motor neurons and results in death within 2 to 3 years from the symptom onset. Speed of progression for different patients are heterogeneous with significant variability. The SOD1G93A transgenic mice from different backgrounds (129Sv and C57 showed consistent phenotypic differences for disease progression. A hierarchy of Gaussian isused processes to model condition-specific and gene-specific temporal co-variances. This study demonstrated about finding some significant gene expression profiles and clusters of associated or co-regulated gene expressions together from four groups of data (SOD1G93A and Ntg from 129Sv and C57 backgrounds. Our study shows the effectiveness of sharing information between replicates and different model conditions when modelling gene expression time series. Further gene enrichment score analysis and ontology pathway analysis of some specified clusters for a particular group may lead toward identifying features underlying the differential speed of disease progression.

  3. Isoeugenol monooxygenase and its putative regulatory gene are located in the eugenol metabolic gene cluster in Pseudomonas nitroreducens Jin1.

    Science.gov (United States)

    Ryu, Ji-Young; Seo, Jiyoung; Unno, Tatsuya; Ahn, Joong-Hoon; Yan, Tao; Sadowsky, Michael J; Hur, Hor-Gil

    2010-03-01

    The plant-derived phenylpropanoids eugenol and isoeugenol have been proposed as useful precursors for the production of natural vanillin. Genes involved in the metabolism of eugenol and isoeugenol were clustered in region of about a 30 kb of Pseudomonas nitroreducens Jin1. Two of the 23 ORFs in this region, ORFs 26 (iemR) and 27 (iem), were predicted to be involved in the conversion of isoeugenol to vanillin. The deduced amino acid sequence of isoeugenol monooxygenase (Iem) of strain Jin1 had 81.4% identity to isoeugenol monooxygenase from Pseudomonas putida IE27, which also transforms isoeugenol to vanillin. Iem was expressed in E. coli BL21(DE3) and was found to lead to isoeugenol to vanillin transformation. Deletion and cloning analyses indicated that the gene iemR, located upstream of iem, is required for expression of iem in the presence of isoeugenol, suggesting it to be the iem regulatory gene. Reverse transcription, real-time PCR analyses indicated that the genes involved in the metabolism of eugenol and isoeugenol were differently induced by isoeugenol, eugenol, and vanillin.

  4. Seminal Quality Prediction Using Clustering-Based Decision Forests

    Directory of Open Access Journals (Sweden)

    Hong Wang

    2014-08-01

    Full Text Available Prediction of seminal quality with statistical learning tools is an emerging methodology in decision support systems in biomedical engineering and is very useful in early diagnosis of seminal patients and selection of semen donors candidates. However, as is common in medical diagnosis, seminal quality prediction faces the class imbalance problem. In this paper, we propose a novel supervised ensemble learning approach, namely Clustering-Based Decision Forests, to tackle unbalanced class learning problem in seminal quality prediction. Experiment results on real fertility diagnosis dataset have shown that Clustering-Based Decision Forests outperforms decision tree, Support Vector Machines, random forests, multilayer perceptron neural networks and logistic regression by a noticeable margin. Clustering-Based Decision Forests can also be used to evaluate variables’ importance and the top five important factors that may affect semen concentration obtained in this study are age, serious trauma, sitting time, the season when the semen sample is produced, and high fevers in the last year. The findings could be helpful in explaining seminal concentration problems in infertile males or pre-screening semen donor candidates.

  5. Motif-independent prediction of a secondary metabolism gene cluster using comparative genomics: application to sequenced genomes of Aspergillus and ten other filamentous fungal species.

    Science.gov (United States)

    Takeda, Itaru; Umemura, Myco; Koike, Hideaki; Asai, Kiyoshi; Machida, Masayuki

    2014-08-01

    Despite their biological importance, a significant number of genes for secondary metabolite biosynthesis (SMB) remain undetected due largely to the fact that they are highly diverse and are not expressed under a variety of cultivation conditions. Several software tools including SMURF and antiSMASH have been developed to predict fungal SMB gene clusters by finding core genes encoding polyketide synthase, nonribosomal peptide synthetase and dimethylallyltryptophan synthase as well as several others typically present in the cluster. In this work, we have devised a novel comparative genomics method to identify SMB gene clusters that is independent of motif information of the known SMB genes. The method detects SMB gene clusters by searching for a similar order of genes and their presence in nonsyntenic blocks. With this method, we were able to identify many known SMB gene clusters with the core genes in the genomic sequences of 10 filamentous fungi. Furthermore, we have also detected SMB gene clusters without core genes, including the kojic acid biosynthesis gene cluster of Aspergillus oryzae. By varying the detection parameters of the method, a significant difference in the sequence characteristics was detected between the genes residing inside the clusters and those outside the clusters. © The Author 2014. Published by Oxford University Press on behalf of Kazusa DNA Research Institute.

  6. antiSMASH 3.0-a comprehensive resource for the genome mining of biosynthetic gene clusters.

    Science.gov (United States)

    Weber, Tilmann; Blin, Kai; Duddela, Srikanth; Krug, Daniel; Kim, Hyun Uk; Bruccoleri, Robert; Lee, Sang Yup; Fischbach, Michael A; Müller, Rolf; Wohlleben, Wolfgang; Breitling, Rainer; Takano, Eriko; Medema, Marnix H

    2015-07-01

    Microbial secondary metabolism constitutes a rich source of antibiotics, chemotherapeutics, insecticides and other high-value chemicals. Genome mining of gene clusters that encode the biosynthetic pathways for these metabolites has become a key methodology for novel compound discovery. In 2011, we introduced antiSMASH, a web server and stand-alone tool for the automatic genomic identification and analysis of biosynthetic gene clusters, available at http://antismash.secondarymetabolites.org. Here, we present version 3.0 of antiSMASH, which has undergone major improvements. A full integration of the recently published ClusterFinder algorithm now allows using this probabilistic algorithm to detect putative gene clusters of unknown types. Also, a new dereplication variant of the ClusterBlast module now identifies similarities of identified clusters to any of 1172 clusters with known end products. At the enzyme level, active sites of key biosynthetic enzymes are now pinpointed through a curated pattern-matching procedure and Enzyme Commission numbers are assigned to functionally classify all enzyme-coding genes. Additionally, chemical structure prediction has been improved by incorporating polyketide reduction states. Finally, in order for users to be able to organize and analyze multiple antiSMASH outputs in a private setting, a new XML output module allows offline editing of antiSMASH annotations within the Geneious software. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

  7. Multi-documents summarization based on clustering of learning object using hierarchical clustering

    Science.gov (United States)

    Mustamiin, M.; Budi, I.; Santoso, H. B.

    2018-03-01

    The Open Educational Resources (OER) is a portal of teaching, learning and research resources that is available in public domain and freely accessible. Learning contents or Learning Objects (LO) are granular and can be reused for constructing new learning materials. LO ontology-based searching techniques can be used to search for LO in the Indonesia OER. In this research, LO from search results are used as an ingredient to create new learning materials according to the topic searched by users. Summarizing-based grouping of LO use Hierarchical Agglomerative Clustering (HAC) with the dependency context to the user’s query which has an average value F-Measure of 0.487, while summarizing by K-Means F-Measure only has an average value of 0.336.

  8. antiSMASH 4.0-improvements in chemistry prediction and gene cluster boundary identification

    DEFF Research Database (Denmark)

    Blin, Kai; Wolf, Thomas; Chevrette, Marc G.

    2017-01-01

    Many antibiotics, chemotherapeutics, crop protection agents and food preservatives originate from molecules produced by bacteria, fungi or plants. In recent years, genome mining methodologies have been widely adopted to identify and characterize the biosynthetic gene clusters encoding...... the production of such compounds. Since 2011, the 'antibiotics and secondary metabolite analysis shell-antiSMASH' has assisted researchers in efficiently performing this, both as a web server and a standalone tool. Here, we present the thoroughly updated antiSMASH version 4, which adds several novel features...

  9. Medical Imaging Lesion Detection Based on Unified Gravitational Fuzzy Clustering

    Directory of Open Access Journals (Sweden)

    Jean Marie Vianney Kinani

    2017-01-01

    Full Text Available We develop a swift, robust, and practical tool for detecting brain lesions with minimal user intervention to assist clinicians and researchers in the diagnosis process, radiosurgery planning, and assessment of the patient’s response to the therapy. We propose a unified gravitational fuzzy clustering-based segmentation algorithm, which integrates the Newtonian concept of gravity into fuzzy clustering. We first perform fuzzy rule-based image enhancement on our database which is comprised of T1/T2 weighted magnetic resonance (MR and fluid-attenuated inversion recovery (FLAIR images to facilitate a smoother segmentation. The scalar output obtained is fed into a gravitational fuzzy clustering algorithm, which separates healthy structures from the unhealthy. Finally, the lesion contour is automatically outlined through the initialization-free level set evolution method. An advantage of this lesion detection algorithm is its precision and its simultaneous use of features computed from the intensity properties of the MR scan in a cascading pattern, which makes the computation fast, robust, and self-contained. Furthermore, we validate our algorithm with large-scale experiments using clinical and synthetic brain lesion datasets. As a result, an 84%–93% overlap performance is obtained, with an emphasis on robustness with respect to different and heterogeneous types of lesion and a swift computation time.

  10. Cluster chain based energy efficient routing protocol for moblie WSN

    Directory of Open Access Journals (Sweden)

    WU Ziyu

    2016-04-01

    Full Text Available With the ubiquitous smart devices acting as mobile sensor nodes in the wireless sensor networks(WSNs to sense and transmit physical information,routing protocols should be designed to accommodate the mobility issues,in addition to conventional considerations on energy efficiency.However,due to frequent topology change,traditional routing schemes cannot perform well.Moreover,existence of mobile nodes poses new challenges on energy dissipation and packet loss.In this paper,a novel routing scheme called cluster chain based routing protocol(CCBRP is proposed,which employs a combination of cluster and chain structure to accomplish data collection and transmission and thereafter selects qualified cluster heads as chain leaders to transmit data to the sink.Furthermore,node mobility is handled based on periodical membership update of mobile nodes.Simulation results demonstrate that CCBRP has a good performance in terms of network lifetime and packet delivery,also strikes a better balance between successful packet reception and energy consumption.

  11. Green Clustering Implementation Based on DPS-MOPSO

    Directory of Open Access Journals (Sweden)

    Yang Lu

    2014-01-01

    Full Text Available A green clustering implementation is proposed to be as the first method in the framework of an energy-efficient strategy for centralized enterprise high-density WLANs. Traditionally, to maintain the network coverage, all of the APs within the WLAN have to be powered on. Nevertheless, the new algorithm can power off a large proportion of APs while the coverage is maintained as the always-on counterpart. The proposed algorithm is composed of two parallel and concurrent procedures, which are the faster procedure based on K-means and the more accurate procedure based on Dynamic Population Size Multiple Objective Particle Swarm Optimization (DPS-MOPSO. To implement green clustering efficiently and accurately, dynamic population size and mutational operators are introduced as complements for the classical MOPSO. In addition to the function of AP selection, the new green clustering algorithm has another new function as the reference and guidance for AP deployment. This paper also presents simulations in scenarios modeled with ray-tracing method and FDTD technique, and the results show that about 67% up to 90% of energy consumption can be saved while the original network coverage is maintained during periods when few users are online or when the traffic load is low.

  12. Research on Bridge Sensor Validation Based on Correlation in Cluster

    Directory of Open Access Journals (Sweden)

    Huang Xiaowei

    2016-01-01

    Full Text Available In order to avoid the false alarm and alarm failure caused by sensor malfunction or failure, it has been critical to diagnose the fault and analyze the failure of the sensor measuring system in major infrastructures. Based on the real time monitoring of bridges and the study on the correlation probability distribution between multisensors adopted in the fault diagnosis system, a clustering algorithm based on k-medoid is proposed, by dividing sensors of the same type into k clusters. Meanwhile, the value of k is optimized by a specially designed evaluation function. Along with the further study of the correlation of sensors within the same cluster, this paper presents the definition and corresponding calculation algorithm of the sensor’s validation. The algorithm is applied to the analysis of the sensor data from an actual health monitoring system. The result reveals that the algorithm can not only accurately measure the failure degree and orientate the malfunction in time domain but also quantitatively evaluate the performance of sensors and eliminate error of diagnosis caused by the failure of the reference sensor.

  13. Genome-wide identification of physically clustered genes suggests chromatin-level co-regulation in male reproductive development in Arabidopsis thaliana.

    Science.gov (United States)

    Reimegård, Johan; Kundu, Snehangshu; Pendle, Ali; Irish, Vivian F; Shaw, Peter; Nakayama, Naomi; Sundström, Jens F; Emanuelsson, Olof

    2017-04-07

    Co-expression of physically linked genes occurs surprisingly frequently in eukaryotes. Such chromosomal clustering may confer a selective advantage as it enables coordinated gene regulation at the chromatin level. We studied the chromosomal organization of genes involved in male reproductive development in Arabidopsis thaliana. We developed an in-silico tool to identify physical clusters of co-regulated genes from gene expression data. We identified 17 clusters (96 genes) involved in stamen development and acting downstream of the transcriptional activator MS1 (MALE STERILITY 1), which contains a PHD domain associated with chromatin re-organization. The clusters exhibited little gene homology or promoter element similarity, and largely overlapped with reported repressive histone marks. Experiments on a subset of the clusters suggested a link between expression activation and chromatin conformation: qRT-PCR and mRNA in situ hybridization showed that the clustered genes were up-regulated within 48 h after MS1 induction; out of 14 chromatin-remodeling mutants studied, expression of clustered genes was consistently down-regulated only in hta9/hta11, previously associated with metabolic cluster activation; DNA fluorescence in situ hybridization confirmed that transcriptional activation of the clustered genes was correlated with open chromatin conformation. Stamen development thus appears to involve transcriptional activation of physically clustered genes through chromatin de-condensation. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

  14. Image Registration Algorithm Based on Parallax Constraint and Clustering Analysis

    Science.gov (United States)

    Wang, Zhe; Dong, Min; Mu, Xiaomin; Wang, Song

    2018-01-01

    To resolve the problem of slow computation speed and low matching accuracy in image registration, a new image registration algorithm based on parallax constraint and clustering analysis is proposed. Firstly, Harris corner detection algorithm is used to extract the feature points of two images. Secondly, use Normalized Cross Correlation (NCC) function to perform the approximate matching of feature points, and the initial feature pair is obtained. Then, according to the parallax constraint condition, the initial feature pair is preprocessed by K-means clustering algorithm, which is used to remove the feature point pairs with obvious errors in the approximate matching process. Finally, adopt Random Sample Consensus (RANSAC) algorithm to optimize the feature points to obtain the final feature point matching result, and the fast and accurate image registration is realized. The experimental results show that the image registration algorithm proposed in this paper can improve the accuracy of the image matching while ensuring the real-time performance of the algorithm.

  15. Genetic interrelations in the actinomycin biosynthetic gene clusters of Streptomyces antibioticus IMRU 3720 and Streptomyces chrysomallus ATCC11523, producers of actinomycin X and actinomycin C

    Science.gov (United States)

    Crnovčić, Ivana; Rückert, Christian; Semsary, Siamak; Lang, Manuel; Kalinowski, Jörn; Keller, Ullrich

    2017-01-01

    Sequencing the actinomycin (acm) biosynthetic gene cluster of Streptomyces antibioticus IMRU 3720, which produces actinomycin X (Acm X), revealed 20 genes organized into a highly similar framework as in the bi-armed acm C biosynthetic gene cluster of Streptomyces chrysomallus but without an attached additional extra arm of orthologues as in the latter. Curiously, the extra arm of the S. chrysomallus gene cluster turned out to perfectly match the single arm of the S. antibioticus gene cluster in the same order of orthologues including the the presence of two pseudogenes, scacmM and scacmN, encoding a cytochrome P450 and its ferredoxin, respectively. Orthologues of the latter genes were both missing in the principal arm of the S. chrysomallus acm C gene cluster. All orthologues of the extra arm showed a G +C-contents different from that of their counterparts in the principal arm. Moreover, the similarities of translation products from the extra arm were all higher to the corresponding translation products of orthologue genes from the S. antibioticus acm X gene cluster than to those encoded by the principal arm of their own gene cluster. This suggests that the duplicated structure of the S. chrysomallus acm C biosynthetic gene cluster evolved from previous fusion between two one-armed acm gene clusters each from a different genetic background. However, while scacmM and scacmN in the extra arm of the S. chrysomallus acm C gene cluster are mutated and therefore are non-functional, their orthologues saacmM and saacmN in the S. antibioticus acm C gene cluster show no defects seemingly encoding active enzymes with functions specific for Acm X biosynthesis. Both acm biosynthetic gene clusters lack a kynurenine-3-monooxygenase gene necessary for biosynthesis of 3-hydroxy-4-methylanthranilic acid, the building block of the Acm chromophore, which suggests participation of a genome-encoded relevant monooxygenase during Acm biosynthesis in both S. chrysomallus and S

  16. Deletion of the MBII-85 snoRNA gene cluster in mice results in postnatal growth retardation.

    Directory of Open Access Journals (Sweden)

    Boris V Skryabin

    2007-12-01

    Full Text Available Prader-Willi syndrome (PWS [MIM 176270] is a neurogenetic disorder characterized by decreased fetal activity, muscular hypotonia, failure to thrive, short stature, obesity, mental retardation, and hypogonadotropic hypogonadism. It is caused by the loss of function of one or more imprinted, paternally expressed genes on the proximal long arm of chromosome 15. Several potential PWS mouse models involving the orthologous region on chromosome 7C exist. Based on the analysis of deletions in the mouse and gene expression in PWS patients with chromosomal translocations, a critical region (PWScr for neonatal lethality, failure to thrive, and growth retardation was narrowed to the locus containing a cluster of neuronally expressed MBII-85 small nucleolar RNA (snoRNA genes. Here, we report the deletion of PWScr. Mice carrying the maternally inherited allele (PWScr(m-/p+ are indistinguishable from wild-type littermates. All those with the paternally inherited allele (PWScr(m+/p- consistently display postnatal growth retardation, with about 15% postnatal lethality in C57BL/6, but not FVB/N crosses. This is the first example in a multicellular organism of genetic deletion of a C/D box snoRNA gene resulting in a pronounced phenotype.

  17. A multi-Poisson dynamic mixture model to cluster developmental patterns of gene expression by RNA-seq.

    Science.gov (United States)

    Ye, Meixia; Wang, Zhong; Wang, Yaqun; Wu, Rongling

    2015-03-01

    Dynamic changes of gene expression reflect an intrinsic mechanism of how an organism responds to developmental and environmental signals. With the increasing availability of expression data across a time-space scale by RNA-seq, the classification of genes as per their biological function using RNA-seq data has become one of the most significant challenges in contemporary biology. Here we develop a clustering mixture model to discover distinct groups of genes expressed during a period of organ development. By integrating the density function of multivariate Poisson distribution, the model accommodates the discrete property of read counts characteristic of RNA-seq data. The temporal dependence of gene expression is modeled by the first-order autoregressive process. The model is implemented with the Expectation-Maximization algorithm and model selection to determine the optimal number of gene clusters and obtain the estimates of Poisson parameters that describe the pattern of time-dependent expression of genes from each cluster. The model has been demonstrated by analyzing a real data from an experiment aimed to link the pattern of gene expression to catkin development in white poplar. The usefulness of the model has been validated through computer simulation. The model provides a valuable tool for clustering RNA-seq data, facilitating our global view of expression dynamics and understanding of gene regulation mechanisms. © The Author 2014. Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

  18. Identification of a trichothecene gene cluster and description of the harzianum A biosynthesis pathway in the fungus Trichoderma arundinaceum

    Science.gov (United States)

    Trichothecenes are sesquiterpenes that act like mycotoxins. Their biosynthesis has been mainly studied in the fungal genera Fusarium, where most of the biosynthetic genes (tri) are grouped in a cluster regulated by ambient conditions and regulatory genes. Unexpectedly, few studies are available abou...

  19. The entire β-globin gene cluster is deleted in a form of τδβ-thalassemia.

    NARCIS (Netherlands)

    E.R. Fearon; H.H.Jr. Kazazian; P.G. Waber (Pamela); J.I. Lee (Joseph); S.E. Antonarakis; S.H. Orkin (Stuart); E.F. Vanin; P.S. Henthorn; F.G. Grosveld (Frank); A.F. Scott; G.R. Buchanan

    1983-01-01

    textabstractWe have used restriction endonuclease mapping to study a deletion involving the beta-globin gene cluster in a Mexican-American family with gamma delta beta-thalassemia. Analysis of DNA polymorphisms demonstrated deletion of the beta-globin gene from the affected chromosome. Using a DNA

  20. Targeted capture and heterologous expression of the Pseudoalteromonas alterochromide gene cluster in Escherichia coli represents a promising natural product exploratory platform.

    Science.gov (United States)

    Ross, Avena C; Gulland, Lauren E S; Dorrestein, Pieter C; Moore, Bradley S

    2015-04-17

    Marine pseudoalteromonads represent a very promising source of biologically important natural product molecules. To access and exploit the full chemical capacity of these cosmopolitan Gram-(-) bacteria, we sought to apply universal synthetic biology tools to capture, refactor, and express biosynthetic gene clusters for the production of complex organic compounds in reliable host organisms. Here, we report a platform for the capture of proteobacterial gene clusters using a transformation-associated recombination (TAR) strategy coupled with direct pathway manipulation and expression in Escherichia coli. The ~34 kb pathway for production of alterochromide lipopeptides by Pseudoalteromonas piscicida JCM 20779 was captured and heterologously expressed in E. coli utilizing native and E. coli-based T7 promoter sequences. Our approach enabled both facile production of the alterochromides and in vivo interrogation of gene function associated with alterochromide's unusual brominated lipid side chain. This platform represents a simple but effective strategy for the discovery and biosynthetic characterization of natural products from marine proteobacteria.

  1. Human major histocompatibility complex contains a minimum of 19 genes between the complement cluster and HLA-B

    International Nuclear Information System (INIS)

    Spies, T.; Bresnahan, M.; Strominger, J.L.

    1989-01-01

    A 600-kilobase (kb) DNA segment from the human major histocompatibility complex (MHC) class III region was isolated by extension of a previous 435-kb chromosome walk. The contiguous series of cloned overlapping cosmids contains the entire 555-kb interval between C2 in the complement gene cluster and HLA-B. This region is known to encode the tumor necrosis factors (TNFs) α and β, B144, and the major heat shock protein HSP70. Moreover, a cluster of genes, BAT1-BAT5 (HLA-B-associated transcripts) have been localized in the vicinity of the genes for TNFα and TNFβ. An additional four genes were identified by isolation of corresponding cDNA clones with cosmid DNA probes. These genes for BAT6-BAT9 were mapped near the gene for C2 within a 120-kb region that includes a HSP70 gene pair. These results, together with complementary data from a similar recent study, indicated the presence of a minimum of 19 genes within the C2-HLA-B interval of the MHC class III region. Although the functional properties of most of these genes are yet unknown, they may be involved in some aspects of immunity. This idea is supported by the genetic mapping of the hematopoietic histocompatibility locus-1 (Hh-1) in recombinant mice between TNFα and H-2S, which is homologous to the complement gene cluster in humans

  2. SPINE: SParse eIgengene NEtwork linking gene expression clusters in Dehalococcoides mccartyi to perturbations in experimental conditions.

    Directory of Open Access Journals (Sweden)

    Cresten B Mansfeldt

    Full Text Available We present a statistical model designed to identify the effect of experimental perturbations on the aggregate behavior of the transcriptome expressed by the bacterium Dehalococcoides mccartyi strain 195. Strains of Dehalococcoides are used in sub-surface bioremediation applications because they organohalorespire tetrachloroethene and trichloroethene (common chlorinated solvents that contaminate the environment to non-toxic ethene. However, the biochemical mechanism of this process remains incompletely described. Additionally, the response of Dehalococcoides to stress-inducing conditions that may be encountered at field-sites is not well understood. The constructed statistical model captured the aggregate behavior of gene expression phenotypes by modeling the distinct eigengenes of 100 transcript clusters, determining stable relationships among these clusters of gene transcripts with a sparse network-inference algorithm, and directly modeling the effect of changes in experimental conditions by constructing networks conditioned on the experimental state. Based on the model predictions, we discovered new response mechanisms for DMC, notably when the bacterium is exposed to solvent toxicity. The network identified a cluster containing thirteen gene transcripts directly connected to the solvent toxicity condition. Transcripts in this cluster include an iron-dependent regulator (DET0096-97 and a methylglyoxal synthase (DET0137. To validate these predictions, additional experiments were performed. Continuously fed cultures were exposed to saturating levels of tetrachloethene, thereby causing solvent toxicity, and transcripts that were predicted to be linked to solvent toxicity were monitored by quantitative reverse-transcription polymerase chain reaction. Twelve hours after being shocked with saturating levels of tetrachloroethene, the control transcripts (encoding for a key hydrogenase and the 16S rRNA did not significantly change. By contrast

  3. A Clustering-Oriented Closeness Measure Based on Neighborhood Chain and Its Application in the Clustering Ensemble Framework Based on the Fusion of Different Closeness Measures

    Directory of Open Access Journals (Sweden)

    Shaoyi Liang

    2017-09-01

    Full Text Available Closeness measures are crucial to clustering methods. In most traditional clustering methods, the closeness between data points or clusters is measured by the geometric distance alone. These metrics quantify the closeness only based on the concerned data points’ positions in the feature space, and they might cause problems when dealing with clustering tasks having arbitrary clusters shapes and different clusters densities. In this paper, we first propose a novel Closeness Measure between data points based on the Neighborhood Chain (CMNC. Instead of using geometric distances alone, CMNC measures the closeness between data points by quantifying the difficulty for one data point to reach another through a chain of neighbors. Furthermore, based on CMNC, we also propose a clustering ensemble framework that combines CMNC and geometric-distance-based closeness measures together in order to utilize both of their advantages. In this framework, the “bad data points” that are hard to cluster correctly are identified; then different closeness measures are applied to different types of data points to get the unified clustering results. With the fusion of different closeness measures, the framework can get not only better clustering results in complicated clustering tasks, but also higher efficiency.

  4. BGDMdocker: a Docker workflow for data mining and visualization of bacterial pan-genomes and biosynthetic gene clusters

    Directory of Open Access Journals (Sweden)

    Gong Cheng

    2017-11-01

    Full Text Available Recently, Docker technology has received increasing attention throughout the bioinformatics community. However, its implementation has not yet been mastered by most biologists; accordingly, its application in biological research has been limited. In order to popularize this technology in the field of bioinformatics and to promote the use of publicly available bioinformatics tools, such as Dockerfiles and Images from communities, government sources, and private owners in the Docker Hub Registry and other Docker-based resources, we introduce here a complete and accurate bioinformatics workflow based on Docker. The present workflow enables analysis and visualization of pan-genomes and biosynthetic gene clusters of bacteria. This provides a new solution for bioinformatics mining of big data from various publicly available biological databases. The present step-by-step guide creates an integrative workflow through a Dockerfile to allow researchers to build their own Image and run Container easily.

  5. BGDMdocker: a Docker workflow for data mining and visualization of bacterial pan-genomes and biosynthetic gene clusters.

    Science.gov (United States)

    Cheng, Gong; Lu, Quan; Ma, Ling; Zhang, Guocai; Xu, Liang; Zhou, Zongshan

    2017-01-01

    Recently, Docker technology has received increasing attention throughout the bioinformatics community. However, its implementation has not yet been mastered by most biologists; accordingly, its application in biological research has been limited. In order to popularize this technology in the field of bioinformatics and to promote the use of publicly available bioinformatics tools, such as Dockerfiles and Images from communities, government sources, and private owners in the Docker Hub Registry and other Docker-based resources, we introduce here a complete and accurate bioinformatics workflow based on Docker. The present workflow enables analysis and visualization of pan-genomes and biosynthetic gene clusters of bacteria. This provides a new solution for bioinformatics mining of big data from various publicly available biological databases. The present step-by-step guide creates an integrative workflow through a Dockerfile to allow researchers to build their own Image and run Container easily.

  6. Discovering biomarkers from gene expression data for predicting cancer subgroups using neural networks and relational fuzzy clustering

    Directory of Open Access Journals (Sweden)

    Sharma Animesh

    2007-01-01

    Full Text Available Abstract Background The four heterogeneous childhood cancers, neuroblastoma, non-Hodgkin lymphoma, rhabdomyosarcoma, and Ewing sarcoma present a similar histology of small round blue cell tumor (SRBCT and thus often leads to misdiagnosis. Identification of biomarkers for distinguishing these cancers is a well studied problem. Existing methods typically evaluate each gene separately and do not take into account the nonlinear interaction between genes and the tools that are used to design the diagnostic prediction system. Consequently, more genes are usually identified as necessary for prediction. We propose a general scheme for finding a small set of biomarkers to design a diagnostic system for accurate classification of the cancer subgroups. We use multilayer networks with online gene selection ability and relational fuzzy clustering to identify a small set of biomarkers for accurate classification of the training and blind test cases of a well studied data set. Results Our method discerned just seven biomarkers that precisely categorized the four subgroups of cancer both in training and blind samples. For the same problem, others suggested 19–94 genes. These seven biomarkers include three novel genes (NAB2, LSP1 and EHD1 – not identified by others with distinct class-specific signatures and important role in cancer biology, including cellular proliferation, transendothelial migration and trafficking of MHC class antigens. Interestingly, NAB2 is downregulated in other tumors including Non-Hodgkin lymphoma and Neuroblastoma but we observed moderate to high upregulation in a few cases of Ewing sarcoma and Rabhdomyosarcoma, suggesting that NAB2 might be mutated in these tumors. These genes can discover the subgroups correctly with unsupervised learning, can differentiate non-SRBCT samples and they perform equally well with other machine learning tools including support vector machines. These biomarkers lead to four simple human interpretable

  7. Accumulation of transposable elements in Hox gene clusters during adaptive radiation of Anolis lizards.

    Science.gov (United States)

    Feiner, Nathalie

    2016-10-12

    Transposable elements (TEs) are DNA sequences that can insert elsewhere in the genome and modify genome structure and gene regulation. The role of TEs in evolution is contentious. One hypothesis posits that TE activity generates genomic incompatibilities that can cause reproductive isolation between incipient species. This predicts that TEs will accumulate during speciation events. Here, I tested the prediction that extant lineages with a relatively high rate of speciation have a high number of TEs in their genomes. I sequenced and analysed the TE content of a marker genomic region (Hox clusters) in Anolis lizards, a classic case of an adaptive radiation. Unlike other vertebrates, including closely related lizards, Anolis lizards have high numbers of TEs in their Hox clusters, genomic regions that regulate development of the morphological adaptations that characterize habitat specialists in these lizards. Following a burst of TE activity in the lineage leading to extant Anolis, TEs have continued to accumulate during or after speciation events, resulting in a positive relationship between TE density and lineage speciation rate. These results are consistent with the prediction that TE activity contributes to adaptive radiation by promoting speciation. Although there was no evidence that TE density per se is associated with ecological morphology, the activity of TEs in Hox clusters could have been a rich source for phenotypic variation that may have facilitated the rapid parallel morphological adaptation to microhabitats seen in extant Anolis lizards. © 2016 The Author(s).

  8. Performance Based Clustering for Benchmarking of Container Ports: an Application of Dea and Cluster Analysis Technique

    Directory of Open Access Journals (Sweden)

    Jie Wu

    2010-12-01

    Full Text Available The operational performance of container ports has received more and more attentions in both academic and practitioner circles, the performance evaluation and process improvement of container ports have also been the focus of several studies. In this paper, Data Envelopment Analysis (DEA, an effective tool for relative efficiency assessment, is utilized for measuring the performances and benchmarking of the 77 world container ports in 2007. The used approaches in the current study consider four inputs (Capacity of Cargo Handling Machines, Number of Berths, Terminal Area and Storage Capacity and a single output (Container Throughput. The results for the efficiency scores are analyzed, and a unique ordering of the ports based on average cross efficiency is provided, also cluster analysis technique is used to select the more appropriate targets for poorly performing ports to use as benchmarks.

  9. Personalized PageRank Clustering: A graph clustering algorithm based on random walks

    Science.gov (United States)

    A. Tabrizi, Shayan; Shakery, Azadeh; Asadpour, Masoud; Abbasi, Maziar; Tavallaie, Mohammad Ali

    2013-11-01

    Graph clustering has been an essential part in many methods and thus its accuracy has a significant effect on many applications. In addition, exponential growth of real-world graphs such as social networks, biological networks and electrical circuits demands clustering algorithms with nearly-linear time and space complexity. In this paper we propose Personalized PageRank Clustering (PPC) that employs the inherent cluster exploratory property of random walks to reveal the clusters of a given graph. We combine random walks and modularity to precisely and efficiently reveal the clusters of a graph. PPC is a top-down algorithm so it can reveal inherent clusters of a graph more accurately than other nearly-linear approaches that are mainly bottom-up. It also gives a hierarchy of clusters that is useful in many applications. PPC has a linear time and space complexity and has been superior to most of the available clustering algorithms on many datasets. Furthermore, its top-down approach makes it a flexible solution for clustering problems with different requirements.

  10. Microbial communication leading to the activation of silent fungal secondary metabolite gene clusters

    Directory of Open Access Journals (Sweden)

    Tina eNetzker

    2015-04-01

    Full Text Available Microorganisms form diverse multispecies communities in various ecosystems. The high abundance of fungal and bacterial species in these consortia results in specific communication between the microorganisms. A key role in this communication is played by secondary metabolites (SMs, which are also called natural products. Recently, it was shown that interspecies ‘talk’ between microorganisms represents a physiological trigger to activate silent gene clusters leading to the formation of novel SMs by the involved species. This review focuses on mixed microbial cultivation, mainly between bacteria and fungi, with a special emphasis on the induced formation of fungal SMs in co-cultures. In addition, the role of chromatin remodeling in the induction is examined, and methodical perspectives for the analysis of natural products are presented. As an example for an intermicrobial interaction elucidated at the molecular level, we discuss the specific interaction between the filamentous fungi Aspergillus nidulans and Aspergillus fumigatus with the soil bacterium Streptomyces rapamycinicus, which provides an excellent model system to enlighten molecular concepts behind regulatory mechanisms and will pave the way to a novel avenue of drug discovery through targeted activation of silent SM gene clusters through co-cultivations of microorganisms.

  11. Functional Analysis of the Chaperone-Usher Fimbrial Gene Clusters of Salmonella enterica serovar Typhi.

    Science.gov (United States)

    Dufresne, Karine; Saulnier-Bellemare, Julie; Daigle, France

    2018-01-01

    The human-specific pathogen Salmonella enterica serovar Typhi causes typhoid, a major public health issue in developing countries. Several aspects of its pathogenesis are still poorly understood. S . Typhi possesses 14 fimbrial gene clusters including 12 chaperone-usher fimbriae ( stg, sth, bcf , fim, saf , sef , sta, stb, stc, std, ste , and tcf ). These fimbriae are weakly expressed in laboratory conditions and only a few are actually characterized. In this study, expression of all S . Typhi chaperone-usher fimbriae and their potential roles in pathogenesis such as interaction with host cells, motility, or biofilm formation were assessed. All S . Typhi fimbriae were better expressed in minimal broth. Each system was overexpressed and only the fimbrial gene clusters without pseudogenes demonstrated a putative major subunits of about 17 kDa on SDS-PAGE. Six of these (Fim, Saf, Sta, Stb, Std, and Tcf) also show extracellular structure by electron microscopy. The impact of fimbrial deletion in a wild-type strain or addition of each individual fimbrial system to an S . Typhi afimbrial strain were tested for interactions with host cells, biofilm formation and motility. Several fimbriae modified bacterial interactions with human cells (THP-1 and INT-407) and biofilm formation. However, only Fim fimbriae had a deleterious effect on motility when overexpressed. Overall, chaperone-usher fimbriae seem to be an important part of the balance between the different steps (motility, adhesion, host invasion and persistence) of S . Typhi pathogenesis.

  12. Heterologous expression of the Halothiobacillus neapolitanus carboxysomal gene cluster in Corynebacterium glutamicum.

    Science.gov (United States)

    Baumgart, Meike; Huber, Isabel; Abdollahzadeh, Iman; Gensch, Thomas; Frunzke, Julia

    2017-09-20

    Compartmentalization represents a ubiquitous principle used by living organisms to optimize metabolic flux and to avoid detrimental interactions within the cytoplasm. Proteinaceous bacterial microcompartments (BMCs) have therefore created strong interest for the encapsulation of heterologous pathways in microbial model organisms. However, attempts were so far mostly restricted to Escherichia coli. Here, we introduced the carboxysomal gene cluster of Halothiobacillus neapolitanus into the biotechnological platform species Corynebacterium gluta-micum. Transmission electron microscopy, fluorescence microscopy and single molecule localization microscopy suggested the formation of BMC-like structures in cells expressing the complete carboxysome operon or only the shell proteins. Purified carboxysomes consisted of the expected protein components as verified by mass spectrometry. Enzymatic assays revealed the functional production of RuBisCO in C. glutamicum both in the presence and absence of carboxysomal shell proteins. Furthermore, we could show that eYFP is targeted to the carboxysomes by fusion to the large RuBisCO subunit. Overall, this study represents the first transfer of an α-carboxysomal gene cluster into a Gram-positive model species supporting the modularity and orthogonality of these microcompartments, but also identified important challenges which need to be addressed on the way towards biotechnological application. Copyright © 2017 Elsevier B.V. All rights reserved.

  13. Cluster of differentiation 14 gene polymorphism and its association with incidence of clinical mastitis in Karan fries cattle

    Directory of Open Access Journals (Sweden)

    A. Sakthivel Selvan

    2014-12-01

    Full Text Available Aim: The present study was undertaken with the objectives to characterize, identify DNA polymorphism in cluster of differentiation 14 (CD14 gene in Karan Fries (KF cattle and to analyze association between genetic variants with incidence of clinical mastitis in National Dairy Research Institute (NDRI herd, Karnal. Materials and Methods: Genomic DNA was extracted using blood of randomly selected hundred KF lactating cattle by phenol-chloroform method. After checking its quality and quantity, polymerase chain reaction (PCR was carried out using reported primers to amplify 832 base pair region covering nucleotide base position number 1012 to 1843 (part of promoter, 5’UTR, exon 1, intron 1 and part of exon 2 of bovine CD14 gene. The PCR amplified target product was purified, sequenced and further ClustalW analysis was done to align edited sequence with reported Bos taurus sequence (EU148610.1. The restriction fragment length polymorphism (RFLP analysis was performed for each KF cow using HinfI restriction enzyme (RE. Cows were assigned genotypes obtained by PCR-RFLP analysis and association study was done using Chi-square (χ2 test. Results: After PCR amplification, DNA sequencing of amplicon confirmed the 832 bases covering 1012 to 1843 nucleotide base position of bovine CD14 gene. ClustalW multiple sequence alignment program for DNA revealed six nucleotide changes in KF cows at positions T1117D, T1239G, T1291C, G1359C, G1361A, and G1811A. Cows were also screened using PCR-RFLP with HinfI RE, which revealed three genotypes CC, CD and DD that differed significantly regarding mastitis incidence. Within CC genotype, 72.73% of cows were in a mastitis non-affected group whereas, those in CD and DD genotypes 69.44% and 60.38% respectively were mastitis affected. Conclusion: KF cows with allele C of CD14 gene were less susceptibility to mastitis compared with D allele.

  14. Centroid based clustering of high throughput sequencing reads based on n-mer counts.

    Science.gov (United States)

    Solovyov, Alexander; Lipkin, W Ian

    2013-09-08

    Many problems in computational biology require alignment-free sequence comparisons. One of the common tasks involving sequence comparison is sequence clustering. Here we apply methods of alignment-free comparison (in particular, comparison using sequence composition) to the challenge of sequence clustering. We study several centroid based algorithms for clustering sequences based on word counts. Study of their performance shows that using k-means algorithm with or without the data whitening is efficient from the computational point of view. A higher clustering accuracy can be achieved using the soft expectation maximization method, whereby each sequence is attributed to each cluster with a specific probability. We implement an open source tool for alignment-free clustering. It is publicly available from github: https://github.com/luscinius/afcluster. We show the utility of alignment-free sequence clustering for high throughput sequencing analysis despite its limitations. In particular, it allows one to perform assembly with reduced resources and a minimal loss of quality. The major factor affecting performance of alignment-free read clustering is the length of the read.

  15. Identification of the Regulator Gene Responsible for the Acetone-Responsive Expression of the Binuclear Iron Monooxygenase Gene Cluster in Mycobacteria ▿

    Science.gov (United States)

    Furuya, Toshiki; Hirose, Satomi; Semba, Hisashi; Kino, Kuniki

    2011-01-01

    The mimABCD gene cluster encodes the binuclear iron monooxygenase that oxidizes propane and phenol in Mycobacterium smegmatis strain MC2 155 and Mycobacterium goodii strain 12523. Interestingly, expression of the mimABCD gene cluster is induced by acetone. In this study, we investigated the regulator gene responsible for this acetone-responsive expression. In the genome sequence of M. smegmatis strain MC2 155, the mimABCD gene cluster is preceded by a gene designated mimR, which is divergently transcribed. Sequence analysis revealed that MimR exhibits amino acid similarity with the NtrC family of transcriptional activators, including AcxR and AcoR, which are involved in acetone and acetoin metabolism, respectively. Unexpectedly, many homologs of the mimR gene were also found in the sequenced genomes of actinomycetes. A plasmid carrying a transcriptional fusion of the intergenic region between the mimR and mimA genes with a promoterless green fluorescent protein (GFP) gene was constructed and introduced into M. smegmatis strain MC2 155. Using a GFP reporter system, we confirmed by deletion and complementation analyses that the mimR gene product is the positive regulator of the mimABCD gene cluster expression that is responsive to acetone. M. goodii strain 12523 also utilized the same regulatory system as M. smegmatis strain MC2 155. Although transcriptional activators of the NtrC family generally control transcription using the σ54 factor, a gene encoding the σ54 factor was absent from the genome sequence of M. smegmatis strain MC2 155. These results suggest the presence of a novel regulatory system in actinomycetes, including mycobacteria. PMID:21856847

  16. Plasmid Complement of Lactococcus lactis NCDO712 Reveals a Novel Pilus Gene Cluster.

    Science.gov (United States)

    Tarazanova, Mariya; Beerthuyzen, Marke; Siezen, Roland; Fernandez-Gutierrez, Marcela M; de Jong, Anne; van der Meulen, Sjoerd; Kok, Jan; Bachmann, Herwig

    2016-01-01

    Lactococcus lactis MG1363 is an important gram-positive model organism. It is a plasmid-free and phage-cured derivative of strain NCDO712. Plasmid-cured strains facilitate studies on molecular biological aspects, but many properties which make L. lactis an important organism in the dairy industry are plasmid encoded. We sequenced the total DNA of strain NCDO712 and, contrary to earlier reports, revealed that the strain carries 6 rather than 5 plasmids. A new 50-kb plasmid, designated pNZ712, encodes functional nisin immunity (nisCIP) and copper resistance (lcoRSABC). The copper resistance could be used as a marker for the conjugation of pNZ712 to L. lactis MG1614. A genome comparison with the plasmid cured daughter strain MG1363 showed that the number of single nucleotide polymorphisms that accumulated in the laboratory since the strains diverted more than 30 years ago is limited to 11 of which only 5 lead to amino acid changes. The 16-kb plasmid pSH74 was found to contain a novel 8-kb pilus gene cluster spaCB-spaA-srtC1-srtC2, which is predicted to encode a pilin tip protein SpaC, a pilus basal subunit SpaB, and a pilus backbone protein SpaA. The sortases SrtC1/SrtC2 are most likely involved in pilus polymerization while the chromosomally encoded SrtA could act to anchor the pilus to peptidoglycan in the cell wall. Overexpression of the pilus gene cluster from a multi-copy plasmid in L. lactis MG1363 resulted in cell chaining, aggregation, rapid sedimentation and increased conjugation efficiency of the cells. Electron microscopy showed that the over-expression of the pilus gene cluster leads to appendices on the cell surfaces. A deletion of the gene encoding the putative basal protein spaB, by truncating spaCB, led to more pilus-like structures on the cell surface, but cell aggregation and cell chaining were no longer observed. This is consistent with the prediction that spaB is involved in the anchoring of the pili to the cell.

  17. A first packet processing subdomain cluster model based on SDN

    Science.gov (United States)

    Chen, Mingyong; Wu, Weimin

    2017-08-01

    For the current controller cluster packet processing performance bottlenecks and controller downtime problems. An SDN controller is proposed to allocate the priority of each device in the SDN (Software Defined Network) network, and the domain contains several network devices and Controller, the controller is responsible for managing the network equipment within the domain, the switch performs data delivery based on the load of the controller, processing network equipment data. The experimental results show that the model can effectively solve the risk of single point failure of the controller, and can solve the performance bottleneck of the first packet processing.

  18. Genomic characterization of a new endophytic Streptomyces kebangsaanensis identifies biosynthetic pathway gene clusters for novel phenazine antibiotic production

    Directory of Open Access Journals (Sweden)

    Juwairiah Remali

    2017-11-01

    Full Text Available Background Streptomyces are well known for their capability to produce many bioactive secondary metabolites with medical and industrial importance. Here we report a novel bioactive phenazine compound, 6-((2-hydroxy-4-methoxyphenoxy carbonyl phenazine-1-carboxylic acid (HCPCA extracted from Streptomyces kebangsaanensis, an endophyte isolated from the ethnomedicinal Portulaca oleracea. Methods The HCPCA chemical structure was determined using nuclear magnetic resonance spectroscopy. We conducted whole genome sequencing for the identification of the gene cluster(s believed to be responsible for phenazine biosynthesis in order to map its corresponding pathway, in addition to bioinformatics analysis to assess the potential of S. kebangsaanensis in producing other useful secondary metabolites. Results The S. kebangsaanensis genome comprises an 8,328,719 bp linear chromosome with high GC content (71.35% consisting of 12 rRNA operons, 81 tRNA, and 7,558 protein coding genes. We identified 24 gene clusters involved in polyketide, nonribosomal peptide, terpene, bacteriocin, and siderophore biosynthesis, as well as a gene cluster predicted to be responsible for phenazine biosynthesis. Discussion The HCPCA phenazine structure was hypothesized to derive from the combination of two biosynthetic pathways, phenazine-1,6-dicarboxylic acid and 4-methoxybenzene-1,2-diol, originated from the shikimic acid pathway. The identification of a biosynthesis pathway gene cluster for phenazine antibiotics might facilitate future genetic engineering design of new synthetic phenazine antibiotics. Additionally, these findings confirm the potential of S. kebangsaanensis for producing various antibiotics and secondary metabolites.

  19. Clustering-based analysis for residential district heating data

    DEFF Research Database (Denmark)

    Gianniou, Panagiota; Liu, Xiufeng; Heller, Alfred

    2018-01-01

    The wide use of smart meters enables collection of a large amount of fine-granular time series, which can be used to improve the understanding of consumption behavior and used for consumption optimization. This paper presents a clustering-based knowledge discovery in databases method to analyze r....... These findings will be valuable for district heating utilities and energy planners to optimize their operations, design demand-side management strategies, and develop targeting energy-efficiency programs or policies.......The wide use of smart meters enables collection of a large amount of fine-granular time series, which can be used to improve the understanding of consumption behavior and used for consumption optimization. This paper presents a clustering-based knowledge discovery in databases method to analyze...... residential heating consumption data and evaluate information included in national building databases. The proposed method uses the K-means algorithm to segment consumption groups based on consumption intensity and representative patterns and ranks the groups according to daily consumption. This paper also...

  20. Mouse Nkrp1-Clr gene cluster sequence and expression analyses reveal conservation of tissue-specific MHC-independent immunosurveillance.

    Directory of Open Access Journals (Sweden)

    Qiang Zhang

    Full Text Available The Nkrp1 (Klrb1-Clr (Clec2 genes encode a receptor-ligand system utilized by NK cells as an MHC-independent immunosurveillance strategy for innate immune responses. The related Ly49 family of MHC-I receptors displays extreme allelic polymorphism and haplotype plasticity. In contrast, previous BAC-mapping and aCGH studies in the mouse suggest the neighboring and related Nkrp1-Clr cluster is evolutionarily stable. To definitively compare the relative evolutionary rate of Nkrp1-Clr vs. Ly49 gene clusters, the Nkrp1-Clr gene clusters from two Ly49 haplotype-disparate inbred mouse strains, BALB/c and 129S6, were sequenced. Both Nkrp1-Clr gene cluster sequences are highly similar to the C57BL/6 reference sequence, displaying the same gene numbers and order, complete pseudogenes, and gene fragments. The Nkrp1-Clr clusters contain a strikingly dissimilar proportion of repetitive elements compared to the Ly49 clusters, suggesting that certain elements may be partly responsible for the highly disparate Ly49 vs. Nkrp1 evolutionary rate. Focused allelic polymorphisms were found within the Nkrp1b/d (Klrb1b, Nkrp1c (Klrb1c, and Clr-c (Clec2f genes, suggestive of possible immune selection. Cell-type specific transcription of Nkrp1-Clr genes in a large panel of tissues/organs was determined. Clr-b (Clec2d and Clr-g (Clec2i showed wide expression, while other Clr genes showed more tissue-specific expression patterns. In situ hybridization revealed specific expression of various members of the Clr family in leukocytes/hematopoietic cells of immune organs, various tissue-restricted epithelial cells (including intestinal, kidney tubular, lung, and corneal progenitor epithelial cells, as well as myocytes. In summary, the Nkrp1-Clr gene cluster appears to evolve more slowly relative to the related Ly49 cluster, and likely regulates innate immunosurveillance in a tissue-specific manner.

  1. Molecular identification and characterization of clustered regularly interspaced short palindromic repeat (CRISPR) gene cluster in Taylorella equigenitalis.

    Science.gov (United States)

    Hara, Yasushi; Hayashi, Kyohei; Nakajima, Takuya; Kagawa, Shizuko; Tazumi, Akihiro; Moore, John E; Matsuda, Motoo

    2013-09-01

    Clustered regularly interspaced short palindromic repeats (CRISPRs), of approximately 10,000 base pairs (bp) in length, were shown to occur in the Japanese Taylorella equigenitalis strain, EQ59. The locus was composed of the putative CRISPRs-associated with 5 (cas5), RAMP csd1, csd2, recB, cas1, a leader region, 13 CRISPR consensus sequence repeats (each 32 bp; 5'-TCAGCCACGTTCGCGTGGCTGTGTGTTTAAAG-3'). These were in turn separated by 12 non repetitive unique spacer regions of similar length. In addition, a leader region, a transposase/IS protein, a leader region, and cas3 were also seen. All seven putative open reading frames carry their ribosome binding sites. Promoter consensus sequences at the -35 and -10 regions and putative intrinsic ρ-independent transcription terminator regions also occurred. A possible long overlap of 170 bp in length occurred between the recB and cas1 loci. Positive reverse transcription PCR signals of cas5, RAMP csd1, csd2-recB/cas1, and cas3 were generated. A putative secondary structure of the CRISPR consensus repeats was constructed. Following this, CRISPR results of the T. equigenitalis EQ59 isolate were subsequently compared with those from the Taylorella asinigenitalis MCE3 isolate.

  2. Regulatory role of tetR gene in a novel gene cluster of Acidovorax avenae subsp. avenae RS-1 under oxidative stress

    Directory of Open Access Journals (Sweden)

    He eLiu

    2014-10-01

    Full Text Available Acidovorax avenae subsp. avenae is the causal agent of bacterial brown stripe disease in rice. In this study, we characterized a novel horizontal transfer of a gene cluster, including tetR, on the chromosome of A. avenae subsp. avenae RS-1 by genome-wide analysis. TetR acted as a repressor in this gene cluster and the oxidative stress resistance was enhanced in tetR-deletion mutant strain. Electrophoretic mobility shift assay (EMSA demonstrated that TetR regulator bound directly to the promoter of this gene cluster. Consistently, the results of quantitative real-time PCR also showed alterations in expression of associated genes. Moreover, the proteins affected by TetR under oxidative stress were revealed by comparing proteomic profiles of wild-type and mutant strains via 1D SDS-PAGE and LC-MS/MS analyses. Taken together, our results demonstrated that tetR gene in this novel gene cluster contributed to cell survival under oxidative stress, and TetR protein played an important regulatory role in growth kinetics, biofilm-forming capability, SOD and catalase activity, and oxide detoxicating ability.

  3. Regulatory role of tetR gene in a novel gene cluster of Acidovorax avenae subsp. avenae RS-1 under oxidative stress.

    Science.gov (United States)

    Liu, He; Yang, Chun-Lan; Ge, Meng-Yu; Ibrahim, Muhammad; Li, Bin; Zhao, Wen-Jun; Chen, Gong-You; Zhu, Bo; Xie, Guan-Lin

    2014-01-01

    Acidovorax avenae subsp. avenae is the causal agent of bacterial brown stripe disease in rice. In this study, we characterized a novel horizontal transfer of a gene cluster, including tetR, on the chromosome of A. avenae subsp. avenae RS-1 by genome-wide analysis. TetR acted as a repressor in this gene cluster and the oxidative stress resistance was enhanced in tetR-deletion mutant strain. Electrophoretic mobility shift assay demonstrated that TetR regulator bound directly to the promoter of this gene cluster. Consistently, the results of quantitative real-time PCR also showed alterations in expression of associated genes. Moreover, the proteins affected by TetR under oxidative stress were revealed by comparing proteomic profiles of wild-type and mutant strains via 1D SDS-PAGE and LC-MS/MS analyses. Taken together, our results demonstrated that tetR gene in this novel gene cluster contributed to cell survival under oxidative stress, and TetR protein played an important regulatory role in growth kinetics, biofilm-forming capability, superoxide dismutase and catalase activity, and oxide detoxicating ability.

  4. Clustering of 18 Local Black Rice Base on Total Anthocyanin

    Directory of Open Access Journals (Sweden)

    Kristamtini Kristamtini

    2017-10-01

    Full Text Available Black rice has a high anthocyanin content in the pericarp layer, which provides a dark purple color. Anthocyanin serve as an antioxidant that control cholesterol level in the blood, prevent anemia, potentially improve the body's resistance to disease, improve damage to liver cells (hepatitis and chirrosis, prevent impaired kidney function, prevent cancer/tumors, slows down antiaging, and prevent atherosclerosis and cardiovascular disease. Exploration results at AIAT Yogyakarta, Indonesia from 2011 to 2014 obtained 18 cultivar of local black rice Indonesia. The names of the rice are related to the color (black, red or purple formed by anthocyanin deposits in the pericarp layer, seed coat or aleuron. The objective of the study was to classify several types of local black rice from explorations based on the total anthocyanin content. The study was conducted by clustering analyzing the total anthocyanin content of 18 local black rice cultivars in Indonesia. Cluster analysis of total anthocyanin content were done using SAS ver. 9.2. Clustering dendogram shows that there were 4 groups of black rice cultivars based on the total anthocyanin content. Group I consists of Melik black rice, Patalan black rice, Yunianto black rice, Muharjo black rice, Ngatijo black rice, short life of Tugiyo black rice, Andel hitam 1, Jlitheng, and Sragen black rice. Group II consists of Pari ireng, Magelang black hairy rice, Banjarnegara-Wonosobo black rice, and Banjarnegara black rice. Group III consists of NTT black rice, Magelang non hairy black rice, Sembada hitam, and longevity Tugiyo black rice. Group IV consist only one type of black rice namely Cempo ireng. The grouping result indicate the existence of duplicate names among the black rice namely Patalan with Yunianto black rice, and short life Tugiyo with Andel hitam 1 black rice.

  5. Ancient expansion of the hox cluster in lepidoptera generated four homeobox genes implicated in extra-embryonic tissue formation.

    Directory of Open Access Journals (Sweden)

    Laura Ferguson

    2014-10-01

    Full Text Available Gene duplications within the conserved Hox cluster are rare in animal evolution, but in Lepidoptera an array of divergent Hox-related genes (Shx genes has been reported between pb and zen. Here, we use genome sequencing of five lepidopteran species (Polygonia c-album, Pararge aegeria, Callimorpha dominula, Cameraria ohridella, Hepialus sylvina plus a caddisfly outgroup (Glyphotaelius pellucidus to trace the evolution of the lepidopteran Shx genes. We demonstrate that Shx genes originated by tandem duplication of zen early in the evolution of large clade Ditrysia; Shx are not found in a caddisfly and a member of the basally diverging Hepialidae (swift moths. Four distinct Shx genes were generated early in ditrysian evolution, and were stably retained in all descendent Lepidoptera except the silkmoth which has additional duplications. Despite extensive sequence divergence, molecular modelling indicates that all four Shx genes have the potential to encode stable homeodomains. The four Shx genes have distinct spatiotemporal expression patterns in early development of the Speckled Wood butterfly (Pararge aegeria, with ShxC demarcating the future sites of extraembryonic tissue formation via strikingly localised maternal RNA in the oocyte. All four genes are also expressed in presumptive serosal cells, prior to the onset of zen expression. Lepidopteran Shx genes represent an unusual example of Hox cluster expansion and integration of novel genes into ancient developmental regulatory networks.

  6. Development and mapping of SSR markers linked to resistance-gene homologue clusters in common bean

    Institute of Scientific and Technical Information of China (English)

    Luz; Nayibe; Garzon; Matthew; Wohlgemuth; Blair

    2014-01-01

    Common bean is an important but often a disease-susceptible legume crop of temperate,subtropical and tropical regions worldwide. The crop is affected by bacterial, fungal and viral pathogens. The strategy of resistance-gene homologue(RGH) cloning has proven to be an efficient tool for identifying markers and R(resistance) genes associated with resistances to diseases. Microsatellite or SSR markers can be identified by physical association with RGH clones on large-insert DNA clones such as bacterial artificial chromosomes(BACs). Our objectives in this work were to identify RGH-SSR in a BAC library from the Andean genotype G19833 and to test and map any polymorphic markers to identify associations with known positions of disease resistance genes. We developed a set of specific probes designed for clades of common bean RGH genes and then identified positive BAC clones and developed microsatellites from BACs having SSR loci in their end sequences. A total of 629 new RGH-SSRs were identified and named BMr(bean microsatellite RGH-associated markers). A subset of these markers was screened for detecting polymorphism in the genetic mapping population DOR364 × G19833. A genetic map was constructed with a total of 264 markers,among which were 80 RGH loci anchored to single-copy RFLP and SSR markers. Clusters of RGH-SSRs were observed on most of the linkage groups of common bean and in positions associated with R-genes and QTL. The use of these new markers to select for disease resistance is discussed.

  7. Novel density-based and hierarchical density-based clustering algorithms for uncertain data.

    Science.gov (United States)

    Zhang, Xianchao; Liu, Han; Zhang, Xiaotong

    2017-09-01

    Uncertain data has posed a great challenge to traditional clustering algorithms. Recently, several algorithms have been proposed for clustering uncertain data, and among them density-based techniques seem promising for handling data uncertainty. However, some issues like losing uncertain information, high time complexity and nonadaptive threshold have not been addressed well in the previous density-based algorithm FDBSCAN and hierarchical density-based algorithm FOPTICS. In this paper, we firstly propose a novel density-based algorithm PDBSCAN, which improves the previous FDBSCAN from the following aspects: (1) it employs a more accurate method to compute the probability that the distance between two uncertain objects is less than or equal to a boundary value, instead of the sampling-based method in FDBSCAN; (2) it introduces new definitions of probability neighborhood, support degree, core object probability, direct reachability probability, thus reducing the complexity and solving the issue of nonadaptive threshold (for core object judgement) in FDBSCAN. Then, we modify the algorithm PDBSCAN to an improved version (PDBSCANi), by using a better cluster assignment strategy to ensure that every object will be assigned to the most appropriate cluster, thus solving the issue of nonadaptive threshold (for direct density reachability judgement) in FDBSCAN. Furthermore, as PDBSCAN and PDBSCANi have difficulties for clustering uncertain data with non-uniform cluster density, we propose a novel hierarchical density-based algorithm POPTICS by extending the definitions of PDBSCAN, adding new definitions of fuzzy core distance and fuzzy reachability distance, and employing a new clustering framework. POPTICS can reveal the cluster structures of the datasets with different local densities in different regions better than PDBSCAN and PDBSCANi, and it addresses the issues in FOPTICS. Experimental results demonstrate the superiority of our proposed algorithms over the existing

  8. Reliability analysis of cluster-based ad-hoc networks

    International Nuclear Information System (INIS)

    Cook, Jason L.; Ramirez-Marquez, Jose Emmanuel

    2008-01-01

    The mobile ad-hoc wireless network (MAWN) is a new and emerging network scheme that is being employed in a variety of applications. The MAWN varies from traditional networks because it is a self-forming and dynamic network. The MAWN is free of infrastructure and, as such, only the mobile nodes comprise the network. Pairs of nodes communicate either directly or through other nodes. To do so, each node acts, in turn, as a source, destination, and relay of messages. The virtue of a MAWN is the flexibility this provides; however, the challenge for reliability analyses is also brought about by this unique feature. The variability and volatility of the MAWN configuration makes typical reliability methods (e.g. reliability block diagram) inappropriate because no single structure or configuration represents all manifestations of a MAWN. For this reason, new methods are being developed to analyze the reliability of this new networking technology. New published methods adapt to this feature by treating the configuration probabilistically or by inclusion of embedded mobility models. This paper joins both methods together and expands upon these works by modifying the problem formulation to address the reliability analysis of a cluster-based MAWN. The cluster-based MAWN is deployed in applications with constraints on networking resources such as bandwidth and energy. This paper presents the problem's formulation, a discussion of applicable reliability metrics for the MAWN, and illustration of a Monte Carlo simulation method through the analysis of several example networks

  9. MODEL-BASED CLUSTERING FOR CLASSIFICATION OF AQUATIC SYSTEMS AND DIAGNOSIS OF ECOLOGICAL STRESS

    Science.gov (United States)

    Clustering approaches were developed using the classification likelihood, the mixture likelihood, and also using a randomization approach with a model index. Using a clustering approach based on the mixture and classification likelihoods, we have developed an algorithm that...

  10. Regulation of the Apolipoprotein Gene Cluster by a Long Noncoding RNA

    Directory of Open Access Journals (Sweden)

    Paul Halley

    2014-01-01

    Full Text Available Apolipoprotein A1 (APOA1 is the major protein component of high-density lipoprotein (HDL in plasma. We have identified an endogenously expressed long noncoding natural antisense transcript, APOA1-AS, which acts as a negative transcriptional regulator of APOA1 both in vitro and in vivo. Inhibition of APOA1-AS in cultured cells resulted in the increased expression of APOA1 and two neighboring genes in the APO cluster. Chromatin immunoprecipitation (ChIP analyses of a ∼50 kb chromatin region flanking the APOA1 gene demonstrated that APOA1-AS can modulate distinct histone methylation patterns that mark active and/or inactive gene expression through the recruitment of histone-modifying enzymes. Targeting APOA1-AS with short antisense oligonucleotides also enhanced APOA1 expression in both human and monkey liver cells and induced an increase in hepatic RNA and protein expression in African green monkeys. Furthermore, the results presented here highlight the significant local modulatory effects of long noncoding antisense RNAs and demonstrate the therapeutic potential of manipulating the expression of these transcripts both in vitro and in vivo.

  11. Comprehensive identification and clustering of CLV3/ESR-related (CLE) genes in plants finds groups with potentially shared function.

    Science.gov (United States)

    Goad, David M; Zhu, Chuanmei; Kellogg, Elizabeth A

    2017-10-01

    CLV3/ESR (CLE) proteins are important signaling peptides in plants. The short CLE peptide (12-13 amino acids) is cleaved from a larger pre-propeptide and functions as an extracellular ligand. The CLE family is large and has resisted attempts at classification because the CLE domain is too short for reliable phylogenetic analysis and the pre-propeptide is too variable. We used a model-based search for CLE domains from 57 plant genomes and used the entire pre-propeptide for comprehensive clustering analysis. In total, 1628 CLE genes were identified in land plants, with none recognizable from green algae. These CLEs form 12 groups within which CLE domains are largely conserved and pre-propeptides can be aligned. Most clusters contain sequences from monocots, eudicots and Amborella trichopoda, with sequences from Picea abies, Selaginella moellendorffii and Physcomitrella patens scattered in some clusters. We easily identified previously known clusters involved in vascular differentiation and nodulation. In addition, we found a number of discrete groups whose function remains poorly characterized. Available data indicate that CLE proteins within a cluster are likely to share function, whereas those from different clusters play at least partially different roles. Our analysis provides a foundation for future evolutionary and functional studies. © 2016 The Authors. New Phytologist © 2016 New Phytologist Trust.

  12. Coherence-based Time Series Clustering for Brain Connectivity Visualization

    KAUST Repository

    Euan, Carolina

    2017-11-19

    We develop the hierarchical cluster coherence (HCC) method for brain signals, a procedure for characterizing connectivity in a network by clustering nodes or groups of channels that display high level of coordination as measured by

  13. Cluster-based centralized data fusion for tracking maneuvering ...

    Indian Academy of Sciences (India)

    R. Narasimhan (Krishtel eMaging) 1461 1996 Oct 15 13:05:22

    In this scheme, measurements are sent to the data fusion centre where the mea- ... using 'clusters' (a cluster by definition is a type of parallel or distributed processing ... working together as a single, integrated computing resource) is proposed.

  14. Coherence-based Time Series Clustering for Brain Connectivity Visualization

    KAUST Repository

    Euan, Carolina; Sun, Ying; Ombao, Hernando

    2017-01-01

    We develop the hierarchical cluster coherence (HCC) method for brain signals, a procedure for characterizing connectivity in a network by clustering nodes or groups of channels that display high level of coordination as measured by

  15. Regulatory role of tetR gene in a novel gene cluster of Acidovorax avenae subsp. avenae RS-1 under oxidative stress

    OpenAIRE

    Liu, He; Yang, Chun-Lan; Ge, Meng-Yu; Ibrahim, Muhammad; Li, Bin; Zhao, Wen-Jun; Chen, Gong-You; Zhu, Bo; Xie, Guan-Lin

    2014-01-01

    Acidovorax avenae subsp. avenae is the causal agent of bacterial brown stripe disease in rice. In this study, we characterized a novel horizontal transfer of a gene cluster, including tetR, on the chromosome of A. avenae subsp. avenae RS-1 by genome-wide analysis. TetR acted as a repressor in this gene cluster and the oxidative stress resistance was enhanced in tetR-deletion mutant strain. Electrophoretic mobility shift assay demonstrated that TetR regulator bound directly to the promoter of ...

  16. Bootstrap-Based Improvements for Inference with Clustered Errors

    OpenAIRE

    Doug Miller; A. Colin Cameron; Jonah B. Gelbach

    2006-01-01

    Microeconometrics researchers have increasingly realized the essential need to account for any within-group dependence in estimating standard errors of regression parameter estimates. The typical preferred solution is to calculate cluster-robust or sandwich standard errors that permit quite general heteroskedasticity and within-cluster error correlation, but presume that the number of clusters is large. In applications with few (5-30) clusters, standard asymptotic tests can over-reject consid...

  17. Customer Clustering Based on Customer Purchasing Sequence Data

    OpenAIRE

    Yen-Chung Liu; Yen-Liang Chen

    2017-01-01

    Customer clustering has become a priority for enterprises because of the importance of customer relationship management. Customer clustering can improve understanding of the composition and characteristics of customers, thereby enabling the creation of appropriate marketing strategies for each customer group. Previously, different customer clustering approaches have been proposed according to data type, namely customer profile data, customer value data, customer transaction data, and customer...

  18. Genetic algorithm based two-mode clustering of metabolomics data

    NARCIS (Netherlands)

    Hageman, J.A.; van den Berg, R.A.; Westerhuis, J.A.; van der Werf, M.J.; Smilde, A.K.

    2008-01-01

    Metabolomics and other omics tools are generally characterized by large data sets with many variables obtained under different environmental conditions. Clustering methods and more specifically two-mode clustering methods are excellent tools for analyzing this type of data. Two-mode clustering

  19. Galaxy clusters in the SDSS Stripe 82 based on photometric redshifts

    International Nuclear Information System (INIS)

    Durret, F.; Adami, C.; Bertin, E.; Hao, J.; Márquez, I.

    2015-01-01

    Based on a recent photometric redshift galaxy catalogue, we have searched for galaxy clusters in the Stripe ~82 region of the Sloan Digital Sky Survey by applying the Adami & MAzure Cluster FInder (AMACFI). Extensive tests were made to fine-tune the AMACFI parameters and make the cluster detection as reliable as possible. The same method was applied to the Millennium simulation to estimate our detection efficiency and the approximate masses of the detected clusters. Considering all the cluster galaxies (i.e. within a 1 Mpc radius of the cluster to which they belong and with a photoz differing by less than 0.05 from that of the cluster), we stacked clusters in various redshift bins to derive colour-magnitude diagrams and galaxy luminosity functions (GLFs). For each galaxy with absolute magnitude brighter than -19.0 in the r band, we computed the disk and spheroid components by applying SExtractor, and by stacking clusters we determined how the disk-to-spheroid flux ratio varies with cluster redshift and mass. We also detected 3663 clusters in the redshift range 0.15< z<0.70, with estimated mean masses between 10"1"3 and a few 10"1"4 solar masses. Furthermore, by stacking the cluster galaxies in various redshift bins, we find a clear red sequence in the (g'-r') versus r' colour-magnitude diagrams, and the GLFs are typical of clusters, though with a possible contamination from field galaxies. The morphological analysis of the cluster galaxies shows that the fraction of late-type to early-type galaxies shows an increase with redshift (particularly in high mass clusters) and a decrease with detection level, i.e. cluster mass. From the properties of the cluster galaxies, the majority of the candidate clusters detected here seem to be real clusters with typical cluster properties.

  20. Sexuality generates diversity in the aflatoxin gene cluster: evidence on a global scale.

    Directory of Open Access Journals (Sweden)

    Geromy G Moore

    Full Text Available Aflatoxins are produced by Aspergillus flavus and A. parasiticus in oil-rich seed and grain crops and are a serious problem in agriculture, with aflatoxin B₁ being the most carcinogenic natural compound known. Sexual reproduction in these species occurs between individuals belonging to different vegetative compatibility groups (VCGs. We examined natural genetic variation in 758 isolates of A. flavus, A. parasiticus and A. minisclerotigenes sampled from single peanut fields in the United States (Georgia, Africa (Benin, Argentina (Córdoba, Australia (Queensland and India (Karnataka. Analysis of DNA sequence variation across multiple intergenic regions in the aflatoxin gene clusters of A. flavus, A. parasiticus and A. minisclerotigenes revealed significant linkage disequilibrium (LD organized into distinct blocks that are conserved across different localities, suggesting that genetic recombination is nonrandom and a global occurrence. To assess the contributions of asexual and sexual reproduction to fixation and maintenance of toxin chemotype diversity in populations from each locality/species, we tested the null hypothesis of an equal number of MAT1-1 and MAT1-2 mating-type individuals, which is indicative of a sexually recombining population. All samples were clone-corrected using multi-locus sequence typing which associates closely with VCG. For both A. flavus and A. parasiticus, when the proportions of MAT1-1 and MAT1-2 were significantly different, there was more extensive LD in the aflatoxin cluster and populations were fixed for specific toxin chemotype classes, either the non-aflatoxigenic class in A. flavus or the B₁-dominant and G₁-dominant classes in A. parasiticus. A mating type ratio close to 1∶1 in A. flavus, A. parasiticus and A. minisclerotigenes was associated with higher recombination rates in the aflatoxin cluster and less pronounced chemotype differences in populations. This work shows that the reproductive nature of

  1. Global analysis of biosynthetic gene clusters reveals vast potential of secondary metabolite production in Penicillium species

    DEFF Research Database (Denmark)

    Nielsen, Jens Christian; Grijseels, Sietske; Prigent, Sylvain

    2017-01-01

    Filamentous fungi produce a wide range of bioactive compounds with important pharmaceutical applications, such as antibiotic penicillins and cholesterol-lowering statins. However, less attention has been paid to fungal secondary metabolites compared to those from bacteria. In this study, we...... sequenced the genomes of 9 Penicillium species and, together with 15 published genomes, we investigated the secondary metabolism of Penicillium and identified an immense, unexploited potential for producing secondary metabolites by this genus. A total of 1,317 putative biosynthetic gene clusters (BGCs) were......-referenced the predicted pathways with published data on the production of secondary metabolites and experimentally validated the production of antibiotic yanuthones in Penicillia and identified a previously undescribed compound from the yanuthone pathway. This study is the first genus-wide analysis of the genomic...

  2. Insights into variability of actinorhodopsin genes of the LG1 cluster in two different freshwater habitats.

    Directory of Open Access Journals (Sweden)

    Jitka Jezberová

    Full Text Available Actinorhodopsins (ActRs are recently discovered proteorhodopsins present in Actinobacteria, enabling them to adapt to a wider spectrum of environmental conditions. Frequently, a large fraction of freshwater bacterioplankton belongs to the acI lineage of Actinobacteria and codes the LG1 type of ActRs. In this paper we studied the genotype variability of the LG1 ActRs. We have constructed two clone libraries originating from two environmentally different habitats located in Central Europe; the large alkaline lake Mondsee (Austria and the small humic reservoir Jiřická (the Czech Republic. The 75 yielded clones were phylogenetically analyzed together with all ActR sequences currently available in public databases. Altogether 156 sequences were analyzed and 13 clusters of ActRs were distinguished. Newly obtained clones are distributed over all three LG1 subgroups--LG1-A, B and C. Eighty percent of the sequences belonged to the acI lineage (LG1-A ActR gene bearers further divided into LG1-A1 and LG1-A2 subgroups. Interestingly, the two habitats markedly differed in genotype composition with no identical sequence found in both samples of clones. Moreover, Jiřická reservoir contained three so far not reported clusters, one of them LG1-C related, presenting thus completely new, so far undescribed, genotypes of Actinobacteria in freshwaters.

  3. A Secure Cluster-Based Multipath Routing Protocol for WMSNs

    Directory of Open Access Journals (Sweden)

    Jamal N. Al-Karaki

    2011-04-01

    Full Text Available The new characteristics of Wireless Multimedia Sensor Network (WMSN and its design issues brought by handling different traffic classes of multimedia content (video streams, audio, and still images as well as scalar data over the network, make the proposed routing protocols for typical WSNs not directly applicable for WMSNs. Handling real-time multimedia data requires both energy efficiency and QoS assurance in order to ensure efficient utility of different capabilities of sensor resources and correct delivery of collected information. In this paper, we propose a Secure Cluster-based Multipath Routing protocol for WMSNs, SCMR, to satisfy the requirements of delivering different data types and support high data rate multimedia traffic. SCMR exploits the hierarchical structure of powerful cluster heads and the optimized multiple paths to support timeliness and reliable high data rate multimedia communication with minimum energy dissipation. Also, we present a light-weight distributed security mechanism of key management in order to secure the communication between sensor nodes and protect the network against different types of attacks. Performance evaluation from simulation results demonstrates a significant performance improvement comparing with existing protocols (which do not even provide any kind of security feature in terms of average end-to-end delay, network throughput, packet delivery ratio, and energy consumption.

  4. Comparing large covariance matrices under weak conditions on the dependence structure and its application to gene clustering.

    Science.gov (United States)

    Chang, Jinyuan; Zhou, Wen; Zhou, Wen-Xin; Wang, Lan

    2017-03-01

    Comparing large covariance matrices has important applications in modern genomics, where scientists are often interested in understanding whether relationships (e.g., dependencies or co-regulations) among a large number of genes vary between different biological states. We propose a computationally fast procedure for testing the equality of two large covariance matrices when the dimensions of the covariance matrices are much larger than the sample sizes. A distinguishing feature of the new procedure is that it imposes no structural assumptions on the unknown covariance matrices. Hence, the test is robust with respect to various complex dependence structures that frequently arise in genomics. We prove that the proposed procedure is asymptotically valid under weak moment conditions. As an interesting application, we derive a new gene clustering algorithm which shares the same nice property of avoiding restrictive structural assumptions for high-dimensional genomics data. Using an asthma gene expression dataset, we illustrate how the new test helps compare the covariance matrices of the genes across different gene sets/pathways between the disease group and the control group, and how the gene clustering algorithm provides new insights on the way gene clustering patterns differ between the two groups. The proposed methods have been implemented in an R-package HDtest and are available on CRAN. © 2016, The International Biometric Society.

  5. An additional k-means clustering step improves the biological features of WGCNA gene co-expression networks.

    Science.gov (United States)

    Botía, Juan A; Vandrovcova, Jana; Forabosco, Paola; Guelfi, Sebastian; D'Sa, Karishma; Hardy, John; Lewis, Cathryn M; Ryten, Mina; Weale, Michael E

    2017-04-12

    Weighted Gene Co-expression Network Analysis (WGCNA) is a widely used R software package for the generation of gene co-expression networks (GCN). WGCNA generates both a GCN and a derived partitioning of clusters of genes (modules). We propose k-means clustering as an additional processing step to conventional WGCNA, which we have implemented in the R package km2gcn (k-means to gene co-expression network, https://github.com/juanbot/km2gcn ). We assessed our method on networks created from UKBEC data (10 different human brain tissues), on networks created from GTEx data (42 human tissues, including 13 brain tissues), and on simulated networks derived from GTEx data. We observed substantially improved module properties, including: (1) few or zero misplaced genes; (2) increased counts of replicable clusters in alternate tissues (x3.1 on average); (3) improved enrichment of Gene Ontology terms (seen in 48/52 GCNs) (4) improved cell type enrichment signals (seen in 21/23 brain GCNs); and (5) more accurate partitions in simulated data according to a range of similarity indices. The results obtained from our investigations indicate that our k-means method, applied as an adjunct to standard WGCNA, results in better network partitions. These improved partitions enable more fruitful downstream analyses, as gene modules are more biologically meaningful.

  6. Analysis of healthy cohorts for single nucleotide polymorphisms in C1q gene cluster

    Directory of Open Access Journals (Sweden)

    MARIA A. RADANOVA

    2015-12-01

    Full Text Available C1q is the first component of the classical pathway of complement activation. The coding region for C1q is localized on chromosome 1p34.1–36.3. Mutations or single nucleotide polymorphisms (SNPs in C1q gene cluster can cause developing of Systemic lupus erythematosus (SLE because of C1q deficiency or other unknown reason. We selected five SNPs located in 7.121 kbp region on chromosome 1, which were previously associated with SLE and/or low C1q level, but not causing C1q deficiency and analyzed them in terms of allele frequencies and genotype distribution in comparison with Hispanic, Asian, African and other Caucasian cohorts. These SNPs were: rs587585, rs292001, rs172378, rs294179 and rs631090. One hundred eighty five healthy Bulgarian volunteers were genotyped for the selected five C1q SNPs by quantative real-time PCR methods. International HapMap Project has been used for information about genotype distribution and allele frequencies of the five SNPs in, Hispanics, Asians, Africans and others Caucasian cohorts. Bulgarian healthy volunteers and another pooled Caucasian cohort had similar frequencies of genotypes and alleles of rs587585, rs292001, rs294179 and rs631090 SNPs. Nevertheless, genotype AA of rs172378 was significantly overrepresented in Bulgarians when compared to other healthy Caucasians from USA and UK (60% vs 31%. Genotype distribution of rs172378 in Bulgarians was similar to Greek-Cyriot Caucasians. For all Caucasians the major allele of rs172378 was A. This is the first study analyzing the allele frequencies and genotype distribution of C1q gene cluster SNPs in Bulgarian healthy population.

  7. Ancestral Variations of the PCDHG Gene Cluster Predispose to Dyslexia in a Multiplex Family

    Directory of Open Access Journals (Sweden)

    Teesta Naskar

    2018-02-01

    Full Text Available Dyslexia is a heritable neurodevelopmental disorder characterized by difficulties in reading and writing. In this study, we describe the identification of a set of 17 polymorphisms located across 1.9 Mb region on chromosome 5q31.3, encompassing genes of the PCDHG cluster, TAF7, PCDH1 and ARHGAP26, dominantly inherited with dyslexia in a multi-incident family. Strikingly, the non-risk form of seven variations of the PCDHG cluster, are preponderant in the human lineage, while risk alleles are ancestral and conserved across Neanderthals to non-human primates. Four of these seven ancestral variations (c.460A > C [p.Ile154Leu], c.541G > A [p.Ala181Thr], c.2036G > C [p.Arg679Pro] and c.2059A > G [p.Lys687Glu] result in amino acid alterations. p.Ile154Leu and p.Ala181Thr are present at EC2: EC3 interacting interface of γA3-PCDH and γA4-PCDH respectively might affect trans-homophilic interaction and hence neuronal connectivity. p.Arg679Pro and p.Lys687Glu are present within the linker region connecting trans-membrane to extracellular domain. Sequence analysis indicated the importance of p.Ile154, p.Arg679 and p.Lys687 in maintaining class specificity. Thus the observed association of PCDHG genes encoding neural adhesion proteins reinforces the hypothesis of aberrant neuronal connectivity in the pathophysiology of dyslexia. Additionally, the striking conservation of the identified variants indicates a role of PCDHG in the evolution of highly specialized cognitive skills critical to reading.

  8. Novel Tissue Level Effects of the Staphylococcus aureus Enterotoxin Gene Cluster Are Essential for Infective Endocarditis.

    Science.gov (United States)

    Stach, Christopher S; Vu, Bao G; Merriman, Joseph A; Herrera, Alfa; Cahill, Michael P; Schlievert, Patrick M; Salgado-Pabón, Wilmara

    2016-01-01

    Superantigens are indispensable virulence factors for Staphylococcus aureus in disease causation. Superantigens stimulate massive immune cell activation, leading to toxic shock syndrome (TSS) and contributing to other illnesses. However, superantigens differ in their capacities to induce body-wide effects. For many, their production, at least as tested in vitro, is not high enough to reach the circulation, or the proteins are not efficient in crossing epithelial and endothelial barriers, thus remaining within tissues or localized on mucosal surfaces where they exert only local effects. In this study, we address the role of TSS toxin-1 (TSST-1) and most importantly the enterotoxin gene cluster (egc) in infective endocarditis and sepsis, gaining insights into the body-wide versus local effects of superantigens. We examined S. aureus TSST-1 gene (tstH) and egc deletion strains in the rabbit model of infective endocarditis and sepsis. Importantly, we also assessed the ability of commercial human intravenous immunoglobulin (IVIG) plus vancomycin to alter the course of infective endocarditis and sepsis. TSST-1 contributed to infective endocarditis vegetations and lethal sepsis, while superantigens of the egc, a cluster with uncharacterized functions in S. aureus infections, promoted vegetation formation in infective endocarditis. IVIG plus vancomycin prevented lethality and stroke development in infective endocarditis and sepsis. Our studies support the local tissue effects of egc superantigens for establishment and progression of infective endocarditis providing evidence for their role in life-threatening illnesses. In contrast, TSST-1 contributes to both infective endocarditis and lethal sepsis. IVIG may be a useful adjunct therapy for infective endocarditis and sepsis.

  9. Histone and ribosomal RNA repetitive gene clusters of the boll weevil are linked in a tandem array.

    Science.gov (United States)

    Roehrdanz, R; Heilmann, L; Senechal, P; Sears, S; Evenson, P

    2010-08-01

    Histones are the major protein component of chromatin structure. The histone family is made up of a quintet of proteins, four core histones (H2A, H2B, H3 & H4) and the linker histones (H1). Spacers are found between the coding regions. Among insects this quintet of genes is usually clustered and the clusters are tandemly repeated. Ribosomal DNA contains a cluster of the rRNA sequences 18S, 5.8S and 28S. The rRNA genes are separated by the spacers ITS1, ITS2 and IGS. This cluster is also tandemly repeated. We found that the ribosomal RNA repeat unit of at least two species of Anthonomine weevils, Anthonomus grandis and Anthonomus texanus (Coleoptera: Curculionidae), is interspersed with a block containing the histone gene quintet. The histone genes are situated between the rRNA 18S and 28S genes in what is known as the intergenic spacer region (IGS). The complete reiterated Anthonomus grandis histone-ribosomal sequence is 16,248 bp.

  10. Genetic interrelations in the actinomycin biosynthetic gene clusters of Streptomyces antibioticus IMRU 3720 and Streptomyces chrysomallus ATCC11523, producers of actinomycin X and actinomycin C

    Directory of Open Access Journals (Sweden)

    Crnovčić I

    2017-04-01

    Full Text Available Ivana Crnovčić,1 Christian Rückert,2 Siamak Semsary,1 Manuel Lang,1 Jörn Kalinowski,2 Ullrich Keller1 1Institut für Chemie, Technische Universität Berlin, Berlin-Charlottenburg, 2Technology Platform Genomics, Center for Biotechnology, Bielefeld University, Bielefeld, Germany Abstract: Sequencing the actinomycin (acm biosynthetic gene cluster of Streptomyces antibioticus IMRU 3720, which produces actinomycin X (Acm X, revealed 20 genes organized into a highly similar framework as in the bi-armed acm C biosynthetic gene cluster of Streptomyces chrysomallus but without an attached additional extra arm of orthologues as in the latter. Curiously, the extra arm of the S. chrysomallus gene cluster turned out to perfectly match the single arm of the S. antibioticus gene cluster in the same order of orthologues including the the presence of two pseudogenes, scacmM and scacmN, encoding a cytochrome P450 and its ferredoxin, respectively. Orthologues of the latter genes were both missing in the principal arm of the S. chrysomallus acm C gene cluster. All orthologues of the extra arm showed a G +C-contents different from that of their counterparts in the principal arm. Moreover, the similarities of translation products from the extra arm were all higher to the corresponding translation products of orthologue genes from the S. antibioticus acm X gene cluster than to those encoded by the principal arm of their own gene cluster. This suggests that the duplicated structure of the S. chrysomallus acm C biosynthetic gene cluster evolved from previous fusion between two one-armed acm gene clusters each from a different genetic background. However, while scacmM and scacmN in the extra arm of the S. chrysomallus acm C gene cluster are mutated and therefore are non-functional, their orthologues saacmM and saacmN in the S. antibioticus acm C gene cluster show no defects seemingly encoding active enzymes with functions specific for Acm X biosynthesis. Both acm

  11. Short-Term Wind Power Forecasting Based on Clustering Pre-Calculated CFD Method

    Directory of Open Access Journals (Sweden)

    Yimei Wang

    2018-04-01

    Full Text Available To meet the increasing wind power forecasting (WPF demands of newly built wind farms without historical data, physical WPF methods are widely used. The computational fluid dynamics (CFD pre-calculated flow fields (CPFF-based WPF is a promising physical approach, which can balance well the competing demands of computational efficiency and accuracy. To enhance its adaptability for wind farms in complex terrain, a WPF method combining wind turbine clustering with CPFF is first proposed where the wind turbines in the wind farm are clustered and a forecasting is undertaken for each cluster. K-means, hierarchical agglomerative and spectral analysis methods are used to establish the wind turbine clustering models. The Silhouette Coefficient, Calinski-Harabaz index and within-between index are proposed as criteria to evaluate the effectiveness of the established clustering models. Based on different clustering methods and schemes, various clustering databases are built for clustering pre-calculated CFD (CPCC-based short-term WPF. For the wind farm case studied, clustering evaluation criteria show that hierarchical agglomerative clustering has reasonable results, spectral clustering is better and K-means gives the best performance. The WPF results produced by different clustering databases also prove the effectiveness of the three evaluation criteria in turn. The newly developed CPCC model has a much higher WPF accuracy than the CPFF model without using clustering techniques, both on temporal and spatial scales. The research provides supports for both the development and improvement of short-term physical WPF systems.

  12. The relationship between supplier networks and industrial clusters: an analysis based on the cluster mapping method

    Directory of Open Access Journals (Sweden)

    Ichiro IWASAKI

    2010-06-01

    Full Text Available Michael Porter’s concept of competitive advantages emphasizes the importance of regional cooperation of various actors in order to gain competitiveness on globalized markets. Foreign investors may play an important role in forming such cooperation networks. Their local suppliers tend to concentrate regionally. They can form, together with local institutions of education, research, financial and other services, development agencies, the nucleus of cooperative clusters. This paper deals with the relationship between supplier networks and clusters. Two main issues are discussed in more detail: the interest of multinational companies in entering regional clusters and the spillover effects that may stem from their participation. After the discussion on the theoretical background, the paper introduces a relatively new analytical method: “cluster mapping” - a method that can spot regional hot spots of specific economic activities with cluster building potential. Experience with the method was gathered in the US and in the European Union. After the discussion on the existing empirical evidence, the authors introduce their own cluster mapping results, which they obtained by using a refined version of the original methodology.

  13. Functional characterization of KanP, a methyltransferase from the kanamycin biosynthetic gene cluster of Streptomyces kanamyceticus.

    Science.gov (United States)

    Nepal, Keshav Kumar; Yoo, Jin Cheol; Sohng, Jae Kyung

    2010-09-20

    KanP, a putative methyltransferase, is located in the kanamycin biosynthetic gene cluster of Streptomyces kanamyceticus ATCC12853. Amino acid sequence analysis of KanP revealed the presence of S-adenosyl-L-methionine binding motifs, which are present in other O-methyltransferases. The kanP gene was expressed in Escherichia coli BL21 (DE3) to generate the E. coli KANP recombinant strain. The conversion of external quercetin to methylated quercetin in the culture extract of E. coli KANP proved the function of kanP as S-adenosyl-L-methionine-dependent methyltransferase. This is the first report concerning the identification of an O-methyltransferase gene from the kanamycin gene cluster. The resistant activity assay and RT-PCR analysis demonstrated the leeway for obtaining methylated kanamycin derivatives from the wild-type strain of kanamycin producer. 2009 Elsevier GmbH. All rights reserved.

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

    Science.gov (United States)

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

    2016-06-01

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

  15. PBL - Problem Based Learning for Companies and Clusters

    Energy Technology Data Exchange (ETDEWEB)

    Hamburg, I; Vladut, G.

    2016-07-01

    Small and medium sized companies (SMEs) assure economic growth in Europe. Generally many SMEs are struggling to survive in an ongoing global recession and often they are becoming reluctant to release or pay for staff training. In this paper we present shortly the learning methods in SMEs particularly the Problem Based Learning (PBL) as an efficient form for SMEs and entrepreneurship education. In the field of Urban Logistics it was developed four Clusters with potential of innovation and research in four European Regions: Tuscany - Italy, Valencia - Spain, Lisbon and Tagus - Portugal, Oltenia – Romania. Training and mentoring for SMEs, are essential to create competitiveness. Information and communication technologies (ICT) support the tutors by using an ICT platform which is in the development. (Author)

  16. Neuro-fuzzy system modeling based on automatic fuzzy clustering

    Institute of Scientific and Technical Information of China (English)

    Yuangang TANG; Fuchun SUN; Zengqi SUN

    2005-01-01

    A neuro-fuzzy system model based on automatic fuzzy clustering is proposed.A hybrid model identification algorithm is also developed to decide the model structure and model parameters.The algorithm mainly includes three parts:1) Automatic fuzzy C-means (AFCM),which is applied to generate fuzzy rules automatically,and then fix on the size of the neuro-fuzzy network,by which the complexity of system design is reducesd greatly at the price of the fitting capability;2) Recursive least square estimation (RLSE).It is used to update the parameters of Takagi-Sugeno model,which is employed to describe the behavior of the system;3) Gradient descent algorithm is also proposed for the fuzzy values according to the back propagation algorithm of neural network.Finally,modeling the dynamical equation of the two-link manipulator with the proposed approach is illustrated to validate the feasibility of the method.

  17. A Geometric Fuzzy-Based Approach for Airport Clustering

    Directory of Open Access Journals (Sweden)

    Maria Nadia Postorino

    2014-01-01

    Full Text Available Airport classification is a common need in the air transport field due to several purposes—such as resource allocation, identification of crucial nodes, and real-time identification of substitute nodes—which also depend on the involved actors’ expectations. In this paper a fuzzy-based procedure has been proposed to cluster airports by using a fuzzy geometric point of view according to the concept of unit-hypercube. By representing each airport as a point in the given reference metric space, the geometric distance among airports—which corresponds to a measure of similarity—has in fact an intrinsic fuzzy nature due to the airport specific characteristics. The proposed procedure has been applied to a test case concerning the Italian airport network and the obtained results are in line with expectations.

  18. Community Clustering Algorithm in Complex Networks Based on Microcommunity Fusion

    Directory of Open Access Journals (Sweden)

    Jin Qi

    2015-01-01

    Full Text Available With the further research on physical meaning and digital features of the community structure in complex networks in recent years, the improvement of effectiveness and efficiency of the community mining algorithms in complex networks has become an important subject in this area. This paper puts forward a concept of the microcommunity and gets final mining results of communities through fusing different microcommunities. This paper starts with the basic definition of the network community and applies Expansion to the microcommunity clustering which provides prerequisites for the microcommunity fusion. The proposed algorithm is more efficient and has higher solution quality compared with other similar algorithms through the analysis of test results based on network data set.

  19. Operational Numerical Weather Prediction systems based on Linux cluster architectures

    International Nuclear Information System (INIS)

    Pasqui, M.; Baldi, M.; Gozzini, B.; Maracchi, G.; Giuliani, G.; Montagnani, S.

    2005-01-01

    The progress in weather forecast and atmospheric science has been always closely linked to the improvement of computing technology. In order to have more accurate weather forecasts and climate predictions, more powerful computing resources are needed, in addition to more complex and better-performing numerical models. To overcome such a large computing request, powerful workstations or massive parallel systems have been used. In the last few years, parallel architectures, based on the Linux operating system, have been introduced and became popular, representing real high performance-low cost systems. In this work the Linux cluster experience achieved at the Laboratory far Meteorology and Environmental Analysis (LaMMA-CNR-IBIMET) is described and tips and performances analysed

  20. Cost/Performance Ratio Achieved by Using a Commodity-Based Cluster

    Science.gov (United States)

    Lopez, Isaac

    2001-01-01

    Researchers at the NASA Glenn Research Center acquired a commodity cluster based on Intel Corporation processors to compare its performance with a traditional UNIX cluster in the execution of aeropropulsion applications. Since the cost differential of the clusters was significant, a cost/performance ratio was calculated. After executing a propulsion application on both clusters, the researchers demonstrated a 9.4 cost/performance ratio in favor of the Intel-based cluster. These researchers utilize the Aeroshark cluster as one of the primary testbeds for developing NPSS parallel application codes and system software. The Aero-shark cluster provides 64 Intel Pentium II 400-MHz processors, housed in 32 nodes. Recently, APNASA - a code developed by a Government/industry team for the design and analysis of turbomachinery systems was used for a simulation on Glenn's Aeroshark cluster.

  1. Characterization of a multicopper oxidase gene cluster in Phanerochaete chrysosporium and evidence of altered splicing of the mco transcripts

    Science.gov (United States)

    Luis F. Larrondo; Bernardo Gonzalez; Dan Cullen; Rafael Vicuna

    2004-01-01

    A cluster of multicopper oxidase genes (mco1, mco2, mco3, mco4) from the lignin-degrading basidiomycete Phanerochaete chrysosporium is described. The four genes share the same transcriptional orientation within a 25 kb region. mco1, mco2 and mco3 are tightly grouped, with intergenic regions of 2.3 and 0.8 kb, respectively, whereas mco4 is located 11 kb upstream of mco1...

  2. Visualizing Confidence in Cluster-Based Ensemble Weather Forecast Analyses.

    Science.gov (United States)

    Kumpf, Alexander; Tost, Bianca; Baumgart, Marlene; Riemer, Michael; Westermann, Rudiger; Rautenhaus, Marc

    2018-01-01

    In meteorology, cluster analysis is frequently used to determine representative trends in ensemble weather predictions in a selected spatio-temporal region, e.g., to reduce a set of ensemble members to simplify and improve their analysis. Identified clusters (i.e., groups of similar members), however, can be very sensitive to small changes of the selected region, so that clustering results can be misleading and bias subsequent analyses. In this article, we - a team of visualization scientists and meteorologists-deliver visual analytics solutions to analyze the sensitivity of clustering results with respect to changes of a selected region. We propose an interactive visual interface that enables simultaneous visualization of a) the variation in composition of identified clusters (i.e., their robustness), b) the variability in cluster membership for individual ensemble members, and c) the uncertainty in the spatial locations of identified trends. We demonstrate that our solution shows meteorologists how representative a clustering result is, and with respect to which changes in the selected region it becomes unstable. Furthermore, our solution helps to identify those ensemble members which stably belong to a given cluster and can thus be considered similar. In a real-world application case we show how our approach is used to analyze the clustering behavior of different regions in a forecast of "Tropical Cyclone Karl", guiding the user towards the cluster robustness information required for subsequent ensemble analysis.

  3. Glutamic acid promotes monacolin K production and monacolin K biosynthetic gene cluster expression in Monascus.

    Science.gov (United States)

    Zhang, Chan; Liang, Jian; Yang, Le; Chai, Shiyuan; Zhang, Chenxi; Sun, Baoguo; Wang, Chengtao

    2017-12-01

    This study investigated the effects of glutamic acid on production of monacolin K and expression of the monacolin K biosynthetic gene cluster. When Monascus M1 was grown in glutamic medium instead of in the original medium, monacolin K production increased from 48.4 to 215.4 mg l -1 , monacolin K production increased by 3.5 times. Glutamic acid enhanced monacolin K production by upregulating the expression of mokB-mokI; on day 8, the expression level of mokA tended to decrease by Reverse Transcription-polymerase Chain Reaction. Our findings demonstrated that mokA was not a key gene responsible for the quantity of monacolin K production in the presence of glutamic acid. Observation of Monascus mycelium morphology using Scanning Electron Microscope showed glutamic acid significantly increased the content of Monascus mycelium, altered the permeability of Monascus mycelium, enhanced secretion of monacolin K from the cell, and reduced the monacolin K content in Monascus mycelium, thereby enhancing monacolin K production.

  4. Archaeal Clusters of Orthologous Genes (arCOGs): An Update and Application for Analysis of Shared Features between Thermococcales, Methanococcales, and Methanobacteriales

    OpenAIRE

    Makarova, Kira; Wolf, Yuri; Koonin, Eugene

    2015-01-01

    With the continuously accelerating genome sequencing from diverse groups of archaea and bacteria, accurate identification of gene orthology and availability of readily expandable clusters of orthologous genes are essential for the functional annotation of new genomes. We report an update of the collection of archaeal Clusters of Orthologous Genes (arCOGs) to cover, on average, 91% of the protein-coding genes in 168 archaeal genomes. The new arCOGs were constructed using refined algorithms for...

  5. Deletion of a regulatory gene within the cpk gene cluster reveals novel antibacterial activity in Streptomyces coelicolor A3(2)

    NARCIS (Netherlands)

    Gottelt, Marco; Kol, Stefan; Gomez-Escribano, Juan Pablo; Bibb, Mervyn; Takano, Eriko

    Genome sequencing of Streptomyces coelicolor A3(2) revealed an uncharacterized type I polyketide synthase gene cluster (cpk) Here we describe the discovery of a novel antibacterial activity (abCPK) and a yellow-pigmented secondary metabolite (yCPK) after deleting a presumed pathway-specific

  6. Evolution of the C-Type Lectin-Like Receptor Genes of the DECTIN-1 Cluster in the NK Gene Complex

    Directory of Open Access Journals (Sweden)

    Susanne Sattler

    2012-01-01

    Full Text Available Pattern recognition receptors are crucial in initiating and shaping innate and adaptive immune responses and often belong to families of structurally and evolutionarily related proteins. The human C-type lectin-like receptors encoded in the DECTIN-1 cluster within the NK gene complex contain prominent receptors with pattern recognition function, such as DECTIN-1 and LOX-1. All members of this cluster share significant homology and are considered to have arisen from subsequent gene duplications. Recent developments in sequencing and the availability of comprehensive sequence data comprising many species showed that the receptors of the DECTIN-1 cluster are not only homologous to each other but also highly conserved between species. Even in Caenorhabditis elegans, genes displaying homology to the mammalian C-type lectin-like receptors have been detected. In this paper, we conduct a comprehensive phylogenetic survey and give an up-to-date overview of the currently available data on the evolutionary emergence of the DECTIN-1 cluster genes.

  7. Functional Reconstitution of a Fungal Natural Product Gene Cluster by Advanced Genome Editing

    DEFF Research Database (Denmark)

    Weber, Jakob; Valiante, Vito; Nødvig, Christina Spuur

    2017-01-01

    is not produced among different isolates. Combining computational analysis with targeted gene editing, we could link a single nucleotide insertion in the polyketide synthase of the trypacidin biosynthetic pathway and reconstitute its production in a nonproducing strain. Thus, we present a CRISPR/Cas9-based tool...... for advanced molecular genetic studies in filamentous fungi, exploiting selectable markers separated from the edited locus....

  8. Canonical PSO Based K-Means Clustering Approach for Real Datasets.

    Science.gov (United States)

    Dey, Lopamudra; Chakraborty, Sanjay

    2014-01-01

    "Clustering" the significance and application of this technique is spread over various fields. Clustering is an unsupervised process in data mining, that is why the proper evaluation of the results and measuring the compactness and separability of the clusters are important issues. The procedure of evaluating the results of a clustering algorithm is known as cluster validity measure. Different types of indexes are used to solve different types of problems and indices selection depends on the kind of available data. This paper first proposes Canonical PSO based K-means clustering algorithm and also analyses some important clustering indices (intercluster, intracluster) and then evaluates the effects of those indices on real-time air pollution database, wholesale customer, wine, and vehicle datasets using typical K-means, Canonical PSO based K-means, simple PSO based K-means, DBSCAN, and Hierarchical clustering algorithms. This paper also describes the nature of the clusters and finally compares the performances of these clustering algorithms according to the validity assessment. It also defines which algorithm will be more desirable among all these algorithms to make proper compact clusters on this particular real life datasets. It actually deals with the behaviour of these clustering algorithms with respect to validation indexes and represents their results of evaluation in terms of mathematical and graphical forms.

  9. Scuba: scalable kernel-based gene prioritization.

    Science.gov (United States)

    Zampieri, Guido; Tran, Dinh Van; Donini, Michele; Navarin, Nicolò; Aiolli, Fabio; Sperduti, Alessandro; Valle, Giorgio

    2018-01-25

    The uncovering of genes linked to human diseases is a pressing challenge in molecular biology and precision medicine. This task is often hindered by the large number of candidate genes and by the heterogeneity of the available information. Computational methods for the prioritization of candidate genes can help to cope with these problems. In particular, kernel-based methods are a powerful resource for the integration of heterogeneous biological knowledge, however, their practical implementation is often precluded by their limited scalability. We propose Scuba, a scalable kernel-based method for gene prioritization. It implements a novel multiple kernel learning approach, based on a semi-supervised perspective and on the optimization of the margin distribution. Scuba is optimized to cope with strongly unbalanced settings where known disease genes are few and large scale predictions are required. Importantly, it is able to efficiently deal both with a large amount of candidate genes and with an arbitrary number of data sources. As a direct consequence of scalability, Scuba integrates also a new efficient strategy to select optimal kernel parameters for each data source. We performed cross-validation experiments and simulated a realistic usage setting, showing that Scuba outperforms a wide range of state-of-the-art methods. Scuba achieves state-of-the-art performance and has enhanced scalability compared to existing kernel-based approaches for genomic data. This method can be useful to prioritize candidate genes, particularly when their number is large or when input data is highly heterogeneous. The code is freely available at https://github.com/gzampieri/Scuba .

  10. Genetic diversity of K-antigen gene clusters of Escherichia coli and their molecular typing using a suspension array.

    Science.gov (United States)

    Yang, Shuang; Xi, Daoyi; Jing, Fuyi; Kong, Deju; Wu, Junli; Feng, Lu; Cao, Boyang; Wang, Lei

    2018-04-01

    Capsular polysaccharides (CPSs), or K-antigens, are the major surface antigens of Escherichia coli. More than 80 serologically unique K-antigens are classified into 4 groups (Groups 1-4) of capsules. Groups 1 and 4 contain the Wzy-dependent polymerization pathway and the gene clusters are in the order galF to gnd; Groups 2 and 3 contain the ABC-transporter-dependent pathway and the gene clusters consist of 3 regions, regions 1, 2 and 3. Little is known about the variations among the gene clusters. In this study, 9 serotypes of K-antigen gene clusters (K2ab, K11, K20, K24, K38, K84, K92, K96, and K102) were sequenced and correlated with their CPS chemical structures. On the basis of sequence data, a K-antigen-specific suspension array that detects 10 distinct CPSs, including the above 9 CPSs plus K30, was developed. This is the first report to catalog the genetic features of E. coli K-antigen variations and to develop a suspension array for their molecular typing. The method has a number of advantages over traditional bacteriophage and serum agglutination methods and lays the foundation for straightforward identification and detection of additional K-antigens in the future.

  11. vanI: a novel d-Ala-d-Lac vancomycin resistance gene cluster found in Desulfitobacterium hafniense

    NARCIS (Netherlands)

    Kruse, T.; Levisson, M.; Vos, de W.M.; Smidt, H.

    2014-01-01

    The glycopeptide vancomycin was until recently considered a drug of last resort against Gram-positive bacteria. Increasing numbers of bacteria, however, are found to carry genes that confer resistance to this antibiotic. So far, 10 different vancomycin resistance clusters have been described. A

  12. Characterization and transcriptional analysis of two gene clusters for type IV secretion machinery in Wolbachia of Armadillidium vulgare

    DEFF Research Database (Denmark)

    Félix, Christine; Pichon, Samuel; Braquart-Varnier, Christine

    2008-01-01

    Wolbachia are maternally inherited alpha-proteobacteria that induce feminization of genetic males in most terrestrial crustacean isopods. Two clusters of vir genes for a type IV secretion machinery have been identified at two separate loci and characterized for the first time in a feminizing Wolb...

  13. Histone and Ribosomal RNA Repetitive Gene Clusters of the Boll Weevil are Linked in a Tandem Array

    Science.gov (United States)

    Histones are the major protein component of chromatin structure. The histone family is made up of a quintet of proteins, four core histones (H2A, H2B, H3 & H4) and the linker histones (H1). Spacers are found between the coding regions. Among insects this quintet of genes is usually clustered and ...

  14. Genomewide Analysis of Aryl Hydrocarbon Receptor Binding Targets Reveals an Extensive Array of Gene Clusters that Control Morphogenetic and Developmental Programs

    Science.gov (United States)

    Sartor, Maureen A.; Schnekenburger, Michael; Marlowe, Jennifer L.; Reichard, John F.; Wang, Ying; Fan, Yunxia; Ma, Ci; Karyala, Saikumar; Halbleib, Danielle; Liu, Xiangdong; Medvedovic, Mario; Puga, Alvaro

    2009-01-01

    Background The vertebrate aryl hydrocarbon receptor (AHR) is a ligand-activated transcription factor that regulates cellular responses to environmental polycyclic and halogenated compounds. The naive receptor is believed to reside in an inactive cytosolic complex that translocates to the nucleus and induces transcription of xenobiotic detoxification genes after activation by ligand. Objectives We conducted an integrative genomewide analysis of AHR gene targets in mouse hepatoma cells and determined whether AHR regulatory functions may take place in the absence of an exogenous ligand. Methods The network of AHR-binding targets in the mouse genome was mapped through a multipronged approach involving chromatin immunoprecipitation/chip and global gene expression signatures. The findings were integrated into a prior functional knowledge base from Gene Ontology, interaction networks, Kyoto Encyclopedia of Genes and Genomes pathways, sequence motif analysis, and literature molecular concepts. Results We found the naive receptor in unstimulated cells bound to an extensive array of gene clusters with functions in regulation of gene expression, differentiation, and pattern specification, connecting multiple morphogenetic and developmental programs. Activation by the ligand displaced the receptor from some of these targets toward sites in the promoters of xenobiotic metabolism genes. Conclusions The vertebrate AHR appears to possess unsuspected regulatory functions that may be potential targets of environmental injury. PMID:19654925

  15. Organization of nif gene cluster in Frankia sp. EuIK1 strain, a symbiont of Elaeagnus umbellata.

    Science.gov (United States)

    Oh, Chang Jae; Kim, Ho Bang; Kim, Jitae; Kim, Won Jin; Lee, Hyoungseok; An, Chung Sun

    2012-01-01

    The nucleotide sequence of a 20.5-kb genomic region harboring nif genes was determined and analyzed. The fragment was obtained from Frankia sp. EuIK1 strain, an indigenous symbiont of Elaeagnus umbellata. A total of 20 ORFs including 12 nif genes were identified and subjected to comparative analysis with the genome sequences of 3 Frankia strains representing diverse host plant specificities. The nucleotide and deduced amino acid sequences showed highest levels of identity with orthologous genes from an Elaeagnus-infecting strain. The gene organization patterns around the nif gene clusters were well conserved among all 4 Frankia strains. However, characteristic features appeared in the location of the nifV gene for each Frankia strain, depending on the type of host plant. Sequence analysis was performed to determine the transcription units and suggested that there could be an independent operon starting from the nifW gene in the EuIK strain. Considering the organization patterns and their total extensions on the genome, we propose that the nif gene clusters remained stable despite genetic variations occurring in the Frankia genomes.

  16. A novel polyketide biosynthesis gene cluster is involved in fruiting body morphogenesis in the filamentous fungi Sordaria macrospora and Neurospora crassa.

    Science.gov (United States)

    Nowrousian, Minou

    2009-04-01

    During fungal fruiting body development, hyphae aggregate to form multicellular structures that protect and disperse the sexual spores. Analysis of microarray data revealed a gene cluster strongly upregulated during fruiting body development in the ascomycete Sordaria macrospora. Real time PCR analysis showed that the genes from the orthologous cluster in Neurospora crassa are also upregulated during development. The cluster encodes putative polyketide biosynthesis enzymes, including a reducing polyketide synthase. Analysis of knockout strains of a predicted dehydrogenase gene from the cluster showed that mutants in N. crassa and S. macrospora are delayed in fruiting body formation. In addition to the upregulated cluster, the N. crassa genome comprises another cluster containing a polyketide synthase gene, and five additional reducing polyketide synthase (rpks) genes that are not part of clusters. To study the role of these genes in sexual development, expression of the predicted rpks genes in S. macrospora (five genes) and N. crassa (six genes) was analyzed; all but one are upregulated during sexual development. Analysis of knockout strains for the N. crassa rpks genes showed that one of them is essential for fruiting body formation. These data indicate that polyketides produced by RPKSs are involved in sexual development in filamentous ascomycetes.

  17. D Partition-Based Clustering for Supply Chain Data Management

    Science.gov (United States)

    Suhaibah, A.; Uznir, U.; Anton, F.; Mioc, D.; Rahman, A. A.

    2015-10-01

    Supply Chain Management (SCM) is the management of the products and goods flow from its origin point to point of consumption. During the process of SCM, information and dataset gathered for this application is massive and complex. This is due to its several processes such as procurement, product development and commercialization, physical distribution, outsourcing and partnerships. For a practical application, SCM datasets need to be managed and maintained to serve a better service to its three main categories; distributor, customer and supplier. To manage these datasets, a structure of data constellation is used to accommodate the data into the spatial database. However, the situation in geospatial database creates few problems, for example the performance of the database deteriorate especially during the query operation. We strongly believe that a more practical hierarchical tree structure is required for efficient process of SCM. Besides that, three-dimensional approach is required for the management of SCM datasets since it involve with the multi-level location such as shop lots and residential apartments. 3D R-Tree has been increasingly used for 3D geospatial database management due to its simplicity and extendibility. However, it suffers from serious overlaps between nodes. In this paper, we proposed a partition-based clustering for the construction of a hierarchical tree structure. Several datasets are tested using the proposed method and the percentage of the overlapping nodes and volume coverage are computed and compared with the original 3D R-Tree and other practical approaches. The experiments demonstrated in this paper substantiated that the hierarchical structure of the proposed partitionbased clustering is capable of preserving minimal overlap and coverage. The query performance was tested using 300,000 points of a SCM dataset and the results are presented in this paper. This paper also discusses the outlook of the structure for future reference.

  18. Model-based clustering of DNA methylation array data: a recursive-partitioning algorithm for high-dimensional data arising as a mixture of beta distributions

    Directory of Open Access Journals (Sweden)

    Wiemels Joseph

    2008-09-01

    Full Text Available Abstract Background Epigenetics is the study of heritable changes in gene function that cannot be explained by changes in DNA sequence. One of the most commonly studied epigenetic alterations is cytosine methylation, which is a well recognized mechanism of epigenetic gene silencing and often occurs at tumor suppressor gene loci in human cancer. Arrays are now being used to study DNA methylation at a large number of loci; for example, the Illumina GoldenGate platform assesses DNA methylation at 1505 loci associated with over 800 cancer-related genes. Model-based cluster analysis is often used to identify DNA methylation subgroups in data, but it is unclear how to cluster DNA methylation data from arrays in a scalable and reliable manner. Results We propose a novel model-based recursive-partitioning algorithm to navigate clusters in a beta mixture model. We present simulations that show that the method is more reliable than competing nonparametric clustering approaches, and is at least as reliable as conventional mixture model methods. We also show that our proposed method is more computationally efficient than conventional mixture model approaches. We demonstrate our method on the normal tissue samples and show that the clusters are associated with tissue type as well as age. Conclusion Our proposed recursively-partitioned mixture model is an effective and computationally efficient method for clustering DNA methylation data.

  19. blockcluster: An R Package for Model-Based Co-Clustering

    Directory of Open Access Journals (Sweden)

    Parmeet Singh Bhatia

    2017-02-01

    Full Text Available Simultaneous clustering of rows and columns, usually designated by bi-clustering, coclustering or block clustering, is an important technique in two way data analysis. A new standard and efficient approach has been recently proposed based on the latent block model (Govaert and Nadif 2003 which takes into account the block clustering problem on both the individual and variable sets. This article presents our R package blockcluster for co-clustering of binary, contingency and continuous data based on these very models. In this document, we will give a brief review of the model-based block clustering methods, and we will show how the R package blockcluster can be used for co-clustering.

  20. Genome mining of the sordarin biosynthetic gene cluster from Sordaria araneosa Cain ATCC 36386: characterization of cycloaraneosene synthase and GDP-6-deoxyaltrose transferase.

    Science.gov (United States)

    Kudo, Fumitaka; Matsuura, Yasunori; Hayashi, Takaaki; Fukushima, Masayuki; Eguchi, Tadashi

    2016-07-01

    Sordarin is a glycoside antibiotic with a unique tetracyclic diterpene aglycone structure called sordaricin. To understand its intriguing biosynthetic pathway that may include a Diels-Alder-type [4+2]cycloaddition, genome mining of the gene cluster from the draft genome sequence of the producer strain, Sordaria araneosa Cain ATCC 36386, was carried out. A contiguous 67 kb gene cluster consisting of 20 open reading frames encoding a putative diterpene cyclase, a glycosyltransferase, a type I polyketide synthase, and six cytochrome P450 monooxygenases were identified. In vitro enzymatic analysis of the putative diterpene cyclase SdnA showed that it catalyzes the transformation of geranylgeranyl diphosphate to cycloaraneosene, a known biosynthetic intermediate of sordarin. Furthermore, a putative glycosyltransferase SdnJ was found to catalyze the glycosylation of sordaricin in the presence of GDP-6-deoxy-d-altrose to give 4'-O-demethylsordarin. These results suggest that the identified sdn gene cluster is responsible for the biosynthesis of sordarin. Based on the isolated potential biosynthetic intermediates and bioinformatics analysis, a plausible biosynthetic pathway for sordarin is proposed.

  1. The Genome Sequence of the Cyanobacterium Oscillatoria sp. PCC 6506 Reveals Several Gene Clusters Responsible for the Biosynthesis of Toxins and Secondary Metabolites▿

    Science.gov (United States)

    Méjean, Annick; Mazmouz, Rabia; Mann, Stéphane; Calteau, Alexandra; Médigue, Claudine; Ploux, Olivier

    2010-01-01

    We report a draft sequence of the genome of Oscillatoria sp. PCC 6506, a cyanobacterium that produces anatoxin-a and homoanatoxin-a, two neurotoxins, and cylindrospermopsin, a cytotoxin. Beside the clusters of genes responsible for the biosynthesis of these toxins, we have found other clusters of genes likely involved in the biosynthesis of not-yet-identified secondary metabolites. PMID:20675499

  2. A strategy of gene overexpression based on tandem repetitive promoters in Escherichia coli

    Directory of Open Access Journals (Sweden)

    Li Mingji

    2012-02-01

    Full Text Available Abstract Background For metabolic engineering, many rate-limiting steps may exist in the pathways of accumulating the target metabolites. Increasing copy number of the desired genes in these pathways is a general method to solve the problem, for example, the employment of the multi-copy plasmid-based expression system. However, this method may bring genetic instability, structural instability and metabolic burden to the host, while integrating of the desired gene into the chromosome may cause inadequate transcription or expression. In this study, we developed a strategy for obtaining gene overexpression by engineering promoter clusters consisted of multiple core-tac-promoters (MCPtacs in tandem. Results Through a uniquely designed in vitro assembling process, a series of promoter clusters were constructed. The transcription strength of these promoter clusters showed a stepwise enhancement with the increase of tandem repeats number until it reached the critical value of five. Application of the MCPtacs promoter clusters in polyhydroxybutyrate (PHB production proved that it was efficient. Integration of the phaCAB genes with the 5CPtacs promoter cluster resulted in an engineered E.coli that can accumulate 23.7% PHB of the cell dry weight in batch cultivation. Conclusions The transcription strength of the MCPtacs promoter cluster can be greatly improved by increasing the tandem repeats number of the core-tac-promoter. By integrating the desired gene together with the MCPtacs promoter cluster into the chromosome of E. coli, we can achieve high and stale overexpression with only a small size. This strategy has an application potential in many fields and can be extended to other bacteria.

  3. A functional bikaverin biosynthesis gene cluster in rare strains of Botrytis cinerea is positively controlled by VELVET.

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    Julia Schumacher

    Full Text Available The gene cluster responsible for the biosynthesis of the red polyketidic pigment bikaverin has only been characterized in Fusarium ssp. so far. Recently, a highly homologous but incomplete and nonfunctional bikaverin cluster has been found in the genome of the unrelated phytopathogenic fungus Botrytis cinerea. In this study, we provided evidence that rare B. cinerea strains such as 1750 have a complete and functional cluster comprising the six genes orthologous to Fusarium fujikuroi ffbik1-ffbik6 and do produce bikaverin. Phylogenetic analysis confirmed that the whole cluster was acquired from Fusarium through a horizontal gene transfer (HGT. In the bikaverin-nonproducing strain B05.10, the genes encoding bikaverin biosynthesis enzymes are nonfunctional due to deleterious mutations (bcbik2-3 or missing (bcbik1 but interestingly, the genes encoding the regulatory proteins BcBIK4 and BcBIK5 do not harbor deleterious mutations which suggests that they may still be functional. Heterologous complementation of the F. fujikuroi Δffbik4 mutant confirmed that bcbik4 of strain B05.10 is indeed fully functional. Deletion of bcvel1 in the pink strain 1750 resulted in loss of bikaverin and overproduction of melanin indicating that the VELVET protein BcVEL1 regulates the biosynthesis of the two pigments in an opposite manner. Although strain 1750 itself expresses a truncated BcVEL1 protein (100 instead of 575 aa that is nonfunctional with regard to sclerotia formation, virulence and oxalic acid formation, it is sufficient to regulate pigment biosynthesis (bikaverin and melanin and fenhexamid HydR2 type of resistance. Finally, a genetic cross between strain 1750 and a bikaverin-nonproducing strain sensitive to fenhexamid revealed that the functional bikaverin cluster is genetically linked to the HydR2 locus.

  4. Genome-wide association study identifies the SERPINB gene cluster as a susceptibility locus for food allergy.

    Science.gov (United States)

    Marenholz, Ingo; Grosche, Sarah; Kalb, Birgit; Rüschendorf, Franz; Blümchen, Katharina; Schlags, Rupert; Harandi, Neda; Price, Mareike; Hansen, Gesine; Seidenberg, Jürgen; Röblitz, Holger; Yürek, Songül; Tschirner, Sebastian; Hong, Xiumei; Wang, Xiaobin; Homuth, Georg; Schmidt, Carsten O; Nöthen, Markus M; Hübner, Norbert; Niggemann, Bodo; Beyer, Kirsten; Lee, Young-Ae

    2017-10-20

    Genetic factors and mechanisms underlying food allergy are largely unknown. Due to heterogeneity of symptoms a reliable diagnosis is often difficult to make. Here, we report a genome-wide association study on food allergy diagnosed by oral food challenge in 497 cases and 2387 controls. We identify five loci at genome-wide significance, the clade B serpin (SERPINB) gene cluster at 18q21.3, the cytokine gene cluster at 5q31.1, the filaggrin gene, the C11orf30/LRRC32 locus, and the human leukocyte antigen (HLA) region. Stratifying the results for the causative food demonstrates that association of the HLA locus is peanut allergy-specific whereas the other four loci increase the risk for any food allergy. Variants in the SERPINB gene cluster are associated with SERPINB10 expression in leukocytes. Moreover, SERPINB genes are highly expressed in the esophagus. All identified loci are involved in immunological regulation or epithelial barrier function, emphasizing the role of both mechanisms in food allergy.

  5. De novo deletion of HOXB gene cluster in a patient with failure to thrive, developmental delay, gastroesophageal reflux and bronchiectasis.

    Science.gov (United States)

    Pajusalu, Sander; Reimand, Tiia; Uibo, Oivi; Vasar, Maire; Talvik, Inga; Zilina, Olga; Tammur, Pille; Õunap, Katrin

    2015-01-01

    We report a female patient with a complex phenotype consisting of failure to thrive, developmental delay, congenital bronchiectasis, gastroesophageal reflux and bilateral inguinal hernias. Chromosomal microarray analysis revealed a 230 kilobase deletion in chromosomal region 17q21.32 (arr[hg19] 17q21.32(46 550 362-46 784 039)×1) encompassing only 9 genes - HOXB1 to HOXB9. The deletion was not found in her mother or father. This is the first report of a patient with a HOXB gene cluster deletion involving only HOXB1 to HOXB9 genes. By comparing our case to previously reported five patients with larger chromosomal aberrations involving the HOXB gene cluster, we can suppose that HOXB gene cluster deletions are responsible for growth retardation, developmental delay, and specific facial dysmorphic features. Also, we suppose that bilateral inguinal hernias, tracheo-esophageal abnormalities, and lung malformations represent features with incomplete penetrance. Interestingly, previously published knock-out mice with targeted heterozygous deletion comparable to our patient did not show phenotypic alterations. Copyright © 2015 Elsevier Masson SAS. All rights reserved.

  6. A Coupled User Clustering Algorithm Based on Mixed Data for Web-Based Learning Systems

    Directory of Open Access Journals (Sweden)

    Ke Niu

    2015-01-01

    Full Text Available In traditional Web-based learning systems, due to insufficient learning behaviors analysis and personalized study guides, a few user clustering algorithms are introduced. While analyzing the behaviors with these algorithms, researchers generally focus on continuous data but easily neglect discrete data, each of which is generated from online learning actions. Moreover, there are implicit coupled interactions among the data but are frequently ignored in the introduced algorithms. Therefore, a mass of significant information which can positively affect clustering accuracy is neglected. To solve the above issues, we proposed a coupled user clustering algorithm for Wed-based learning systems by taking into account both discrete and continuous data, as well as intracoupled and intercoupled interactions of the data. The experiment result in this paper demonstrates the outperformance of the proposed algorithm.

  7. The human TREM gene cluster at 6p21.1 encodes both activating and inhibitory single IgV domain receptors and includes NKp44.

    Science.gov (United States)

    Allcock, Richard J N; Barrow, Alexander D; Forbes, Simon; Beck, Stephan; Trowsdale, John

    2003-02-01

    We have characterized a cluster of single immunoglobulin variable (IgV) domain receptors centromeric of the major histocompatibility complex (MHC) on human chromosome 6. In addition to triggering receptor expressed on myeloid cells (TREM)-1 and TREM2, the cluster contains NKp44, a triggering receptor whose expression is limited to NK cells. We identified three new related genes and two gene fragments within a cluster of approximately 200 kb. Two of the three new genes lack charged residues in their transmembrane domain tails. Further, one of the genes contains two potential immunotyrosine Inhibitory motifs in its cytoplasmic tail, suggesting that it delivers inhibitory signals. The human and mouse TREM clusters appear to have diverged such that there are unique sequences in each species. Finally, each gene in the TREM cluster was expressed in a different range of cell types.

  8. Centrosome clustering and cyclin D1 gene amplification in double minutes are common events in chromosomal unstable bladder tumors

    International Nuclear Information System (INIS)

    Rey, Javier del; Prat, Esther; Ponsa, Immaculada; Lloreta, Josep; Gelabert, Antoni; Algaba, Ferran; Camps, Jordi; Miró, Rosa

    2010-01-01

    Aneuploidy, centrosome abnormalities and gene amplification are hallmarks of chromosome instability (CIN) in cancer. Yet there are no studies of the in vivo behavior of these phenomena within the same bladder tumor. Twenty-one paraffin-embedded bladder tumors were analyzed by conventional comparative genome hybridization and fluorescence in situ hybridization (FISH) with a cyclin D1 gene (CCND1)/centromere 11 dual-color probe. Immunofluorescent staining of α, β and γ tubulin was also performed. Based on the CIN index, defined as the percentage of cells not displaying the modal number for chromosome 11, tumors were classified as CIN-negative and CIN-positive. Fourteen out of 21 tumors were considered CIN-positive. All T1G3 tumors were included in the CIN-positive group whereas the majority of Ta samples were classified as CIN-negative tumors. Centrosome clustering was observed in six out of 12 CIN-positive tumors analyzed. CCND1 amplification in homogeneously staining regions was present in six out of 14 CIN-positive tumors; three of them also showed amplification of this gene in double minutes. Complex in vivo behavior of CCND1 amplicon in bladder tumor cells has been demonstrated by accurate FISH analysis on paraffin-embedded tumors. Positive correlation between high heterogeneity, centrosome abnormalities and CCND1 amplification was found in T1G3 bladder carcinomas. This is the first study to provide insights into the coexistence of CCND1 amplification in homogeneously staining regions and double minutes in primary bladder tumors. It is noteworthy that those patients whose tumors showed double minutes had a significantly shorter overall survival rate (p < 0.001)

  9. A Cluster-Based Dual-Adaptive Topology Control Approach in Wireless Sensor Networks

    Science.gov (United States)

    Gui, Jinsong; Zhou, Kai; Xiong, Naixue

    2016-01-01

    Multi-Input Multi-Output (MIMO) can improve wireless network performance. Sensors are usually single-antenna devices due to the high hardware complexity and cost, so several sensors are used to form virtual MIMO array, which is a desirable approach to efficiently take advantage of MIMO gains. Also, in large Wireless Sensor Networks (WSNs), clustering can improve the network scalability, which is an effective topology control approach. The existing virtual MIMO-based clustering schemes do not either fully explore the benefits of MIMO or adaptively determine the clustering ranges. Also, clustering mechanism needs to be further improved to enhance the cluster structure life. In this paper, we propose an improved clustering scheme for virtual MIMO-based topology construction (ICV-MIMO), which can determine adaptively not only the inter-cluster transmission modes but also the clustering ranges. Through the rational division of cluster head function and the optimization of cluster head selection criteria and information exchange process, the ICV-MIMO scheme effectively reduces the network energy consumption and improves the lifetime of the cluster structure when compared with the existing typical virtual MIMO-based scheme. Moreover, the message overhead and time complexity are still in the same order of magnitude. PMID:27681731

  10. A Cluster-Based Dual-Adaptive Topology Control Approach in Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Jinsong Gui

    2016-09-01

    Full Text Available Multi-Input Multi-Output (MIMO can improve wireless network performance. Sensors are usually single-antenna devices due to the high hardware complexity and cost, so several sensors are used to form virtual MIMO array, which is a desirable approach to efficiently take advantage of MIMO gains. Also, in large Wireless Sensor Networks (WSNs, clustering can improve the network scalability, which is an effective topology control approach. The existing virtual MIMO-based clustering schemes do not either fully explore the benefits of MIMO or adaptively determine the clustering ranges. Also, clustering mechanism needs to be further improved to enhance the cluster structure life. In this paper, we propose an improved clustering scheme for virtual MIMO-based topology construction (ICV-MIMO, which can determine adaptively not only the inter-cluster transmission modes but also the clustering ranges. Through the rational division of cluster head function and the optimization of cluster head selection criteria and information exchange process, the ICV-MIMO scheme effectively reduces the network energy consumption and improves the lifetime of the cluster structure when compared with the existing typical virtual MIMO-based scheme. Moreover, the message overhead and time complexity are still in the same order of magnitude.

  11. A Cluster-Based Dual-Adaptive Topology Control Approach in Wireless Sensor Networks.

    Science.gov (United States)

    Gui, Jinsong; Zhou, Kai; Xiong, Naixue

    2016-09-25

    Multi-Input Multi-Output (MIMO) can improve wireless network performance. Sensors are usually single-antenna devices due to the high hardware complexity and cost, so several sensors are used to form virtual MIMO array, which is a desirable approach to efficiently take advantage of MIMO gains. Also, in large Wireless Sensor Networks (WSNs), clustering can improve the network scalability, which is an effective topology control approach. The existing virtual MIMO-based clustering schemes do not either fully explore the benefits of MIMO or adaptively determine the clustering ranges. Also, clustering mechanism needs to be further improved to enhance the cluster structure life. In this paper, we propose an improved clustering scheme for virtual MIMO-based topology construction (ICV-MIMO), which can determine adaptively not only the inter-cluster transmission modes but also the clustering ranges. Through the rational division of cluster head function and the optimization of cluster head selection criteria and information exchange process, the ICV-MIMO scheme effectively reduces the network energy consumption and improves the lifetime of the cluster structure when compared with the existing typical virtual MIMO-based scheme. Moreover, the message overhead and time complexity are still in the same order of magnitude.

  12. Cluster-based Data Gathering in Long-Strip Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    FANG, W.

    2012-02-01

    Full Text Available This paper investigates a special class of wireless sensor networks that are different from traditional ones in that the sensor nodes in this class of networks are deployed along narrowly elongated geographical areas and form a long-strip topology. According to hardware capabilities of current sensor nodes, a cluster-based protocol for reliable and efficient data gathering in long-strip wireless sensor networks (LSWSN is proposed. A well-distributed cluster-based architecture is first formed in the whole network through contention-based cluster head election. Cluster heads are responsible for coordination among the nodes within their clusters and aggregation of their sensory data, as well as transmission the data to the sink node on behalf of their own clusters. The intra-cluster coordination is based on the traditional TDMA schedule, in which the inter-cluster interference caused by the border nodes is solved by the multi-channel communication technique. The cluster reporting is based on the CSMA contention, in which a connected overlay network is formed by relay nodes to forward the data from the cluster heads through multi-hops to the sink node. The relay nodes are non-uniformly deployed to resolve the energy-hole problem which is extremely serious in the LSWSN. Extensive simulation results illuminate the distinguished performance of the proposed protocol.

  13. In silico exploration of Red Sea Bacillus genomes for natural product biosynthetic gene clusters

    KAUST Repository

    Othoum, Ghofran K

    2018-05-22

    BackgroundThe increasing spectrum of multidrug-resistant bacteria is a major global public health concern, necessitating discovery of novel antimicrobial agents. Here, members of the genus Bacillus are investigated as a potentially attractive source of novel antibiotics due to their broad spectrum of antimicrobial activities. We specifically focus on a computational analysis of the distinctive biosynthetic potential of Bacillus paralicheniformis strains isolated from the Red Sea, an ecosystem exposed to adverse, highly saline and hot conditions.ResultsWe report the complete circular and annotated genomes of two Red Sea strains, B. paralicheniformis Bac48 isolated from mangrove mud and B. paralicheniformis Bac84 isolated from microbial mat collected from Rabigh Harbor Lagoon in Saudi Arabia. Comparing the genomes of B. paralicheniformis Bac48 and B. paralicheniformis Bac84 with nine publicly available complete genomes of B. licheniformis and three genomes of B. paralicheniformis, revealed that all of the B. paralicheniformis strains in this study are more enriched in nonribosomal peptides (NRPs). We further report the first computationally identified trans-acyltransferase (trans-AT) nonribosomal peptide synthetase/polyketide synthase (PKS/ NRPS) cluster in strains of this species.ConclusionsB. paralicheniformis species have more genes associated with biosynthesis of antimicrobial bioactive compounds than other previously characterized species of B. licheniformis, which suggests that these species are better potential sources for novel antibiotics. Moreover, the genome of the Red Sea strain B. paralicheniformis Bac48 is more enriched in modular PKS genes compared to B. licheniformis strains and other B. paralicheniformis strains. This may be linked to adaptations that strains surviving in the Red Sea underwent to survive in the relatively hot and saline ecosystems.

  14. A comparison of heuristic and model-based clustering methods for dietary pattern analysis.

    Science.gov (United States)

    Greve, Benjamin; Pigeot, Iris; Huybrechts, Inge; Pala, Valeria; Börnhorst, Claudia

    2016-02-01

    Cluster analysis is widely applied to identify dietary patterns. A new method based on Gaussian mixture models (GMM) seems to be more flexible compared with the commonly applied k-means and Ward's method. In the present paper, these clustering approaches are compared to find the most appropriate one for clustering dietary data. The clustering methods were applied to simulated data sets with different cluster structures to compare their performance knowing the true cluster membership of observations. Furthermore, the three methods were applied to FFQ data assessed in 1791 children participating in the IDEFICS (Identification and Prevention of Dietary- and Lifestyle-Induced Health Effects in Children and Infants) Study to explore their performance in practice. The GMM outperformed the other methods in the simulation study in 72 % up to 100 % of cases, depending on the simulated cluster structure. Comparing the computationally less complex k-means and Ward's methods, the performance of k-means was better in 64-100 % of cases. Applied to real data, all methods identified three similar dietary patterns which may be roughly characterized as a 'non-processed' cluster with a high consumption of fruits, vegetables and wholemeal bread, a 'balanced' cluster with only slight preferences of single foods and a 'junk food' cluster. The simulation study suggests that clustering via GMM should be preferred due to its higher flexibility regarding cluster volume, shape and orientation. The k-means seems to be a good alternative, being easier to use while giving similar results when applied to real data.

  15. Efficient similarity-based data clustering by optimal object to cluster reallocation.

    Science.gov (United States)

    Rossignol, Mathias; Lagrange, Mathieu; Cont, Arshia

    2018-01-01

    We present an iterative flat hard clustering algorithm designed to operate on arbitrary similarity matrices, with the only constraint that these matrices be symmetrical. Although functionally very close to kernel k-means, our proposal performs a maximization of average intra-class similarity, instead of a squared distance minimization, in order to remain closer to the semantics of similarities. We show that this approach permits the relaxing of some conditions on usable affinity matrices like semi-positiveness, as well as opening possibilities for computational optimization required for large datasets. Systematic evaluation on a variety of data sets shows that compared with kernel k-means and the spectral clustering methods, the proposed approach gives equivalent or better performance, while running much faster. Most notably, it significantly reduces memory access, which makes it a good choice for large data collections. Material enabling the reproducibility of the results is made available online.

  16. A model-based clustering method to detect infectious disease transmission outbreaks from sequence variation.

    Directory of Open Access Journals (Sweden)

    Rosemary M McCloskey

    2017-11-01

    Full Text Available Clustering infections by genetic similarity is a popular technique for identifying potential outbreaks of infectious disease, in part because sequences are now routinely collected for clinical management of many infections. A diverse number of nonparametric clustering methods have been developed for this purpose. These methods are generally intuitive, rapid to compute, and readily scale with large data sets. However, we have found that nonparametric clustering methods can be biased towards identifying clusters of diagnosis-where individuals are sampled sooner post-infection-rather than the clusters of rapid transmission that are meant to be potential foci for public health efforts. We develop a fundamentally new approach to genetic clustering based on fitting a Markov-modulated Poisson process (MMPP, which represents the evolution of transmission rates along the tree relating different infections. We evaluated this model-based method alongside five nonparametric clustering methods using both simulated and actual HIV sequence data sets. For simulated clusters of rapid transmission, the MMPP clustering method obtained higher mean sensitivity (85% and specificity (91% than the nonparametric methods. When we applied these clustering methods to published sequences from a study of HIV-1 genetic clusters in Seattle, USA, we found that the MMPP method categorized about half (46% as many individuals to clusters compared to the other methods. Furthermore, the mean internal branch lengths that approximate transmission rates were significantly shorter in clusters extracted using MMPP, but not by other methods. We determined that the computing time for the MMPP method scaled linearly with the size of trees, requiring about 30 seconds for a tree of 1,000 tips and about 20 minutes for 50,000 tips on a single computer. This new approach to genetic clustering has significant implications for the application of pathogen sequence analysis to public health, where

  17. Development of a gene cloning system in a fast-growing and moderately thermophilic Streptomyces species and heterologous expression of Streptomyces antibiotic biosynthetic gene clusters

    Science.gov (United States)

    2011-01-01

    Background Streptomyces species are a major source of antibiotics. They usually grow slowly at their optimal temperature and fermentation of industrial strains in a large scale often takes a long time, consuming more energy and materials than some other bacterial industrial strains (e.g., E. coli and Bacillus). Most thermophilic Streptomyces species grow fast, but no gene cloning systems have been developed in such strains. Results We report here the isolation of 41 fast-growing (about twice the rate of S. coelicolor), moderately thermophilic (growing at both 30°C and 50°C) Streptomyces strains, detection of one linear and three circular plasmids in them, and sequencing of a 6996-bp plasmid, pTSC1, from one of them. pTSC1-derived pCWH1 could replicate in both thermophilic and mesophilic Streptomyces strains. On the other hand, several Streptomyces replicons function in thermophilic Streptomyces species. By examining ten well-sporulating strains, we found two promising cloning hosts, 2C and 4F. A gene cloning system was established by using the two strains. The actinorhodin and anthramycin biosynthetic gene clusters from mesophilic S. coelicolor A3(2) and thermophilic S. refuineus were heterologously expressed in one of the hosts. Conclusions We have developed a gene cloning and expression system in a fast-growing and moderately thermophilic Streptomyces species. Although just a few plasmids and one antibiotic biosynthetic gene cluster from mesophilic Streptomyces were successfully expressed in thermophilic Streptomyces species, we expect that by utilizing thermophilic Streptomyces-specific promoters, more genes and especially antibiotic genes clusters of mesophilic Streptomyces should be heterologously expressed. PMID:22032628

  18. Endophytic actinobacteria: Diversity, secondary metabolism and mechanisms to unsilence biosynthetic gene clusters.

    Science.gov (United States)

    Dinesh, Raghavan; Srinivasan, Veeraraghavan; T E, Sheeja; Anandaraj, Muthuswamy; Srambikkal, Hamza

    2017-09-01

    Endophytic actinobacteria, which reside in the inner tissues of host plants, are gaining serious attention due to their capacity to produce a plethora of secondary metabolites (e.g. antibiotics) possessing a wide variety of biological activity with diverse functions. This review encompasses the recent reports on endophytic actinobacterial species diversity, in planta habitats and mechanisms underlying their mode of entry into plants. Besides, their metabolic potential, novel bioactive compounds they produce and mechanisms to unravel their hidden metabolic repertoire by activation of cryptic or silent biosynthetic gene clusters (BGCs) for eliciting novel secondary metabolite production are discussed. The study also reviews the classical conservative techniques (chemical/biological/physical elicitation, co-culturing) as well as modern microbiology tools (e.g. next generation sequencing) that are being gainfully employed to uncover the vast hidden scaffolds for novel secondary metabolites produced by these endophytes, which would subsequently herald a revolution in drug engineering. The potential role of these endophytes in the agro-environment as promising biological candidates for inhibition of phytopathogens and the way forward to thoroughly exploit this unique microbial community by inducing expression of cryptic BGCs for encoding unseen products with novel therapeutic properties are also discussed.

  19. Clustering-based urbanisation to improve enterprise information systems agility

    Science.gov (United States)

    Imache, Rabah; Izza, Said; Ahmed-Nacer, Mohamed

    2015-11-01

    Enterprises are daily facing pressures to demonstrate their ability to adapt quickly to the unpredictable changes of their dy